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Sample records for predict individual efficiency

  1. 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.

  2. 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

  3. Neuroanatomy predicts individual risk attitudes.

    PubMed

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

    2014-09-10

    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

  4. 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

  5. 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

  6. Predicting future violence among individuals with psychopathy.

    PubMed

    Coid, Jeremy W; Ullrich, Simone; Kallis, Constantinos

    2013-11-01

    Structured risk assessment aims to help clinicians classify offenders according to likelihood of future violent and criminal behaviour. We investigated how confident clinicians can be using three commonly used instruments (HCR-20, VRAG, OGRS-II) in individuals with different diagnoses. Moderate to good predictive accuracy for future violence was achieved for released prisoners with no mental disorder, low to moderate for clinical syndromes and personality disorder, but accuracy was no better than chance for individuals with psychopathy. Comprehensive diagnostic assessment should precede an assessment of risk. Risk assessment instruments cannot be relied upon when managing public risk from individuals with psychopathy. PMID:24072757

  7. 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.

  8. 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.

  9. Efficiently Finding Individuals from Video Dataset

    NASA Astrophysics Data System (ADS)

    Hao, Pengyi; Kamata, Sei-Ichiro

    We are interested in retrieving video shots or videos containing particular people from a video dataset. Owing to the large variations in pose, illumination conditions, occlusions, hairstyles and facial expressions, face tracks have recently been researched in the fields of face recognition, face retrieval and name labeling from videos. However, when the number of face tracks is very large, conventional methods, which match all or some pairs of faces in face tracks, will not be effective. Therefore, in this paper, an efficient method for finding a given person from a video dataset is presented. In our study, in according to performing research on face tracks in a single video, we also consider how to organize all the faces in videos in a dataset and how to improve the search quality in the query process. Different videos may include the same person; thus, the management of individuals in different videos will be useful for their retrieval. The proposed method includes the following three points. (i) Face tracks of the same person appearing for a period in each video are first connected on the basis of scene information with a time constriction, then all the people in one video are organized by a proposed hierarchical clustering method. (ii) After obtaining the organizational structure of all the people in one video, the people are organized into an upper layer by affinity propagation. (iii) Finally, in the process of querying, a remeasuring method based on the index structure of videos is performed to improve the retrieval accuracy. We also build a video dataset that contains six types of videos: films, TV shows, educational videos, interviews, press conferences and domestic activities. The formation of face tracks in the six types of videos is first researched, then experiments are performed on this video dataset containing more than 1 million faces and 218,786 face tracks. The results show that the proposed approach has high search quality and a short search time.

  10. 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. PMID:27132070

  11. 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.

  12. 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. PMID:20798810

  13. A Simple Model Predicting Individual Weight Change in Humans

    PubMed Central

    Thomas, Diana M.; Martin, Corby K.; Heymsfield, Steven; Redman, Leanne M.; Schoeller, Dale A.; Levine, James A.

    2010-01-01

    Excessive weight in adults is a national concern with over 2/3 of the US population deemed overweight. Because being overweight has been correlated to numerous diseases such as heart disease and type 2 diabetes, there is a need to understand mechanisms and predict outcomes of weight change and weight maintenance. A simple mathematical model that accurately predicts individual weight change offers opportunities to understand how individuals lose and gain weight and can be used to foster patient adherence to diets in clinical settings. For this purpose, we developed a one dimensional differential equation model of weight change based on the energy balance equation is paired to an algebraic relationship between fat free mass and fat mass derived from a large nationally representative sample of recently released data collected by the Centers for Disease Control. We validate the model's ability to predict individual participants’ weight change by comparing model estimates of final weight data from two recent underfeeding studies and one overfeeding study. Mean absolute error and standard deviation between model predictions and observed measurements of final weights are less than 1.8 ± 1.3 kg for the underfeeding studies and 2.5 ± 1.6 kg for the overfeeding study. Comparison of the model predictions to other one dimensional models of weight change shows improvement in mean absolute error, standard deviation of mean absolute error, and group mean predictions. The maximum absolute individual error decreased by approximately 60% substantiating reliability in individual weight change predictions. The model provides a viable method for estimating individual weight change as a result of changes in intake and determining individual dietary adherence during weight change studies. PMID:24707319

  14. A Simple Model Predicting Individual Weight Change in Humans.

    PubMed

    Thomas, Diana M; Martin, Corby K; Heymsfield, Steven; Redman, Leanne M; Schoeller, Dale A; Levine, James A

    2011-11-01

    Excessive weight in adults is a national concern with over 2/3 of the US population deemed overweight. Because being overweight has been correlated to numerous diseases such as heart disease and type 2 diabetes, there is a need to understand mechanisms and predict outcomes of weight change and weight maintenance. A simple mathematical model that accurately predicts individual weight change offers opportunities to understand how individuals lose and gain weight and can be used to foster patient adherence to diets in clinical settings. For this purpose, we developed a one dimensional differential equation model of weight change based on the energy balance equation is paired to an algebraic relationship between fat free mass and fat mass derived from a large nationally representative sample of recently released data collected by the Centers for Disease Control. We validate the model's ability to predict individual participants' weight change by comparing model estimates of final weight data from two recent underfeeding studies and one overfeeding study. Mean absolute error and standard deviation between model predictions and observed measurements of final weights are less than 1.8 ± 1.3 kg for the underfeeding studies and 2.5 ± 1.6 kg for the overfeeding study. Comparison of the model predictions to other one dimensional models of weight change shows improvement in mean absolute error, standard deviation of mean absolute error, and group mean predictions. The maximum absolute individual error decreased by approximately 60% substantiating reliability in individual weight change predictions. The model provides a viable method for estimating individual weight change as a result of changes in intake and determining individual dietary adherence during weight change studies. PMID:24707319

  15. 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. PMID:27386283

  16. Sizing up your enemy: individual predation vulnerability predicts migratory probability.

    PubMed

    Skov, Christian; Baktoft, Henrik; Brodersen, Jakob; Brönmark, Christer; Chapman, Ben B; Hansson, Lars-Anders; Nilsson, P Anders

    2011-05-01

    Partial migration, in which a fraction of a population migrate and the rest remain resident, occurs in an extensive range of species and can have powerful ecological consequences. The question of what drives differences in individual migratory tendency is a contentious one. It has been shown that the timing of partial migration is based upon a trade-off between seasonal fluctuations in predation risk and growth potential. Phenotypic variation in either individual predation risk or growth potential should thus mediate the strength of the trade-off and ultimately predict patterns of partial migration at the individual level (i.e. which individuals migrate and which remain resident). We provide cross-population empirical support for the importance of one component of this model--individual predation risk--in predicting partial migration in wild populations of bream Abramis brama, a freshwater fish. Smaller, high-risk individuals migrate with a higher probability than larger, low-risk individuals, and we suggest that predation risk maintains size-dependent partial migration in this system. PMID:20980300

  17. Sizing up your enemy: individual predation vulnerability predicts migratory probability

    PubMed Central

    Skov, Christian; Baktoft, Henrik; Brodersen, Jakob; Brönmark, Christer; Chapman, Ben B.; Hansson, Lars-Anders; Nilsson, P. Anders

    2011-01-01

    Partial migration, in which a fraction of a population migrate and the rest remain resident, occurs in an extensive range of species and can have powerful ecological consequences. The question of what drives differences in individual migratory tendency is a contentious one. It has been shown that the timing of partial migration is based upon a trade-off between seasonal fluctuations in predation risk and growth potential. Phenotypic variation in either individual predation risk or growth potential should thus mediate the strength of the trade-off and ultimately predict patterns of partial migration at the individual level (i.e. which individuals migrate and which remain resident). We provide cross-population empirical support for the importance of one component of this model—individual predation risk—in predicting partial migration in wild populations of bream Abramis brama, a freshwater fish. Smaller, high-risk individuals migrate with a higher probability than larger, low-risk individuals, and we suggest that predation risk maintains size-dependent partial migration in this system. PMID:20980300

  18. 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:…

  19. 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)…

  20. 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. PMID

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

    PubMed

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

    2013-01-01

    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. PMID:23531805

  2. Prediction of INDIVIDUAL'S Movement Based on Interesting Places

    NASA Astrophysics Data System (ADS)

    Feuerhake, U.

    2012-07-01

    In general, the development of prediction methods is a quite challenging field. However, as difficult the development is, as useful those methods can be in a large variety of use cases. Whether the weather of tomorrow or the destination of a moving individual is to be predicted, in both cases many different aspects have to be considered, because as well as the weather's behaviour the one of individuals, especially human beings, is influenced by many factors. For instance, movements of human beings are either planned, arbitrary or influenced by their environment or social aspects. In most cases a combination of those factors is involved. In this paper, motivated by the context of a decentralized surveillance scenario, we present an approach for predicting movements on the basis of a prediction model generated from the knowledge, which is implicated in spatio-temporal trajectories. This model is based on extracted interesting places and considers several aspects, which contain gained information about the movement behaviour in a given scenario.

  3. Individual differences in physiological flexibility predict spontaneous avoidance.

    PubMed

    Aldao, Amelia; Dixon-Gordon, Katherine L; De Los Reyes, Andres

    2016-08-01

    People often regulate their emotions by resorting to avoidance, a putatively maladaptive strategy. Prior work suggests that increased psychopathology symptoms predict greater spontaneous utilisation of this strategy. Extending this work, we examined whether heightened resting cardiac vagal tone (which reflects a general ability to regulate emotions in line with contextual demands) predicts decreased spontaneous avoidance. In Study 1, greater resting vagal tone was associated with reduced spontaneous avoidance in response to disgust-eliciting pictures, beyond anxiety and depression symptoms and emotional reactivity. In Study 2, resting vagal tone interacted with anxiety and depression symptoms to predict spontaneous avoidance in response to disgust-eliciting film clips. The positive association between symptoms and spontaneous avoidance was more pronounced among participants with reduced resting vagal tone. Thus, increased resting vagal tone might protect against the use of avoidance. Our findings highlight the importance of assessing both subjective and biological processes when studying individual differences in emotion regulation. PMID:26147365

  4. 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

  5. Predicting individual variation in language from infant speech perception measures.

    PubMed

    Cristia, Alejandrina; Seidl, Amanda; Junge, Caroline; Soderstrom, Melanie; Hagoort, Peter

    2014-01-01

    There are increasing reports that individual variation in behavioral and neurophysiological measures of infant speech processing predicts later language outcomes, and specifically concurrent or subsequent vocabulary size. If such findings are held up under scrutiny, they could both illuminate theoretical models of language development and contribute to the prediction of communicative disorders. A qualitative, systematic review of this emergent literature illustrated the variety of approaches that have been used and highlighted some conceptual problems regarding the measurements. A quantitative analysis of the same data established that the bivariate relation was significant, with correlations of similar strength to those found for well-established nonlinguistic predictors of language. Further exploration of infant speech perception predictors, particularly from a methodological perspective, is recommended. PMID:24320112

  6. 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.

  7. Compulsivity predicts fronto striatal activation in severely anorectic individuals.

    PubMed

    Rothemund, Y; Buchwald, C; Georgiewa, P; Bohner, G; Bauknecht, H-C; Ballmaier, M; Klapp, B F; Klingebiel, R

    2011-12-01

    Anorexia nervosa is a severe illness and shows one of the highest death rates among psychiatric or psychosomatic diseases. However, despite several lines of research, the etiology of this disease is still unknown. One of those features is the rigidity of behaviors, for example, controlling of weight and pursuing of thinness, that often meets the criteria for obsessive-compulsive behavior. In this study, it was investigated whether the clinical feature of compulsivity in anorexia nervosa patients relates to regional brain activation. Using functional magnetic resonance imaging, 12 severely anorectic women were compared to 12 normal-weight female individuals following a cue-reactivity paradigm. Cues comprised food cues of high and low calorie content as well as eating-related utensils. Voxel-based morphometric analysis indicated significantly overall reduced gray matter volume and significantly increased cerebrospinal fluids in anorexia nervosa (AN) patients, which was controlled for in subsequent analyses. Following the high-calorie stimulation, AN patients activated the right caudate body and right precuneus, whereas control subjects did not show significant regional activations. In both other conditions, low-calorie foods and eating utensils, regional brain activations did not survive FDR thresholds. During the high-calorie condition, compulsivity, that is, the subscore "obsessive thoughts," predicted activation of the superior frontal gyrus [Brodmann areas (BA) 10], inferior frontal gyrus, anterior cingulate cortex (BA 32), cingulate gyrus (BA 24), caudate body, cuneus, pre- and postcentral gyrus. The subscore "compulsive acts" correlated with activation of the claustrum during the high-calorie condition and predicted a number of deactivations of frontal and temporal regions. We conclude that in severely anorectic individuals, the degree of compulsivity predicts activation and deactivation of the fronto-striatal pathway. PMID:21952129

  8. 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

  9. 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. PMID:27336162

  10. Dopaminergic genes predict individual differences in susceptibility to confirmation bias

    PubMed Central

    Doll, Bradley B.; Hutchison, Kent E.; Frank, Michael J.

    2011-01-01

    The striatum is critical for the incremental learning of values associated with behavioral actions. The pre-frontal cortex (PFC) represents abstract rules and explicit contingencies to support rapid behavioral adaptation in the absence of cumulative experience. Here we test two alternative models of the interaction between these systems, and individual differences thereof, when human subjects are instructed with prior information about reward contingencies that may or may not be accurate. Behaviorally, subjects are overly influenced by prior instructions, at the expense of learning true reinforcement statistics. Computational analysis found that this pattern of data is best accounted for by a confirmation bias mechanism in which prior beliefs - putatively represented in PFC - influence the learning that occurs in the striatum such that reinforcement statistics are distorted. We assessed genetic variants affecting prefrontal and striatal dopaminergic neurotransmission. A polymorphism in the COMT gene (rs4680), associated with prefrontal dopaminergic function, was predictive of the degree to which participants persisted in responding in accordance with prior instructions even as evidence against their veracity accumulated. Polymorphisms in genes associated with striatal dopamine function (DARPP-32, rs907094, and DRD2, rs6277), were predictive of learning from positive and negative outcomes. Notably, these same variants were predictive of the degree to which such learning was overly inflated or neglected when outcomes are consistent or inconsistent with prior instructions. These findings indicate dissociable neurocomputational and genetic mechanisms by which initial biases are strengthened by experience. PMID:21508242

  11. Dopaminergic genes predict individual differences in susceptibility to confirmation bias.

    PubMed

    Doll, Bradley B; Hutchison, Kent E; Frank, Michael J

    2011-04-20

    The striatum is critical for the incremental learning of values associated with behavioral actions. The prefrontal cortex (PFC) represents abstract rules and explicit contingencies to support rapid behavioral adaptation in the absence of cumulative experience. Here we test two alternative models of the interaction between these systems, and individual differences thereof, when human subjects are instructed with prior information about reward contingencies that may or may not be accurate. Behaviorally, subjects are overly influenced by prior instructions, at the expense of learning true reinforcement statistics. Computational analysis found that this pattern of data is best accounted for by a confirmation bias mechanism in which prior beliefs--putatively represented in PFC--influence the learning that occurs in the striatum such that reinforcement statistics are distorted. We assessed genetic variants affecting prefrontal and striatal dopaminergic neurotransmission. A polymorphism in the COMT gene (rs4680), associated with prefrontal dopaminergic function, was predictive of the degree to which participants persisted in responding in accordance with prior instructions even as evidence against their veracity accumulated. Polymorphisms in genes associated with striatal dopamine function (DARPP-32, rs907094, and DRD2, rs6277) were predictive of learning from positive and negative outcomes. Notably, these same variants were predictive of the degree to which such learning was overly inflated or neglected when outcomes are consistent or inconsistent with prior instructions. These findings indicate dissociable neurocomputational and genetic mechanisms by which initial biases are strengthened by experience. PMID:21508242

  12. Predicting the Time Course of Individual Objects with MEG.

    PubMed

    Clarke, Alex; Devereux, Barry J; Randall, Billi; Tyler, Lorraine K

    2015-10-01

    To respond appropriately to objects, we must process visual inputs rapidly and assign them meaning. This involves highly dynamic, interactive neural processes through which information accumulates and cognitive operations are resolved across multiple time scales. However, there is currently no model of object recognition which provides an integrated account of how visual and semantic information emerge over time; therefore, it remains unknown how and when semantic representations are evoked from visual inputs. Here, we test whether a model of individual objects--based on combining the HMax computational model of vision with semantic-feature information--can account for and predict time-varying neural activity recorded with magnetoencephalography. We show that combining HMax and semantic properties provides a better account of neural object representations compared with the HMax alone, both through model fit and classification performance. Our results show that modeling and classifying individual objects is significantly improved by adding semantic-feature information beyond ∼200 ms. These results provide important insights into the functional properties of visual processing across time. PMID:25209607

  13. 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

  14. Individual predictions of eye-movements with dynamic scenes

    NASA Astrophysics Data System (ADS)

    Barth, Erhardt; Drewes, Jan; Martinetz, Thomas

    2003-06-01

    We present a model that predicts saccadic eye-movements and can be tuned to a particular human observer who is viewing a dynamic sequence of images. Our work is motivated by applications that involve gaze-contingent interactive displays on which information is displayed as a function of gaze direction. The approach therefore differs from standard approaches in two ways: (1) we deal with dynamic scenes, and (2) we provide means of adapting the model to a particular observer. As an indicator for the degree of saliency we evaluate the intrinsic dimension of the image sequence within a geometric approach implemented by using the structure tensor. Out of these candidate saliency-based locations, the currently attended location is selected according to a strategy found by supervised learning. The data are obtained with an eye-tracker and subjects who view video sequences. The selection algorithm receives candidate locations of current and past frames and a limited history of locations attended in the past. We use a linear mapping that is obtained by minimizing the quadratic difference between the predicted and the actually attended location by gradient descent. Being linear, the learned mapping can be quickly adapted to the individual observer.

  15. 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. PMID:27260516

  16. Efficient Methods to Compute Genomic Predictions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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. 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

  18. Computationally efficient prediction of area per lipid

    NASA Astrophysics Data System (ADS)

    Chaban, Vitaly

    2014-11-01

    Area per lipid (APL) is an important property of biological and artificial membranes. Newly constructed bilayers are characterized by their APL and newly elaborated force fields must reproduce APL. Computer simulations of APL are very expensive due to slow conformational dynamics. The simulated dynamics increases exponentially with respect to temperature. APL dependence on temperature is linear over an entire temperature range. I provide numerical evidence that thermal expansion coefficient of a lipid bilayer can be computed at elevated temperatures and extrapolated to the temperature of interest. Thus, sampling times to predict accurate APL are reduced by a factor of ∼10.

  19. Efficient prediction of (p,n) yields

    SciTech Connect

    Swift, D C; McNaney, J M; Higginson, D P; Beg, F

    2009-09-09

    In the continuous deceleration approximation, charged particles decelerate without any spread in energy as they traverse matter. This approximation simplifies the calculation of the yield of nuclear reactions, for which the cross-section depends on the particle energy. We calculated (p,n) yields for a LiF target, using the Bethe-Bloch relation for proton deceleration, and predicted that the maximum yield would be around 0.25% neutrons per incident proton, for an initial proton energy of 70 MeV or higher. Yield-energy relations calculated in this way can readily be used to optimize source and (p,n) converter characteristics.

  20. Efficient prediction designs for random fields

    PubMed Central

    Müller, Werner G; Pronzato, Luc; Rendas, Joao; Waldl, Helmut

    2015-01-01

    For estimation and predictions of random fields, it is increasingly acknowledged that the kriging variance may be a poor representative of true uncertainty. Experimental designs based on more elaborate criteria that are appropriate for empirical kriging (EK) are then often non-space-filling and very costly to determine. In this paper, we investigate the possibility of using a compound criterion inspired by an equivalence theorem type relation to build designs quasi-optimal for the EK variance when space-filling designs become unsuitable. Two algorithms are proposed, one relying on stochastic optimization to explicitly identify the Pareto front, whereas the second uses the surrogate criteria as local heuristic to choose the points at which the (costly) true EK variance is effectively computed. We illustrate the performance of the algorithms presented on both a simple simulated example and a real oceanographic dataset. © 2014 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons, Ltd. PMID:26300698

  1. 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

  2. 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. PMID:10808644

  3. Predicting individual brain maturity using dynamic functional connectivity

    PubMed Central

    Qin, Jian; Chen, Shan-Guang; Hu, Dewen; Zeng, Ling-Li; Fan, Yi-Ming; Chen, Xiao-Ping; Shen, Hui

    2015-01-01

    Neuroimaging-based functional connectivity (FC) analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI; n = 183, ages 7–30) and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN) and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains. PMID:26236224

  4. 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. PMID:26710824

  5. 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.…

  6. 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. PMID:26712471

  7. Benchmarking the Predictive Power of Ligand Efficiency Indices in QSAR.

    PubMed

    Cortes-Ciriano, Isidro

    2016-08-22

    Compound physicochemical properties favoring in vitro potency are not always correlated to desirable pharmacokinetic profiles. Therefore, using potency (i.e., IC50) as the main criterion to prioritize candidate drugs at early stage drug discovery campaigns has been questioned. Yet, the vast majority of the virtual screening models reported in the medicinal chemistry literature predict the biological activity of compounds by regressing in vitro potency on topological or physicochemical descriptors. Two studies published in this journal showed that higher predictive power on external molecules can be achieved by using ligand efficiency indices as the dependent variable instead of a metric of potency (IC50) or binding affinity (Ki). The present study aims at filling the shortage of a thorough assessment of the predictive power of ligand efficiency indices in QSAR. To this aim, the predictive power of 11 ligand efficiency indices has been benchmarked across four algorithms (Gradient Boosting Machines, Partial Least Squares, Random Forest, and Support Vector Machines), two descriptor types (Morgan fingerprints, and physicochemical descriptors), and 29 data sets collected from the literature and ChEMBL database. Ligand efficiency metrics led to the highest predictive power on external molecules irrespective of the descriptor type or algorithm used, with an R(2)test difference of ∼0.3 units and a this difference ∼0.4 units when modeling small data sets and a normalized RMSE decrease of >0.1 units in some cases. Polarity indices, such as SEI and NSEI, led to higher predictive power than metrics based on molecular size, i.e., BEI, NBEI, and LE. LELP, which comprises a polarity factor (cLogP) and a size parameter (LE) constantly led to the most predictive models, suggesting that these two properties convey a complementary predictive signal. Overall, this study suggests that using ligand efficiency indices as the dependent variable might be an efficient strategy to model

  8. 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 or…

  9. Generalization on the Basis of Prior Experience Is Predicted by Individual Differences in Working Memory.

    PubMed

    Lenaert, Bert; van de Ven, Vincent; Kaas, Amanda L; Vlaeyen, Johan W S

    2016-01-01

    Generalization on the basis of prior experience is a central feature of human and nonhuman behavior, and anomalies in generalization can give rise to a wide array of problems. For instance, elevated levels of generalization have been shown in individuals suffering from an anxiety disorder. Identifying the individual difference variables that influence the extent to which behavior generalizes to novel stimuli may help our understanding of generalization and its potential maladaptive consequences. In this study, we first present an index of generalization that captures individual differences in generalization in a single continuous measure, thereby surpassing problems associated with traditional analyzing techniques. Further, we investigate whether generalization is predicted by working memory capacity. More precisely, it is hypothesized that generalization is a function of individual differences in the capacity to compare the current situation with previous learning experiences in working memory, and to adjust subsequent behavior accordingly. In a community sample, we found higher levels of generalization in individuals who were less efficient at filtering out irrelevant information from access to working memory. These results suggest that working memory impairments may contribute to elevated and potentially maladaptive levels of generalization. PMID:26763503

  10. ANNIT - An Efficient Inversion Algorithm based on Prediction Principles

    NASA Astrophysics Data System (ADS)

    Růžek, B.; Kolář, P.

    2009-04-01

    Solution of inverse problems represents meaningful job in geophysics. The amount of data is continuously increasing, methods of modeling are being improved and the computer facilities are also advancing great technical progress. Therefore the development of new and efficient algorithms and computer codes for both forward and inverse modeling is still up to date. ANNIT is contributing to this stream since it is a tool for efficient solution of a set of non-linear equations. Typical geophysical problems are based on parametric approach. The system is characterized by a vector of parameters p, the response of the system is characterized by a vector of data d. The forward problem is usually represented by unique mapping F(p)=d. The inverse problem is much more complex and the inverse mapping p=G(d) is available in an analytical or closed form only exceptionally and generally it may not exist at all. Technically, both forward and inverse mapping F and G are sets of non-linear equations. ANNIT solves such situation as follows: (i) joint subspaces {pD, pM} of original data and model spaces D, M, resp. are searched for, within which the forward mapping F is sufficiently smooth that the inverse mapping G does exist, (ii) numerical approximation of G in subspaces {pD, pM} is found, (iii) candidate solution is predicted by using this numerical approximation. ANNIT is working in an iterative way in cycles. The subspaces {pD, pM} are searched for by generating suitable populations of individuals (models) covering data and model spaces. The approximation of the inverse mapping is made by using three methods: (a) linear regression, (b) Radial Basis Function Network technique, (c) linear prediction (also known as "Kriging"). The ANNIT algorithm has built in also an archive of already evaluated models. Archive models are re-used in a suitable way and thus the number of forward evaluations is minimized. ANNIT is now implemented both in MATLAB and SCILAB. Numerical tests show good

  11. 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…

  12. 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…

  13. 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"…

  14. Improving Intra Prediction in High-Efficiency Video Coding.

    PubMed

    Chen, Haoming; Zhang, Tao; Sun, Ming-Ting; Saxena, Ankur; Budagavi, Madhukar

    2016-08-01

    Intra prediction is an important tool in intra-frame video coding to reduce the spatial redundancy. In current coding standard H.265/high-efficiency video coding (HEVC), a copying-based method based on the boundary (or interpolated boundary) reference pixels is used to predict each pixel in the coding block to remove the spatial redundancy. We find that the conventional copying-based method can be further improved in two cases: 1) the boundary has an inhomogeneous region and 2) the predicted pixel is far away from the boundary that the correlation between the predicted pixel and the reference pixels is relatively weak. This paper performs a theoretical analysis of the optimal weights based on a first-order Gaussian Markov model and the effects when the pixel values deviate from the model and the predicted pixel is far away from the reference pixels. It also proposes a novel intra prediction scheme based on the analysis that smoothing the copying-based prediction can derive a better prediction block. Both the theoretical analysis and the experimental results show the effectiveness of the proposed intra prediction method. An average gain of 2.3% on all intra coding can be achieved with the HEVC reference software. PMID:27249831

  15. 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.

  16. Individual differences in infants' information processing: reliability, stability, and prediction.

    PubMed

    Rose, S A; Feldman, J F; Wallace, I F

    1988-10-01

    A group of 46 full-term and 54 high-risk preterm (less than 1,500 grams birthweight) infants were tested at 6, 7, and/or 8 months of age (corrected age for preterms) on a battery of problems assessing visual recognition memory and tactual-visual cross-modal transfer. At all 3 ages, scores obtained on aggregates of 6-11 problems in the battery significantly predicted 3-year Stanford-Binet IQ: correlations ranged from r = .37 to r = .63, and clustered between r = .50 and r = .60. When aggregates from 2 or 3 ages were used as predictors, multiple correlations were as high as R = .60 and R = .70. Cutoffs for predicting children at risk for mental retardation (IQ less than 70) or cognitive delay (IQ less than 85) showed reasonable sensitivity and specificity, although low scores were poor at detecting IQs less than 70. The internal consistency of composites, indexed by alpha coefficients, was unexpectedly low, primarily because the problems shared little variance. However, stability coefficients between assessments as much as 1 and 2 months apart were moderate in magnitude, ranging from r = .30 to r = .50. Considering the high degree of predictive validity, the stability figures appear to be better estimates of reliability for these measures than are indices of internal consistency. The relations reported here were similar for both full-terms and preterms. PMID:3168635

  17. 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. PMID:17552936

  18. Comparison of measured efficiencies of nine turbine designs with efficiencies predicted by two empirical methods

    NASA Technical Reports Server (NTRS)

    English, Robert E; Cavicchi, Richard H

    1951-01-01

    Empirical methods of Ainley and Kochendorfer and Nettles were used to predict performances of nine turbine designs. Measured and predicted performances were compared. Appropriate values of blade-loss parameter were determined for the method of Kochendorfer and Nettles. The measured design-point efficiencies were lower than predicted by as much as 0.09 (Ainley and 0.07 (Kochendorfer and Nettles). For the method of Kochendorfer and Nettles, appropriate values of blade-loss parameter ranged from 0.63 to 0.87 and the off-design performance was accurately predicted.

  19. Efficient Modelling and Prediction of Meshing Noise from Chain Drives

    NASA Astrophysics Data System (ADS)

    ZHENG, H.; WANG, Y. Y.; LIU, G. R.; LAM, K. Y.; QUEK, K. P.; ITO, T.; NOGUCHI, Y.

    2001-08-01

    This paper presents a practical approach for predicting the meshing noise due to the impact of chain rollers against the sprocket of chain drives. An acoustical model relating dynamic response of rollers and its induced sound pressure is developed based on the fact that the acoustic field is mainly created by oscillating rigid cylindrical rollers. Finite element techniques and numerical software codes are employed to model and simulate the acceleration response of each chain roller which is necessary for noise level prediction of a chain drive under varying operation conditions and different sprocket configurations. The predicted acoustic pressure levels of meshing noise are compared with the available experimental measurements. It is shown that the predictions are in reasonable agreement with the experiments and the approach enables designers to obtain required information on the noise level of a selected chain drive in a time- and cost-efficient manner.

  20. Individual differences in holistic processing predict face recognition ability.

    PubMed

    Wang, Ruosi; Li, Jingguang; Fang, Huizhen; Tian, Moqian; Liu, Jia

    2012-02-01

    Why do some people recognize faces easily and others frequently make mistakes in recognizing faces? Classic behavioral work has shown that faces are processed in a distinctive holistic manner that is unlike the processing of objects. In the study reported here, we investigated whether individual differences in holistic face processing have a significant influence on face recognition. We found that the magnitude of face-specific recognition accuracy correlated with the extent to which participants processed faces holistically, as indexed by the composite-face effect and the whole-part effect. This association is due to face-specific processing in particular, not to a more general aspect of cognitive processing, such as general intelligence or global attention. This finding provides constraints on computational models of face recognition and may elucidate mechanisms underlying cognitive disorders, such as prosopagnosia and autism, that are associated with deficits in face recognition. PMID:22222218

  1. Patient Characteristics Predicting Readmission Among Individuals Hospitalized for Heart Failure

    PubMed Central

    O'Connor, Melissa; Murtaugh, Christopher M.; Shah, Shivani; Barrón-Vaya, Yolanda; Bowles, Kathryn H.; Peng, Timothy R.; Zhu, Carolyn W.; Feldman, Penny H.

    2015-01-01

    Heart failure is difficult to manage and increasingly common with many individuals experiencing frequent hospitalizations. Little is known about patient factors consistently associated with hospital readmission. A literature review was conducted to identify heart failure patient characteristics, measured before discharge, that contribute to variation in hospital readmission rates. Database searches yielded 950 potential articles, of which 34 studies met inclusion criteria. Patient characteristics generally have a very modest effect on all-cause or heart failure–related readmission within 7 to 180 days of index hospital discharge. A range of cardiac diseases and other comorbidities only minimally increase readmission rates. No single patient characteristic stands out as a key contributor across multiple studies underscoring the challenge of developing successful interventions to reduce readmissions. Interventions may need to be general in design with the specific intervention depending on each patient's unique clinical profile. PMID:26180045

  2. 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.

  3. 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

  4. Individual Differences in Personality Predict How People Look at Faces

    PubMed Central

    Perlman, Susan B.; Morris, James P.; Vander Wyk, Brent C.; Green, Steven R.; Doyle, Jaime L.; Pelphrey, Kevin A.

    2009-01-01

    Background Determining the ways in which personality traits interact with contextual determinants to shape social behavior remains an important area of empirical investigation. The specific personality trait of neuroticism has been related to characteristic negative emotionality and associated with heightened attention to negative, emotionally arousing environmental signals. However, the mechanisms by which this personality trait may shape social behavior remain largely unspecified. Methodology/Principal Findings We employed eye tracking to investigate the relationship between characteristics of visual scanpaths in response to emotional facial expressions and individual differences in personality. We discovered that the amount of time spent looking at the eyes of fearful faces was positively related to neuroticism. Conclusions/Significance This finding is discussed in relation to previous behavioral research relating personality to selective attention for trait-congruent emotional information, neuroimaging studies relating differences in personality to amygdala reactivity to socially relevant stimuli, and genetic studies suggesting linkages between the serotonin transporter gene and neuroticism. We conclude that personality may be related to interpersonal interaction by shaping aspects of social cognition as basic as eye contact. In this way, eye gaze represents a possible behavioral link in a complex relationship between genes, brain function, and personality. PMID:19543398

  5. Individual Differences in Impulsivity Predict Anticipatory Eye Movements

    PubMed Central

    Cirilli, Laetitia; de Timary, Philippe; Lefèvre, Phillipe; Missal, Marcus

    2011-01-01

    Impulsivity is the tendency to act without forethought. It is a personality trait commonly used in the diagnosis of many psychiatric diseases. In clinical practice, impulsivity is estimated using written questionnaires. However, answers to questions might be subject to personal biases and misinterpretations. In order to alleviate this problem, eye movements could be used to study differences in decision processes related to impulsivity. Therefore, we investigated correlations between impulsivity scores obtained with a questionnaire in healthy subjects and characteristics of their anticipatory eye movements in a simple smooth pursuit task. Healthy subjects were asked to answer the UPPS questionnaire (Urgency Premeditation Perseverance and Sensation seeking Impulsive Behavior scale), which distinguishes four independent dimensions of impulsivity: Urgency, lack of Premeditation, lack of Perseverance, and Sensation seeking. The same subjects took part in an oculomotor task that consisted of pursuing a target that moved in a predictable direction. This task reliably evoked anticipatory saccades and smooth eye movements. We found that eye movement characteristics such as latency and velocity were significantly correlated with UPPS scores. The specific correlations between distinct UPPS factors and oculomotor anticipation parameters support the validity of the UPPS construct and corroborate neurobiological explanations for impulsivity. We suggest that the oculomotor approach of impulsivity put forth in the present study could help bridge the gap between psychiatry and physiology. PMID:22046334

  6. 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…

  7. 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…

  8. 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. PMID:25343279

  9. 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. PMID:23416541

  10. 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.

  11. 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.

  12. Prediction of 2-level PWM inverter efficiency using MATLAB/Simulink

    NASA Astrophysics Data System (ADS)

    Kim, Yoon-Ho; Kim, Seong-Je

    2015-10-01

    This article proposes a direct approach for the prediction of inverter efficiency using MATLAB/Simulink, instead of an indirect loss calculation approach based on analytical models. In analytical approach, efficiency is obtained by calculating individual losses separately, such as switching losses, conduction losses and harmonic losses using analytical models. However, this approach requires accurate analytical models and complicated calculations, due to the variation in the switching frequency, switching transient and modulation techniques. In the proposed approach, the actual waveform of the inverter system is directly generated using MATLAB/Simulink. The instantaneous voltage and current waveform including switching transients are generated. Thus, the proposed approach is very simple and convenient for efficiency prediction. The proposed approach also works for any system parameters or control methods, such as various pulse-width modulation (PWM) techniques, different switching frequencies, switching devices and load types. The proposed approach can be adopted for the efficiency prediction of any switching strategies and any types of inverters such as neutral-point-clamped (NPC) inverters, H bridge inverters and H5 topology, since the topologies are modelled as circuits in the MATLAB/Simulink program and no analytical model is required for the proposed approach. Furthermore, the proposed approach can provide operation techniques and conditions such as PWM techniques and switching frequency that offer high efficiency. In this article, inverter performance is evaluated for various PWM techniques and switching frequencies. The PWM technique and switching frequency that offer high efficiency is obtained. Finally, the proposed approach is verified by experimental results.

  13. 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.

  14. 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. PMID:22943555

  15. 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

  16. Predicting Individuals' Turnover and Internal Transfer Behavior. Wisconsin Working Paper 6-82-31.

    ERIC Educational Resources Information Center

    Taylor, M. Susan; Covaleski, Mark A.

    Researchers have spent considerable time and effort in the last 5 years developing process models to explain individuals' job turnover behavior. To examine the predictability of internal job transfers and turnover behavior from individuals' work values, career plans, and job satisfaction, nurses (N=160) completed questionnaires on demographic…

  17. 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

  18. Individual differences in activation of the parental care motivational system: assessment, prediction, and implications.

    PubMed

    Buckels, Erin E; Beall, Alec T; Hofer, Marlise K; Lin, Eden Y; Zhou, Zenan; Schaller, Mark

    2015-03-01

    We report on the development, validation, and utility of a measure assessing individual differences in activation of the parental care motivational system: The Parental Care and Tenderness (PCAT) questionnaire. Results from 1,608 adults (including parents and nonparents) show that the 25-item PCAT measure has high internal consistency, high test-retest reliability, high construct validity, and unique predictive utility. Among parents, it predicted self-child identity overlap and caring child-rearing attitudes; among nonparents, it predicted desire to have children. PCAT scores predicted the intensity of tender emotions aroused by infants, and also predicted the amount of time individuals chose look at infant (but not adult) faces. PCAT scores uniquely predicted additional outcomes in the realm of social perception, including mate preferences, moral judgments, and trait inferences about baby-faced adults. Practical and conceptual implications are discussed. PMID:25559194

  19. An unsteady aerodynamic formulation for efficient rotor tonal noise prediction

    NASA Astrophysics Data System (ADS)

    Gennaretti, M.; Testa, C.; Bernardini, G.

    2013-12-01

    An aerodynamic/aeroacoustic solution methodology for predction of tonal noise emitted by helicopter rotors and propellers is presented. It is particularly suited for configurations dominated by localized, high-frequency inflow velocity fields as those generated by blade-vortex interactions. The unsteady pressure distributions are determined by the sectional, frequency-domain Küssner-Schwarz formulation, with downwash including the wake inflow velocity predicted by a three-dimensional, unsteady, panel-method formulation suited for the analysis of rotors operating in complex aerodynamic environments. The radiated noise is predicted through solution of the Ffowcs Williams-Hawkings equation. The proposed approach yields a computationally efficient solution procedure that may be particularly useful in preliminary design/multidisciplinary optimization applications. It is validated through comparisons with solutions that apply the airloads directly evaluated by the time-marching, panel-method formulation. The results are provided in terms of blade loads, noise signatures and sound pressure level contours. An estimation of the computational efficiency of the proposed solution process is also presented.

  20. 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

  1. 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.

  2. 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

    2016-04-01

    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. PMID:27124457

  3. Prediction of Giant Thermoelectric Efficiency in Crystals with Interlaced Nanostructure.

    PubMed

    Puzyrev, Y S; Shen, X; Pantelides, S T

    2016-01-13

    We present a theoretical study of the thermoelectric efficiency of "interlaced crystals", recently discovered in hexagonal-CuInS2 nanoparticles. Interlaced crystals are I-III-VI2 or II-IV-V2 tetrahedrally bonded compounds. They have a perfect Bravais lattice in which the two cations have an infinite set of possible ordering patterns within the cation sublattice. The material comprises nanoscale interlaced domains and phases with corresponding boundaries. Here we employ density functional theory and large-scale molecular dynamics calculations based on model classical potentials to demonstrate that the phase and domain boundaries are effective phonon scatterers and greatly suppress thermal conductivity. However, the absence of both structural defects and strain in the interlaced material results in a minimal effect on electronic properties. We predict an increase of thermal resistivity of up to 2 orders of magnitude, which makes interlaced crystals an exceptional candidate for thermoelectric applications. PMID:26691292

  4. Individual differences in distraction by motion predicted by neural activity in MT/V5

    PubMed Central

    Lechak, Jennifer R.; Leber, Andrew B.

    2011-01-01

    Individuals differ substantially in their susceptibility to distraction by irrelevant visual information. Previous research has uncovered how individual variability in the goal-driven component of attentional control influences distraction, yet it remains unknown whether other sources of variability between individuals also predict distraction. In this fMRI study, we showed that an individual's inherent sensitivity to passively viewed visual motion predicts his/her susceptibility to distraction by motion. Bilateral MT/V5 was localized in participants during passive viewing of moving stimuli, affording a baseline measure of motion sensitivity. Next, participants performed a visual search task with an irrelevant motion singleton distractor, and both behavioral and neural indices of distraction were recorded. Results revealed that both of these indices were predicted by the independent index of motion sensitivity. An additional analysis of moment-to-moment fluctuations in distraction within individuals revealed that distraction could be predicted by pretrial fMRI activity in several brain regions, including MT+, which likely reflected the observer's momentary propensity to process motion. Together, these results shed light on how variability in factors other than goal-driven processing, both within and between individuals, affects attentional control and one's perception of the visual world. PMID:22375110

  5. Individual differences in spatial configuration learning predict the occurrence of intrusive memories.

    PubMed

    Meyer, Thomas; Smeets, Tom; Giesbrecht, Timo; Quaedflieg, Conny W E M; Girardelli, Marta M; Mackay, Georgina R N; Merckelbach, Harald

    2013-03-01

    The dual-representation model of posttraumatic stress disorder (PTSD; Brewin, Gregory, Lipton, & Burgess, Psychological Review, 117, 210-232 2010) argues that intrusions occur when people fail to construct context-based representations during adverse experiences. The present study tested a specific prediction flowing from this model. In particular, we investigated whether the efficiency of temporal-lobe-based spatial configuration learning would account for individual differences in intrusive experiences and physiological reactivity in the laboratory. Participants (N = 82) completed the contextual cuing paradigm, which assesses spatial configuration learning that is believed to depend on associative encoding in the parahippocampus. They were then shown a trauma film. Afterward, startle responses were quantified during presentation of trauma reminder pictures versus unrelated neutral and emotional pictures. PTSD symptoms were recorded in the week following participation. Better configuration learning performance was associated with fewer perceptual intrusions, r = -.33, p < .01, but was unrelated to physiological responses to trauma reminder images (ps > .46) and had no direct effect on intrusion-related distress and overall PTSD symptoms, rs > -.12, ps > .29. However, configuration learning performance tended to be associated with reduced physiological responses to unrelated negative images, r = -.20, p = .07. Thus, while spatial configuration learning appears to be unrelated to affective responding to trauma reminders, our overall findings support the idea that the context-based memory system helps to reduce intrusions. PMID:23001992

  6. Predicting individuals' learning success from patterns of pre-learning MRI activity.

    PubMed

    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

  7. 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. PMID:27288771

  8. 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. PMID:26595414

  9. Changes in Predicted Muscle Coordination with Subject-Specific Muscle Parameters for Individuals after Stroke

    PubMed Central

    Knarr, Brian A.; Reisman, Darcy S.; Binder-Macleod, Stuart A.; Higginson, Jill S.

    2014-01-01

    Muscle weakness is commonly seen in individuals after stroke, characterized by lower forces during a maximal volitional contraction. Accurate quantification of muscle weakness is paramount when evaluating individual performance and response to after stroke rehabilitation. The objective of this study was to examine the effect of subject-specific muscle force and activation deficits on predicted muscle coordination when using musculoskeletal models for individuals after stroke. Maximum force generating ability and central activation ratio of the paretic plantar flexors, dorsiflexors, and quadriceps muscle groups were obtained using burst superimposition for four individuals after stroke with a range of walking speeds. Two models were created per subject: one with generic and one with subject-specific activation and maximum isometric force parameters. The inclusion of subject-specific muscle data resulted in changes in the model-predicted muscle forces and activations which agree with previously reported compensation patterns and match more closely the timing of electromyography for the plantar flexor and hamstring muscles. This was the first study to create musculoskeletal simulations of individuals after stroke with subject-specific muscle force and activation data. The results of this study suggest that subject-specific muscle force and activation data enhance the ability of musculoskeletal simulations to accurately predict muscle coordination in individuals after stroke. PMID:25093141

  10. Optimal predictions in everyday cognition: the wisdom of individuals or crowds?

    PubMed

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

    2008-10-01

    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 averages over many individuals. On the conjecture that the accuracy of the group response is chiefly a consequence of aggregating across individuals, we constructed simple, heuristic approximations to the Bayesian model premised on the hypothesis that individuals have access merely to a sample of k instances drawn from the relevant distribution. The accuracy of the group response reported by Griffiths and Tenenbaum could be accounted for by supposing that individuals each utilize only two instances. Moreover, the variability of the group data is more consistent with this small-sample hypothesis than with the hypothesis that people utilize veridical or nearly veridical representations of the underlying prior distributions. Our analyses lead to a qualitatively different view of how individuals reason from past experience than the view espoused by Griffiths and Tenenbaum. PMID:21585446

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

    PubMed Central

    Eksborg, Staffan

    2013-01-01

    Objectives 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. Methods 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. Results 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. Conclusion 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.

  12. A modified Hill muscle model that predicts muscle power output and efficiency during sinusoidal length changes.

    PubMed

    Lichtwark, G A; Wilson, A M

    2005-08-01

    The power output of a muscle and its efficiency vary widely under different activation conditions. This is partially due to the complex interaction between the contractile component of a muscle and the serial elasticity. We investigated the relationship between power output and efficiency of muscle by developing a model to predict the power output and efficiency of muscles under varying activation conditions during cyclical length changes. A comparison to experimental data from two different muscle types suggests that the model can effectively predict the time course of force and mechanical energetic output of muscle for a wide range of contraction conditions, particularly during activation of the muscle. With fixed activation properties, discrepancies in the work output between the model and the experimental results were greatest at the faster and slower cycle frequencies than that for which the model was optimised. Further optimisation of the activation properties across each individual cycle frequency examined demonstrated that a change in the relationship between the concentration of the activator (Ca2+) and the activation level could account for these discrepancies. The variation in activation properties with speed provides evidence for the phenomenon of shortening deactivation, whereby at higher speeds of contraction the muscle deactivates at a faster rate. The results of this study demonstrate that predictions about the mechanics and energetics of muscle are possible when sufficient information is known about the specific muscle. PMID:16043588

  13. 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

  14. Content and activity of human liver microsomal protein and prediction of individual hepatic clearance in vivo

    PubMed Central

    Zhang, Haifeng; Gao, Na; Tian, Xin; Liu, Tingting; Fang, Yan; Zhou, Jun; Wen, Qiang; Xu, Binbin; Qi, Bing; Gao, Jie; Li, Hongmeng; Jia, Linjing; Qiao, Hailing

    2015-01-01

    The lack of information concerning individual variation in content and activity of human liver microsomal protein is one of the most important obstacles for designing personalized medicines. We demonstrated that the mean value of microsomal protein per gram of liver (MPPGL) was 39.46 mg/g in 128 human livers and up to 19-fold individual variations existed. Meanwhile, the metabolic activities of 10 cytochrome P450 (CYPs) were detected in microsomes and liver tissues, respectively, which showed huge individual variations (200-fold). Compared with microsomes, the activities of liver tissues were much suitable to express the individual variations of CYP activities. Furthermore, individual variations in the in vivo clearance of tolbutamide were successfully predicted with the individual parameter values. In conclusion, we offer the values for MPPGL contents in normal liver tissues and build a new method to assess the in vitro CYP activities. In addition, large individual variations exist in predicted hepatic clearance of tolbutamide. These findings provide important physiological parameters for physiologically-based pharmacokinetics models and thus, establish a solid foundation for future development of personalized medicines. PMID:26635233

  15. Enhancing Arithmetic and Word-Problem Solving Skills Efficiently by Individualized Computer-Assisted Practice

    ERIC Educational Resources Information Center

    Schoppek, Wolfgang; Tulis, Maria

    2010-01-01

    The fluency of basic arithmetical operations is a precondition for mathematical problem solving. However, the training of skills plays a minor role in contemporary mathematics instruction. The authors proposed individualization of practice as a means to improve its efficiency, so that the time spent with the training of skills is minimized. As a…

  16. Predicting lymph node output efficiency using systems biology

    PubMed Central

    Gong, Chang; Mattila, Joshua T.; Miller, Mark; Flynn, JoAnne L.; Linderman, Jennifer J.; Kirschner, D.

    2013-01-01

    Dendritic cells (DCs) capture pathogens and foreign antigen (Ag) in peripheral tissues and migrate to secondary lymphoid tissues, such as lymph nodes (LNs), where they present processed Ag as MHC-bound peptide (pMHC) to naïve T cells. Interactions between DCs and T cells result, over periods of hours, in activation, clonal expansion and differentiation of antigen-specific T cells, leading to primed cells that can now participate in immune responses. Two-photon microscopy (2PM) has been widely adopted to analyze lymphocyte dynamics and can serve as a powerful in vivo assay for cell trafficking and activation over short length and time scales. Linking biological phenomena between vastly different spatiotemporal scales can be achieved using a systems biology approach. We developed a 3D agent-based cellular model of a LN that allows for the simultaneous in silico simulation of T cell trafficking, activation and production of effector cells under different antigen (Ag) conditions. The model anatomy is based on in situ analysis of LN sections (from primates and mice) and cell dynamics based on quantitative measurements from 2PM imaging of mice. Our simulations make three important predictions. First, T cell encounters by DCs and T cell receptor (TCR) repertoire scanning are more efficient in a 3D model compared with 2D, suggesting that a 3D model is needed to analyze LN function. Second, LNs are able to produce primed CD4+T cells at the same efficiency over broad ranges of cognate frequencies (from 10−5 to 10−2). Third, reducing the time that naïve T cells are required to bind DCs before becoming activated will increase the rate at which effector cells are produced. This 3D model provides a robust platform to study how T cell trafficking and activation dynamics relate to the efficiency of T cell priming and clonal expansion. We envision that this systems biology approach will provide novel insights for guiding vaccine development and understanding immune responses

  17. 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…

  18. 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…

  19. Individual differences and the neural representations of reward expectation and reward prediction error

    PubMed Central

    2007-01-01

    Reward expectation and reward prediction errors are thought to be critical for dynamic adjustments in decision-making and reward-seeking behavior, but little is known about their representation in the brain during uncertainty and risk-taking. Furthermore, little is known about what role individual differences might play in such reinforcement processes. In this study, it is shown behavioral and neural responses during a decision-making task can be characterized by a computational reinforcement learning model and that individual differences in learning parameters in the model are critical for elucidating these processes. In the fMRI experiment, subjects chose between high- and low-risk rewards. A computational reinforcement learning model computed expected values and prediction errors that each subject might experience on each trial. These outputs predicted subjects’ trial-to-trial choice strategies and neural activity in several limbic and prefrontal regions during the task. Individual differences in estimated reinforcement learning parameters proved critical for characterizing these processes, because models that incorporated individual learning parameters explained significantly more variance in the fMRI data than did a model using fixed learning parameters. These findings suggest that the brain engages a reinforcement learning process during risk-taking and that individual differences play a crucial role in modeling this process. PMID:17710118

  20. 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

  1. Predicting shifts in dynamics of cannibalistic field populations using individual-based models.

    PubMed

    Persson, Lennart; de Roos, André M; Bertolo, Andrea

    2004-12-01

    The occurrence of qualitative shifts in population dynamical regimes has long been the focus of population biologists. Nonlinear ecological models predict that these shifts in dynamical regimes may occur as a result of parameter shifts, but unambiguous empirical evidence is largely restricted to laboratory populations. We used an individual-based modelling approach to predict dynamical shifts in field fish populations where the capacity to cannibalize differed between species. Model-generated individual growth trajectories that reflect different population dynamics were confronted with empirically observed growth trajectories, showing that our ordering and quantitative estimates of the different cannibalistic species in terms of life-history characteristics led to correct qualitative predictions of their dynamics. PMID:15590600

  2. Left anterior cingulate activity predicts intra-individual reaction time variability in healthy adults.

    PubMed

    Johnson, Beth P; Pinar, Ari; Fornito, Alex; Nandam, L Sanjay; Hester, Robert; Bellgrove, Mark A

    2015-06-01

    Within-subject, or intra-individual, variability in reaction time (RT) is increasingly recognised as an important indicator of the efficiency of attentional control, yet there have been few investigations of the neural correlates of trial-to-trial RT variability in healthy adults. We sought to determine the neural correlates of intra-individual RT variability during a go/no-go response inhibition task in 27 healthy, male participants. We found that reduced trial-to-trial RT variability (i.e. greater response stability) was significantly associated with greater activation in the left pregenual anterior cingulate. These results support the role of the left anterior cingulate in the dynamic control of attention and efficient response selection. Greater understanding of intra-individual RT variability and top-down attentional control in healthy adults may help to inform disorders that impact executive/attentional control, such as attention deficit hyperactivity disorder and schizophrenia. PMID:25791710

  3. 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. PMID:22179807

  4. 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. PMID:25642722

  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. PMID:20561339

  6. Multi-prediction particle filter for efficient parallelized implementation

    NASA Astrophysics Data System (ADS)

    Chu, Chun-Yuan; Chao, Chih-Hao; Chao, Min-An; Wu, An-Yeu Andy

    2011-12-01

    Particle filter (PF) is an emerging signal processing methodology, which can effectively deal with nonlinear and non-Gaussian signals by a sample-based approximation of the state probability density function. The particle generation of the PF is a data-independent procedure and can be implemented in parallel. However, the resampling procedure in the PF is a sequential task in natural and difficult to be parallelized. Based on the Amdahl's law, the sequential portion of a task limits the maximum speed-up of the parallelized implementation. Moreover, large particle number is usually required to obtain an accurate estimation, and the complexity of the resampling procedure is highly related to the number of particles. In this article, we propose a multi-prediction (MP) framework with two selection approaches. The proposed MP framework can reduce the required particle number for target estimation accuracy, and the sequential operation of the resampling can be reduced. Besides, the overhead of the MP framework can be easily compensated by parallel implementation. The proposed MP-PF alleviates the global sequential operation by increasing the local parallel computation. In addition, the MP-PF is very suitable for multi-core graphics processing unit (GPU) platform, which is a popular parallel processing architecture. We give prototypical implementations of the MP-PFs on multi-core GPU platform. For the classic bearing-only tracking experiments, the proposed MP-PF can be 25.1 and 15.3 times faster than the sequential importance resampling-PF with 10,000 and 20,000 particles, respectively. Hence, the proposed MP-PF can enhance the efficiency of the parallelization.

  7. 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. PMID:26776214

  8. Value signals in the prefrontal cortex predict individual preferences across reward categories.

    PubMed

    Gross, Jörg; Woelbert, Eva; Zimmermann, Jan; Okamoto-Barth, Sanae; Riedl, Arno; Goebel, Rainer

    2014-05-28

    Humans can choose between fundamentally different options, such as watching a movie or going out for dinner. According to the utility concept, put forward by utilitarian philosophers and widely used in economics, this may be accomplished by mapping the value of different options onto a common scale, independent of specific option characteristics (Fehr and Rangel, 2011; Levy and Glimcher, 2012). If this is the case, value-related activity patterns in the brain should allow predictions of individual preferences across fundamentally different reward categories. We analyze fMRI data of the prefrontal cortex while subjects imagine the pleasure they would derive from items belonging to two distinct reward categories: engaging activities (like going out for drinks, daydreaming, or doing sports) and snack foods. Support vector machines trained on brain patterns related to one category reliably predict individual preferences of the other category and vice versa. Further, we predict preferences across participants. These findings demonstrate that prefrontal cortex value signals follow a common scale representation of value that is even comparable across individuals and could, in principle, be used to predict choice. PMID:24872562

  9. Can the Foot Posture Index or their individual criteria predict dynamic plantar pressures?

    PubMed

    Sánchez-Rodríguez, Raquel; Martínez-Nova, Alfonso; Escamilla-Martínez, Elena; Pedrera-Zamorano, Juan Diego

    2012-07-01

    The Foot Posture Index (FPI) quantifies foot posture through the evaluation of six individual criteria. The objective of the present study was then to establish the plantar pressure differences between types of feet, and to study the capacity of the whole FPI value and the six individual criteria to predict the pattern of plantar pressures. In a sample of 400 healthy subjects (201 men and 199 women), the FPI was evaluated and plantar pressures were measured in 10 zones using the Footscan(®) platform. Five plantar pressures measurements were made for each foot, using for the study the mean of these measurements for each subject's left foot. The hallux and the lesser toes had lower pressure indices in highly supinated feet, with the values increasing progressively toward the highly pronated feet (p<0.001 and p=0.019 respectively). The fifth metatarsal head (MTH) values were greater in highly supinated feet, and decreased in the highly pronated feet (p<0.001). The FPI value predicts low variability of plantar pressures, mainly in the heel and midfoot, while the individual criteria predict higher variability in the forefoot. The talonavicular prominence and the calcaneal frontal plane position was the most influential criterion, explaining 8.5% of the hallux pressure and 11.1% of the fifth MTH pressure. Neither talar head palpation nor the supra and infra malleolar curvature predicted any of the plantar pressures variables. The FPI can distinguish three groups of feet--pronated, neutral, and supinated. Its individual criteria predict moderate or low plantar pressures variability, with the talonavicular prominence being the most influential criterion. PMID:22727718

  10. 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.

  11. Individual risk of cutaneous melanoma in New Zealand: developing a clinical prediction aid

    PubMed Central

    2014-01-01

    Background New Zealand and Australia have the highest melanoma incidence rates worldwide. In New Zealand, both the incidence and thickness have been increasing. Clinical decisions require accurate risk prediction but a simple list of genetic, phenotypic and behavioural risk factors is inadequate to estimate individual risk as the risk factors for melanoma have complex interactions. In order to offer tailored clinical management strategies, we developed a New Zealand prediction model to estimate individual 5-year absolute risk of melanoma. Methods A population-based case–control study (368 cases and 270 controls) of melanoma risk factors provided estimates of relative risks for fair-skinned New Zealanders aged 20–79 years. Model selection techniques and multivariate logistic regression were used to determine the important predictors. The relative risks for predictors were combined with baseline melanoma incidence rates and non-melanoma mortality rates to calculate individual probabilities of developing melanoma within 5 years. Results For women, the best model included skin colour, number of moles > =5 mm on the right arm, having a 1st degree relative with large moles, and a personal history of non-melanoma skin cancer (NMSC). The model correctly classified 68% of participants; the C-statistic was 0.74. For men, the best model included age, place of occupation up to age 18 years, number of moles > =5 mm on the right arm, birthplace, and a history of NMSC. The model correctly classified 67% of cases; the C-statistic was 0.71. Conclusions We have developed the first New Zealand risk prediction model that calculates individual absolute 5-year risk of melanoma. This model will aid physicians to identify individuals at high risk, allowing them to individually target surveillance and other management strategies, and thereby reduce the high melanoma burden in New Zealand. PMID:24884419

  12. 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

  13. Healthy individuals maintain adaptive stimulus evaluation under predictable and unpredictable threat.

    PubMed

    Klinkenberg, Isabelle A G; Rehbein, Maimu A; Steinberg, Christian; Klahn, Anna Luisa; Zwanzger, Peter; Zwitserlood, Pienie; Junghöfer, Markus

    2016-08-01

    The anxiety inducing paradigms such as the threat-of-shock paradigm have provided ample data on the emotional processing of predictable and unpredictable threat, but little is known about the processing of aversive, threat-irrelevant stimuli in these paradigms. We investigated how the predictability of threat influences the neural visual processing of threat-irrelevant fearful and neutral faces. Thirty-two healthy individuals participated in an NPU-threat test, consisting of a safe or neutral condition (N) and a predictable (P) as well as an unpredictable (U) threat condition, using audio-visual threat stimuli. In all NPU-conditions, we registered participants' brain responses to threat-irrelevant faces via magnetoencephalography. The data showed that increasing unpredictability of threat evoked increasing emotion regulation during face processing predominantly in dorsolateral prefrontal cortex regions during an early to mid-latency time interval. Importantly, we obtained only main effects but no significant interaction of facial expression and conditions of different threat predictability, neither in behavioral nor in neural data. Healthy individuals with average trait anxiety are thus able to maintain adaptive stimulus evaluation processes under predictable and unpredictable threat conditions. PMID:27208859

  14. Ecological rationality or nested sets? Individual differences in cognitive processing predict Bayesian reasoning.

    PubMed

    Sirota, Miroslav; Juanchich, Marie; Hagmayer, York

    2014-02-01

    The presentation of a Bayesian inference problem in terms of natural frequencies rather than probabilities has been shown to enhance performance. The effect of individual differences in cognitive processing on Bayesian reasoning has rarely been studied, despite enabling us to test process-oriented variants of the two main accounts of the facilitative effect of natural frequencies: The ecological rationality account (ERA), which postulates an evolutionarily shaped ease of natural frequency automatic processing, and the nested sets account (NSA), which posits analytical processing of nested sets. In two experiments, we found that cognitive reflection abilities predicted normative performance equally well in tasks featuring whole and arbitrarily parsed objects (Experiment 1) and that cognitive abilities and thinking dispositions (analytical vs. intuitive) predicted performance with single-event probabilities, as well as natural frequencies (Experiment 2). Since these individual differences indicate that analytical processing improves Bayesian reasoning, our findings provide stronger support for the NSA than for the ERA. PMID:23794254

  15. Using individual differences to predict job performance: correcting for direct and indirect restriction of range.

    PubMed

    Sjöberg, Sofia; Sjöberg, Anders; Näswall, Katharina; Sverke, Magnus

    2012-08-01

    The present study investigates the relationship between individual differences, indicated by personality (FFM) and general mental ability (GMA), and job performance applying two different methods of correction for range restriction. The results, derived by analyzing meta-analytic correlations, show that the more accurate method of correcting for indirect range restriction increased the operational validity of individual differences in predicting job performance and that this increase primarily was due to general mental ability being a stronger predictor than any of the personality traits. The estimates for single traits can be applied in practice to maximize prediction of job performance. Further, differences in the relative importance of general mental ability in relation to overall personality assessment methods was substantive and the estimates provided enables practitioners to perform a correct utility analysis of their overall selection procedure. PMID:22612634

  16. Predicting the clinical effect of a short acting bronchodilator in individual patients using artificial neural networks.

    PubMed

    de Matas, Marcel; Shao, Qun; Biddiscombe, Martyn F; Meah, Sally; Chrystyn, Henry; Usmani, Omar S

    2010-12-23

    Artificial neural networks were used in this study to model the relationships between in vitro data, subject characteristics and in vivo outcomes from N=18 mild-moderate asthmatics receiving monodisperse salbutamol sulphate aerosols of 1.5, 3 and 6 μm mass median aerodynamic diameter in a cumulative dosing schedule of 10, 20, 40 and 100 μg. Input variables to the model were aerodynamic particle size (APS), body surface area (BSA), age, pre-treatment forced expiratory volume in one-second (FEV(1)), forced vital capacity, cumulative emitted drug dose and bronchodilator reversibility to a standard salbutamol sulphate 200 μg dose MDI (REV(%)). These factors were used by the model to predict the bronchodilator response at 10 (T10) and 20 (T20) min after receiving each of the 4 doses for each of the 3 different particle sizes. Predictability was assessed using data from selected patients in this study, which were set aside and not used in model generation. Models reliably predicted ΔFEV(1)(%) in individual subjects with non-linear determinants (R(2)) of ≥ 0.8. The average error between predicted and observed ΔFEV(1)(%) for individual subjects was <4% across the cumulative dosing regimen. Increases in APS and drug dose gave improved ΔFEV(1)(%). Models also showed trends towards improved responses in younger patients and those having greater REV(%), whilst BSA was also shown to influence clinical effect. These data show that APS can be used to discriminate predictably between aerosols giving different bronchodilator responses across a cumulative dosing schedule, whilst patient characteristics can be used to reliably estimate clinical response in individual subjects. PMID:20932900

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

    PubMed

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

    2010-07-15

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

  18. 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

  19. Group decisions and individual differences: route fidelity predicts flight leadership in homing pigeons (Columba livia)

    PubMed Central

    Freeman, Robin; Mann, Richard; Guilford, Tim; Biro, Dora

    2011-01-01

    How social-living animals make collective decisions is currently the subject of intense scientific interest, with increasing focus on the role of individual variation within the group. Previously, we demonstrated that during paired flight in homing pigeons, a fully transitive leadership hierarchy emerges as birds are forced to choose between their own and their partner's habitual routes. This stable hierarchy suggests a role for individual differences mediating leadership decisions within homing pigeon pairs. What these differences are, however, has remained elusive. Using novel quantitative techniques to analyse habitual route structure, we show here that leadership can be predicted from prior route-following fidelity. Birds that are more faithful to their own route when homing alone are more likely to emerge as leaders when homing socially. We discuss how this fidelity may relate to the leadership phenomenon, and propose that leadership may emerge from the interplay between individual route confidence and the dynamics of paired flight. PMID:20810431

  20. Individual Differences in Anterior Cingulate Activation Associated with Attentional Bias Predict Cocaine Use After Treatment

    PubMed Central

    Marhe, Reshmi; Luijten, Maartje; van de Wetering, Ben J M; Smits, Marion; Franken, Ingmar H A

    2013-01-01

    Drug-dependent patients often relapse into drug use after treatment. Behavioral studies show that enhanced attentional bias to drug cues is a precursor of relapse. The present functional magnetic resonance imaging (fMRI) study examined whether brain regions involved in attentional bias are predictive of cocaine use after treatment. Attentional bias-related brain activity was measured—with a cocaine Stroop task—in cocaine-dependent patients during their first week in detoxification treatment and was used to predict cocaine use at 3-month follow-up. The predictive value of attentional bias-related brain activity in a priori defined regions of interest, in addition to other measures such as self-reports of substance severity, craving, and behavioral attentional bias were examined. The results show that craving in the week before treatment and individual variability in attentional bias-related activity in the dorsal anterior cingulate cortex (dACC) were significant predictors of days of cocaine use at 3-month follow-up and accounted for 45% in explained variance. Brain activity in the dACC uniquely contributed 22% of explained variance to the prediction model. These findings suggest that hyperactive attentional bias-related brain activity in the dACC might be a biomarker of relapse vulnerability as early as in the first week of detoxification treatment. Ultimately, this may help to develop individually tailored treatment interventions to reduce relapse risk. PMID:23303067

  1. 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

  2. Predicting sexual infidelity in a population-based sample of married individuals.

    PubMed

    Whisman, Mark A; Gordon, Kristina Coop; Chatav, Yael

    2007-06-01

    Predictors of 12-month prevalence of sexual infidelity were examined in a population-based sample of married individuals (N = 2,291). Predictor variables were organized in terms of involved-partner (e.g., personality, religiosity), marital (e.g., marital dissatisfaction, partner affair), and extradyadic (e.g., parenting) variables. Annual prevalence of infidelity was 2.3%. Controlling for marital dissatisfaction and demographic variables, infidelity was predicted by greater neuroticism and lower religiosity; wives' pregnancy also increased the risk of infidelity for husbands. In comparison, self-esteem and partners' suspected affair were predictive of infidelity when controlling for demographic variables but were not uniquely predictive of infidelity when also controlling for marital dissatisfaction. Religiosity and wives' pregnancy moderated the association between marital dissatisfaction and infidelity. PMID:17605555

  3. 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. PMID:20703629

  4. 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

  5. Individual prediction of treatment outcome in patients with temporomandibular disorders. A quality improvement model.

    PubMed

    Sundqvist, Bertil

    2007-01-01

    The general aim of this thesis was to create and evaluate a quality improvement model for prediction of treatment outcome in patients diagnosed with Temporomandibular Disorders (TMD) of either Muscle or Mainly TMJ (Temporomandibular Joint) origin, treated with interocclusal appliances and/or occlusal adjustment. The model was assumed to generate negative predictors of treatment outcome through evaluating all patients predicted Good reaching an objective treatment goal but not having an improvement of 50% or more. The model was created and evaluated by one TMD specialist. The questions were: (I) Was it possible for the TMD specialist to predict treatment outcome individually in patients diagnosed with TMD and, from the results, create a quality improvement model? (II) Was it possible for eight TMD-trained general dental practitioners, under the supervision of the TMD specialist, to treat TMD patients with similar results to the TMD specialist if the TMD specialist had examined, treatment planned, and individually predicted the treatment outcome? (III) Was it possible for the TMD specialist to improve the possibility to predict individual treatment outcome overtime? (IV) Was it possible for one TMD-trained general dental practitioner to copy the clinical part of the model and achieve the same results as the TMD specialist, in patients selected by the TMD specialist? Out of 5165 patients subjected to a functional examination of the masticatory system, 3602 were diagnosed with TMD and subgrouped as either Muscle or Mainly TMJ symptoms. The patients were predicted to have a Good, Dubious, or Poor possibility to have an improvement of 50% or more after treatment. Patients predicted Poor were not offered any treatment. A correct prediction of actual treatment outcome Good was defined as an improvement of 50% or more for muscle and/or TMJ symptoms. A total of 2625 patients began treatment at the specialist clinic for TMD and 2128 completed the full course of treatment. The

  6. Efficiency test of earthquake prediction around Thessaloniki from electrotelluric precursors

    NASA Astrophysics Data System (ADS)

    Meyer, K.; Varotsos, P.; Alexopoulos, K.; Nomicos, K.

    1985-11-01

    Since the completion of the network in January 1983, the electric field of the earth has been continuously monitored at four sites near Thessaloniki, the capital of northern Greece. From the present study and from previous investigations by similar measurements in Greece, it is evident that transient changes of the electrotelluric field occur prior to earthquakes. The analysis of these electric forerunners leads in many cases to a successful prediction of the epicentral area, the magnitude and the time of the impending event. Predictions prior to regional earthquakes are issued and documented with telegrams. From November 1983 until the end of May 1984 twelve earthquakes ( M L > 3.5 ) occurred in the vicinity of Thessaloniki. Ten of these were predicted and warnings given by telegram, whereas two smaller seismic events were missed. Two additional predictions were unsuccessful. Independent of their magnitudes, predicted events took place within a time window of 6 hrs to 6 days after the observations of the electrotelluric anomalies. The accuracy of the predicted epicenters in eight cases is better than 100 km, which corresponds roughly to the mean distance between the electric stations. Magnitude estimates deviate by less than 0.5 magnitude units from the seismically observed ones. Considering the two largest earthquakes, it is shown that the probability of making each of these predictions by chance is of the order of 10 -2.

  7. Practical prediction model for the risk of 2-year mortality of individuals in the general population.

    PubMed

    Goldfarb-Rumyantzev, Alexander; Gautam, Shiva; Brown, Robert S

    2016-04-01

    This study proposed to validate a prediction model and risk-stratification tool of 2-year mortality rates of individuals in the general population suitable for office practice use. A risk indicator (R) derived from data in the literature was based on only 6 variables: to calculate R for an individual, starting with 0, for each year of age above 60, add 0.14; for a male, add 0.9; for diabetes mellitus, add 0.7; for albuminuria >30 mg/g of creatinine, add 0.7; for stage ≥3 chronic kidney disease (CKD), add 0.9; for cardiovascular disease (CVD), add 1.4; or for both CKD and CVD, add 1.7. We developed a univariate logistic regression model predicting 2-year individual mortality rates. The National Health and Nutrition Examination Survey (NHANES) data set (1999-2004 with deaths through 2006) was used as the target for validation. These 12,515 subjects had a mean age of 48.9±18.1 years, 48% males, 9.5% diabetes, 11.7% albuminuria, 6.8% CVD, 5.4% CKD, and 2.8% both CKD and CVD. Using the risk indicator R alone to predict mortality demonstrated good performance with area under the receiver operating characteristic (ROC) curve of 0.84. Dividing subjects into low-risk (R=0-1.0), low intermediate risk (R>1.0-3.0), high intermediate risk (R>3.0-5.0) or high-risk (R>5.0) categories predicted 2-year mortality rates of 0.52%, 1.44%, 5.19% and 15.24%, respectively, by the prediction model compared with actual mortality rates of 0.29%, 2.48%, 5.13% and 13.40%, respectively. We have validated a model of risk stratification using easily identified clinical characteristics to predict 2-year mortality rates of individuals in the general population. The model demonstrated performance adequate for its potential use for clinical practice and research decisions. PMID:26951378

  8. Predicting the Efficiency of Photoswitches Using Force Analysis.

    PubMed

    Stauch, Tim; Dreuw, Andreas

    2016-04-01

    Photoswitches convert light into mechanical energy by exerting forces on their environment during photoisomerization. However, the mechanical efficiency of this conversion is limited because a plethora of internal modes of the photoswitch do not contribute to the desired switching function but are also changed during the photoisomerization. Here we present a computational approach to quantify the efficiency of a photoswitch during the initial motion on the excited-state potential energy surface. We demonstrate the gist of our method by looking at the excited-state relaxation of carbon monoxide. Subsequently, the photoswitching efficiency of p-coumaric acid is analyzed as one representative example of the approach. PMID:27003338

  9. 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. PMID:26813241

  10. 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. PMID:25193945

  11. 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

  12. Efficient Gaussian Process-Based Modelling and Prediction of Image Time Series.

    PubMed

    Lorenzi, Marco; Ziegler, Gabriel; Alexander, Daniel C; Ourselin, Sebastien

    2015-01-01

    In this work we propose a novel Gaussian process-based spatio-temporal model of time series of images. By assuming separability of spatial and temporal processes we provide a very efficient and robust formulation for the marginal likelihood computation and the posterior prediction. The model adaptively accounts for local spatial correlations of the data, and the covariance structure is effectively parameterised by the Kronecker product of covariance matrices of very small size, each encoding only a single direction in space. We provide a simple and flexible framework for within- and between-subject modelling and prediction. In particular, we introduce the Hoffman-Ribak method for efficient inference on posterior processes and its uncertainty. The proposed framework is applied in the context of longitudinal modelling in Alzheimer's disease. We firstly demonstrate the advantage of our non-parametric method for modelling of within-subject structural changes. The results show that non-parametric methods demonstrably outperform conventional parametric methods. Then the framework is extended to optimize complex parametrized covariate kernels. Using Bayesian model comparison via marginal likelihood the framework enables to compare different hypotheses about individual change processes of images. PMID:26221708

  13. 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

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

    PubMed

    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

  15. Prediction of driving safety in individuals with homonymous hemianopia and quadrantanopia from clinical neuroimaging.

    PubMed

    Vaphiades, Michael S; Kline, Lanning B; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M

    2014-01-01

    Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from -0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions. PMID:24683493

  16. Prediction of Driving Safety in Individuals with Homonymous Hemianopia and Quadrantanopia from Clinical Neuroimaging

    PubMed Central

    Vaphiades, Michael S.; Kline, Lanning B.; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M.

    2014-01-01

    Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from −0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions. PMID:24683493

  17. Individual Differences in Childhood Sleep Problems Predict Later Cognitive Executive Control

    PubMed Central

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

    2009-01-01

    Study Objective: 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. Participants: 916 twins (465 female, 451 male) and parents from the Colorado Longitudinal Twin Study. Measurements and Results: 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 ~70% of children having ≥ 1 problem at age 4 and ~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). Conclusions: 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. Citation: Friedman NP; Corley RP; Hewitt JK; Wright KP. Individual differences in childhood sleep problems predict later cognitive executive control. SLEEP 2009;32(3):323-333. PMID:19294952

  18. 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

  19. Efficient Prediction of Co-Complexed Proteins Based on Coevolution

    PubMed Central

    de Vienne, Damien M.; Azé, Jérôme

    2012-01-01

    The prediction of the network of protein-protein interactions (PPI) of an organism is crucial for the understanding of biological processes and for the development of new drugs. Machine learning methods have been successfully applied to the prediction of PPI in yeast by the integration of multiple direct and indirect biological data sources. However, experimental data are not available for most organisms. We propose here an ensemble machine learning approach for the prediction of PPI that depends solely on features independent from experimental data. We developed new estimators of the coevolution between proteins and combined them in an ensemble learning procedure. We applied this method to a dataset of known co-complexed proteins in Escherichia coli and compared it to previously published methods. We show that our method allows prediction of PPI with an unprecedented precision of 95.5% for the first 200 sorted pairs of proteins compared to 28.5% on the same dataset with the previous best method. A close inspection of the best predicted pairs allowed us to detect new or recently discovered interactions between chemotactic components, the flagellar apparatus and RNA polymerase complexes in E. coli. PMID:23152796

  20. Towards a comprehensive model for predicting the quality of individual visual experience

    NASA Astrophysics Data System (ADS)

    Zhu, Yi; Heynderickx, Ingrid; Hanjalic, Alan; Redi, Judith A.

    2015-03-01

    Recently, a lot of effort has been devoted to estimating the Quality of Visual Experience (QoVE) in order to optimize video delivery to the user. For many decades, existing objective metrics mainly focused on estimating the perceived quality of a video, i.e., the extent to which artifacts due to e.g. compression disrupt the appearance of the video. Other aspects of the visual experience, such as enjoyment of the video content, were, however, neglected. In addition, typically Mean Opinion Scores were targeted, deeming the prediction of individual quality preferences too hard of a problem. In this paper, we propose a paradigm shift, and evaluate the opportunity of predicting individual QoVE preferences, in terms of video enjoyment as well as perceived quality. To do so, we explore the potential of features of different nature to be predictive for a user's specific experience with a video. We consider thus not only features related to the perceptual characteristics of a video, but also to its affective content. Furthermore, we also integrate in our framework the information about the user and use context. The results show that effective feature combinations can be identified to estimate the QoVE from the perspective of both the enjoyment and perceived quality.

  1. 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

  2. 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. PMID:24366051

  3. Lexical familiarity and processing efficiency: individual differences in naming, lexical decision, and semantic categorization.

    PubMed

    Lewellen, M J; Goldinger, S D; Pisoni, D B; Greene, B G

    1993-09-01

    College students were separated into 2 groups (high and low) on the basis of 3 measures: subjective familiarity ratings of words, self-reported language experiences, and a test of vocabulary knowledge. Three experiments were conducted to determine if the groups also differed in visual word naming, lexical decision, and semantic categorization. High Ss were consistently faster than low Ss in naming visually presented words. They were also faster and more accurate in making difficult lexical decisions and in rejecting homophone foils in semantic categorization. Taken together, the results demonstrate that Ss who differ in lexical familiarity also differ in processing efficiency. The relationship between processing efficiency and working memory accounts of individual differences in language processing is also discussed. PMID:8371087

  4. 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

  5. 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.

  6. Frontolimbic Neural Circuitry at 6 Months Predicts Individual Differences in Joint Attention at 9 Months

    PubMed Central

    Elison, Jed T.; Wolff, Jason J.; Heimer, Debra C.; Paterson, Sarah J.; Gu, Hongbin; Hazlett, Heather C.; Styner, Martin; Gerig, Guido; Piven, Joseph

    2012-01-01

    Elucidating the neural basis of joint attention in infancy promises to yield important insights into the development of language and social cognition, and directly informs developmental models of autism. We describe a new method for evaluating responding to joint attention performance in infancy that highlights the 9 to 10 month period as a time interval of maximal individual differences. We then demonstrate that fractional anisotropy in the right uncinate fasciculus, a white matter fiber bundle connecting the amygdala to the ventral-medial prefrontal cortex and anterior temporal pole, measured in 6 month-olds predicts individual differences in responding to joint attention at 9 months of age. The white matter microstructure of the right uncinate was not related to receptive language ability at 9 months. These findings suggest that the development of core nonverbal social communication skills in infancy is largely supported by preceding developments within right lateralized frontotemporal brain systems. PMID:23432829

  7. 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. PMID:24813571

  8. Frontolimbic neural circuitry at 6 months predicts individual differences in joint attention at 9 months.

    PubMed

    Elison, Jed T; Wolff, Jason J; Heimer, Debra C; Paterson, Sarah J; Gu, Hongbin; Hazlett, Heather C; Styner, Martin; Gerig, Guido; Piven, Joseph

    2013-03-01

    Elucidating the neural basis of joint attention in infancy promises to yield important insights into the development of language and social cognition, and directly informs developmental models of autism. We describe a new method for evaluating responding to joint attention performance in infancy that highlights the 9- to 10-month period as a time interval of maximal individual differences. We then demonstrate that fractional anisotropy in the right uncinate fasciculus, a white matter fiber bundle connecting the amygdala to the ventral-medial prefrontal cortex and anterior temporal pole, measured in 6-month-olds predicts individual differences in responding to joint attention at 9 months of age. The white matter microstructure of the right uncinate was not related to receptive language ability at 9 months. These findings suggest that the development of core nonverbal social communication skills in infancy is largely supported by preceding developments within right lateralized frontotemporal brain systems. PMID:23432829

  9. 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.

  10. 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

  11. Improving Neural Network Prediction Accuracy for PM10 Individual Air Quality Index Pollution Levels

    PubMed Central

    Feng, Qi; Wu, Shengjun; Du, Yun; Xue, Huaiping; Xiao, Fei; Ban, Xuan; Li, Xiaodong

    2013-01-01

    Abstract Fugitive dust deriving from construction sites is a serious local source of particulate matter (PM) that leads to air pollution in cities undergoing rapid urbanization in China. In spite of this fact, no study has yet been published relating to prediction of high levels of PM with diameters <10 μm (PM10) as adjudicated by the Individual Air Quality Index (IAQI) on fugitive dust from nearby construction sites. To combat this problem, the Construction Influence Index (Ci) is introduced in this article to improve forecasting models based on three neural network models (multilayer perceptron, Elman, and support vector machine) in predicting daily PM10 IAQI one day in advance. To obtain acceptable forecasting accuracy, measured time series data were decomposed into wavelet representations and wavelet coefficients were predicted. Effectiveness of these forecasters were tested using a time series recorded between January 1, 2005, and December 31, 2011, at six monitoring stations situated within the urban area of the city of Wuhan, China. Experimental trials showed that the improved models provided low root mean square error values and mean absolute error values in comparison to the original models. In addition, these improved models resulted in higher values of coefficients of determination and AHPC (the accuracy rate of high PM10 IAQI caused by nearby construction activity) compared to the original models when predicting high PM10 IAQI levels attributable to fugitive dust from nearby construction sites. PMID:24381481

  12. 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

  13. 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.

  14. 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

  15. 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

  16. Plasma HHV8 DNA predicts relapse in individuals with HIV-associated multicentric Castleman disease.

    PubMed

    Stebbing, Justin; Adams, Caroline; Sanitt, Adam; Mletzko, Salvinia; Nelson, Mark; Gazzard, Brian; Newsom-Davis, Tom; Bower, Mark

    2011-07-14

    HIV-associated multicentric Castleman disease (HIV-MCD) is a rare lymphoproliferative disorder caused by infection with human herpesvirus-8. The disease follows a relapsing and remitting clinical course, with marked systemic symptoms during an active attack, which can prove fatal. Its incidence is rising, and new data indicate the utility of the anti-CD20 monoclonal antibody rituximab at inducing remissions in both first- and second-line settings, although biomarkers associated with relapse have not been previously identified. In 52 individuals with a histologic diagnosis of HIV-MCD, we performed univariate and multivariate analyses to predict factors associated with an HIV-MCD attack. Although a younger age (< 50 years) was associated with an attack, the strongest association was observed with plasma levels of human herpesvirus-8 DNA. Rising levels predicted an attack (hazard ratio = 2.9; 95% confidence interval, 1.3-6.7), and maintenance therapy with rituximab should be considered in these individuals. PMID:21511959

  17. 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

  18. 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

  19. 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. PMID:24040031

  20. 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. PMID:27188981

  1. 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. PMID:26789839

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

    PubMed Central

    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. PMID:26789839

  3. 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.

  4. 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.

  5. Efficient prediction methods for selecting effective siRNA sequences.

    PubMed

    Takasaki, Shigeru

    2010-02-01

    Although short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells, its gene silencing efficacy varies markedly and there are only a few consistencies among the recently reported design rules/guidelines for selecting siRNA sequences effective for mammalian genes. Another shortcoming of the previously reported methods is that they cannot estimate the probability that a candidate sequence will silence the target gene. This paper first reviewed the recently reported siRNA design guidelines and clarified the problems concerning the guidelines. It then proposed two prediction methods-Radial Basis Function (RBF) network and decision tree learning-and their combined method for selecting effective siRNA target sequences from many possible candidate sequences. They are quite different from the previous score-based siRNA design techniques and can predict the probability that a candidate siRNA sequence will be effective. The methods imply high estimation accuracy for selecting candidate siRNA sequences. PMID:20022002

  6. 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. PMID:23108272

  7. Changes in Early Cortical Visual Processing Predict Enhanced Reactivity in Deaf Individuals

    PubMed Central

    Bottari, Davide; Caclin, Anne; Giard, Marie-Hélène; Pavani, Francesco

    2011-01-01

    Individuals with profound deafness rely critically on vision to interact with their environment. Improvement of visual performance as a consequence of auditory deprivation is assumed to result from cross-modal changes occurring in late stages of visual processing. Here we measured reaction times and event-related potentials (ERPs) in profoundly deaf adults and hearing controls during a speeded visual detection task, to assess to what extent the enhanced reactivity of deaf individuals could reflect plastic changes in the early cortical processing of the stimulus. We found that deaf subjects were faster than hearing controls at detecting the visual targets, regardless of their location in the visual field (peripheral or peri-foveal). This behavioural facilitation was associated with ERP changes starting from the first detectable response in the striate cortex (C1 component) at about 80 ms after stimulus onset, and in the P1 complex (100–150 ms). In addition, we found that P1 peak amplitudes predicted the response times in deaf subjects, whereas in hearing individuals visual reactivity and ERP amplitudes correlated only at later stages of processing. These findings show that long-term auditory deprivation can profoundly alter visual processing from the earliest cortical stages. Furthermore, our results provide the first evidence of a co-variation between modified brain activity (cortical plasticity) and behavioural enhancement in this sensory-deprived population. PMID:21980501

  8. Increased Copper in Individuals with Autism Normalizes Post Zinc Therapy More Efficiently in Individuals with Concurrent GI Disease

    PubMed Central

    Russo, Anthony J.

    2011-01-01

    Aim: To assess plasma zinc and copper concentration in individuals with autism. Subjects and methods: Plasma from 79 autistic individuals, and 18 age and gender similar neurotypical controls, were tested for plasma zinc and copper using inductively-coupled plasma-mass spectrometry. Results: Autistic individuals had significantly elevated plasma levels of copper and Cu/Zn and lower, but not significantly lower, plasma Zn compared to neurotypical controls. Zn levels increased significantly in autistic individuals with and without GI disease after zinc therapy. Cu decreased significantly after zinc therapy in the GI disease group but not in the autistic group without GI disease. Autistic children significantly improved with respect to hyperactivity and stimming after zinc therapy in autistic children with GI disease. Autistic children without GI disease did not improve in these symptoms after the same therapy. Discussion: These results suggest an association between zinc and copper plasma levels and autism, and they suggest that zinc therapy may be most effective at lowering copper levels in autistic children with GI disease. PMID:23946661

  9. Investigation of the relative significance of individual environmental parameters to sonar performance prediction uncertainty

    NASA Astrophysics Data System (ADS)

    Wang, Ding; Xu, Wen; Schmidt, Henrik

    2002-11-01

    A large part of sonar performance prediction uncertainty is associated with the uncertain ocean acoustic environment. Optimal in situ measurement strategy, i.e. adaptively capturing the most critical uncertain environmental parameters within operational constrains can minimize the sonar performance prediction uncertainty. Understanding the relative significance of individual environmental parameters to sonar performance prediction uncertainty is fundamental to the heuristics to determine the most critical environmental parameters. Based on this understanding, the optimal parametrization of ocean acoustic environments can be defined, which will significantly simplify the adaptively sampling pattern. As an example, the matched-field processing is used to localize an unknown sound source position in a realistic ocean environment. Typical shallow water environmental models are used with some of the properties being stochastic variables. The ratio of the main lobe peak to the maximum side lobe peak of the ambiguity function and the main lobe peak displacement due to mismatch are chosen as performance metrics, respectively, in two different scenarios. The relative significance of some environmental parameters such as sediment thickness, weights of empirical orthogonal functions (EOFs) has been computed. Some preliminary results are discussed.

  10. Mood variability predicts the course of suicidal ideation in individuals with first and second episode psychosis.

    PubMed

    Palmier-Claus, Jasper; Shryane, Nick; Taylor, Peter; Lewis, Shôn; Drake, Richard

    2013-04-30

    Suicide risk is high in early psychosis. Recent research has suggested that mood variability may be associated with levels of suicidal thoughts and behaviour. This has not been investigated in individuals during and following a first or second episode of non-affective psychosis. Repeated-measures data over 18 months from a large randomised controlled trial for cognitive behaviour therapy (N=309) were analysed using latent growth curve modelling, whereby both the variability and the level of depression, anxiety and guilt were entered as predictors of suicidality. The variability of depression, but not guilt and anxiety, predicted the course of suicidality even when controlling for a large range of potential confounders. The level of depression, anxiety and guilt for each participant also strongly predicted the development of suicidality. The findings support the theory that variability in depression may contribute to the formation of suicidal ideation and related behaviour. More variable depression may be harder to predict and intervene against, and therefore increase the likelihood that suicidality escalates. The levels of emotions may also be an important determinant. This has implications for the treatment and assessment of suicidality in early psychosis. PMID:23234757

  11. A new predictive equation for resting energy expenditure in healthy individuals.

    PubMed

    Mifflin, M D; St Jeor, S T; Hill, L A; Scott, B J; Daugherty, S A; Koh, Y O

    1990-02-01

    A predictive equation for resting energy expenditure (REE) was derived from data from 498 healthy subjects, including females (n = 247) and males (n = 251), aged 19-78 y (45 +/- 14 y, mean +/- SD). Normal-weight (n = 264) and obese (n = 234) individuals were studied and REE was measured by indirect calorimetry. Multiple-regression analyses were employed to drive relationships between REE and weight, height, and age for both men and women (R2 = 0.71): REE = 9.99 x weight + 6.25 x height - 4.92 x age + 166 x sex (males, 1; females, 0) - 161. Simplification of this formula and separation by sex did not affect its predictive value: REE (males) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) + 5; REE (females) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) - 161. The inclusion of relative body weight and body-weight distribution did not significantly improve the predictive value of these equations. The Harris-Benedict Equations derived in 1919 overestimated measured REE by 5% (p less than 0.01). Fat-free mass (FFM) was the best single predictor of REE (R2 = 0.64): REE = 19.7 x FFM + 413. Weight also was closely correlated with REE (R2 = 0.56): REE = 15.1 x weight + 371. PMID:2305711

  12. Efficient Reconstruction of Predictive Consensus Metabolic Network Models.

    PubMed

    van Heck, Ruben G A; Ganter, Mathias; Martins Dos Santos, Vitor A P; Stelling, Joerg

    2016-08-01

    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

  13. 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

  14. Efficient prediction of the quality factors of micromechanical resonators

    NASA Astrophysics Data System (ADS)

    Choi, Jinbok; Cho, Maenghyo; Rhim, Jaewook

    2010-01-01

    A high quality factor (Q-factor) is one of the major requirements of high-performance resonators. An understanding of the dissipation mechanism is crucial for maximizing the quality factor by reducing the energy loss. Thermoelastic damping has been well-known as the important intrinsic dissipation that affects the quality factor of micro-resonators. In this study, a finite element formulation based on the weak form of fully coupled thermoelastic problems is suggested. The coupled thermoelastic equation usually leads to a large-size complex eigenvalue problem, which is very massive and time-consuming to solve. Therefore, we also applied the model order reduction (MOR) scheme to this coupled multiphysical problem in order to achieve computational efficiency. The present approach is validated by comparing the numerical results and analytical solutions.

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

    PubMed

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

    2015-09-01

    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

  16. Predicted versus monitored performance of energy-efficiency measures in new commercial buildings from energy edge

    SciTech Connect

    Piette, M.A.; Nordman, B.; deBuen, O.; Diamond, R.

    1993-08-01

    Energy Edge is a research-oriented demonstration program involving 28 new commercial buildings in the Pacific Northwest. This paper discusses the energy savings and cost-effectiveness of energy-efficiency measures for the first 12 buildings evaluated using simulation models calibrated with measured end-use data. Average energy savings per building from the simulated code baseline building was 19%, less than the 30% target. The most important factor for the lower savings is that many of the installed measures differ from the measures specified in the design predictions. Only one of the first 12 buildings met the project objective of reducing energy use by more than 30% at a cost below the target of 56 mills/kWh (in 1991 dollars). Based on results from the first 12 calibrated simulation models, 29 of the 66 energy-efficiency measures, or 44%, met the levelized cost criterion. Despite the lower energy savings from individual measures, the energy-use intensities of the buildings are lower than other regional comparison data for new buildings. The authors review factors that contribute to the uncertainty regarding measured savings and suggest methods to improve future evaluations.

  17. 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. PMID:24404133

  18. Efficiency improvement of a new vertical axis wind turbine by individual active control of blade motion

    NASA Astrophysics Data System (ADS)

    Hwang, In Seong; Min, Seung Yong; Jeong, In Oh; Lee, Yun Han; Kim, Seung Jo

    2006-03-01

    In this paper, a research for the performance improvement of the straight-bladed vertical axis wind turbine is described. To improve the performance of the power generation system, which consists of several blades rotating about axis in parallel direction, the cycloidal blade system and the individual active blade control system are adopted, respectively. Both methods are variable pitch system. For cycloidal wind turbine, aerodynamic analysis is carried out by changing pitch angle and phase angle based on the cycloidal motion according to the change of wind speed and wind direction, and control mechanism using the cycloidal blade system is realized for 1kw class wind turbine. By this method, electrical power is generated about 30% higher than wind turbine using fixed pitch angle method. And for more efficient wind turbine, individual pitch angle control of each blade is studied. By maximizing the tangential force in each rotating blade at the specific rotating position, optimal pitch angle variation is obtained. And several airfoil shapes of NACA 4-digit and NACA 6-series are studied. Aerodynamic analysis shows performance improvement of 60%. To realize this motion, sensing and actuating system is designed.

  19. 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.

  20. Flexible control in processing affective and non-affective material predicts individual differences in trait resilience.

    PubMed

    Genet, Jessica J; Siemer, Matthias

    2011-02-01

    Trait resilience is a stable personality characteristic that involves the self-reported ability to flexibly adapt to emotional events and situations. The present study examined cognitive processes that may explain individual differences in trait resilience. Participants completed self-report measures of trait resilience, cognitive flexibility and working memory capacity tasks, and a novel affective task-switching paradigm that assesses the ability to flexibly switch between processing the affective versus non-affective qualities of affective stimuli (i.e., flexible affective processing). As hypothesised, cognitive flexibility and flexible affective processing were unique predictors of trait resilience. Working memory capacity was not predictive of trait resilience, indicating that trait resilience is tied to specific cognitive processes rather than overall better cognitive functioning. Cognitive flexibility and flexible affective processing were not associated with other trait measures, suggesting that these flexibility processes are unique to trait resilience. This study was among the first to investigate the cognitive abilities underlying trait resilience. PMID:21432680

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

    PubMed Central

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

    2011-01-01

    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 obtained from the U.S. Census regarding rates of community poverty and unemployment in participants’ neighborhoods. Results indicated that high rates of community poverty and unemployment, children’s depressive attributional style, and low levels of self-perceived competence predict children’s depressive symptoms, even after accounting for demographic and familial risk factors, such as parental education and negative parenting behaviors. The effect of negative parenting behaviors on depressive symptoms was partially mediated by personal variables like children’s self-perceived competence. Recommendations for future research, intervention and prevention programs are discussed. PMID:25364062

  2. 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

  3. 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. PMID:23576778

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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. PMID:24219574

  10. Plasma oxytocin levels predict social cue recognition in individuals with schizophrenia.

    PubMed

    Strauss, Gregory P; Keller, William R; Koenig, James I; Gold, James M; Frost, Katherine H; Buchanan, Robert W

    2015-03-01

    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

  11. Benchmarking Deep Networks for Predicting Residue-Specific Quality of Individual Protein Models in CASP11

    PubMed Central

    Liu, Tong; Wang, Yiheng; Eickholt, Jesse; Wang, Zheng

    2016-01-01

    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. PMID:26763289

  12. Benchmarking Deep Networks for Predicting Residue-Specific Quality of Individual Protein Models in CASP11

    NASA Astrophysics Data System (ADS)

    Liu, Tong; Wang, Yiheng; Eickholt, Jesse; Wang, Zheng

    2016-01-01

    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.

  13. Network, anatomical, and non-imaging measures for the prediction of ADHD diagnosis in individual subjects.

    PubMed

    Bohland, Jason W; Saperstein, Sara; Pereira, Francisco; Rapin, Jérémy; Grady, Leo

    2012-01-01

    Brain imaging methods have long held promise as diagnostic aids for neuropsychiatric conditions with complex behavioral phenotypes such as Attention-Deficit/Hyperactivity Disorder. This promise has largely been unrealized, at least partly due to the heterogeneity of clinical populations and the small sample size of many studies. A large, multi-center dataset provided by the ADHD-200 Consortium affords new opportunities to test methods for individual diagnosis based on MRI-observable structural brain attributes and functional interactions observable from resting-state fMRI. In this study, we systematically calculated a large set of standard and new quantitative markers from individual subject datasets. These features (>12,000 per subject) consisted of local anatomical attributes such as cortical thickness and structure volumes, and both local and global resting-state network measures. Three methods were used to compute graphs representing interdependencies between activations in different brain areas, and a full set of network features was derived from each. Of these, features derived from the inverse of the time series covariance matrix, under an L1-norm regularization penalty, proved most powerful. Anatomical and network feature sets were used individually, and combined with non-imaging phenotypic features from each subject. Machine learning algorithms were used to rank attributes, and performance was assessed under cross-validation and on a separate test set of 168 subjects for a variety of feature set combinations. While non-imaging features gave highest performance in cross-validation, the addition of imaging features in sufficient numbers led to improved generalization to new data. Stratification by gender also proved to be a fruitful strategy to improve classifier performance. We describe the overall approach used, compare the predictive power of different classes of features, and describe the most impactful features in relation to the current literature

  14. 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

  15. High-Throughput Near-Infrared Reflectance Spectroscopy for Predicting Quantitative and Qualitative Composition Phenotypes of Individual Maize Kernels

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  16. 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…

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

    PubMed

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

    2014-07-21

    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. PMID:24830733

  18. The Carbon_h-Factor: Predicting Individuals' Research Impact at Early Stages of Their Career

    PubMed Central

    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

  19. 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

  20. Variations in EEG discharges predict ADHD severity within individual Smith-Lemli-Opitz patients

    PubMed Central

    Schreiber, John M.; Lanham, Diane C.; Trescher, William H.; Sparks, Susan E.; Wassif, Christopher A.; Caffo, Brian S.; Porter, Forbes D.; Tierney, Elaine; Gropman, Andrea L.

    2014-01-01

    Objective: We sought to examine the prevalence of EEG abnormalities in Smith-Lemli-Opitz syndrome (SLOS) as well as the relationship between interictal epileptiform discharges (IEDs) and within-subject variations in attentional symptom severity. Methods: In the context of a clinical trial for SLOS, we performed cross-sectional and repeated-measure observational studies of the relationship between EEG findings and cognitive/behavioral factors on 23 children (aged 4–17 years). EEGs were reviewed for clinical abnormalities, including IEDs, by readers blinded to participants' behavioral symptoms. Between-group differences in baseline characteristics of participants with and without IEDs were analyzed. Within-subject analyses examined the association between the presence of IEDs and changes in attention-deficit/hyperactivity disorder (ADHD) symptoms. Results: Of 85 EEGs, 43 (51%) were abnormal, predominantly because of IEDs. Only one subject had documented clinical seizures. IEDs clustered in 13 subjects (57%), whereas 9 subjects (39%) had EEGs consistently free of IEDs. While there were no significant group differences in sex, age, intellectual disability, language level, or baseline ADHD symptoms, autistic symptoms tended to be more prevalent in the “IED” group (according to Autism Diagnostic Observation Schedule–2 criteria). Within individuals, the presence of IEDs on a particular EEG predicted, on average, a 27% increase in ADHD symptom severity. Conclusions: Epileptiform discharges are common in SLOS, despite a relatively low prevalence of epilepsy. Fluctuations in the presence of epileptiform discharges within individual children with a developmental disability syndrome may be associated with fluctuations in ADHD symptomatology, even in the absence of clinical seizures. PMID:24920862

  1. The Individualized Genetic Barrier Predicts Treatment Response in a Large Cohort of HIV-1 Infected Patients

    PubMed Central

    Beerenwinkel, Niko; Montazeri, Hesam; Schuhmacher, Heike; Knupfer, Patrick; von Wyl, Viktor; Furrer, Hansjakob; Battegay, Manuel; Hirschel, Bernard; Cavassini, Matthias; Vernazza, Pietro; Bernasconi, Enos; Yerly, Sabine; Böni, Jürg; Klimkait, Thomas; Cellerai, Cristina; Günthard, Huldrych F.

    2013-01-01

    The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational pathways, and we modeled phenotypic drug resistance as monotonically increasing along any escape pathway. Using this model, the individualized genetic barrier (IGB) to each drug is derived as the probability of the virus not acquiring additional mutations that confer resistance. Drug-specific IGBs were combined to obtain the IGB to an entire regimen, which quantifies the virus' genetic potential for developing drug resistance under combination therapy. The IGB was tested as a predictor of therapeutic outcome using between 2,185 and 2,631 treatment change episodes of subtype B infected patients from the Swiss HIV Cohort Study Database, a large observational cohort. Using logistic regression, significant univariate predictors included most of the 18 drugs and single-drug IGBs, the IGB to the entire regimen, the expert rules-based genotypic susceptibility score (GSS), several individual mutations, and the peak viral load before treatment change. In the multivariate analysis, the only genotype-derived variables that remained significantly associated with virological success were GSS and, with 10-fold stronger association, IGB to regimen. When predicting suppression of viral load below 400 cps/ml, IGB outperformed GSS and also improved GSS-containing predictors significantly, but the difference was not significant for suppression below 50 cps/ml. Thus, the IGB to regimen is a novel data-derived predictor of treatment outcome that has potential to improve the interpretation of genotypic drug resistance tests. PMID:24009493

  2. Neural activity tied to reading predicts individual differences in extended-text comprehension.

    PubMed

    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

  3. A model for predicting individuals' absolute risk of esophageal adenocarcinoma: Moving toward tailored screening and prevention.

    PubMed

    Xie, Shao-Hua; Lagergren, Jesper

    2016-06-15

    Esophageal adenocarcinoma (EAC) is characterized by rapidly increasing incidence and poor prognosis, stressing the need for preventive and early detection strategies. We used data from a nationwide population-based case-control study, which included 189 incident cases of EAC and 820 age- and sex-matched control participants, from 1995 through 1997 in Sweden. We developed risk prediction models based on unconditional logistic regression. Candidate predictors included established and readily identifiable risk factors for EAC. The performance of model was assessed by the area under receiver operating characteristic curve (AUC) with cross-validation. The final model could explain 94% of all case patients with EAC (94% population attributable risk) and included terms for gastro-esophageal reflux symptoms or use of antireflux medication, body mass index (BMI), tobacco smoking, duration of living with a partner, previous diagnoses of esophagitis and diaphragmatic hernia and previous surgery for esophagitis, diaphragmatic hernia or severe reflux or gastric or duodenal ulcer. The AUC was 0.84 (95% confidence interval [CI] 0.81-0.87) and slightly lower after cross-validation. A simpler model, based only on reflux symptoms or use of antireflux medication, BMI and tobacco smoking could explain 91% of the case patients with EAC and had an AUC of 0.82 (95% CI 0.78-0.85). These EAC prediction models showed good discriminative accuracy, but need to be validated in other populations. These models have the potential for future use in identifying individuals with high absolute risk of EAC in the population, who may be considered for endoscopic screening and targeted prevention. PMID:26756848

  4. 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

    2015-04-01

    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. PMID:25712786

  5. [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. PMID:26863781

  6. 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. PMID:11763003

  7. Neuronal synchrony reveals working memory networks and predicts individual memory capacity

    PubMed Central

    Palva, J. Matias; Monto, Simo; Kulashekhar, Shrikanth; Palva, Satu

    2010-01-01

    Visual working memory (VWM) is used to maintain sensory information for cognitive operations, and its deficits are associated with several neuropsychological disorders. VWM is based on sustained neuronal activity in a complex cortical network of frontal, parietal, occipital, and temporal areas. The neuronal mechanisms that coordinate this distributed processing to sustain coherent mental images and the mechanisms that set the behavioral capacity limit have remained unknown. We mapped the anatomical and dynamic structures of network synchrony supporting VWM by using a neuro informatics approach and combined magnetoencephalography and electroencephalography. Interareal phase synchrony was sustained and stable during the VWM retention period among frontoparietal and visual areas in α- (10–13 Hz), β- (18–24 Hz), and γ- (30–40 Hz) frequency bands. Furthermore, synchrony was strengthened with increasing memory load among the frontoparietal regions known to underlie executive and attentional functions during memory maintenance. On the other hand, the subjects’ individual behavioral VWM capacity was predicted by synchrony in a network in which the intraparietal sulcus was the most central hub. These data suggest that interareal phase synchrony in the α-, β-, and γ-frequency bands among frontoparietal and visual regions could be a systems level mechanism for coordinating and regulating the maintenance of neuronal object representations in VWM. PMID:20368447

  8. Individual differences in attributional style but not in interoceptive sensitivity, predict subjective estimates of action intention

    PubMed Central

    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. PMID:25191254

  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. Within-Person Changes in Individual Symptoms of Depression Predict Subsequent Depressive Episodes in Adolescents: a Prospective Study.

    PubMed

    Kouros, Chrystyna D; Morris, Matthew C; Garber, Judy

    2016-04-01

    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

  11. 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

    2015-01-01

    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

  12. 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

  13. Accuracy of genomic predictions for feed efficiency traits of beef cattle using 50K and imputed HD genotypes.

    PubMed

    Lu, D; Akanno, E C; Crowley, J J; Schenkel, F; Li, H; De Pauw, M; Moore, S S; Wang, Z; Li, C; Stothard, P; Plastow, G; Miller, S P; Basarab, J A

    2016-04-01

    The accuracy of genomic predictions can be used to assess the utility of dense marker genotypes for genetic improvement of beef efficiency traits. This study was designed to test the impact of genomic distance between training and validation populations, training population size, statistical methods, and density of genetic markers on prediction accuracy for feed efficiency traits in multibreed and crossbred beef cattle. A total of 6,794 beef cattle data collated from various projects and research herds across Canada were used. Illumina BovineSNP50 (50K) and imputed Axiom Genome-Wide BOS 1 Array (HD) genotypes were available for all animals. The traits studied were DMI, ADG, and residual feed intake (RFI). Four validation groups of 150 animals each, including Angus (AN), Charolais (CH), Angus-Hereford crosses (ANHH), and a Charolais-based composite (TX) were created by considering the genomic distance between pairs of individuals in the validation groups. Each validation group had 7 corresponding training groups of increasing sizes ( = 1,000, 1,999, 2,999, 3,999, 4,999, 5,998, and 6,644), which also represent increasing average genomic distance between pairs of individuals in the training and validations groups. Prediction of genomic estimated breeding values (GEBV) was performed using genomic best linear unbiased prediction (GBLUP) and Bayesian method C (BayesC). The accuracy of genomic predictions was defined as the Pearson's correlation between adjusted phenotype and GEBV (), unless otherwise stated. Using 50K genotypes, the highest average achieved in purebreds (AN, CH) was 0.41 for DMI, 0.34 for ADG, and 0.35 for RFI, whereas in crossbreds (ANHH, TX) it was 0.38 for DMI, 0.21 for ADG, and 0.25 for RFI. Similarly, when imputed HD genotypes were applied in purebreds (AN, CH), the highest average was 0.14 for DMI, 0.15 for ADG, and 0.14 for RFI, whereas in crossbreds (ANHH, TX) it was 0.38 for DMI, 0.22 for ADG, and 0.24 for RFI. The of GBLUP predictions were

  14. 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

  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. 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

  17. 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

    2016-01-01

    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. PMID:27051007

  18. 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

  19. 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…

  20. 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

    2016-01-01

    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

  1. 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.

  2. 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.

  3. 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

    2015-11-01

    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

  4. Adaptive inter color residual prediction for efficient red-green-blue intra coding

    NASA Astrophysics Data System (ADS)

    Jeong, Jinwoo; Choe, Yoonsik; Kim, Yong-Goo

    2011-07-01

    Intra coding of an RGB video is important to many high fidelity multimedia applications because video acquisition is mostly done in RGB space, and the coding of decorrelated color video loses its virtue in high quality ranges. In order to improve the compression performance of an RGB video, this paper proposes an inter color prediction using adaptive weights. For making full use of spatial, as well as inter color correlation of an RGB video, the proposed scheme is based on a residual prediction approach, and thus the incorporated prediction is performed on the transformed frequency components of spatially predicted residual data of each color plane. With the aid of efficient prediction employing frequency domain inter color residual correlation, the proposed scheme achieves up to 24.3% of bitrate reduction, compared to the common mode of H.264/AVC high 4:4:4 intra profile.

  5. 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. PMID:26926280

  6. 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

  7. 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…

  8. 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

  9. 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

  10. 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…

  11. 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…

  12. 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…

  13. 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

  14. Curious Eyes: Individual Differences in Personality Predict Eye Movement Behavior in Scene-Viewing

    ERIC Educational Resources Information Center

    Risko, Evan F.; Anderson, Nicola C.; Lanthier, Sophie; Kingstone, Alan

    2012-01-01

    Visual exploration is driven by two main factors--the stimuli in our environment, and our own individual interests and intentions. Research investigating these two aspects of attentional guidance has focused almost exclusively on factors common across individuals. The present study took a different tack, and examined the role played by individual…

  15. 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…

  16. Peer assessments of normative and individual teacher–student support predict social acceptance and engagement among low-achieving children

    PubMed Central

    Hughes, Jan N.; Zhang, Duan; Hill, Crystal R.

    2010-01-01

    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 Texas School districts (1 urban, 2 small city) who scored below their school district median on a measure of literacy administered at the beginning of first grade. Peer nominations from 5147 classmates were used to assess both normative and individual levels of teacher support. Normative classroom teacher–student support predicted children's peer acceptance and classroom engagement, above the effects of child gender, ethnic minority status, and individual teacher–student support. Results are discussed in terms of implications for teacher preparation and professional development. PMID:20411044

  17. Distribution patterns predict individual specialization in the diet of dolphin gulls.

    PubMed

    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 (δ(15)N) 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

  18. 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

  19. Individual difference in prepulse inhibition does not predict spatial learning and memory performance in C57BL/6 mice.

    PubMed

    Peleg-Raibstein, Daria; Philipp, Singer; Feldon, Joram; Yee, Benjamin K

    2015-12-01

    The startle reflex to an intense acoustic pulse stimulus is attenuated if the pulse stimulus is shortly preceded by a weak non-startling prepulse stimulus. This attenuation of the startle reflex represents a form of pre-attentional sensory gating known as prepulse inhibition (PPI). Although PPI does not require learning, its expression is regulated by higher cognitive processes. PPI deficits have been detected in several psychiatric conditions including schizophrenia where they co-exist with cognitive deficits. A potential link between PPI expression and cognitive performance has therefore been suggested such that poor PPI may predict, or may be mechanistically linked to, overt cognitive impairments. A positive relationship between PPI and strategy formation, planning efficiency, and execution speed has been observed in healthy humans. However, parallel studies in healthy animals are rare. It thus remains unclear what cognitive domains may be associated with, or orthogonal to, sensory gating in the form of PPI in healthy animals. The present study evaluated a potential link between the magnitude of PPI and spatial memory performance by comparing two subgroups of animals differing substantially in baseline PPI expression (low-PPI vs high-PPI) within a homogenous cohort of 100 male adult C57BL/6 mice. Assessment of spatial reference memory in the Morris water maze and spatial recognition memory in the Y-maze failed to reveal any difference between low-PPI and high-PPI subjects. These negative findings contrast with our previous reports that individual difference in PPI correlated with sustained attention and working memory performance in C57BL/6 mice. PMID:25893564

  20. Prediction of siRNA knockdown efficiency using artificial neural network models

    SciTech Connect

    Ge Guangtao . E-mail: guge@eecs.tufts.edu; Wong, G.William . E-mail: wong@wi.mit.edu; Luo Biao . E-mail: bluo@broad.mit.edu

    2005-10-21

    Selective knockdown of gene expression by short interference RNAs (siRNAs) has allowed rapid validation of gene functions and made possible a high throughput, genome scale approach to interrogate gene function. However, randomly designed siRNAs display different knockdown efficiencies of target genes. Hence, various prediction algorithms based on siRNA functionality have recently been constructed to increase the likelihood of selecting effective siRNAs, thereby reducing the experimental cost. Toward this end, we have trained three Back-propagation and Bayesian neural network models, previously not used in this context, to predict the knockdown efficiencies of 180 experimentally verified siRNAs on their corresponding target genes. Using our input coding based primarily on RNA structure thermodynamic parameters and cross-validation method, we showed that our neural network models outperformed most other methods and are comparable to the best predicting algorithm thus far published. Furthermore, our neural network models correctly classified 74% of all siRNAs into different efficiency categories; with a correlation coefficient of 0.43 and receiver operating characteristic curve score of 0.78, thus highlighting the potential utility of this method to complement other existing siRNA classification and prediction schemes.

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

    PubMed

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

    2015-05-14

    Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures of performance for the prediction model were calculated using cross-validation. For the prediction model of fruit, vegetable and juice intake, the root mean squared error (RMSE) was 258.0 g, the correlation between observed and predicted intake was 0.78 and the mean difference between observed and predicted intake was - 1.7 g (limits of agreement: - 466.3, 462.8 g). For the prediction of fruit and vegetable intake (excluding juices), the RMSE was 201.1 g, the correlation was 0.65 and the mean bias was 2.4 g (limits of agreement: -368.2, 373.0 g). The prediction models which include the biomarkers and subject characteristics may be used to estimate average intake at the group level and to investigate the ranking of individuals with regard to their intake of fruit and vegetables when validating questionnaires that measure intake. PMID:25850683

  2. Adaptive Prediction Error Coding in the Human Midbrain and Striatum Facilitates Behavioral Adaptation and Learning Efficiency.

    PubMed

    Diederen, Kelly M J; Spencer, Tom; Vestergaard, Martin D; Fletcher, Paul C; Schultz, Wolfram

    2016-06-01

    Effective error-driven learning benefits from scaling of prediction errors to reward variability. Such behavioral adaptation may be facilitated by neurons coding prediction errors relative to the standard deviation (SD) of reward distributions. To investigate this hypothesis, we required participants to predict the magnitude of upcoming reward drawn from distributions with different SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. In line with the notion of adaptive coding, BOLD response slopes in the Substantia Nigra/Ventral Tegmental Area (SN/VTA) and ventral striatum were steeper for prediction errors occurring in distributions with smaller SDs. SN/VTA adaptation was not instantaneous but developed across trials. Adaptive prediction error coding was paralleled by behavioral adaptation, as reflected by SD-dependent changes in learning rate. Crucially, increased SN/VTA and ventral striatal adaptation was related to improved task performance. These results suggest that adaptive coding facilitates behavioral adaptation and supports efficient learning. PMID:27181060

  3. Investigating the importance of various individual, interpersonal, organisational and demographic variables when predicting job burnout in disability support workers.

    PubMed

    Vassos, Maria V; Nankervis, Karen L

    2012-01-01

    Previous research has highlighted that factors such as large workload, role ambiguity, lack of support from colleagues, and challenging behaviour are associated with higher levels of burnout within the disability support worker (DSW) population. The aim of this research was to investigate which factors contribute the most to the prediction of the three facets of burnout--feeling exhausted and overextended by one's work (emotional exhaustion), detached and callous responses towards work (depersonalisation) and a lack of achievement and productivity within one's role (personal accomplishment). The factors chosen for analysis within this research were analysed within four categories linked to theories of burnout development (individual, interpersonal, organisational and demographic). A sample of 108 DSWs completed a questionnaire booklet that contained standardised measures of burnout and job stressors related to disability work. Results highlighted the importance of predictors such as challenging behaviour (interpersonal), workload (individual), supervisor support (individual), work-home conflict (individual), job feedback (individual), role ambiguity (organisational), low job status (organisational), role conflict (organisational), gender (demographic) and work hours (demographic) when predicting one or more of the facets of burnout. In conclusion, disability services and organisations may benefit from focusing on remodelling their staff-related organisational practices in order to prevent the development of burnout in their DSWs (e.g., increase supervision and support practices). PMID:22699251

  4. Can We Predict Individual Combined Benefit and Harm of Therapy? Warfarin Therapy for Atrial Fibrillation as a Test Case

    PubMed Central

    Li, Guowei; Thabane, Lehana; Delate, Thomas; Witt, Daniel M.; Levine, Mitchell A. H.; Cheng, Ji; Holbrook, Anne

    2016-01-01

    Objectives To construct and validate a prediction model for individual combined benefit and harm outcomes (stroke with no major bleeding, major bleeding with no stroke, neither event, or both) in patients with atrial fibrillation (AF) with and without warfarin therapy. Methods Using the Kaiser Permanente Colorado databases, we included patients newly diagnosed with AF between January 1, 2005 and December 31, 2012 for model construction and validation. The primary outcome was a prediction model of composite of stroke or major bleeding using polytomous logistic regression (PLR) modelling. The secondary outcome was a prediction model of all-cause mortality using the Cox regression modelling. Results We included 9074 patients with 4537 and 4537 warfarin users and non-users, respectively. In the derivation cohort (n = 4632), there were 136 strokes (2.94%), 280 major bleedings (6.04%) and 1194 deaths (25.78%) occurred. In the prediction models, warfarin use was not significantly associated with risk of stroke, but increased the risk of major bleeding and decreased the risk of death. Both the PLR and Cox models were robust, internally and externally validated, and with acceptable model performances. Conclusions In this study, we introduce a new methodology for predicting individual combined benefit and harm outcomes associated with warfarin therapy for patients with AF. Should this approach be validated in other patient populations, it has potential advantages over existing risk stratification approaches as a patient-physician aid for shared decision-making PMID:27513986

  5. "All in a day's work": how follower individual differences and justice perceptions predict OCB role definitions and behavior.

    PubMed

    Kamdar, Dishan; McAllister, Daniel J; Turban, Daniel B

    2006-07-01

    The authors draw on theories of social exchange and prosocial behavior to explain how employee perceptions of procedural justice and individual differences in reciprocation wariness, empathic concern, and perspective taking function jointly as determinants of organizational citizenship behavior (OCB) role definitions and behavior. As hypothesized, empirical findings from a field study show both direct and interactive effects of procedural justice perceptions and individual differences on OCB role definition. In turn, OCB role definitions not only predict OCB directly but also moderate the effects of procedural justice perceptions on OCB. The authors explore the implications of these findings for practice as well as research. PMID:16834509

  6. 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.…

  7. Predicting Gene Function from Uncontrolled Expression Variation among Individual Wild-Type Arabidopsis Plants[W

    PubMed Central

    Bhosale, Rahul; Jewell, Jeremy B.; Hollunder, Jens; Koo, Abraham J.K.; Vuylsteke, Marnik; Michoel, Tom; Hilson, Pierre; Goossens, Alain; Howe, Gregg A.; Browse, John; Maere, Steven

    2013-01-01

    Gene expression profiling studies are usually performed on pooled samples grown under tightly controlled experimental conditions to suppress variability among individuals and increase experimental reproducibility. In addition, to mask unwanted residual effects, the samples are often subjected to relatively harsh treatments that are unrealistic in a natural context. Here, we show that expression variations among individual wild-type Arabidopsis thaliana plants grown under the same macroscopic growth conditions contain as much information on the underlying gene network structure as expression profiles of pooled plant samples under controlled experimental perturbations. We advocate the use of subtle uncontrolled variations in gene expression between individuals to uncover functional links between genes and unravel regulatory influences. As a case study, we use this approach to identify ILL6 as a new regulatory component of the jasmonate response pathway. PMID:23943861

  8. Functional connectivity between posterior hippocampus and retrosplenial complex predicts individual differences in navigational ability.

    PubMed

    Sulpizio, Valentina; Boccia, Maddalena; Guariglia, Cecilia; Galati, Gaspare

    2016-07-01

    Individuals vary widely in their ability to orient and navigate within the environment. Previous neuroimaging research has shown that hippocampus (HC) and scene-responsive regions (retrosplenial complex [RSC] and parahippocampal gyrus/parahippocampal place area [PPA]) were crucial for spatial orienting and navigation. Resting-state functional connectivity and a self-reported questionnaire of navigational ability were used to examine the hypothesis that the pattern of reciprocal connections between these regions reflects individual differences in spatial navigation. It was found that the functional connectivity between the posterior HC and RSC was significantly higher in good than in poor navigators. These results confirmed the crucial role of hippocampal and extra-hippocampal regions in spatial navigation and provided new insight into how spontaneous brain activity may account for individual differences in spatial ability. © 2016 Wiley Periodicals, Inc. PMID:27013151

  9. Resting-state Networks Predict Individual Differences in Common and Specific Aspects of Executive Function

    PubMed Central

    Reineberg, Andrew E.; Andrews-Hanna, Jessica R.; Depue, Brendan; Friedman, Naomi P.; Banich, Marie T.

    2014-01-01

    The goal of the present study was to examine relationships between individual differences in resting state functional connectivity as ascertained by fMRI (rs-fcMRI) and performance on tasks of executive function (EF), broadly defined as the ability to regulate thoughts and actions. Unlike most previous research that focused on the relationship between rs-fcMRI and a single behavioral measure of EF, in the current study we examined the relationship of rs-fcMRI with individual differences in subcomponents of EF. Ninety-one adults completed a resting state fMRI scan and three separate EF tasks outside the magnet: inhibition of prepotent responses, task set shifting, and working memory updating. From these three measures, we derived estimates of common aspects of EF, as well as abilities specific to working memory updating and task shifting. Using Independent Components Analysis (ICA), we identified across the group of participants several networks of regions (Resting State Networks, RSNs) with temporally correlated time courses. We then used dual regression to explore how these RSNs covaried with individual differences in EF. Dual regression revealed that increased higher common EF was associated with connectivity of a) frontal pole with an attentional RSN, and b) Crus I and II of the cerebellum with the right frontoparietal RSN. Moreover, higher shifting-specific abilities were associated with increased connectivity of angular gyrus with a ventral attention RSN. The results of the current study suggest that the organization of the brain at rest may have important implications for individual differences in EF, and that individuals higher in EF may have expanded resting state networks as compared to individuals with lower EF. PMID:25281800

  10. Using individual interest and conscientiousness to predict academic effort: Additive, synergistic, or compensatory effects?

    PubMed

    Trautwein, Ulrich; Lüdtke, Oliver; Nagy, Nicole; Lenski, Anna; Niggli, Alois; Schnyder, Inge

    2015-07-01

    Although both conscientiousness and domain-specific interest are believed to be major determinants of academic effort, they have rarely been brought together in empirical studies. In the present research, it was hypothesized that both interest and conscientiousness uniquely predict academic effort and statistically interact with each other to predict academic effort. In 4 studies with 2,557, 415, 1,025, and 1,531 students, respectively, conscientiousness and interest meaningfully and uniquely predicted academic effort. In addition, conscientiousness interacted with interest in a compensatory pattern, indicating that conscientiousness is especially important when a student finds a school subject uninteresting and that domain-specific interest plays a particularly important role for students low in conscientiousness. PMID:25915134