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Sample records for activity change predict

  1. Stock price change rate prediction by utilizing social network activities.

    Science.gov (United States)

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  2. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    Directory of Open Access Journals (Sweden)

    Shangkun Deng

    2014-01-01

    Full Text Available Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL and genetic algorithm (GA. MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  3. Neural activity predicts attitude change in cognitive dissonance.

    Science.gov (United States)

    van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

    2009-11-01

    When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

  4. LSD-induced entropic brain activity predicts subsequent personality change.

    Science.gov (United States)

    Lebedev, A V; Kaelen, M; Lövdén, M; Nilsson, J; Feilding, A; Nutt, D J; Carhart-Harris, R L

    2016-09-01

    Personality is known to be relatively stable throughout adulthood. Nevertheless, it has been shown that major life events with high personal significance, including experiences engendered by psychedelic drugs, can have an enduring impact on some core facets of personality. In the present, balanced-order, placebo-controlled study, we investigated biological predictors of post-lysergic acid diethylamide (LSD) changes in personality. Nineteen healthy adults underwent resting state functional MRI scans under LSD (75µg, I.V.) and placebo (saline I.V.). The Revised NEO Personality Inventory (NEO-PI-R) was completed at screening and 2 weeks after LSD/placebo. Scanning sessions consisted of three 7.5-min eyes-closed resting-state scans, one of which involved music listening. A standardized preprocessing pipeline was used to extract measures of sample entropy, which characterizes the predictability of an fMRI time-series. Mixed-effects models were used to evaluate drug-induced shifts in brain entropy and their relationship with the observed increases in the personality trait openness at the 2-week follow-up. Overall, LSD had a pronounced global effect on brain entropy, increasing it in both sensory and hierarchically higher networks across multiple time scales. These shifts predicted enduring increases in trait openness. Moreover, the predictive power of the entropy increases was greatest for the music-listening scans and when "ego-dissolution" was reported during the acute experience. These results shed new light on how LSD-induced shifts in brain dynamics and concomitant subjective experience can be predictive of lasting changes in personality. Hum Brain Mapp 37:3203-3213, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  5. Predicting Wetland Distribution Changes under Climate Change and Human Activities in a Mid- and High-Latitude Region

    Directory of Open Access Journals (Sweden)

    Dandan Zhao

    2018-03-01

    Full Text Available Wetlands in the mid- and high-latitudes are particularly vulnerable to environmental changes and have declined dramatically in recent decades. Climate change and human activities are arguably the most important factors driving wetland distribution changes which will have important implications for wetland ecological functions and services. We analyzed the importance of driving variables for wetland distribution and investigated the relative importance of climatic factors and human activity factors in driving historical wetland distribution changes. We predicted wetland distribution changes under climate change and human activities over the 21st century using the Random Forest model in a mid- and high-latitude region of Northeast China. Climate change scenarios included three Representative Concentration Pathways (RCPs based on five general circulation models (GCMs downloaded from the Coupled Model Intercomparison Project, Phase 5 (CMIP5. The three scenarios (RCP 2.6, RCP 4.5, and RCP 8.5 predicted radiative forcing to peak at 2.6, 4.5, and 8.5 W/m2 by the 2100s, respectively. Our results showed that the variables with high importance scores were agricultural population proportion, warmness index, distance to water body, coldness index, and annual mean precipitation; climatic variables were given higher importance scores than human activity variables on average. Average predicted wetland area among three emission scenarios were 340,000 ha, 123,000 ha, and 113,000 ha for the 2040s, 2070s, and 2100s, respectively. Average change percent in predicted wetland area among three periods was greatest under the RCP 8.5 emission scenario followed by RCP 4.5 and RCP 2.6 emission scenarios, which were 78%, 64%, and 55%, respectively. Losses in predicted wetland distribution were generally around agricultural lands and expanded continually from the north to the whole region over time, while the gains were mostly associated with grasslands and water in the

  6. Factors predicting changes in physical activity through adolescence: the Young-HUNT Study, Norway.

    Science.gov (United States)

    Rangul, Vegar; Holmen, Turid Lingaas; Bauman, Adrian; Bratberg, Grete H; Kurtze, Nanna; Midthjell, Kristian

    2011-06-01

    The purpose of this prospective population-based study was to analyze predictors of changes in physical activity (PA) levels from early to late adolescence. Data presented are from 2,348 adolescents and their parents who participated in the Nord-Trøndelag Health study (HUNT 2, 1995-1997) and at follow-up in Young-HUNT 2, 2000-2001 Participants completed a self-reported questionnaire and participated in a clinical examination that included measurements of height and weight. Four patterns of PA emerged in the study: active or inactive at both time points (active maintainers, 13%; inactive maintainers, 59%), inactive and became active (adopters, 12%), active and became inactive (relapsers, 16%). Being overweight, dissatisfied with life, and not actively participating in sports at baseline were significant predictors of change regarding PA among boys at follow-up. For girls, smoking, drinking, low maternal education, and physical inactivity predicted relapsers and inactive maintainers. Higher levels of education and more physically active parents at baseline seemed to protect against decreased PA during follow-up for both genders. Predictors of change in, or maintaining PA status during adolescence differed by gender. These results suggest that PA-promoting interventions should be tailored by gender and focus on encouraging activity for inactive adolescents and maintenance of PA in those already active. Copyright © 2011 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  7. Situational Motivation and Perceived Intensity: Their Interaction in Predicting Changes in Positive Affect from Physical Activity

    Directory of Open Access Journals (Sweden)

    Eva Guérin

    2012-01-01

    Full Text Available There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE] in predicting changes in positive affect following an acute bout of preferred physical activity, namely, running. Fourty-one female runners engaged in a 30-minute self-paced treadmill run in a laboratory context. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect between RPE and introjection (P<.05 but not between RPE and identified regulation or intrinsic motivation. At low levels of introjection, the influence of RPE on the change in positive affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The implications of the findings in light of SDT principles as well as the potential contingencies between the regulations and RPE in predicting positive affect among women are discussed.

  8. Situational motivation and perceived intensity: their interaction in predicting changes in positive affect from physical activity.

    Science.gov (United States)

    Guérin, Eva; Fortier, Michelle S

    2012-01-01

    There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE)] in predicting changes in positive affect following an acute bout of preferred physical activity, namely, running. Fourty-one female runners engaged in a 30-minute self-paced treadmill run in a laboratory context. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect between RPE and introjection (P positive affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The implications of the findings in light of SDT principles as well as the potential contingencies between the regulations and RPE in predicting positive affect among women are discussed.

  9. Predicting space climate change

    Science.gov (United States)

    Balcerak, Ernie

    2011-10-01

    Galactic cosmic rays and solar energetic particles can be hazardous to humans in space, damage spacecraft and satellites, pose threats to aircraft electronics, and expose aircrew and passengers to radiation. A new study shows that these threats are likely to increase in coming years as the Sun approaches the end of the period of high solar activity known as “grand solar maximum,” which has persisted through the past several decades. High solar activity can help protect the Earth by repelling incoming galactic cosmic rays. Understanding the past record can help scientists predict future conditions. Barnard et al. analyzed a 9300-year record of galactic cosmic ray and solar activity based on cosmogenic isotopes in ice cores as well as on neutron monitor data. They used this to predict future variations in galactic cosmic ray flux, near-Earth interplanetary magnetic field, sunspot number, and probability of large solar energetic particle events. The researchers found that the risk of space weather radiation events will likely increase noticeably over the next century compared with recent decades and that lower solar activity will lead to increased galactic cosmic ray levels. (Geophysical Research Letters, doi:10.1029/2011GL048489, 2011)

  10. Prediction of Physical Activity Level Using Processes of Change From the Transtheoretical Model: Experiential, Behavioral, or an Interaction Effect?

    Science.gov (United States)

    Romain, Ahmed Jérôme; Horwath, Caroline; Bernard, Paquito

    2018-01-01

    The purpose of the present study was to compare prediction of physical activity (PA) by experiential or behavioral processes of change (POCs) or an interaction between both types of processes. A cross-sectional study. This study was conducted using an online questionnaire. A total of 394 participants (244 women, 150 men), with a mean age of 35.12 ± 12.04 years and a mean body mass index of 22.97 ± 4.25 kg/m 2 were included. Participants completed the Processes of Change, Stages of Change questionnaires, and the International Physical Activity Questionnaire to evaluate self-reported PA level (total, vigorous, and moderate PA). Hierarchical multiple regression models were used to test the prediction of PA level. For both total PA (β = .261; P behavioral POCs were a significant predictor. Regarding moderate PA, only the interaction between experiential and behavioral POCs was a significant predictor (β = .123; P = .017). Our results provide confirmation that behavioral processes are most prominent in PA behavior. Nevertheless, it is of interest to note that the interaction between experiential and behavioral POCs was the only element predicting moderate PA level. Experiential processes were not associated with PA level.

  11. Differential Patterns of Amygdala and Ventral Striatum Activation Predict Gender-Specific Changes in Sexual Risk Behavior

    Science.gov (United States)

    Sansosti, Alexandra A.; Bowman, Hilary C.; Hariri, Ahmad R.

    2015-01-01

    Although the initiation of sexual behavior is common among adolescents and young adults, some individuals express this behavior in a manner that significantly increases their risk for negative outcomes including sexually transmitted infections. Based on accumulating evidence, we have hypothesized that increased sexual risk behavior reflects, in part, an imbalance between neural circuits mediating approach and avoidance in particular as manifest by relatively increased ventral striatum (VS) activity and relatively decreased amygdala activity. Here, we test our hypothesis using data from seventy 18- to 22-year-old university students participating in the Duke Neurogenetics Study. We found a significant three-way interaction between amygdala activation, VS activation, and gender predicting changes in the number of sexual partners over time. Although relatively increased VS activation predicted greater increases in sexual partners for both men and women, the effect in men was contingent on the presence of relatively decreased amygdala activation and the effect in women was contingent on the presence of relatively increased amygdala activation. These findings suggest unique gender differences in how complex interactions between neural circuit function contributing to approach and avoidance may be expressed as sexual risk behavior in young adults. As such, our findings have the potential to inform the development of novel, gender-specific strategies that may be more effective at curtailing sexual risk behavior. PMID:26063921

  12. Situational Motivation and Perceived Intensity: Their Interaction in Predicting Changes in Positive Affect from Physical Activity

    OpenAIRE

    Eva Guérin; Michelle S. Fortier

    2012-01-01

    There is evidence that affective experiences surrounding physical activity can contribute to the proper self-regulation of an active lifestyle. Motivation toward physical activity, as portrayed by self-determination theory, has been linked to positive affect, as has the intensity of physical activity, especially of a preferred nature. The purpose of this experimental study was to examine the interaction between situational motivation and intensity [i.e., ratings of perceived exertion (RPE)] i...

  13. Dynamic Variation in Pleasure in Children Predicts Nonlinear Change in Lateral Frontal Brain Electrical Activity

    Science.gov (United States)

    Light, Sharee N.; Coan, James A.; Frye, Corrina; Goldsmith, H. Hill; Davidson, Richard J.

    2009-01-01

    Individual variation in the experience and expression of pleasure may relate to differential patterns of lateral frontal activity. Brain electrical measures have been used to study the asymmetric involvement of lateral frontal cortex in positive emotion, but the excellent time resolution of these measures has not been used to capture…

  14. Are Some Semantic Changes Predictable?

    DEFF Research Database (Denmark)

    Schousboe, Steen

    2010-01-01

      Historical linguistics is traditionally concerned with phonology and syntax. With the exception of grammaticalization - the development of auxiliary verbs, the syntactic rather than localistic use of prepositions, etc. - semantic change has usually not been described as a result of regular...... developments, but only as specific meaning changes in individual words. This paper will suggest some regularities in semantic change, regularities which, like sound laws, have predictive power and can be tested against recorded languages....

  15. Optimization of muscle activity for task-level goals predicts complex changes in limb forces across biomechanical contexts.

    Directory of Open Access Journals (Sweden)

    J Lucas McKay

    Full Text Available Optimality principles have been proposed as a general framework for understanding motor control in animals and humans largely based on their ability to predict general features movement in idealized motor tasks. However, generalizing these concepts past proof-of-principle to understand the neuromechanical transformation from task-level control to detailed execution-level muscle activity and forces during behaviorally-relevant motor tasks has proved difficult. In an unrestrained balance task in cats, we demonstrate that achieving task-level constraints center of mass forces and moments while minimizing control effort predicts detailed patterns of muscle activity and ground reaction forces in an anatomically-realistic musculoskeletal model. Whereas optimization is typically used to resolve redundancy at a single level of the motor hierarchy, we simultaneously resolved redundancy across both muscles and limbs and directly compared predictions to experimental measures across multiple perturbation directions that elicit different intra- and interlimb coordination patterns. Further, although some candidate task-level variables and cost functions generated indistinguishable predictions in a single biomechanical context, we identified a common optimization framework that could predict up to 48 experimental conditions per animal (n = 3 across both perturbation directions and different biomechanical contexts created by altering animals' postural configuration. Predictions were further improved by imposing experimentally-derived muscle synergy constraints, suggesting additional task variables or costs that may be relevant to the neural control of balance. These results suggested that reduced-dimension neural control mechanisms such as muscle synergies can achieve similar kinetics to the optimal solution, but with increased control effort (≈2× compared to individual muscle control. Our results are consistent with the idea that hierarchical, task

  16. Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information.

    Directory of Open Access Journals (Sweden)

    Antonio Montresor

    2016-04-01

    Full Text Available Estimating the reduction in levels of infection during implementation of soil-transmitted helminth (STH control programmes is important to measure their performance and to plan interventions. Markov modelling techniques have been used with some success to predict changes in STH prevalence following treatment in Viet Nam. The model is stationary and to date, the prediction has been obtained by calculating the transition probabilities between the different classes of intensity following the first year of drug distribution and assuming that these remain constant in subsequent years. However, to run this model longitudinal parasitological data (including intensity of infection are required for two consecutive years from at least 200 individuals. Since this amount of data is not often available from STH control programmes, the possible application of the model in control programme is limited. The present study aimed to address this issue by adapting the existing Markov model to allow its application when a more limited amount of data is available and to test the predictive capacities of these simplified models.We analysed data from field studies conducted with different combination of three parameters: (i the frequency of drug administration; (ii the drug distributed; and (iii the target treatment population (entire population or school-aged children only. This analysis allowed us to define 10 sets of standard transition probabilities to be used to predict prevalence changes when only baseline data are available (simplified model 1. We also formulated three equations (one for each STH parasite to calculate the predicted prevalence of the different classes of intensity from the total prevalence. These equations allowed us to design a simplified model (SM2 to obtain predictions when the classes of intensity at baseline were not known. To evaluate the performance of the simplified models, we collected data from the scientific literature on changes in

  17. Are abrupt climate changes predictable?

    Science.gov (United States)

    Ditlevsen, Peter

    2013-04-01

    It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope

  18. Changes in retinal venular oxygen saturation predict activity of proliferative diabetic retinopathy 3 months after panretinal photocoagulation.

    Science.gov (United States)

    Torp, Thomas Lee; Kawasaki, Ryo; Wong, Tien Yin; Peto, Tunde; Grauslund, Jakob

    2018-03-01

    Proliferative diabetic retinopathy (PDR) is a severe blinding condition. We investigated whether retinal metabolism, measured by retinal oximetry, may predict PDR activity after panretinal laser photocoagulation (PRP). We performed a prospective, interventional, clinical study of patients with treatment-naive PDR. Wide-field fluorescein angiography (OPTOS, Optomap) and global and focal retinal oximetry (Oxymap T1) were performed at baseline (BL), and 3 months (3M) after PRP. Angiographic findings were used to divide patients according to progression or non-progression of PDR after PRP. We evaluated differences in global and focal retinal oxygen saturation between patients with and without progression of PDR after PRP treatment. We included 45 eyes of 37 patients (median age and duration of diabetes were 51.6 and 20 years). Eyes with progression of PDR developed a higher retinal venous oxygen saturation than eyes with non-progression at 3M (global: +5.9% (95% CI -1.5 to 12.9), focal: +5.4%, (95% CI -4.1 to 14.8)). Likewise, progression of PDR was associated with a lower arteriovenular (AV) oxygen difference between BL and 3M (global: -6.1%, (95% CI -13.4 to -1.4), focal: -4.5% (95% CI -12.1 to 3.2)). In a multiple logistic regression model, increment in global retinal venular oxygen saturation (OR 1.30 per 1%-point increment, p=0.017) and decrement in AV oxygen saturation difference (OR 0.72 per 1%-point increment, p=0.016) at 3M independently predicted progression of PDR. Development of higher retinal venular and lower AV global oxygen saturation independently predicts progression of PDR despite standard PRP and might be a potential non-invasive marker of angiogenic disease activity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  19. Changes in retinal venular oxygen saturation predict activity of proliferative diabetic retinopathy 3 months after panretinal photocoagulation

    DEFF Research Database (Denmark)

    Torp, Thomas Lee; Kawasaki, Ryo; Wong, Tien Yin

    2018-01-01

    .4 to -1.4), focal: -4.5% (95% CI -12.1 to 3.2)). In a multiple logistic regression model, increment in global retinal venular oxygen saturation (OR 1.30 per 1%-point increment, p=0.017) and decrement in AV oxygen saturation difference (OR 0.72 per 1%-point increment, p=0.016) at 3M independently predicted...

  20. Effects of the activation of self-esteem and perceived temporal distance on the preparation for an examination(2): Temporal changes in performance prediction

    OpenAIRE

    藤島, 喜嗣; Yoshitsugu, FUJISHIMA; 昭和女子大学大学院生活機構研究科

    2012-01-01

    Self-esteem is a global representation of the self that varies in its level of activation. Self-esteem should have an influence on future prediction depending on its activation level. According to the construal level theory, temporal distance moderates the influence of the activated self-esteem. Undergraduates (n=89) participated in a panel survey on predictions about their examination performance, in which their level of self-esteem activation was manipulated. Contrary to the hypothesis, the...

  1. Which psychological, social and physical environmental characteristics predict changes in physical activity and sedentary behaviors during early retirement? A longitudinal study

    Directory of Open Access Journals (Sweden)

    Delfien Van Dyck

    2017-05-01

    Full Text Available Background In the context of healthy ageing, it is necessary to identify opportunities to implement health interventions in order to develop an active lifestyle with sufficient physical activity and limited sedentary time in middle-aged and older adults. The transition to retirement is such an opportunity, as individuals tend to establish new routines at the start of retirement. Before health interventions can be developed, the psychological, social and physical environmental determinants of physical activity and sedentary behaviors during early retirement should be identified, ideally with longitudinal studies. The aim of this paper was first to examine whether psychological, social and physical environmental factors at the start of retirement predict longitudinal changes in physical activity and sedentary behaviors during the first years of retirement. Second, moderating effects of gender and educational levels were examined. Methods This longitudinal study was conducted in Flanders, Belgium. In total, 180 recently retired (>1 month, <2 years at baseline adults completed a postal questionnaire twice (in 2012–2013 and two years later in 2014–2015. The validated questionnaire assessed socio-demographic information, physical activity, sedentary behaviors, and psychological, social and physical environmental characteristics. Multiple moderated hierarchic regression analyses were conducted in SPSS 22.0. Results Higher perceived residential density (p < 0.001 and lower aesthetics (p = 0.08 predicted an increase in active transportation (adjusted R2 = 0.18. Higher baseline self-efficacy was associated with an increase in leisure-time physical activity (p = 0.001, adjusted R2 = 0.13. A more positive perception of old age (p = 0.04 and perceiving less street connectivity (p = 0.001 were associated with an increase in screen time (adjusted R2 = 0.06. Finally, higher baseline levels of modeling from friends (p = 0.06 and lower

  2. Predicting Persuasion-Induced Behavior Change from the Brain

    Science.gov (United States)

    Falk, Emily B.; Berkman, Elliot T.; Mann, Traci; Harrison, Brittany; Lieberman, Matthew D.

    2011-01-01

    Although persuasive messages often alter people’s self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p < 0.05). Additionally, an iterative cross-validation approach using activity in this MPFC ROI predicted an average 23% of the variance in behavior change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance. PMID:20573889

  3. Predicting postoperative haemoglobin changes after burn surgery

    African Journals Online (AJOL)

    Burn surgery is associated with significant peri-operative haemoglobin. (Hb) changes. ... operative factors predictive of an Hb <7 g/dL on the first day after surgery, which were ..... clinical judgement, taking into consideration the risk associated.

  4. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Data.gov (United States)

    U.S. Environmental Protection Agency — Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational...

  5. Empirical analysis of change metrics for software fault prediction

    NARCIS (Netherlands)

    Choudhary, Garvit Rajesh; Kumar, Sandeep; Kumar, Kuldeep; Mishra, Alok; Catal, Cagatay

    2018-01-01

    A quality assurance activity, known as software fault prediction, can reduce development costs and improve software quality. The objective of this study is to investigate change metrics in conjunction with code metrics to improve the performance of fault prediction models. Experimental studies are

  6. Climate Change as a Predictable Surprise

    International Nuclear Information System (INIS)

    Bazerman, M.H.

    2006-01-01

    In this article, I analyze climate change as a 'predictable surprise', an event that leads an organization or nation to react with surprise, despite the fact that the information necessary to anticipate the event and its consequences was available (Bazerman and Watkins, 2004). I then assess the cognitive, organizational, and political reasons why society fails to implement wise strategies to prevent predictable surprises generally and climate change specifically. Finally, I conclude with an outline of a set of response strategies to overcome barriers to change

  7. Human activity recognition and prediction

    CERN Document Server

    2016-01-01

    This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .

  8. Climate modelling, uncertainty and responses to predictions of change

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    1996-01-01

    Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by, inter alia, incorporating climate change risk assessment into development planning processes, i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. An urgent issue is the mismatch between the predictions of global climatic change and the need for information on local to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. And, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. But, climate models can't yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes

  9. CERAPP: Collaborative estrogen receptor activity prediction project

    DEFF Research Database (Denmark)

    Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra

    2016-01-01

    ). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. oBjectives: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project...... States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical......: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. conclusion: This project demonstrated...

  10. Predicting environmental restoration activities through static simulation

    International Nuclear Information System (INIS)

    Ross, T.L.; King, D.A.; Wilkins, M.L.; Forward, M.F.

    1994-12-01

    This paper discusses a static simulation model that predicts several performance measures of environmental restoration activities over different remedial strategies. Basic model operation consists of manipulating and processing waste streams via selecting and applying remedial technologies according to the strategy. Performance measure prediction is possible for contaminated soil, solid waste, surface water, groundwater, storage tank, and facility sites. Simulations are performed for the U.S. Department of Energy in support of its Programmatic Environmental Impact Statement

  11. Why looking at the whole hippocampus is not enough – a critical role for anteroposterior axis, subfield and activation analyses to enhance predictive value of hippocampal changes for Alzheimer’s disease diagnosis.

    Directory of Open Access Journals (Sweden)

    Aleksandra eMaruszak

    2014-03-01

    Full Text Available The hippocampus is one of the earliest affected brain regions in Alzheimer´s disease (AD and its dysfunction is believed to underlie the core feature of the disease- memory impairment. Given that hippocampal volume is one of the best AD biomarkers, our review focuses on distinct subfields within the hippocampus, pinpointing regions that might enhance the predictive value of current diagnostic methods. Our review presents how changes in hippocampal volume, shape, symmetry and activation are reflected by cognitive impairment and how they are linked with neurogenesis alterations. Moreover, we revisit the functional differentiation along the anteroposterior longitudinal axis of the hippocampus and discuss its relevance for AD diagnosis. Finally, we indicate that apart from hippocampal subfield volumetry, the characteristic pattern of hippocampal hyperactivation associated with seizures and neurogenesis changes is another promising candidate for an early AD biomarker that could become also a target for early interventions.

  12. Predicting Immediate Belief Change and Adherence to Argument Claims.

    Science.gov (United States)

    Hample, Dale

    1978-01-01

    Discusses the probative potential of evidence in argument, and evaluates the importance of evidence in predicting belief change. Predicts adherence to argument claims and confirms the traditionally recognized importance of evidence to persuasion. (JMF)

  13. Diffusion changes predict cognitive and functional outcome

    DEFF Research Database (Denmark)

    Jokinen, Hanna; Schmidt, Reinhold; Ropele, Stefan

    2013-01-01

    A study was undertaken to determine whether diffusion-weighted imaging (DWI) abnormalities in normal-appearing brain tissue (NABT) and in white matter hyperintensities (WMH) predict longitudinal cognitive decline and disability in older individuals independently of the concomitant magnetic...

  14. Symptomatic cardiac toxicity is predicted by dosimetric and patient factors rather than changes in 18F-FDG PET determination of myocardial activity after chemoradiotherapy for esophageal cancer

    International Nuclear Information System (INIS)

    Konski, Andre; Li Tianyu; Christensen, Michael; Cheng, Jonathan D.; Yu, Jian Q.; Crawford, Kevin; Haluszka, Oleh; Tokar, Jeffrey; Scott, Walter; Meropol, Neal J.; Cohen, Steven J.; Maurer, Alan; Freedman, Gary M.

    2012-01-01

    Purpose: To determine factors associated with symptomatic cardiac toxicity in patients with esophageal cancer treated with chemoradiotherapy. Material and methods: We retrospectively evaluated 102 patients treated with chemoradiotherapy for locally advanced esophageal cancer. Our primary endpoint was symptomatic cardiac toxicity. Radiation dosimetry, patient demographic factors, and myocardial changes seen on 18 F-FDG PET were correlated with subsequent cardiac toxicity. Cardiac toxicity measured by RTOG and CTCAE v3.0 criteria was identified by chart review. Results: During the follow up period, 12 patients were identified with treatment related cardiac toxicity, 6 of which were symptomatic. The mean heart V20 (79.7% vs. 67.2%, p = 0.05), V30 (75.8% vs. 61.9%, p = 0.04), and V40 (69.2% vs. 53.8%, p = 0.03) were significantly higher in patients with symptomatic cardiac toxicity than those without. We found the threshold for symptomatic cardiac toxicity to be a V20, V30 and V40 above 70%, 65% and 60%, respectively. There was no correlation between change myocardial SUV on PET and cardiac toxicity, however, a greater proportion of women suffered symptomatic cardiac toxicity compared to men (p = 0.005). Conclusions: A correlation did not exist between percent change in myocardial SUV and cardiac toxicity. Patients with symptomatic cardiac toxicity received significantly greater mean V20, 30 and 40 values to the heart compared to asymptomatic patients. These data need validation in a larger independent data set.

  15. Predicting persuasion-induced behavior change from the brain.

    Science.gov (United States)

    Falk, Emily B; Berkman, Elliot T; Mann, Traci; Harrison, Brittany; Lieberman, Matthew D

    2010-06-23

    Although persuasive messages often alter people's self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance.

  16. Climate change affects rainmakers' predictions | IDRC - International ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2010-10-08

    Oct 8, 2010 ... English · Français ... animals, associated with seasonal changes,” Mary O'Neill of Climate Change Adaptation in Africa ( CCAA ) told MediaGlobal. ... and the meteorologists forecast apply on the national and regional level.

  17. Predicting postoperative haemoglobin changes after burn surgery ...

    African Journals Online (AJOL)

    Background. Burn surgery is associated with significant blood loss and fluid shifts that cause rapid haemoglobin (Hb) changes during and after surgery. Understanding the relationship between intraoperative and postoperative (day 1) Hb changes may assist in avoiding postoperative anaemia and unnecessary ...

  18. Climate change and related activities

    International Nuclear Information System (INIS)

    1992-01-01

    The production and consumption of energy contributes to the concentration of greenhouse gases in the atmosphere and is the focus of other environmental concerns as well. Yet the use of energy contributes to worldwide economic growth and development. If we are to achieve environmentally sound economic growth, we must develop and deploy energy technologies that contribute to global stewardship. The Department of Energy carries out an aggressive scientific research program to address some of the key uncertainties associated with the climate change issue. Of course, research simply to study the science of global climate change is not enough. At the heart of any regime of cost-effective actions to address the possibility of global climate change will be a panoply of new technologies-technologies both to provide the services we demand and to use energy more efficiently than in the past. These, too, are important areas of responsibility for the Department. This report is a brief description of the Department's activities in scientific research, technology development, policy studies, and international cooperation that are directly related to or have some bearing on the issue of global climate change

  19. Changing activity in MS lesions

    International Nuclear Information System (INIS)

    Kermode, A.G.; Tofts, P.S.; Thompson, A.J.; Rudge, P.; MacManus, D.G.; Kendall, B.E.; Moseley, I.F.; Kingsley, D.P.E.; McDonald, W.I.

    1989-01-01

    Gd-DTPA enhanced T1 weighted MRI is a discriminating test for a defective blood-brain barrier, with MS lesions showing considerable variation in the pattern of enhancement. Since little is known of the changes in the blood-brain barrier in the active plaque over time, the natural history of blood-brain barrier disturbance in the MS lesion was examined to confirm earlier reports that Gd-DTPA enhancement is a consistent early event in new lesions of relapsing/remitting MS. This knowledge is essential for the use of MRI in monitoring treatment. (author). 9 refs

  20. Features and prospects of juridical predicting of entrepreneurial activity

    Directory of Open Access Journals (Sweden)

    Natalya V. Rubtsova

    2017-03-01

    Full Text Available Objective to identify characteristics and prospects of predicting the business activity. Methods historical sociological logical systematicstructural formallegal comparativelegal legal modeling method. Results in article suggests the legal definition of prediction of business activity as a scientific and practical study aimed at the determination of the future state and prospects of development of business activity consisting of the evaluation of legal regulation and analysis of the prospectsof further socioeconomic development which aims to select the optimal solution for the further development of entrepreneurship through legal regulators. The work proves the necessity of achieving a balanced legal regulation of social relations by changing the legislation in the field of business agreements investment and innovation. Scientific novelty the article for the first time formulates the concept characteristics and features of legal prediction of business activity substantiates the impact of predicting on the development of legal regulation of social relations. Practical significance the main provisions and conclusions of the article can be used in research and teaching while considering the issues of predicting both the socioeconomic processes in general and business activity in particular.

  1. Relationship between efficiency and predictability in stock price change

    Science.gov (United States)

    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.

  2. Predicting Mood Changes in Bipolar Disorder through Heartbeat Nonlinear Dynamics.

    Science.gov (United States)

    Valenza, Gaetano; Nardelli, Mimma; Lanata', Antonio; Gentili, Claudio; Bertschy, Gilles; Kosel, Markus; Scilingo, Enzo Pasquale

    2016-04-20

    Bipolar Disorder (BD) is characterized by an alternation of mood states from depression to (hypo)mania. Mixed states, i.e., a combination of depression and mania symptoms at the same time, can also be present. The diagnosis of this disorder in the current clinical practice is based only on subjective interviews and questionnaires, while no reliable objective psychophysiological markers are available. Furthermore, there are no biological markers predicting BD outcomes, or providing information about the future clinical course of the phenomenon. To overcome this limitation, here we propose a methodology predicting mood changes in BD using heartbeat nonlinear dynamics exclusively, derived from the ECG. Mood changes are here intended as transitioning between two mental states: euthymic state (EUT), i.e., the good affective balance, and non-euthymic (non-EUT) states. Heart Rate Variability (HRV) series from 14 bipolar spectrum patients (age: 33.439.76, age range: 23-54; 6 females) involved in the European project PSYCHE, undergoing whole night ECG monitoring were analyzed. Data were gathered from a wearable system comprised of a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire ECGs. Each patient was monitored twice a week, for 14 weeks, being able to perform normal (unstructured) activities. From each acquisition, the longest artifact-free segment of heartbeat dynamics was selected for further analyses. Sub-segments of 5 minutes of this segment were used to estimate trends of HRV linear and nonlinear dynamics. Considering data from a current observation at day t0, and past observations at days (t1, t2,...,), personalized prediction accuracies in forecasting a mood state (EUT/non-EUT) at day t+1 were 69% on average, reaching values as high as 83.3%. This approach opens to the possibility of predicting mood states in bipolar patients through heartbeat nonlinear dynamics exclusively.

  3. Human medial frontal cortex activity predicts learning from errors.

    Science.gov (United States)

    Hester, Robert; Barre, Natalie; Murphy, Kevin; Silk, Tim J; Mattingley, Jason B

    2008-08-01

    Learning from errors is a critical feature of human cognition. It underlies our ability to adapt to changing environmental demands and to tune behavior for optimal performance. The posterior medial frontal cortex (pMFC) has been implicated in the evaluation of errors to control behavior, although it has not previously been shown that activity in this region predicts learning from errors. Using functional magnetic resonance imaging, we examined activity in the pMFC during an associative learning task in which participants had to recall the spatial locations of 2-digit targets and were provided with immediate feedback regarding accuracy. Activity within the pMFC was significantly greater for errors that were subsequently corrected than for errors that were repeated. Moreover, pMFC activity during recall errors predicted future responses (correct vs. incorrect), despite a sizeable interval (on average 70 s) between an error and the next presentation of the same recall probe. Activity within the hippocampus also predicted future performance and correlated with error-feedback-related pMFC activity. A relationship between performance expectations and pMFC activity, in the absence of differing reinforcement value for errors, is consistent with the idea that error-related pMFC activity reflects the extent to which an outcome is "worse than expected."

  4. Global vegetation change predicted by the modified Budyko model

    Energy Technology Data Exchange (ETDEWEB)

    Monserud, R.A.; Tchebakova, N.M.; Leemans, R. (US Department of Agriculture, Moscow, ID (United States). Intermountain Research Station, Forest Service)

    1993-09-01

    A modified Budyko global vegetation model is used to predict changes in global vegetation patterns resulting from climate change (CO[sub 2] doubling). Vegetation patterns are predicted using a model based on a dryness index and potential evaporation determined by solving radiation balance equations. Climate change scenarios are derived from predictions from four General Circulation Models (GCM's) of the atmosphere (GFDL, GISS, OSU, and UKMO). All four GCM scenarios show similar trends in vegetation shifts and in areas that remain stable, although the UKMO scenario predicts greater warming than the others. Climate change maps produced by all four GCM scenarios show good agreement with the current climate vegetation map for the globe as a whole, although over half of the vegetation classes show only poor to fair agreement. The most stable areas are Desert and Ice/Polar Desert. Because most of the predicted warming is concentrated in the Boreal and Temperate zones, vegetation there is predicted to undergo the greatest change. Most vegetation classes in the Subtropics and Tropics are predicted to expand. Any shift in the Tropics favouring either Forest over Savanna, or vice versa, will be determined by the magnitude of the increased precipitation accompanying global warming. Although the model predicts equilibrium conditions to which many plant species cannot adjust (through migration or microevolution) in the 50-100 y needed for CO[sub 2] doubling, it is not clear if projected global warming will result in drastic or benign vegetation change. 72 refs., 3 figs., 3 tabs.

  5. Resting alpha activity predicts learning ability in alpha neurofeedback

    Directory of Open Access Journals (Sweden)

    Wenya eNan

    2014-07-01

    Full Text Available Individuals differ in their ability to learn how to regulate the alpha activity by neurofeedback. This study aimed to investigate whether the resting alpha activity is related to the learning ability of alpha enhancement in neurofeedback and could be used as a predictor. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback in order to learn how to enhance activity in the alpha frequency band. The learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.

  6. Predicting impacts of climate change on Fasciola hepatica risk.

    Science.gov (United States)

    Fox, Naomi J; White, Piran C L; McClean, Colin J; Marion, Glenn; Evans, Andy; Hutchings, Michael R

    2011-01-10

    Fasciola hepatica (liver fluke) is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.

  7. Predicting impacts of climate change on Fasciola hepatica risk.

    Directory of Open Access Journals (Sweden)

    Naomi J Fox

    2011-01-01

    Full Text Available Fasciola hepatica (liver fluke is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.

  8. Finite element predictions of active buckling control of stiffened panels

    Science.gov (United States)

    Thompson, Danniella M.; Griffin, O. H., Jr.

    1993-04-01

    Materials systems and structures that can respond 'intelligently' to their environment are currently being proposed and investigated. A series of finite element analyses was performed to investigate the potential for active buckling control of two different stiffened panels by embedded shape memory alloy (SMA) rods. Changes in the predicted buckling load increased with the magnitude of the actuation level for a given structural concept. Increasing the number of actuators for a given concept yielded greater predicted increases in buckling load. Considerable control authority was generated with a small number of actuators, with greater authority demonstrated for those structural concepts where the activated SMA rods could develop greater forces and moments on the structure. Relatively simple and inexpensive analyses were performed with standard finite elements to determine such information, indicating the viability of these types of models for design purposes.

  9. Prediction of iodine activity peak during refuelling

    International Nuclear Information System (INIS)

    Hozer, Z.; Vajda, N.

    2001-01-01

    The increase of fission product activities in the primary circuit of a nuclear power plant indicates the existence of defects in some fuel rods. The power change leads to the cooling down of the fuel and results in the fragmentation of the UO 2 pellets, which facilitates the release of fission products from the intergranular regions. Furthermore the injection of boric acid after shutdown will increase the primary activity, due to the solution of deposited fission products from the surface of the core components. The calculation of these phenomena usually is based on the evaluation of activity measurements and power plant data. The estimation of iodine spiking peak during reactor transients is based on correlation with operating parameters, such as reactor power and primary pressure. The approach used in the present method was applied for CANDU reactors. The VVER-440 specific correlations were determined using the activity measurements of the Paks NPP and the data provided by the Russian fuel supplier. The present method is used for the evaluation of the iodine isotopes, as well as the noble gases. A numerical model has been developed for iodine spiking simulation and has been validated against several shutdown transients, measured at Paks NPP. (R.P.)

  10. Regime shifts limit the predictability of land-system change

    DEFF Research Database (Denmark)

    Müller, Daniel; Sun, Zhanli; Vongvisouk, Thoumthone

    2014-01-01

    Payment schemes for ecosystem services such as Reducing Emissions from Deforestation and forest Degradation (REDD) rely on the prediction of ‘business-as-usual’ scenarios to ensure that emission reductions from carbon credits are additional. However, land systems often undergo periods of nonlinear...... and abrupt change that invalidate predictions calibrated on past trends. Rapid land-system change can occur when critical thresholds in broad-scale underlying drivers such as commodity prices and climate conditions are crossed or when sudden events such as political change or natural disasters punctuate long...

  11. Supporting change processes in design: Complexity, prediction and reliability

    Energy Technology Data Exchange (ETDEWEB)

    Eckert, Claudia M. [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: cme26@cam.ac.uk; Keller, Rene [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: rk313@cam.ac.uk; Earl, Chris [Open University, Department of Design and Innovation, Walton Hall, Milton Keynes MK7 6AA (United Kingdom)]. E-mail: C.F.Earl@open.ac.uk; Clarkson, P. John [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: pjc10@cam.ac.uk

    2006-12-15

    Change to existing products is fundamental to design processes. New products are often designed through change or modification to existing products. Specific parts or subsystems are changed to similar ones whilst others are directly reused. Design by modification applies particularly to safety critical products where the reuse of existing working parts and subsystems can reduce cost and risk. However change is rarely a matter of just reusing or modifying parts. Changing one part can propagate through the entire design leading to costly rework or jeopardising the integrity of the whole product. This paper characterises product change based on studies in the aerospace and automotive industry and introduces tools to aid designers in understanding the potential effects of change. Two ways of supporting designers are described: probabilistic prediction of the effects of change and visualisation of change propagation through product connectivities. Change propagation has uncertainties which are amplified by the choices designers make in practice as they implement change. Change prediction and visualisation is discussed with reference to complexity in three areas of product development: the structural backcloth of connectivities in the existing product (and its processes), the descriptions of the product used in design and the actions taken to carry out changes.

  12. Prediction of body lipid change in pregnancy and lactation.

    Science.gov (United States)

    Friggens, N C; Ingvartsen, K L; Emmans, G C

    2004-04-01

    A simple method to predict the genetically driven pattern of body lipid change through pregnancy and lactation in dairy cattle is proposed. The rationale and evidence for genetically driven body lipid change have their basis in evolutionary considerations and in the homeorhetic changes in lipid metabolism through the reproductive cycle. The inputs required to predict body lipid change are body lipid mass at calving (kg) and the date of conception (days in milk). Body lipid mass can be derived from body condition score and live weight. A key assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between calving and a genetically determined time in lactation (T') at which a particular level of body lipid (L') is sought. A second assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between T' and the next calving. The resulting model was evaluated using 2 sets of data. The first was from Holstein cows with 3 different levels of body fatness at calving. The second was from Jersey cows in first, second, and third parity. The model was found to reproduce the observed patterns of change in body lipid reserves through lactation in both data sets. The average error of prediction was low, less than the variation normally associated with the recording of condition score, and was similar for the 2 data sets. When the model was applied using the initially suggested parameter values derived from the literature the average error of prediction was 0.185 units of condition score (+/- 0.086 SD). After minor adjustments to the parameter values, the average error of prediction was 0.118 units of condition score (+/- 0.070 SD). The assumptions on which the model is based were sufficient to predict the changes in body lipid of both Holstein and Jersey cows under different nutritional conditions and parities. Thus, the model presented here shows that it is possible to predict genetically driven curves of body

  13. Changes in Pilot Behavior with Predictive System Status Information

    Science.gov (United States)

    Trujillo, Anna C.

    1998-01-01

    Research has shown a strong pilot preference for predictive information of aircraft system status in the flight deck. However, changes in pilot behavior associated with using this predictive information have not been ascertained. The study described here quantified these changes using three types of predictive information (none, whether a parameter was changing abnormally, and the time for a parameter to reach an alert range) and three initial time intervals until a parameter alert range was reached (ITIs) (1 minute, 5 minutes, and 15 minutes). With predictive information, subjects accomplished most of their tasks before an alert occurred. Subjects organized the time they did their tasks by locus-of-control with no predictive information and for the 1-minute ITI, and by aviatenavigate-communicate for the time for a parameter to reach an alert range and the 15-minute conditions. Overall, predictive information and the longer ITIs moved subjects to performing tasks before the alert actually occurred and had them more mission oriented as indicated by their tasks grouping of aviate-navigate-communicate.

  14. Predicting coastal morphological changes with empirical orthogonal functionmethod

    Directory of Open Access Journals (Sweden)

    Fernando Alvarez

    2016-01-01

    Full Text Available In order to improve the accuracy of prediction when using the empirical orthogonal function (EOF method, this paper describes a novel approach for two-dimensional (2D EOF analysis based on extrapolating both the spatial and temporal EOF components for long-term prediction of coastal morphological changes. The approach was investigated with data obtained from a process-based numerical model, COAST2D, which was applied to an idealized study site with a group of shore-parallel breakwaters. The progressive behavior of the spatial and temporal EOF components, related to bathymetric changes over a training period, was demonstrated, and EOF components were extrapolated with combined linear and exponential functions for long-term prediction. The extrapolated EOF components were then used to reconstruct bathymetric changes. The comparison of the reconstructed bathymetric changes with the modeled results from the COAST2D model illustrates that the presented approach can be effective for long-term prediction of coastal morphological changes, and extrapolating both the spatial and temporal EOF components yields better results than extrapolating only the temporal EOF component.

  15. Predicting vulnerabilities of North American shorebirds to climate change.

    Directory of Open Access Journals (Sweden)

    Hector Galbraith

    Full Text Available Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at-risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners-in-Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90% taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower-risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change.

  16. Timing and Magnitude of Initial Change in Disease Activity Score 28 Predicts the Likelihood of Achieving Low Disease Activity at 1 Year in Rheumatoid Arthritis Patients Treated with Certolizumab Pegol: A Post-hoc Analysis of the RAPID 1 Trial

    NARCIS (Netherlands)

    van der Heijde, Désirée; Keystone, Edward C.; Curtis, Jeffrey R.; Landewé, Robert B.; Schiff, Michael H.; Khanna, Dinesh; Kvien, Tore K.; Ionescu, Lucian; Gervitz, Leon M.; Davies, Owen R.; Luijtens, Kristel; Furst, Daniel E.

    2012-01-01

    Objective. To determine the relationship between timing and magnitude of Disease Activity Score [DAS28(ESR)] nonresponse (DAS28 improvement thresholds not reached) during the first 12 weeks of treatment with certolizumab pegol (CZP) plus methotrexate, and the likelihood of achieving low disease

  17. Climate-Induced Boreal Forest Change: Predictions versus Current Observations

    Science.gov (United States)

    Soja, Amber J.; Tchebakova, Nadezda M.; French, Nancy H. F.; Flannigan, Michael D.; Shugart, Herman H.; Stocks, Brian J.; Sukhinin, Anatoly I.; Parfenova, E. I.; Chapin, F. Stuart, III; Stackhouse, Paul W., Jr.

    2007-01-01

    For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.

  18. THE PROCESS OF CHANGE - PREDICTION OF SPORT ACHIEVEMENTS HISTORICAL TENDENCY

    Directory of Open Access Journals (Sweden)

    Izenedin Mehmeti

    2015-05-01

    Full Text Available The aim of this paper is to summarize the different standpoints and different approaches in regard to the sport performance preparation and achievement prediction. Sports researchers are concerned more directly with learning about scientific sports prediction. Their involvement in the sport sciences focuses on understanding how sports organized and how changes in that organization might influence sports experiences for both athletes and coaches. The goal of these scholars is often to improve sport experiences and performance prediction for current participants and make sport participation more attractive and accessible for those who do not currently play sports, prospective athletes. They also may want to help athletes improve their performance, help coaches work effectively with athletes and win more games. Sports researchers intention is also to assist and help sport organizations grow and operate more efficiently and profitably, and improve sport achievement prediction.

  19. Spontaneous brain activity predicts learning ability of foreign sounds.

    Science.gov (United States)

    Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

    2013-05-29

    Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

  20. Recent and Past Musical Activity Predicts Cognitive Aging Variability: Direct Comparison with Leisure Activities

    Directory of Open Access Journals (Sweden)

    Brenda eHanna-Pladdy

    2012-07-01

    Full Text Available Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years on preserved cognitive functioning in advanced age . These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to nonmusical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study examined the type of leisure activity (musical versus other as well as the timing of engagement (age of acquisition, past versus recent in predictive models of successful cognitive aging. Seventy age and education matched older musicians (> 10 years and nonmusicians (ages 59-80 were evaluated on neuropsychological tests and life-style activities (AAP. Partition analyses were conducted on significant cognitive measures to explain performance variance in musicians. Musicians scored higher on tests of phonemic fluency, verbal immediate recall, judgment of line orientation (JLO, and Letter Number Sequencing (LNS, but not the AAP. The first partition analysis revealed education best predicted JLO in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (< 9 years predicted enhanced LNS in musicians, while analyses for AAP, verbal recall and fluency were not predictive. Recent and past musical activity, but not leisure activity, predicted variability across verbal and visuospatial domains in aging. Early musical acquisition predicted auditory

  1. "Engage" therapy: Prediction of change of late-life major depression.

    Science.gov (United States)

    Alexopoulos, George S; O'Neil, Robert; Banerjee, Samprit; Raue, Patrick J; Victoria, Lindsay W; Bress, Jennifer N; Pollari, Cristina; Arean, Patricia A

    2017-10-15

    Engage grew out of the need for streamlined psychotherapies that can be accurately used by community therapists in late-life depression. Engage was based on the view that dysfunction of reward networks is the principal mechanism mediating depressive symptoms. Accordingly, Engage uses "reward exposure" (exposure to meaningful activities) and assumes that repeated activation of reward networks will normalize these systems. This study examined whether change in a behavioral activation scale, an index of reward system function, predicts change in depressive symptomatology. The participants (N = 48) were older adults with major depression treated with 9 weekly sessions of Engage and assessed 27 weeks after treatment. Depression was assessed with the 24-item Hamilton Depression Rating Scale (HAM-D) and behavioral activation with the four subscales of Behavioral Activation for Depression Scale (activation, avoidance/rumination, work impairment, social impairment) at baseline, 6 weeks (mid-treatment), 9 weeks (end of treatment), and 36 weeks. Change only in the Activation subscale during successive periods of assessment predicted depression severity (HAM-D) at the end of each period (F 1, 47 = 21.05, psocial support. Change in behavioral activation predicts improvement of depressive symptoms and signs in depressed older adults treated with Engage. Copyright © 2017. Published by Elsevier B.V.

  2. Can tail damage outbreaks in the pig be predicted by behavioural change?

    DEFF Research Database (Denmark)

    Larsen, Mona Lilian Vestbjerg; Andersen, Heidi Mai-Lis; Pedersen, Lene Juul

    2016-01-01

    preventive methods. One strategy is the surveillance of the pigs' behaviour for known preceding indicators of tail damage, which makes it possible to predict a tail damage outbreak and prevent it in proper time. This review discusses the existing literature on behavioural changes observed prior to a tail...... damage outbreak. Behaviours found to change prior to an outbreak include increased activity level, increased performance of enrichment object manipulation, and a changed proportion of tail posture with more tails between the legs. Monitoring these types of behaviours is also discussed for the purpose......, starting with the description of the temporal development of the predictive behaviour in relation to tail damage outbreaks...

  3. Changing predictions, stable recognition: Children's representations of downward incline motion.

    Science.gov (United States)

    Hast, Michael; Howe, Christine

    2017-11-01

    Various studies to-date have demonstrated children hold ill-conceived expressed beliefs about the physical world such as that one ball will fall faster than another because it is heavier. At the same time, they also demonstrate accurate recognition of dynamic events. How these representations relate is still unresolved. This study examined 5- to 11-year-olds' (N = 130) predictions and recognition of motion down inclines. Predictions were typically in error, matching previous work, but children largely recognized correct events as correct and rejected incorrect ones. The results also demonstrate while predictions change with increasing age, recognition shows signs of stability. The findings provide further support for a hybrid model of object representations and argue in favour of stable core cognition existing alongside developmental changes. Statement of contribution What is already known on this subject? Children's predictions of physical events show limitations in accuracy Their recognition of such events suggests children may use different knowledge sources in their reasoning What the present study adds? Predictions fluctuate more strongly than recognition, suggesting stable core cognition But recognition also shows some fluctuation, arguing for a hybrid model of knowledge representation. © 2017 The British Psychological Society.

  4. Prediction of Human Activity by Discovering Temporal Sequence Patterns.

    Science.gov (United States)

    Li, Kang; Fu, Yun

    2014-08-01

    Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

  5. "You've Changed": Low Self-Concept Clarity Predicts Lack of Support for Partner Change.

    Science.gov (United States)

    Emery, Lydia F; Gardner, Wendi L; Finkel, Eli J; Carswell, Kathleen L

    2018-03-01

    People often pursue self-change, and having a romantic partner who supports these changes increases relationship satisfaction. However, most existing research focuses only on the experience of the person who is changing. What predicts whether people support their partner's change? People with low self-concept clarity resist self-change, so we hypothesized that they would be unsupportive of their partner's changes. People with low self-concept clarity did not support their partner's change (Study 1a), because they thought they would have to change, too (Study 1b). Low self-concept clarity predicted failing to support a partner's change, but not vice versa (Studies 2 and 3), and only for larger changes (Study 3). Not supporting a partner's change predicted decreases in relationship quality for both members of the couple (Studies 2 and 3). This research underscores the role of partners in self-change, suggesting that failing to support a partner's change may stem from self-concept confusion.

  6. Change in avian abundance predicted from regional forest inventory data

    Science.gov (United States)

    Twedt, Daniel J.; Tirpak, John M.; Jones-Farrand, D. Todd; Thompson, Frank R.; Uihlein, William B.; Fitzgerald, Jane A.

    2010-01-01

    An inability to predict population response to future habitat projections is a shortcoming in bird conservation planning. We sought to predict avian response to projections of future forest conditions that were developed from nationwide forest surveys within the Forest Inventory and Analysis (FIA) program. To accomplish this, we evaluated the historical relationship between silvicolous bird populations and FIA-derived forest conditions within 25 ecoregions that comprise the southeastern United States. We aggregated forest area by forest ownership, forest type, and tree size-class categories in county-based ecoregions for 5 time periods spanning 1963-2008. We assessed the relationship of forest data with contemporaneous indices of abundance for 24 silvicolous bird species that were obtained from Breeding Bird Surveys. Relationships between bird abundance and forest inventory data for 18 species were deemed sufficient as predictive models. We used these empirically derived relationships between regional forest conditions and bird populations to predict relative changes in abundance of these species within ecoregions that are anticipated to coincide with projected changes in forest variables through 2040. Predicted abundances of these 18 species are expected to remain relatively stable in over a quarter (27%) of the ecoregions. However, change in forest area and redistribution of forest types will likely result in changed abundance of some species within many ecosystems. For example, abundances of 11 species, including pine warbler (Dendroica pinus), brown-headed nuthatch (Sitta pusilla), and chuckwills- widow (Caprimulgus carolinensis), are projected to increase within more ecoregions than ecoregions where they will decrease. For 6 other species, such as blue-winged warbler (Vermivora pinus), Carolina wren (Thryothorus ludovicianus), and indigo bunting (Passerina cyanea), we projected abundances will decrease within more ecoregions than ecoregions where they will

  7. Recent and past musical activity predicts cognitive aging variability: direct comparison with general lifestyle activities.

    Science.gov (United States)

    Hanna-Pladdy, Brenda; Gajewski, Byron

    2012-01-01

    Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years) on preserved cognitive functioning in advanced age. These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to non-musical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in general lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study controlled for general activity level in evaluating cognition between musicians and nomusicians. Also, the timing of engagement (age of acquisition, past versus recent) was assessed in predictive models of successful cognitive aging. Seventy age and education matched older musicians (>10 years) and non-musicians (ages 59-80) were evaluated on neuropsychological tests and general lifestyle activities. Musicians scored higher on tests of phonemic fluency, verbal working memory, verbal immediate recall, visuospatial judgment, and motor dexterity, but did not differ in other general leisure activities. Partition analyses were conducted on significant cognitive measures to determine aspects of musical training predictive of enhanced cognition. The first partition analysis revealed education best predicted visuospatial functions in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (memory in musicians, while analyses for other measures were not predictive. Recent and past musical activity, but not general lifestyle activities, predicted variability

  8. Saliency predicts change detection in pictures of natural scenes.

    Science.gov (United States)

    Wright, Michael J

    2005-01-01

    It has been proposed that the visual system encodes the salience of objects in the visual field in an explicit two-dimensional map that guides visual selective attention. Experiments were conducted to determine whether salience measurements applied to regions of pictures of outdoor scenes could predict the detection of changes in those regions. To obtain a quantitative measure of change detection, observers located changes in pairs of colour pictures presented across an interstimulus interval (ISI). Salience measurements were then obtained from different observers for image change regions using three independent methods, and all were positively correlated with change detection. Factor analysis extracted a single saliency factor that accounted for 62% of the variance contained in the four measures. Finally, estimates of the magnitude of the image change in each picture pair were obtained, using nine separate visual filters representing low-level vision features (luminance, colour, spatial frequency, orientation, edge density). None of the feature outputs was significantly associated with change detection or saliency. On the other hand it was shown that high-level (structural) properties of the changed region were related to saliency and to change detection: objects were more salient than shadows and more detectable when changed.

  9. A predictive framework to understand forest responses to global change.

    Science.gov (United States)

    McMahon, Sean M; Dietze, Michael C; Hersh, Michelle H; Moran, Emily V; Clark, James S

    2009-04-01

    Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.

  10. Prediction of permeability changes in an excavation response zone

    International Nuclear Information System (INIS)

    Kinoshita, Naoto; Ishii, Takashi; Kuroda, Hidetaka; Tada, Hiroyuki

    1992-01-01

    In geologic disposal of radioactive wastes, stress changes due to cavern excavation may expand the existing fractures and create possible bypasses for groundwater. This paper proposes a simple method for predicting permeability changes in the excavation response zones. Numerical analyses using this method predict that the response zones created by cavern excavation would differ greatly in thickness and permeability depending on the depth of the cavern site and the initial in-situ stress, that when the cavern site is deeper, response zones would expand more and permeability would increases more, and that if the ratio of horizontal to vertical in-situ stress is small, extensive permeable zones at the crown and the bottom would occur, whereas if the ratio is large, extensive permeable zones would occur in the side walls. (orig.)

  11. Predicting Climate Change Impacts to the Canadian Boreal Forest

    Directory of Open Access Journals (Sweden)

    Trisalyn A. Nelson

    2014-03-01

    Full Text Available Climate change is expected to alter temperature, precipitation, and seasonality with potentially acute impacts on Canada’s boreal. In this research we predicted future spatial distributions of biodiversity in Canada’s boreal for 2020, 2050, and 2080 using indirect indicators derived from remote sensing and based on vegetation productivity. Vegetation productivity indices, representing annual amounts and variability of greenness, have been shown to relate to tree and wildlife richness in Canada’s boreal. Relationships between historical satellite-derived productivity and climate data were applied to modelled scenarios of future climate to predict and map potential future vegetation productivity for 592 regions across Canada. Results indicated that the pattern of vegetation productivity will become more homogenous, particularly west of Hudson Bay. We expect climate change to impact biodiversity along north/south gradients and by 2080 vegetation distributions will be dominated by processes of seasonality in the north and a combination of cumulative greenness and minimum cover in the south. The Hudson Plains, which host the world’s largest and most contiguous wetland, are predicted to experience less seasonality and more greenness. The spatial distribution of predicted trends in vegetation productivity was emphasized over absolute values, in order to support regional biodiversity assessments and conservation planning.

  12. HESS Opinions: Hydrologic predictions in a changing environment: behavioral modeling

    Directory of Open Access Journals (Sweden)

    S. J. Schymanski

    2011-02-01

    Full Text Available Most hydrological models are valid at most only in a few places and cannot be reasonably transferred to other places or to far distant time periods. Transfer in space is difficult because the models are conditioned on past observations at particular places to define parameter values and unobservable processes that are needed to fully characterize the structure and functioning of the landscape. Transfer in time has to deal with the likely temporal changes to both parameters and processes under future changed conditions. This remains an important obstacle to addressing some of the most urgent prediction questions in hydrology, such as prediction in ungauged basins and prediction under global change. In this paper, we propose a new approach to catchment hydrological modeling, based on universal principles that do not change in time and that remain valid across many places. The key to this framework, which we call behavioral modeling, is to assume that there are universal and time-invariant organizing principles that can be used to identify the most appropriate model structure (including parameter values and responses for a given ecosystem at a given moment in time. These organizing principles may be derived from fundamental physical or biological laws, or from empirical laws that have been demonstrated to be time-invariant and to hold at many places and scales. Much fundamental research remains to be undertaken to help discover these organizing principles on the basis of exploration of observed patterns of landscape structure and hydrological behavior and their interpretation as legacy effects of past co-evolution of climate, soils, topography, vegetation and humans. Our hope is that the new behavioral modeling framework will be a step forward towards a new vision for hydrology where models are capable of more confidently predicting the behavior of catchments beyond what has been observed or experienced before.

  13. Activities: Plotting and Predicting from Pairs.

    Science.gov (United States)

    Shulte, Albert P.; Swift, Jim

    1984-01-01

    This teacher's guide provides objectives, procedures, and list of materials needed for activities which center around the use of a scatter plot to examine relationships shown by bivariate data. The activities are suitable for grades 7 to 12. Four student worksheets are included. (JN)

  14. Epigenetic Changes during Hepatic Stellate Cell Activation.

    Directory of Open Access Journals (Sweden)

    Silke Götze

    Full Text Available Hepatic stellate cells (HSC, which can participate in liver regeneration and fibrogenesis, have recently been identified as liver-resident mesenchymal stem cells. During their activation HSC adopt a myofibroblast-like phenotype accompanied by profound changes in the gene expression profile. DNA methylation changes at single genes have been reported during HSC activation and may participate in the regulation of this process, but comprehensive DNA methylation analyses are still missing. The aim of the present study was to elucidate the role of DNA methylation during in vitro activation of HSC.The analysis of DNA methylation changes by antibody-based assays revealed a strong decrease in the global DNA methylation level during culture-induced activation of HSC. To identify genes which may be regulated by DNA methylation, we performed a genome-wide Methyl-MiniSeq EpiQuest sequencing comparing quiescent and early culture-activated HSC. Approximately 400 differentially methylated regions with a methylation change of at least 20% were identified, showing either hypo- or hypermethylation during activation. Further analysis of selected genes for DNA methylation and expression were performed revealing a good correlation between DNA methylation changes and gene expression. Furthermore, global DNA demethylation during HSC activation was investigated by 5-bromo-2-deoxyuridine assay and L-mimosine treatment showing that demethylation was independent of DNA synthesis and thereby excluding a passive DNA demethylation mechanism.In summary, in vitro activation of HSC initiated strong DNA methylation changes, which were associated with gene regulation. These results indicate that epigenetic mechanisms are important for the control of early HSC activation. Furthermore, the data show that global DNA demethylation during activation is based on an active DNA demethylation mechanism.

  15. Caregiver Confidence: Does It Predict Changes in Disability among Elderly Home Care Recipients?

    Science.gov (United States)

    Li, Lydia W.; McLaughlin, Sara J.

    2012-01-01

    Purpose of the study: The primary aim of this investigation was to determine whether caregiver confidence in their care recipients' functional capabilities predicts changes in the performance of activities of daily living (ADL) among elderly home care recipients. A secondary aim was to explore how caregiver confidence and care recipient functional…

  16. Neural response to pictorial health warning labels can predict smoking behavioral change.

    Science.gov (United States)

    Riddle, Philip J; Newman-Norlund, Roger D; Baer, Jessica; Thrasher, James F

    2016-11-01

    In order to improve our understanding of how pictorial health warning labels (HWLs) influence smoking behavior, we examined whether brain activity helps to explain smoking behavior above and beyond self-reported effectiveness of HWLs. We measured the neural response in the ventromedial prefrontal cortex (vmPFC) and the amygdala while adult smokers viewed HWLs. Two weeks later, participants' self-reported smoking behavior and biomarkers of smoking behavior were reassessed. We compared multiple models predicting change in self-reported smoking behavior (cigarettes per day [CPD]) and change in a biomarkers of smoke exposure (expired carbon monoxide [CO]). Brain activity in the vmPFC and amygdala not only predicted changes in CO, but also accounted for outcome variance above and beyond self-report data. Neural data were most useful in predicting behavioral change as quantified by the objective biomarker (CO). This pattern of activity was significantly modulated by individuals' intention to quit. The finding that both cognitive (vmPFC) and affective (amygdala) brain areas contributed to these models supports the idea that smokers respond to HWLs in a cognitive-affective manner. Based on our findings, researchers may wish to consider using neural data from both cognitive and affective networks when attempting to predict behavioral change in certain populations (e.g. cigarette smokers). © The Author (2016). Published by Oxford University Press.

  17. Activity, exposure rate and spectrum prediction with Java programming

    International Nuclear Information System (INIS)

    Sahin, D.; Uenlue, K.

    2009-01-01

    In order to envision the radiation exposure during Neutron Activation Analysis (NAA) experiments, a software called Activity Predictor is developed using Java TM programming language. The Activity Predictor calculates activities, exposure rates and gamma spectra of activated samples for NAA experiments performed at Radiation Science and Engineering Center (RSEC), Penn State Breazeale Reactor (PSBR). The calculation procedure for predictions involves both analytical and Monte Carlo methods. The Activity Predictor software is validated with a series of activation experiments. It has been found that Activity Predictor software calculates the activities and exposure rates precisely. The software also predicts gamma spectrum for each measurement. The predicted spectra agreed partially with measured spectra. The error in net photo peak areas varied from 4.8 to 51.29%, which is considered to be due to simplistic modeling, statistical fluctuations and unknown contaminants in the samples. (author)

  18. Decreased dopamine activity predicts relapse in methamphetamine abusers

    Energy Technology Data Exchange (ETDEWEB)

    Wang G. J.; Wang, G.-J.; Smith, L.; Volkow, N.D.; Telang, F.; Logan, J.; Tomasi, D.; Wong, C.T.; Hoffman, W.; Jayne, M.; Alia-Klein, N.; Thanos, P.; Fowler, J.S.

    2011-01-20

    Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and [{sup 11}C]raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

  19. Decreased dopamine activity predicts relapse in methamphetamine abusers

    International Nuclear Information System (INIS)

    Wang, G.J.; Smith, L.; Volkow, N.D.; Telang, F.; Logan, J.; Tomasi, D.; Wong, C.T.; Hoffman, W.; Jayne, M.; Alia-Klein, N.; Thanos, P.; Fowler, J.S.

    2011-01-01

    Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and ( 11 C)raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

  20. Changes In Growth Culture FDA Activity Under Changing Growth Conditions

    DEFF Research Database (Denmark)

    Jørgensen, Per Elberg; Eriksen, Thomas Juul; Jensen, Bjørn K.

    1992-01-01

    The FDA hydrolysis capacities and bacterial biomass concentrations (estimated by determination of ATP content) of growth cultures prepared from activated sludge and wastewater, were measured to find out whether the FDA activity would reflect bacterial biomass under different physiological states...... of the bacteria. The FDA activity/ATP ratio was calculated for different concentrations of autoclaved sludge. A faster decay rate of ATP relative to FDA hydrolysis activity was observed, thus causing changes in the ratio. Furthermore, comparison between values obtained from pure cultures and different soils...... revealed differences up to two orders of magnitude of the ratio. Based on these results it was concluded that the FDA activity should not be applied for measurements of viable biomass in environments in which different physiological conditions occur....

  1. Predicting mining activity with parallel genetic algorithms

    Science.gov (United States)

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

    2005-01-01

    We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

  2. Predicting the unpredictable: Critical analysis and practical implications of predictive anticipatory activity

    Directory of Open Access Journals (Sweden)

    Julia eMossbridge

    2014-03-01

    Full Text Available A recent meta-analysis of experiments from seven independent laboratories (n=26 published since 1978 indicates that the human body can apparently detect randomly delivered stimuli occurring 1-10 seconds in the future (Mossbridge, Tressoldi, & Utts, 2012. The key observation in these studies is that human physiology appears to be able to distinguish between unpredictable dichotomous future stimuli, such as emotional vs. neutral images or sound vs. silence. This phenomenon has been called presentiment (as in feeling the future. In this paper we call it predictive anticipatory activity or PAA. The phenomenon is predictive because it can distinguish between upcoming stimuli; it is anticipatory because the physiological changes occur before a future event; and it is an activity because it involves changes in the cardiopulmonary, skin, and/or nervous systems. PAA is an unconscious phenomenon that seems to be a time-reversed reflection of the usual physiological response to a stimulus. It appears to resemble precognition (consciously knowing something is going to happen before it does, but PAA specifically refers to unconscious physiological reactions as opposed to conscious premonitions. Though it is possible that PAA underlies the conscious experience of precognition, experiments testing this idea have not produced clear results. The first part of this paper reviews the evidence for PAA and examines the two most difficult challenges for obtaining valid evidence for it: expectation bias and multiple analyses. The second part speculates on possible mechanisms and the theoretical implications of PAA for understanding physiology and consciousness. The third part examines potential practical applications.

  3. Predicting the degradability of waste activated sludge.

    Science.gov (United States)

    Jones, Richard; Parker, Wayne; Zhu, Henry; Houweling, Dwight; Murthy, Sudhir

    2009-08-01

    The objective of this study was to identify methods for estimating anaerobic digestibility of waste activated sludge (WAS). The WAS streams were generated in three sequencing batch reactors (SBRs) treating municipal wastewater. The wastewater and WAS properties were initially determined through simulation of SBR operation with BioWin (EnviroSim Associates Ltd., Flamborough, Ontario, Canada). Samples of WAS from the SBRs were subsequently characterized through respirometry and batch anaerobic digestion. Respirometry was an effective tool for characterizing the active fraction of WAS and could be a suitable technique for determining sludge composition for input to anaerobic models. Anaerobic digestion of the WAS revealed decreasing methane production and lower chemical oxygen demand removals as the SRT of the sludge increased. BioWin was capable of accurately describing the digestion of the WAS samples for typical digester SRTs. For extended digestion times (i.e., greater than 30 days), some degradation of the endogenous decay products was assumed to achieve accurate simulations for all sludge SRTs.

  4. Cod Gadus morhua and climate change: processes, productivity and prediction

    DEFF Research Database (Denmark)

    Brander, Keith

    2010-01-01

    the causes. Investigation of cod Gadus morhua populations across the whole North Atlantic Ocean has shown large-scale patterns of change in productivity due to lower individual growth and condition, caused by large-scale climate forcing. If a population is being heavily exploited then a drop in productivity......Environmental factors act on individual fishes directly and indirectly. The direct effects on rates and behaviour can be studied experimentally and in the field, particularly with the advent of ever smarter tags for tracking fishes and their environment. Indirect effects due to changes in food......, predators, parasites and diseases are much more difficult to estimate and predict. Climate can affect all life-history stages through direct and indirect processes and although the consequences in terms of growth, survival and reproductive output can be monitored, it is often difficult to determine...

  5. Change in BMI accurately predicted by social exposure to acquaintances.

    Directory of Open Access Journals (Sweden)

    Rahman O Oloritun

    Full Text Available Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC and R(2. This study found a model that explains 68% (p<0.0001 of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as

  6. Improving predictive capabilities of environmental change with GLOBE data

    Science.gov (United States)

    Robin, Jessica Hill

    This dissertation addresses two applications of Normalized Difference Vegetation Index (NDVI) essential for predicting environmental changes. The first study focuses on whether NDVI can improve model simulations of evapotranspiration for temperate Northern (>35°) regions. The second study focuses on whether NDVI can detect phenological changes in start of season (SOS) for high Northern (>60°) environments. The overall objectives of this research were to (1) develop a methodology for utilizing GLOBE data in NDVI research; and (2) provide a critical analysis of NDVI as a long-term monitoring tool for environmental change. GLOBE is an international partnership network of K-12 students, teachers, and scientists working together to study and understand the global environment. The first study utilized data collected by one GLOBE school in Greenville, Pennsylvania and the second utilized phenology observations made by GLOBE students in Alaska. Results from the first study showed NDVI could predict transpiration periods for environments like Greenville, Pennsylvania. In phenological terms, these environments have three distinct periods (QI, QII, and QIII). QI reflects onset of the growing season (mid March--mid May) when vegetation is greening up (NDVI 0.60). Results from the second study showed that a climate threshold of 153 +/- 22 growing degree days was a better predictor of SOS for Fairbanks than a NDVI threshold applied to temporal AVHRR and MODIS datasets. Accumulated growing degree days captured the interannual variability of SOS better than the NDVI threshold and most closely resembled actual SOS observations made by GLOBE students. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska. Both studies did show that GLOBE data provides an important source of input and validation information for NDVI research.

  7. Predicting Seagrass Occurrence in a Changing Climate Using Random Forests

    Science.gov (United States)

    Aydin, O.; Butler, K. A.

    2017-12-01

    Seagrasses are marine plants that can quickly sequester vast amounts of carbon (up to 100 times more and 12 times faster than tropical forests). In this work, we present an integrated GIS and machine learning approach to build a data-driven model of seagrass presence-absence. We outline a random forest approach that avoids the prevalence bias in many ecological presence-absence models. One of our goals is to predict global seagrass occurrence from a spatially limited training sample. In addition, we conduct a sensitivity study which investigates the vulnerability of seagrass to changing climate conditions. We integrate multiple data sources including fine-scale seagrass data from MarineCadastre.gov and the recently available globally extensive publicly available Ecological Marine Units (EMU) dataset. These data are used to train a model for seagrass occurrence along the U.S. coast. In situ oceans data are interpolated using Empirical Bayesian Kriging (EBK) to produce globally extensive prediction variables. A neural network is used to estimate probable future values of prediction variables such as ocean temperature to assess the impact of a warming climate on seagrass occurrence. The proposed workflow can be generalized to many presence-absence models.

  8. Predicting incentives to change among adolescents with substance abuse disorder.

    Science.gov (United States)

    Breda, Carolyn; Heflinger, Craig Anne

    2004-05-01

    While interest in understanding the incentives to change among individuals with substance abuse disorders is growing, little is known about incentives among adolescents with substance abuse disorders who are participating in formal services. The present research assesses the degree and nature of motivation and treatment readiness among adolescents admitted to substance abuse services, and whether such factors vary across significant subgroups of youth based on their social, legal, or clinical profiles. Data are based on interviews with 249 youth between 12 and 18 years of age who have been admitted to either inpatient, residential, or outpatient substance abuse treatment. Measures are adapted from an instrument developed to assess multiple domains of motivation to change (e.g., intrinsic and extrinsic motivation, treatment readiness). Results suggest that the incentive to change among adolescents with substance-abusing behavior is modest at best, regardless of dimension. Nonetheless, ethnicity, type of substance use, and psychopathology significantly predict incentives to change, though the predictors depend on which dimension is considered. The most robust predictor of incentives is the severity of negative consequences associated with youth's substance use--the greater the severity, the greater the incentives. Findings underscore the need to examine the utility and dimensionality of incentive for treatment planning, while at the same time, they identify factors that treatment planners can consider as they seek ways to enhance incentives and help adolescents with substance use disorders attain positive outcomes.

  9. Change in BMI accurately predicted by social exposure to acquaintances.

    Science.gov (United States)

    Oloritun, Rahman O; Ouarda, Taha B M J; Moturu, Sai; Madan, Anmol; Pentland, Alex Sandy; Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R(2). This study found a model that explains 68% (pchange in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends.

  10. Predicting implementation from organizational readiness for change: a study protocol

    Directory of Open Access Journals (Sweden)

    Kelly P Adam

    2011-07-01

    Full Text Available Abstract Background There is widespread interest in measuring organizational readiness to implement evidence-based practices in clinical care. However, there are a number of challenges to validating organizational measures, including inferential bias arising from the halo effect and method bias - two threats to validity that, while well-documented by organizational scholars, are often ignored in health services research. We describe a protocol to comprehensively assess the psychometric properties of a previously developed survey, the Organizational Readiness to Change Assessment. Objectives Our objective is to conduct a comprehensive assessment of the psychometric properties of the Organizational Readiness to Change Assessment incorporating methods specifically to address threats from halo effect and method bias. Methods and Design We will conduct three sets of analyses using longitudinal, secondary data from four partner projects, each testing interventions to improve the implementation of an evidence-based clinical practice. Partner projects field the Organizational Readiness to Change Assessment at baseline (n = 208 respondents; 53 facilities, and prospectively assesses the degree to which the evidence-based practice is implemented. We will conduct predictive and concurrent validities using hierarchical linear modeling and multivariate regression, respectively. For predictive validity, the outcome is the change from baseline to follow-up in the use of the evidence-based practice. We will use intra-class correlations derived from hierarchical linear models to assess inter-rater reliability. Two partner projects will also field measures of job satisfaction for convergent and discriminant validity analyses, and will field Organizational Readiness to Change Assessment measures at follow-up for concurrent validity (n = 158 respondents; 33 facilities. Convergent and discriminant validities will test associations between organizational readiness and

  11. Cognitive biases to healthy and unhealthy food words predict change in BMI.

    Science.gov (United States)

    Calitri, Raff; Pothos, Emmanuel M; Tapper, Katy; Brunstrom, Jeffrey M; Rogers, Peter J

    2010-12-01

    The current study explored the predictive value of cognitive biases to food cues (assessed by emotional Stroop and dot probe tasks) on weight change over a 1-year period. This was a longitudinal study with undergraduate students (N = 102) living in shared student accommodation. After controlling for the effects of variables associated with weight (e.g., physical activity, stress, restrained eating, external eating, and emotional eating), no effects of cognitive bias were found with the dot probe. However, for the emotional Stroop, cognitive bias to unhealthy foods predicted an increase in BMI whereas cognitive bias to healthy foods was associated with a decrease in BMI. Results parallel findings in substance abuse research; cognitive biases appear to predict behavior change. Accordingly, future research should consider strategies for attentional retraining, encouraging individuals to reorient attention away from unhealthy eating cues.

  12. Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions.

    Science.gov (United States)

    Fox, Naomi J; Marion, Glenn; Davidson, Ross S; White, Piran C L; Hutchings, Michael R

    2012-03-06

    Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

  13. Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions

    Directory of Open Access Journals (Sweden)

    Ross S. Davidson

    2012-03-01

    Full Text Available Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

  14. Cardiovascular change during encoding predicts the nonconscious mere exposure effect.

    Science.gov (United States)

    Ladd, Sandra L; Toscano, William B; Cowings, Patricia S; Gabrieli, John D E

    2014-01-01

    These studies examined memory encoding to determine whether the mere exposure effect could be categorized as a form of conceptual or perceptual implicit priming and, if it was not conceptual or perceptual, whether cardiovascular psychophysiology could reveal its nature. Experiment 1 examined the effects of study phase level of processing on recognition, the mere exposure effect, and word identification implicit priming. Deep relative to shallow processing improved recognition but did not influence the mere exposure effect for nonwords or word identification implicit priming for words. Experiments 2 and 3 examined the effect of study-test changes in font and orientation, respectively, on the mere exposure effect and word identification implicit priming. Different study-test font and orientation reduced word identification implicit priming but had no influence on the mere exposure effect. Experiments 4 and 5 developed and used, respectively, a cardiovascular psychophysiological implicit priming paradigm to examine whether stimulus-specific cardiovascular reactivity at study predicted the mere exposure effect at test. Blood volume pulse change at study was significantly greater for nonwords that were later preferred than for nonwords that were not preferred at test. There was no difference in blood volume pulse change for words at study that were later either identified or not identified at test. Fluency effects, at encoding or retrieval, are an unlikely explanation for these behavioral and cardiovascular findings. The relation of blood volume pulse to affect suggests that an affective process that is not conceptual or perceptual contributes to the mere exposure effect.

  15. Selenium deficiency risk predicted to increase under future climate change.

    Science.gov (United States)

    Jones, Gerrad D; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P; Seneviratne, Sonia I; Smith, Pete; Winkel, Lenny H E

    2017-03-14

    Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.

  16. Predicting effects of environmental change on river inflows to ...

    Science.gov (United States)

    Estuarine river watersheds provide valued ecosystem services to their surrounding communities including drinking water, fish habitat, and regulation of estuarine water quality. However, the provisioning of these services can be affected by changes in the quantity and quality of river water, such as those caused by altered landscapes or shifting temperatures or precipitation. We used the ecohydrology model, VELMA, in the Trask River watershed to simulate the effects of environmental change scenarios on estuarine river inputs to Tillamook Bay (OR) estuary. The Trask River watershed is 453 km2 and contains extensive agriculture, silviculture, urban, and wetland areas. VELMA was parameterized using existing spatial datasets of elevation, soil type, land use, air temperature, precipitation, river flow, and water quality. Simulated land use change scenarios included alterations in the distribution of the nitrogen-fixing tree species Alnus rubra, and comparisons of varying timber harvest plans. Scenarios involving spatial and temporal shifts in air temperature and precipitation trends were also simulated. Our research demonstrates the utility of ecohydrology models such as VELMA to aid in watershed management decision-making. Model outputs of river water flow, temperature, and nutrient concentrations can be used to predict effects on drinking water quality, salmonid populations, and estuarine water quality. This modeling effort is part of a larger framework of

  17. Catchment coevolution: A useful framework for improving predictions of hydrological change?

    Science.gov (United States)

    Troch, Peter A.

    2017-04-01

    The notion that landscape features have co-evolved over time is well known in the Earth sciences. Hydrologists have recently called for a more rigorous connection between emerging spatial patterns of landscape features and the hydrological response of catchments, and have termed this concept catchment coevolution. In this presentation we present a general framework of catchment coevolution that could improve predictions of hydrologic change. We first present empirical evidence of the interaction and feedback of landscape evolution and changes in hydrological response. From this review it is clear that the independent drivers of catchment coevolution are climate, geology, and tectonics. We identify common currency that allows comparing the levels of activity of these independent drivers, such that, at least conceptually, we can quantify the rate of evolution or aging. Knowing the hydrologic age of a catchment by itself is not very meaningful without linking age to hydrologic response. Two avenues of investigation have been used to understand the relationship between (differences in) age and hydrological response: (i) one that is based on relating present landscape features to runoff processes that are hypothesized to be responsible for the current fingerprints in the landscape; and (ii) one that takes advantage of an experimental design known as space-for-time substitution. Both methods have yielded significant insights in the hydrologic response of landscapes with different histories. If we want to make accurate predictions of hydrologic change, we will also need to be able to predict how the catchment will further coevolve in association with changes in the activity levels of the drivers (e.g., climate). There is ample evidence in the literature that suggests that whole-system prediction of catchment coevolution is, at least in principle, plausible. With this imperative we outline a research agenda that implements the concepts of catchment coevolution for building

  18. Climate change and predicting soil loss from rainfall

    Science.gov (United States)

    Kinnell, Peter

    2017-04-01

    Conceptually, rainfall has a certain capacity to cause soil loss from an eroding area while soil surfaces have a certain resistance to being eroded by rainfall. The terms "rainfall erosivity' and "soil erodibility" are frequently used to encapsulate the concept and in the Revised Universal Soil Loss Equation (RUSLE), the most widely used soil loss prediction equation in the world, average annual values of the R "erosivity" factor and the K "erodibility" factor provide a basis for accounting for variation in rainfall erosion associated with geographic variations of climate and soils. In many applications of RUSLE, R and K are considered to be independent but in reality they are not. In RUSLE2, provision has been made to take account of the fact that K values determined using soil physical factors have to be adjusted for variations in climate because runoff is not directly included as a factor in determining R. Also, the USLE event erosivity index EI30 is better related to accounting for event sediment concentration than event soil loss. While the USLE-M, a modification of the USLE which includes runoff as a factor in determining the event erosivity index provides better estimates of event soil loss when event runoff is known, runoff prediction provides a challenge to modelling event soil loss as climate changes

  19. Incorporating Student Activities into Climate Change Education

    Science.gov (United States)

    Steele, H.; Kelly, K.; Klein, D.; Cadavid, A. C.

    2013-12-01

    atmospheric circulation with applications of the Lorenz model, explored the land-sea breeze problem with the Dynamics and Thermodynamics Circulation Model (DTDM), and developed simple radiative transfer models. Class projects explored the effects of varying the content of CO2 and CH4 in the atmosphere, as well as the properties of paleoclimates in atmospheric simulations using EdGCM. Initial assessment of student knowledge, attitudes, and behaviors associated with these activities, particularly about climate change, was measured. Pre- and post-course surveys provided student perspectives about the courses and their learning about remote sensing and climate change concepts. Student performance on the tutorials and course projects evaluated students' ability to learn and apply their knowledge about climate change and skills with remote sensing to assigned problems or proposed projects of their choice. Survey and performance data illustrated that the exercises were successful in meeting their intended learning objectives as well as opportunities for further refinement and expansion.

  20. Nonlinear Predictive Sliding Mode Control for Active Suspension System

    Directory of Open Access Journals (Sweden)

    Dazhuang Wang

    2018-01-01

    Full Text Available An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven-degree-of-freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

  1. Multinationals' Political Activities on Climate Change

    International Nuclear Information System (INIS)

    Kolk, A.; Pinkse, J.

    2007-01-01

    This article explores the international dimensions of multinationals' corporate political activities, focusing on an international issue - climate change - being implemented differently in a range of countries. Analyzing data from Financial Times Global 500 firms, it examines the influence on types and process of multinationals' political strategies, reckoning with institutional contexts and issue saliency. Findings show that the type of political activities can be characterized as an information strategy to influence policy makers toward market-based solutions, not so much withholding action on emission reduction. Moreover, multinationals pursue self-regulation, targeting a broad range of political actors. The process of political strategy is mostly one of collective action. International differences particularly surface in the type of political actors aimed at, with U.S. and Australian firms focusing more on non-government actors (voluntary programs) than European and Japanese firms. Influencing home-country (not host-country) governments is the main component of international political strategy on climate change

  2. Influence of predicted climage change elements on Z. ...

    Science.gov (United States)

    Global climate change (GCC) is expected to have pronounced impacts on estuarine and marine habitats including sea level rise, increased storm intensity, increased air and water temperatures, changes in upwelling dynamics and ocean acidification. All of these elements are likely to impact the growth and potential distribution of the non-indigenous seagrass Zostera japonica both within the State of Washington and within the region. Understanding how Z. japonica will respond to GCC requires a thorough understanding of plant physiology and predictions of GCC effects. Furthermore, Washington State is proposing to list Z. japonica as a “noxious weed” which will allow the state to use herbicide controls for management. We present data from manipulative experiments designed to better understand how Z. japonica photosynthetic physiology responds to temperature, salinity and light. We found that Z. japonica is well adapted to moderate temperatures and salinity with maximum photosynthesis of salinity of 20. The Coos Bay population had greater Pmax and saturation irradiance (Ik) than the Padilla bay population (p < 0.001) and tolerates daily exposure to both freshwater and marine water, suggesting that this population tolerates fairly extreme environmental fluctuations. Extreme temperatures (35 °C) were generally lethal to Z. japonica populations from Padilla, Coos and Yaquina Bays. High salinity (35) had lower mortality than either salinity of 5 or 20 (p = 0.0

  3. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory.

    Directory of Open Access Journals (Sweden)

    Luis-Miguel Chevin

    2010-04-01

    Full Text Available Many species are experiencing sustained environmental change mainly due to human activities. The unusual rate and extent of anthropogenic alterations of the environment may exceed the capacity of developmental, genetic, and demographic mechanisms that populations have evolved to deal with environmental change. To begin to understand the limits to population persistence, we present a simple evolutionary model for the critical rate of environmental change beyond which a population must decline and go extinct. We use this model to highlight the major determinants of extinction risk in a changing environment, and identify research needs for improved predictions based on projected changes in environmental variables. Two key parameters relating the environment to population biology have not yet received sufficient attention. Phenotypic plasticity, the direct influence of environment on the development of individual phenotypes, is increasingly considered an important component of phenotypic change in the wild and should be incorporated in models of population persistence. Environmental sensitivity of selection, the change in the optimum phenotype with the environment, still crucially needs empirical assessment. We use environmental tolerance curves and other examples of ecological and evolutionary responses to climate change to illustrate how these mechanistic approaches can be developed for predictive purposes.

  4. The climatic change induced by human activities

    International Nuclear Information System (INIS)

    Balairon Ruiz, L.

    2004-01-01

    The climate of the Earth is a changing climate. Along their history many natural climate changes have existed in all time scales. At the present time we use the term climate changes have existed in all time scales. At the present time we use the term climate change in a restricted way, understanding that we have referring to a singular change that has their origin in the modification of the natural composition of the atmosphere. The increase of greenhouse gases from the second half the XVIII century, is due to the human activities of fossil fuels burning to obtain energy and to industrial and agricultural activities needing for the development of a world which population has been duplicated between 1960 and 2000, until overcoming the 6,000 million inhabitants. In particular, the concentrations of carbon dioxide-CO 2 have increased in a 34%. The more recent emission scenarios proposed by the IPCC (SRES, 2000) are based on hypothesis about the population evolution, the energy consumption and the word patterns of development, which are grouped in four families dominated as A1, A2, B1 and B2. The answer for these scenarios from a range of climate models results in an increase of the world average surface atmospheric temperature between 1,4 degree centigrade and 5,8 degree centigrade and a corresponding sea level rise understood between 9 cm and 88 cm. The changes in the precipitation patterns show us that could be above to the current one in high and media latitudes and below in subtropical latitudes, with exceptions highly depending of the model used. (Author)

  5. Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

    Energy Technology Data Exchange (ETDEWEB)

    Morton, M.J., E-mail: michael.morton@astrazeneca.com [Discovery Sciences, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Armstrong, D.; Abi Gerges, N. [Drug Safety and Metabolism, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Bridgland-Taylor, M. [Discovery Sciences, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom); Pollard, C.E.; Bowes, J.; Valentin, J.-P. [Drug Safety and Metabolism, AstraZeneca, Macclesfield, Cheshire SK10 4TG (United Kingdom)

    2014-09-01

    Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity in the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility.

  6. Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

    International Nuclear Information System (INIS)

    Morton, M.J.; Armstrong, D.; Abi Gerges, N.; Bridgland-Taylor, M.; Pollard, C.E.; Bowes, J.; Valentin, J.-P.

    2014-01-01

    Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity in the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility

  7. Emotion dysregulation and social competence: stability, change and predictive power.

    Science.gov (United States)

    Berkovits, L D; Baker, B L

    2014-08-01

    Social difficulties are closely linked to emotion dysregulation among children with typical development (TD). Children with developmental delays (DD) are at risk for poor social outcomes, but the relationship between social and emotional development within this population is not well understood. The current study examines the extent to which emotion dysregulation is related to social problems across middle childhood among children with TD or DD. Children with TD (IQ ≥ 85, n = 113) and children with DD (IQ ≤ 75, n = 61) participated in a longitudinal study. Annual assessments were completed at ages 7, 8 and 9 years. At each assessment, mothers reported on children's emotion dysregulation, and both mothers and teachers reported on children's social difficulties. Children with DD had higher levels of emotion dysregulation and social problems at each age than those with TD. Emotion dysregulation and social problems were significantly positively correlated within both TD and DD groups using mother report of social problems, and within the TD group using teacher report of social problems. Among children with TD, emotion dysregulation consistently predicted change in social problems from one year to the next. However, among children with DD, emotion dysregulation offered no unique prediction value above and beyond current social problems. Results suggested that the influence of emotion regulation abilities on social development may be a less salient pathway for children with DD. These children may have more influences, beyond emotion regulation, on their social behaviour, highlighting the importance of directly targeting social skill deficits among children with DD in order to ameliorate their social difficulties. © 2013 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

  8. Predicting Solar Activity Using Machine-Learning Methods

    Science.gov (United States)

    Bobra, M.

    2017-12-01

    Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections. However, we do not, as of yet, fully understand the physical mechanism that triggers solar eruptions. A machine-learning algorithm, which is favorable in cases where the amount of data is large, is one way to [1] empirically determine the signatures of this mechanism in solar image data and [2] use them to predict solar activity. In this talk, we discuss the application of various machine learning algorithms - specifically, a Support Vector Machine, a sparse linear regression (Lasso), and Convolutional Neural Network - to image data from the photosphere, chromosphere, transition region, and corona taken by instruments aboard the Solar Dynamics Observatory in order to predict solar activity on a variety of time scales. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We discuss our results (Bobra and Couvidat, 2015; Bobra and Ilonidis, 2016; Jonas et al., 2017) as well as other attempts to predict flares using machine-learning (e.g. Ahmed et al., 2013; Nishizuka et al. 2017) and compare these results with the more traditional techniques used by the NOAA Space Weather Prediction Center (Crown, 2012). We also discuss some of the challenges in using machine-learning algorithms for space science applications.

  9. Integrated model for predicting rice yield with climate change

    Science.gov (United States)

    Park, Jin-Ki; Das, Amrita; Park, Jong-Hwa

    2018-04-01

    Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country's economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.

  10. Striatal Activation Predicts Differential Therapeutic Responses to Methylphenidate and Atomoxetine.

    Science.gov (United States)

    Schulz, Kurt P; Bédard, Anne-Claude V; Fan, Jin; Hildebrandt, Thomas B; Stein, Mark A; Ivanov, Iliyan; Halperin, Jeffrey M; Newcorn, Jeffrey H

    2017-07-01

    Methylphenidate has prominent effects in the dopamine-rich striatum that are absent for the selective norepinephrine transporter inhibitor atomoxetine. This study tested whether baseline striatal activation would predict differential response to the two medications in youth with attention-deficit/hyperactivity disorder (ADHD). A total of 36 youth with ADHD performed a Go/No-Go test during functional magnetic resonance imaging at baseline and were treated with methylphenidate and atomoxetine using a randomized cross-over design. Whole-brain task-related activation was regressed on clinical response. Task-related activation in right caudate nucleus was predicted by an interaction of clinical responses to methylphenidate and atomoxetine (F 1,30  = 17.00; p atomoxetine. The rate of robust response was higher for methylphenidate than for atomoxetine in youth with high (94.4% vs. 38.8%; p = .003; number needed to treat = 2, 95% CI = 1.31-3.73) but not low (33.3% vs. 50.0%; p = .375) caudate activation. Furthermore, response to atomoxetine predicted motor cortex activation (F 1,30  = 14.99; p atomoxetine in youth with ADHD, purportedly reflecting the dopaminergic effects of methylphenidate but not atomoxetine in the striatum, whereas motor cortex activation may predict response to atomoxetine. These data do not yet translate directly to the clinical setting, but the approach is potentially important for informing future research and illustrates that it may be possible to predict differential treatment response using a biomarker-driven approach. Stimulant Versus Nonstimulant Medication for Attention Deficit Hyperactivity Disorder in Children; https://clinicaltrials.gov/; NCT00183391. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

  11. ABRUPT LONGITUDINAL MAGNETIC FIELD CHANGES IN FLARING ACTIVE REGIONS

    International Nuclear Information System (INIS)

    Petrie, G. J. D.; Sudol, J. J.

    2010-01-01

    We characterize the changes in the longitudinal photospheric magnetic field during 38 X-class and 39 M-class flares within 65 0 of disk center using 1 minute GONG magnetograms. In all 77 cases, we identify at least one site in the flaring active region where clear, permanent, stepwise field changes occurred. The median duration of the field changes was about 15 minutes and was approximately equal for X-class and for M-class flares. The absolute values of the field changes ranged from the detection limit of ∼10 G to as high as ∼450 G in two exceptional cases. The median value was 69 G. Field changes were significantly stronger for X-class than for M-class flares and for limb flares than for disk-center flares. Longitudinal field changes less than 100 G tended to decrease longitudinal field strengths, both close to disk center and close to the limb, while field changes greater than 100 G showed no such pattern. Likewise, longitudinal flux strengths tended to decrease during flares. Flux changes, particularly net flux changes near disk center, correlated better than local field changes with GOES peak X-ray flux. The strongest longitudinal field and flux changes occurred in flares observed close to the limb. We estimate the change of Lorentz force associated with each flare and find that this is large enough in some cases to power seismic waves. We find that longitudinal field decreases would likely outnumber increases at all parts of the solar disk within 65 0 of disk center, as in our observations, if photospheric field tilts increase during flares as predicted by Hudson et al.

  12. Outlook for activity and structural change

    International Nuclear Information System (INIS)

    Anon.

    1992-01-01

    The level of energy-using activities is continuing to increase throughout the world, but the rates of likely growth differ among regions. Over the next 20 years, manufacturing production is expected to grow at a rapid pace in parts of the developing world, and moderately in the OECD countries. In the Former East Bloc, it seems likely to stagnate or decline for much of the 1990s, but could then grow at a moderate pace if the transition to a market economy is successfully managed. Domestic passenger travel seems likely to increase everywhere, and growth in international travel will be especially strong. Freight transport activity is difficult to evaluate in the aggregate, since the composition of goods changes over time, but increase is expected in all regions, especially in the developing countries. Structural change within sectors will have significant impacts on energy use. In manufacturing, faster growth in light industry will lead to lower energy intensity in the OECD countries and especially in the Former East Bloc. The outlook in the LDCs suggests somewhat higher growth in energy-intensive industries, but this trend will vary among countries. In passenger travel, structural change is pointing toward higher energy intensity in most of the world as the role of automobiles and air travel continues to grow. Increase in the use of trucks is pushing in a similar direction in freight transport. In the residential sector, structural change will have only a moderate impact in the OECD countries, where per capita levels of home services are already high, but will push energy use significantly upward in the LDCs, and to a lesser extent, in the Former East Bloc. 17 refs., 4 figs., 1 tab

  13. Predicting activities after stroke : what is clinically relevant?

    NARCIS (Netherlands)

    Kwakkel, G.; Kollen, B. J.

    Knowledge about factors that determine the final outcome after stroke is important for early stroke management, rehabilitation goals, and discharge planning. This narrative review provides an overview of current knowledge about the prediction of activities after stroke. We reviewed the pattern of

  14. Merlin : microsimulation system for predicting leisure activity-travel patterns

    NARCIS (Netherlands)

    Middelkoop, van M.; Borgers, A.W.J.; Timmermans, H.J.P.

    2004-01-01

    Development of a model of annual activity-travel patterns of leisure and vacation travel is reported. The simulation system, called Merlin, is a hybrid model system consisting of discrete choice models and rule-based models. It predicts the annual number of day trips and vacations, and the profile

  15. Application of Avco data analysis and prediction techniques (ADAPT) to prediction of sunspot activity

    Science.gov (United States)

    Hunter, H. E.; Amato, R. A.

    1972-01-01

    The results are presented of the application of Avco Data Analysis and Prediction Techniques (ADAPT) to derivation of new algorithms for the prediction of future sunspot activity. The ADAPT derived algorithms show a factor of 2 to 3 reduction in the expected 2-sigma errors in the estimates of the 81-day running average of the Zurich sunspot numbers. The report presents: (1) the best estimates for sunspot cycles 20 and 21, (2) a comparison of the ADAPT performance with conventional techniques, and (3) specific approaches to further reduction in the errors of estimated sunspot activity and to recovery of earlier sunspot historical data. The ADAPT programs are used both to derive regression algorithm for prediction of the entire 11-year sunspot cycle from the preceding two cycles and to derive extrapolation algorithms for extrapolating a given sunspot cycle based on any available portion of the cycle.

  16. Changing the world through shareholder activism?

    Directory of Open Access Journals (Sweden)

    Joakim Sandberg

    2011-05-01

    Full Text Available As one of the more progressive facets of the socially responsibleinvestment (SRI movement, shareholder activism isgenerally recommended or justified on the grounds that itcan create social change. But how effective are differentkinds of activist campaigns likely to be in this regard? Thisarticle outlines the full range of different ways in whichshareholder activism could make a difference by carefullygoing through, first, all the more specific lines of actiontypically included under the shareholder activismumbrella and, second, all of the different ways in which ithas been suggested that these could influence the activitiesof commercial companies. It is argued that – althoughmuch more empirical research is needed in the area – thereare at least theoretical reasons for thinking that it will bedifficult to influence companies through the standardactions of filing or voting on shareholder resolutions.However, some alternative strategies open to activists mayallow them to increase their efficacy. It is specificallyargued that even individual investors could be able to pushfor corporate change through devising a radically selfsacrificialcampaign that manages to get the attention ofpowerful forces outside the corporate sphere.

  17. Prediction of adolescents doing physical activity after completing secondary education.

    Science.gov (United States)

    Moreno-Murcia, Juan Antonio; Huéscar, Elisa; Cervelló, Eduardo

    2012-03-01

    The purpose of this study, based on the self-determination theory (Ryan & Deci, 2000) was to test the prediction power of student's responsibility, psychological mediators, intrinsic motivation and the importance attached to physical education in the intention to continue to practice some form of physical activity and/or sport, and the possible relationships that exist between these variables. We used a sample of 482 adolescent students in physical education classes, with a mean age of 14.3 years, which were measured for responsibility, psychological mediators, sports motivation, the importance of physical education and intention to be physically active. We completed an analysis of structural equations modelling. The results showed that the responsibility positively predicted psychological mediators, and this predicted intrinsic motivation, which positively predicted the importance students attach to physical education, and this, finally, positively predicted the intention of the student to continue doing sport. Results are discussed in relation to the promotion of student's responsibility towards a greater commitment to the practice of physical exercise.

  18. Prediction of flare activity of stellar aggregates. I. Theoretical part

    International Nuclear Information System (INIS)

    Mnatsakanyan, M.A.; Mirzoyan, A.L.

    1989-01-01

    The problem is posed of predicting the number n k (t) of flare stars that have exhibited precisely k flares by the time t on the basis of data on these quantities known during the total time T of observations of the aggregate. The problem posed by Ambartsumyan of determining the distribution function f(ν) of the true frequency of stellar flares from known chronology of these data is equivalent to the limiting form of their formulation - prediction in the future over an infinitely long time. An exact analytic solution of the problem obtained without any assumption about the function f(ν) is given. It permits prediction of the steady flare activity of the aggregate into both the future and the (known) past. It follows from this solution that prediction into the future is in principle impossible to times that exceed the doubled time 2T of the available observations (this means that the problem of determining of the function f(ν) cannot be solved). Moreover, because of the unavoidable fluctuations in the observational data n k (T), such prediction is limited to even shorter times, and these are shorter the larger the value of k. Prediction into the past and into the future on the basis of the data n k (T) at the present time and its possible errors due to small fluctuations in these data are illustrated for the examples of the Pleiades and the Orion aggregate

  19. Predicting forest insect flight activity: A Bayesian network approach.

    Directory of Open Access Journals (Sweden)

    Stephen M Pawson

    Full Text Available Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model's predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways.

  20. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and fault...... can be used as a test signal for sanity check at the commissioning or for detection of faults hidden by regulatory actions of the controller. The method is tested on the two tank benchmark example. ©2009 IEEE....

  1. Change in attachment predicts change in emotion regulation particularly among 5-HTTLPR short-allele homozygotes.

    Science.gov (United States)

    Viddal, Kristine Rensvik; Berg-Nielsen, Turid Suzanne; Belsky, Jay; Wichstrøm, Lars

    2017-07-01

    In view of the theory that the attachment relationship provides a foundation for the development of emotion regulation, here, we evaluated (a) whether change in attachment security from 4 to 6 years predicts change in emotion regulation from 6 to 8 years and (b) whether 5-HTTLPR moderates this relation in a Norwegian community sample (n = 678, 99.7% Caucasian). Attachment was measured with the Manchester Child Attachment Story Task, and teachers completed the Emotion Regulation Checklist. Attachment security was modestly stable, with children becoming more secure over time. Regression analyses revealed that increased attachment security from 4 to 6 forecasted increases in emotion regulation from 6 to 8 and decreased attachment security forecasted decreases in emotion regulation. This effect was strongest among the 5-HTTLPR short-allele homozygotes and, according to competitive model fitting, in a differential-susceptibility manner. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  2. Short-term changes in arterial inflammation predict long-term changes in atherosclerosis progression

    Energy Technology Data Exchange (ETDEWEB)

    Joseph, Philip [Massachusetts General Hospital and Harvard Medical School, Cardiology Division and Cardiac MR PET CT Program, Boston, MA (United States); McMaster University, Population Health Research Institute, Department of Medicine, and Department of Radiology, Hamilton, ON (Canada); Ishai, Amorina; Tawakol, Ahmed [Massachusetts General Hospital and Harvard Medical School, Cardiology Division and Cardiac MR PET CT Program, Boston, MA (United States); Mani, Venkatesh [Icahn School of Medicine at Mount Sinai School of Medicine, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States); Kallend, David [The Medicines Company, Parsippany, NJ (United States); Rudd, James H.F. [University of Cambridge, Division of Cardiovascular Medicine, Cambridge (United Kingdom); Fayad, Zahi A. [Icahn School of Medicine at Mount Sinai School of Medicine, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States); Icahn School of Medicine at Mount Sinai School of Medicine, Hess CSM Building Floor TMII, Rm S1-104, Translational and Molecular Imaging Institute and Department of Radiology, New York, NY (United States)

    2017-01-15

    It remains unclear whether changes in arterial wall inflammation are associated with subsequent changes in the rate of structural progression of atherosclerosis. In this sub-study of the dal-PLAQUE clinical trial, multi-modal imaging was performed using 18-fludeoxyglucose (FDG) positron emission tomography (PET, at 0 and 6 months) and magnetic resonance imaging (MRI, at 0 and 24 months). The primary objective was to determine whether increasing FDG uptake at 6 months predicted atherosclerosis progression on MRI at 2 years. Arterial inflammation was measured by the carotid FDG target-to-background ratio (TBR), and atherosclerotic plaque progression was defined as the percentage change in carotid mean wall area (MWA) and mean wall thickness (MWT) on MRI between baseline and 24 months. A total of 42 participants were included in this sub-study. The mean age of the population was 62.5 years, and 12 (28.6 %) were women. In participants with (vs. without) any increase in arterial inflammation over 6 months, the long-term changes in both MWT (% change MWT: 17.49 % vs. 1.74 %, p = 0.038) and MWA (% change MWA: 25.50 % vs. 3.59 %, p = 0.027) were significantly greater. Results remained significant after adjusting for clinical and biochemical covariates. Individuals with no increase in arterial inflammation over 6 months had no significant structural progression of atherosclerosis over 24 months as measured by MWT (p = 0.616) or MWA (p = 0.373). Short-term changes in arterial inflammation are associated with long-term structural atherosclerosis progression. These data support the concept that therapies that reduce arterial inflammation may attenuate or halt progression of atherosclerosis. (orig.)

  3. Short-term changes in arterial inflammation predict long-term changes in atherosclerosis progression

    International Nuclear Information System (INIS)

    Joseph, Philip; Ishai, Amorina; Tawakol, Ahmed; Mani, Venkatesh; Kallend, David; Rudd, James H.F.; Fayad, Zahi A.

    2017-01-01

    It remains unclear whether changes in arterial wall inflammation are associated with subsequent changes in the rate of structural progression of atherosclerosis. In this sub-study of the dal-PLAQUE clinical trial, multi-modal imaging was performed using 18-fludeoxyglucose (FDG) positron emission tomography (PET, at 0 and 6 months) and magnetic resonance imaging (MRI, at 0 and 24 months). The primary objective was to determine whether increasing FDG uptake at 6 months predicted atherosclerosis progression on MRI at 2 years. Arterial inflammation was measured by the carotid FDG target-to-background ratio (TBR), and atherosclerotic plaque progression was defined as the percentage change in carotid mean wall area (MWA) and mean wall thickness (MWT) on MRI between baseline and 24 months. A total of 42 participants were included in this sub-study. The mean age of the population was 62.5 years, and 12 (28.6 %) were women. In participants with (vs. without) any increase in arterial inflammation over 6 months, the long-term changes in both MWT (% change MWT: 17.49 % vs. 1.74 %, p = 0.038) and MWA (% change MWA: 25.50 % vs. 3.59 %, p = 0.027) were significantly greater. Results remained significant after adjusting for clinical and biochemical covariates. Individuals with no increase in arterial inflammation over 6 months had no significant structural progression of atherosclerosis over 24 months as measured by MWT (p = 0.616) or MWA (p = 0.373). Short-term changes in arterial inflammation are associated with long-term structural atherosclerosis progression. These data support the concept that therapies that reduce arterial inflammation may attenuate or halt progression of atherosclerosis. (orig.)

  4. PREDICTS: Projecting Responses of Ecological Diversity in Changing Terrestrial Systems

    Directory of Open Access Journals (Sweden)

    Georgina Mace

    2012-12-01

    Full Text Available The PREDICTS project (www.predicts.org.uk is a three-year NERC-funded project to model and predict at a global scale how local terrestrial diversity responds to human pressures such as land use, land cover, pollution, invasive species and infrastructure. PREDICTS is a collaboration between Imperial College London, the UNEP World Conservation Monitoring Centre, Microsoft Research Cambridge, UCL and the University of Sussex. In order to meet its aims, the project relies on extensive data describing the diversity and composition of biological communities at a local scale. Such data are collected on a vast scale through the committed efforts of field ecologists. If you have appropriate data that you would be willing to share with us, please get in touch (enquiries@predicts.org.uk. All contributions will be acknowledged appropriately and all data contributors will be included as co-authors on an open-access paper describing the database.

  5. Making predictions in a changing world-inference, uncertainty, and learning.

    Science.gov (United States)

    O'Reilly, Jill X

    2013-01-01

    To function effectively, brains need to make predictions about their environment based on past experience, i.e., they need to learn about their environment. The algorithms by which learning occurs are of interest to neuroscientists, both in their own right (because they exist in the brain) and as a tool to model participants' incomplete knowledge of task parameters and hence, to better understand their behavior. This review focusses on a particular challenge for learning algorithms-how to match the rate at which they learn to the rate of change in the environment, so that they use as much observed data as possible whilst disregarding irrelevant, old observations. To do this algorithms must evaluate whether the environment is changing. We discuss the concepts of likelihood, priors and transition functions, and how these relate to change detection. We review expected and estimation uncertainty, and how these relate to change detection and learning rate. Finally, we consider the neural correlates of uncertainty and learning. We argue that the neural correlates of uncertainty bear a resemblance to neural systems that are active when agents actively explore their environments, suggesting that the mechanisms by which the rate of learning is set may be subject to top down control (in circumstances when agents actively seek new information) as well as bottom up control (by observations that imply change in the environment).

  6. Changing currents: a strategy for understanding and predicting the changing ocean circulation.

    Science.gov (United States)

    Bryden, Harry L; Robinson, Carol; Griffiths, Gwyn

    2012-12-13

    Within the context of UK marine science, we project a strategy for ocean circulation research over the next 20 years. We recommend a focus on three types of research: (i) sustained observations of the varying and evolving ocean circulation, (ii) careful analysis and interpretation of the observed climate changes for comparison with climate model projections, and (iii) the design and execution of focused field experiments to understand ocean processes that are not resolved in coupled climate models so as to be able to embed these processes realistically in the models. Within UK-sustained observations, we emphasize smart, cost-effective design of the observational network to extract maximum information from limited field resources. We encourage the incorporation of new sensors and new energy sources within the operational environment of UK-sustained observational programmes to bridge the gap that normally separates laboratory prototype from operational instrument. For interpreting the climate-change records obtained through a variety of national and international sustained observational programmes, creative and dedicated UK scientists should lead efforts to extract the meaningful signals and patterns of climate change and to interpret them so as to project future changes. For the process studies, individual scientists will need to work together in team environments to combine observational and process modelling results into effective improvements in the coupled climate models that will lead to more accurate climate predictions.

  7. Uncertainty in Predicting CCN Activity of Aged and Primary Aerosols

    Science.gov (United States)

    Zhang, Fang; Wang, Yuying; Peng, Jianfei; Ren, Jingye; Collins, Don; Zhang, Renyi; Sun, Yele; Yang, Xin; Li, Zhanqing

    2017-11-01

    Understanding particle CCN activity in diverse atmospheres is crucial when evaluating aerosol indirect effects. Here aerosols measured at three sites in China were categorized as different types for attributing uncertainties in CCN prediction in terms of a comprehensive data set including size-resolved CCN activity, size-resolved hygroscopic growth factor, and chemical composition. We show that CCN activity for aged aerosols is unexpectedly underestimated 22% at a supersaturation (S) of 0.2% when using κ-Kohler theory with an assumption of an internal mixture with measured bulk composition that has typically resulted in an overestimate of the CCN activity in previous studies. We conclude that the underestimation stems from neglect of the effect of aging/coating on particle hygroscopicity, which is not considered properly in most current models. This effect enhanced the hygroscopicity parameter (κ) by between 11% (polluted conditions) and 30% (clean days), as indicated in diurnal cycles of κ based on measurements by different instruments. In the urban Beijing atmosphere heavily influenced by fresh emissions, the CCN activity was overestimated by 45% at S = 0.2%, likely because of inaccurate assumptions of particle mixing state and because of variability of chemical composition over the particle size range. For both fresh and aged aerosols, CCN prediction exhibits very limited sensitivity to κSOA, implying a critical role of other factors like mixing of aerosol components within and between particles in regulating CCN activity. Our findings could help improving CCN parameterization in climate models.

  8. Hemostatic system changes predictive value in patients with ischemic brain disorders

    Directory of Open Access Journals (Sweden)

    Raičević Ranko

    2002-01-01

    Full Text Available The aim of this research was to determine the importance of tracking the dynamics of changes of the hemostatic system factors (aggregation of thrombocytes, D-dimer, PAI-1, antithrombin III, protein C and protein S, factor VII and factor VIII, fibrin degradation products, euglobulin test and the activated partial thromboplastin time – aPTPV in relation to the level of the severity of ischemic brain disorders (IBD and the level of neurological and functional deficiency in the beginning of IBD manifestation from 7 to 10 days, 19 to 21 day, and after 3 to 6 months. The research results confirmed significant predictive value of changes of hemostatic system with the predomination of procoagulant factors, together with the insufficiency of fibrinolysis. Concerning the IBD severity and it's outcome, the significant predictive value was shown in the higher levels of PAI-1 and the lower level of antithrombin III, and borderline significant value was shown in the accelerated aggregation of thrombocytes and the increased concentration of D-dimer. It could be concluded that the tracking of the dynamics of changes in parameters of hemostatic system proved to be an easily accessible method with the significant predictive value regarding the development of more severe. IBD cases and the outcome of the disease itself.

  9. Improving behavioral performance under full attention by adjusting response criteria to changes in stimulus predictability.

    Science.gov (United States)

    Katzner, Steffen; Treue, Stefan; Busse, Laura

    2012-09-04

    One of the key features of active perception is the ability to predict critical sensory events. Humans and animals can implicitly learn statistical regularities in the timing of events and use them to improve behavioral performance. Here, we used a signal detection approach to investigate whether such improvements in performance result from changes of perceptual sensitivity or rather from adjustments of a response criterion. In a regular sequence of briefly presented stimuli, human observers performed a noise-limited motion detection task by monitoring the stimulus stream for the appearance of a designated target direction. We manipulated target predictability through the hazard rate, which specifies the likelihood that a target is about to occur, given it has not occurred so far. Analyses of response accuracy revealed that improvements in performance could be accounted for by adjustments of the response criterion; a growing hazard rate was paralleled by an increasing tendency to report the presence of a target. In contrast, the hazard rate did not affect perceptual sensitivity. Consistent with previous research, we also found that reaction time decreases as the hazard rate grows. A simple rise-to-threshold model could well describe this decrease and attribute predictability effects to threshold adjustments rather than changes in information supply. We conclude that, even under conditions of full attention and constant perceptual sensitivity, behavioral performance can be optimized by dynamically adjusting the response criterion to meet ongoing changes in the likelihood of a target.

  10. Predictors of physical activity change among adults using observational designs.

    Science.gov (United States)

    Rhodes, Ryan E; Quinlan, Alison

    2015-03-01

    Regular physical activity (PA) is foundational to human health, yet most people are inactive. A sound understanding of the determinants of PA may be instructive for building interventions and/or identifying critical target groups to promote PA. Most research on PA correlates has been biased by cross-sectional or passive prospective designs that fail to examine within-person analysis of PA change. The purpose of this review was to collect and appraise the available literature on the predictors of PA change conceived broadly in terms of increases/decreases from baseline assessment as well as specifically in terms of adoption and maintenance. Eligible studies were from English, peer-reviewed published articles that examined predictors of natural change of PA over 3 months + using observational (non-experimental) data in adult samples. Searches were performed from June 2012 to January 2014 in eight databases. Sixty-seven independent data-sets, from 12 countries, primarily of medium quality/risk of bias, were identified with 26 correlates spanning demographic, behavioral, intra-individual, inter-individual, and environmental categories. Only intention and the onset of motherhood could reliably predict overall PA change. Among datasets configured to predict PA adoption, affective judgments and behavioral processes of change were the only reliable predictors, although both only have a small number of available studies. There were no reliable predictors of maintenance when compared to PA relapse. The results underscore the importance of individual-level motivation and behavioral regulation in PA change, but also denote critical social variables. These findings, however, are constrained by PA measurement bias and limited studies that employed time-varying covariation between predictor variables and PA.

  11. Prediction uncertainty of environmental change effects on temperate European biodiversity

    NARCIS (Netherlands)

    Dormann, C.; Schweiger, O.; Arens, P.F.P.; Augenstein, I.; Aviron, S.; Bailey, D.; Baudry, J.; Billeter, R.; Bugter, R.J.F.; Bukacek, R.; Burel, F.; Cerny, M.; Cock, de R.; Blust, de G.; DeFilippi, R.; Diekotter, T.; Dirksen, J.; Durka, W.; Edwards, P.J.; Frenzel, M.; Hamersky, R.; Hendrickx, F.; Herzog, F.; Klotz, S.; Koolstra, B.J.H.; Lausch, A.; Coeur, Le D.; Liira, J.; Maelfait, J.P.; Opdam, P.; Roubalova, M.; Schermann, A.; Schermann, N.; Schmidt, T.; Smulders, M.J.M.; Speelmans, M.; Simova, P.; Verboom, J.; Wingerden, van W.K.R.E.; Zobel, M.

    2008-01-01

    Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental

  12. Impact of climatic change on alpine ecosystems: inference and prediction

    Directory of Open Access Journals (Sweden)

    Nigel G. Yoccoz

    2011-01-01

    Full Text Available Alpine ecosystems will be greatly impacted by climatic change, but other factors, such as land use and invasive species, are likely to play an important role too. Climate can influence ecosystems at several levels. We describe some of them, stressing methodological approaches and available data. Climate can modify species phenology, such as flowering date of plants and hatching date in insects. It can also change directly population demography (survival, reproduction, dispersal, and therefore species distribution. Finally it can effect interactions among species – snow cover for example can affect the success of some predators. One characteristic of alpine ecosystems is the presence of snow cover, but surprisingly the role played by snow is relatively poorly known, mainly for logistical reasons. Even if we have made important progress regarding the development of predictive models, particularly so for distribution of alpine plants, we still need to set up observational and experimental networks which properly take into account the variability of alpine ecosystems and of their interactions with climate.Les écosystèmes alpins vont être grandement influencés par les changements climatiques à venir, mais d’autres facteurs, tels que l’utilisation des terres ou les espèces invasives, pourront aussi jouer un rôle important. Le climat peut influencer les écosystèmes à différents niveaux, et nous en décrivons certains, en mettant l’accent sur les méthodes utilisées et les données disponibles. Le climat peut d’abord modifier la phénologie des espèces, comme la date de floraison des plantes ou la date d’éclosion des insectes. Il peut ensuite affecter directement la démographie des espèces (survie, reproduction, dispersion et donc à terme leur répartition. Il peut enfin agir sur les interactions entre espèces – le couvert neigeux par exemple modifie le succès de certains prédateurs. Une caractéristique des

  13. Can tail damage outbreaks in the pig be predicted by behavioural change?

    Science.gov (United States)

    Larsen, Mona Lilian Vestbjerg; Andersen, Heidi Mai-Lis; Pedersen, Lene Juul

    2016-03-01

    Tail biting, resulting in outbreaks of tail damage in pigs, is a multifactorial welfare and economic problem which is usually partly prevented through tail docking. According to European Union legislation, tail docking is not allowed on a routine basis; thus there is a need for alternative preventive methods. One strategy is the surveillance of the pigs' behaviour for known preceding indicators of tail damage, which makes it possible to predict a tail damage outbreak and prevent it in proper time. This review discusses the existing literature on behavioural changes observed prior to a tail damage outbreak. Behaviours found to change prior to an outbreak include increased activity level, increased performance of enrichment object manipulation, and a changed proportion of tail posture with more tails between the legs. Monitoring these types of behaviours is also discussed for the purpose of developing an automatic warning system for tail damage outbreaks, with activity level showing promising results for being monitored automatically. Encouraging results have been found so far for the development of an automatic warning system; however, there is a need for further investigation and development, starting with the description of the temporal development of the predictive behaviour in relation to tail damage outbreaks. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Understanding, Predicting, and Preventing Life Changing and Life Threatening Health Changes among Aging Veterans and Civilians with Spinal Cord Injury

    Science.gov (United States)

    2017-10-01

    AWARD NUMBER: W81XWH-16-1-0629 TITLE: Understanding, Predicting, and Preventing Life -Changing and Life -Threatening Health Changes among Aging...Annual 3. DATES COVERED 30 Sep 2016 - 29 Sep 2017 4. TITLE AND SUBTITLE Understanding, Predicting, and Preventing Life -Changing and Life ... hope of preventing them. Our purpose is to better understand the how and why of the development of negative health spirals and how they may best be

  15. Ways that Social Change Predicts Personal Quality of Life

    Science.gov (United States)

    Cheung, Chau-Kiu; Leung, Kwok

    2010-01-01

    A notable way that social change affects personal quality of life would rely on the person's experience with social change. This experience may influence societal quality of life and quality of work life, which may in turn affect personal quality of life. Additionally, the experience of social change is possibly less detrimental to personal…

  16. Preparatory neural activity predicts performance on a conflict task.

    Science.gov (United States)

    Stern, Emily R; Wager, Tor D; Egner, Tobias; Hirsch, Joy; Mangels, Jennifer A

    2007-10-24

    Advance preparation has been shown to improve the efficiency of conflict resolution. Yet, with little empirical work directly linking preparatory neural activity to the performance benefits of advance cueing, it is not clear whether this relationship results from preparatory activation of task-specific networks, or from activity associated with general alerting processes. Here, fMRI data were acquired during a spatial Stroop task in which advance cues either informed subjects of the upcoming relevant feature of conflict stimuli (spatial or semantic) or were neutral. Informative cues decreased reaction time (RT) relative to neutral cues, and cues indicating that spatial information would be task-relevant elicited greater activity than neutral cues in multiple areas, including right anterior prefrontal and bilateral parietal cortex. Additionally, preparatory activation in bilateral parietal cortex and right dorsolateral prefrontal cortex predicted faster RT when subjects responded to spatial location. No regions were found to be specific to semantic cues at conventional thresholds, and lowering the threshold further revealed little overlap between activity associated with spatial and semantic cueing effects, thereby demonstrating a single dissociation between activations related to preparing a spatial versus semantic task-set. This relationship between preparatory activation of spatial processing networks and efficient conflict resolution suggests that advance information can benefit performance by leading to domain-specific biasing of task-relevant information.

  17. Changing University Students’ Alternative Conceptions of Optics by Active Learning

    Directory of Open Access Journals (Sweden)

    Zalkida Hadžibegović

    2013-01-01

    Full Text Available Active learning is individual and group participation in effective activities such as in-class observing, writing, experimenting, discussion, solving problems, and talking about to-be-learned topics. Some instructors believe that active learning is impossible, or at least extremely difficult to achieve in large lecture sessions. Nevertheless, the truly impressive implementation results of theSCALE-UP learning environment suggest that such beliefs are false (Beichner et al., 2000. In this study, we present a design of an active learning environment with positive effect on students. The design is based on the following elements: (1 helping students to learn from interactive lecture experiment; (2 guiding students to use justified explanation and prediction after observing and exploring a phenomenon; (3 developing a conceptual question sequencedesigned for use in an interactive lecture with students answering questions in worksheets by writing and drawing; (4 evaluating students’ conceptual change and gains by questions related to light reflection, refraction, and image formation in an exam held a week after the active learning session. Data were collected from 95 science freshmen with different secondary school backgrounds. They participated in geometrical optics classes organized for collecting research results during and after only one active learning session.The results have showed that around 60% of the students changed their initial alternative conceptions of vision and of image formation. It was also found that a large group of university students is likely to be engaged in active learning, shifting from a passive role they usually play during teacher’s lectures.

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

    Science.gov (United States)

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

    2015-04-01

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

  19. A mathematical model for predicting lane changes using the steering wheel angle.

    Science.gov (United States)

    Schmidt, Kim; Beggiato, Matthias; Hoffmann, Karl Heinz; Krems, Josef F

    2014-06-01

    Positive safety effects of advanced driver assistance systems can only become effective if drivers accept and use these systems. Early detection of driver's intention would allow for selective system activation and therefore reduce false alarms. This driving simulator study aims at exploring early predictors of lane changes. In total, 3111 lane changes of 51 participants on a simulated highway track were analyzed. Results show that drivers stopped their engagement in a secondary task about 7s before crossing the lane, which indicates a first planning phase of the maneuver. Subsequently, drivers start moving toward the lane, marking a mean steering wheel angle of 2.5°. Steering wheel angle as a directly measurable vehicle parameter appears as a promising early predictor of a lane change. A mathematical model of the steering wheel angle is presented, which is supposed to contribute for predicting lane change maneuvers. The mathematical model will be part of a further predictor of lane changes. This predictor can be a new advanced driver assistance system able to recognize a driver's intention. With this knowledge, other systems can be activated or deactivated so drivers get no annoying and exhausting alarm signals. This is one way how we can increase the acceptance of assistance systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. The use of specialisation indices to predict vulnerability of coral-feeding butterflyfishes to environmental change

    KAUST Repository

    Lawton, Rebecca J.

    2011-07-14

    In the absence of detailed assessments of extinction risk, ecological specialisation is often used as a proxy of vulnerability to environmental disturbances and extinction risk. Numerous indices can be used to estimate specialisation; however, the utility of these different indices to predict vulnerability to future environmental change is unknown. Here we compare the performance of specialisation indices using coral-feeding butterflyfishes as a model group. Our aims were to 1) quantify the dietary preferences of three butterflyfish species across habitats with differing levels of resource availability; 2) investigate how estimates of dietary specialisation vary with the use of different specialisation indices; 3) determine which specialisation indices best inform predictions of vulnerability to environmental change; and 4) assess the utility of resource selection functions to inform predictions of vulnerability to environmental change. The relative level of dietary specialisation estimated for all three species varied when different specialisation indices were used, indicating that the choice of index can have a considerable impact upon estimates of specialisation. Specialisation indices that do not consider resource abundance may fail to distinguish species that primarily use common resources from species that actively target resources disproportionately more than they are available. Resource selection functions provided the greatest insights into the potential response of species to changes in resource availability. Examination of resource selection functions, in addition to specialisation indices, indicated that Chaetodon trifascialis was the most specialised feeder, with highly conserved dietary preferences across all sites, suggesting that this species is highly vulnerable to the impacts of climate-induced coral loss on reefs. Our results indicate that vulnerability assessments based on some specialisation indices may be misleading and the best estimates of

  1. Planning for subacute care: predicting demand using acute activity data.

    Science.gov (United States)

    Green, Janette P; McNamee, Jennifer P; Kobel, Conrad; Seraji, Md Habibur R; Lawrence, Suanne J

    2016-01-01

    Objective The aim of the present study was to develop a robust model that uses the concept of 'rehabilitation-sensitive' Diagnosis Related Groups (DRGs) in predicting demand for rehabilitation and geriatric evaluation and management (GEM) care following acute in-patient episodes provided in Australian hospitals. Methods The model was developed using statistical analyses of national datasets, informed by a panel of expert clinicians and jurisdictional advice. Logistic regression analysis was undertaken using acute in-patient data, published national hospital statistics and data from the Australasian Rehabilitation Outcomes Centre. Results The predictive model comprises tables of probabilities that patients will require rehabilitation or GEM care after an acute episode, with columns defined by age group and rows defined by grouped Australian Refined (AR)-DRGs. Conclusions The existing concept of rehabilitation-sensitive DRGs was revised and extended. When applied to national data, the model provided a conservative estimate of 83% of the activity actually provided. An example demonstrates the application of the model for service planning. What is known about the topic? Health service planning is core business for jurisdictions and local areas. With populations ageing and an acknowledgement of the underservicing of subacute care, it is timely to find improved methods of estimating demand for this type of care. Traditionally, age-sex standardised utilisation rates for individual DRGs have been applied to Australian Bureau of Statistics (ABS) population projections to predict the future need for subacute services. Improved predictions became possible when some AR-DRGs were designated 'rehabilitation-sensitive'. This improved methodology has been used in several Australian jurisdictions. What does this paper add? This paper presents a new tool, or model, to predict demand for rehabilitation and GEM services based on in-patient acute activity. In this model, the

  2. Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

    Science.gov (United States)

    Cheval, Boris; Sarrazin, Philippe; Pelletier, Luc

    2014-01-01

    Understanding the determinants of non-exercise activity thermogenesis (NEAT) is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91) completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA) and sedentary behaviors (IASB). Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a) positively predicted by IAPA, (b) negatively predicted by IASB, and (c) was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined.

  3. Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

    Directory of Open Access Journals (Sweden)

    Boris Cheval

    Full Text Available Understanding the determinants of non-exercise activity thermogenesis (NEAT is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91 completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA and sedentary behaviors (IASB. Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a positively predicted by IAPA, (b negatively predicted by IASB, and (c was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined.

  4. Predicting Weight Change in Gari in Two Packaging Materials ...

    African Journals Online (AJOL)

    An equation for predicting moisture loss or gain by gari grain packed in two types of materials was developed. From this, it may be possible to establish the storability of gari in these two packaging material. The equation took into account the permeabilities of the materials, which were determined experimentally. The validity ...

  5. Predicting climate change impacts on polar bear litter size.

    Science.gov (United States)

    Molnár, Péter K; Derocher, Andrew E; Klanjscek, Tin; Lewis, Mark A

    2011-02-08

    Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population.

  6. Adaptation is.... Predicting malaria's changing course in East Africa

    International Development Research Centre (IDRC) Digital Library (Canada)

    IDRC

    Health experts say controlling malaria is crucial if the three East African nations are to achieve the UN Millennium. Development Goal of halving the incidence of infectious diseases such as malaria, tuberculosis, and HIV/AIDS by 2015. Looking ahead:Prevention and treatment. Improved malaria prediction will be an.

  7. Forest cover change prediction using hybrid methodology of ...

    Indian Academy of Sciences (India)

    to assess the present and future land use/land cover scenario of Gangtok, the subHimalayan capital of ... data is minimal. Finally, a combination of Markov modelling and SAVI was used to predict the probable land-use scenario in Gangtok in 2020 AD, which indicted that more ... to develop resource allocation strategies.

  8. predicting weight change in gari in two packaging materials

    African Journals Online (AJOL)

    MIS

    1983-09-01

    Sep 1, 1983 ... involved the microbial deterioration of gari stored in hessian and polythene bags, showed that the polythene bag gave a better result when gari was stored at moisture content of 11.2% wet basis. Mizrahi et al (1970) using dehydrated cabbage packed in two types of packaging materials predicted value.

  9. Predicted impacts of land use change on groundwater recharge of ...

    African Journals Online (AJOL)

    2012-04-13

    Apr 13, 2012 ... (2003) found no significant effect of a change in forest cover on peaks and low flows for 25 basins across north- western Europe, while deforestation led to an increase in base flow in more temperate climates (Hornbeck et al., 1993). Land use change also has a direct influence on the catch- ment hydrology ...

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

    Science.gov (United States)

    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.…

  11. Changes in fire weather distributions: effects on predicted fire behavior

    Science.gov (United States)

    Lucy A. Salazar; Larry S. Bradshaw

    1984-01-01

    Data that represent average worst fire weather for a particular area are used to index daily fire danger; however, they do not account for different locations or diurnal weather changes that significantly affect fire behavior potential. To study the effects that selected changes in weather databases have on computed fire behavior parameters, weather data for the...

  12. A linear regression model for predicting PNW estuarine temperatures in a changing climate

    Science.gov (United States)

    Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...

  13. Personality traits in rats predict vulnerability and resilience to developing stress-induced depression-like behaviors, HPA axis hyper-reactivity and brain changes in pERK1/2 activity

    DEFF Research Database (Denmark)

    Castro, Jorge E; Diessler, Shanaz; Varea, Emilio

    2012-01-01

    Emerging evidence indicates that certain behavioral traits, such as anxiety, are associated with the development of depression-like behaviors after exposure to chronic stress. However, single traits do not explain the wide variability in vulnerability to stress observed in outbred populations. We...... hypothesized that a combination of behavioral traits might provide a better characterization of an individual's vulnerability to prolonged stress. Here, we sought to determine whether the characterization of relevant behavioral traits in rats could aid in identifying individuals with different vulnerabilities...... to developing stress-induced depression-like behavioral alterations. We also investigated whether behavioral traits would be related to the development of alterations in the hypothalamic-pituitary-adrenal axis and in brain activity - as measured through phosphorylation of extracellular signal-regulated kinase 1...

  14. Personality traits in rats predict vulnerability and resilience to developing stress-induced depression-like behaviors, HPA axis hyper-reactivity and brain changes in pERK1/2 activity.

    Science.gov (United States)

    Castro, Jorge E; Diessler, Shanaz; Varea, Emilio; Márquez, Cristina; Larsen, Marianne H; Cordero, M Isabel; Sandi, Carmen

    2012-08-01

    Emerging evidence indicates that certain behavioral traits, such as anxiety, are associated with the development of depression-like behaviors after exposure to chronic stress. However, single traits do not explain the wide variability in vulnerability to stress observed in outbred populations. We hypothesized that a combination of behavioral traits might provide a better characterization of an individual's vulnerability to prolonged stress. Here, we sought to determine whether the characterization of relevant behavioral traits in rats could aid in identifying individuals with different vulnerabilities to developing stress-induced depression-like behavioral alterations. We also investigated whether behavioral traits would be related to the development of alterations in the hypothalamic-pituitary-adrenal axis and in brain activity - as measured through phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2)--in response to an acute stressor following either sub-chronic (2 weeks) or chronic (4 weeks) unpredictable stress (CUS). Sprague-Dawley rats were characterized using a battery of behavioral tasks, and three principal traits were identified: anxiety, exploration and activity. When combined, the first two traits were found to explain the variability in the stress responses. Our findings confirm the increased risk of animals with high anxiety developing certain depression-like behaviors (e.g., increased floating time in the forced swim test) when progressively exposed to stress. In contrast, the behavioral profile based on combined low anxiety and low exploration was resistant to alterations related to social behaviors, while the high anxiety and low exploration profile displayed a particularly vulnerable pattern of physiological and neurobiological responses after sub-chronic stress exposure. Our findings indicate important differences in animals' vulnerability and/or resilience to the effects of repeated stress, particularly during initial or

  15. Do Urinary Cystine Parameters Predict Clinical Stone Activity?

    Science.gov (United States)

    Friedlander, Justin I; Antonelli, Jodi A; Canvasser, Noah E; Morgan, Monica S C; Mollengarden, Daniel; Best, Sara; Pearle, Margaret S

    2018-02-01

    An accurate urinary predictor of stone recurrence would be clinically advantageous for patients with cystinuria. A proprietary assay (Litholink, Chicago, Illinois) measures cystine capacity as a potentially more reliable estimate of stone forming propensity. The recommended capacity level to prevent stone formation, which is greater than 150 mg/l, has not been directly correlated with clinical stone activity. We investigated the relationship between urinary cystine parameters and clinical stone activity. We prospectively followed 48 patients with cystinuria using 24-hour urine collections and serial imaging, and recorded stone activity. We compared cystine urinary parameters at times of stone activity with those obtained during periods of stone quiescence. We then performed correlation and ROC analysis to evaluate the performance of cystine parameters to predict stone activity. During a median followup of 70.6 months (range 2.2 to 274.6) 85 stone events occurred which could be linked to a recent urine collection. Cystine capacity was significantly greater for quiescent urine than for stone event urine (mean ± SD 48 ± 107 vs -38 ± 163 mg/l, p stone activity (r = -0.29, p r = -0.88, p r = -0.87, p stone quiescence. Decreasing the cutoff to 90 mg/l or greater improved sensitivity to 25.2% while maintaining specificity at 90.9%. Our results suggest that the target for capacity should be lower than previously advised. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  16. Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

    Science.gov (United States)

    Nielsen, Karina; Cleal, Bryan

    2010-04-01

    Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. Copyright 2010 APA, all rights reserved.

  17. model prediction of maize yield responses to climate change

    African Journals Online (AJOL)

    Prof. Adipala Ekwamu

    identified in the Intergovernmental Panel on Climate Change Third Assessment Report (IPCC-TAR) as a major .... carbon dioxide concentration and management ... address conditions where water is a key limiting ... Laboratory, United States.

  18. Predicting Impact of Climate Change on Water Temperature and Dissolved Oxygen in Tropical Rivers

    Directory of Open Access Journals (Sweden)

    Al-Amin Danladi Bello

    2017-07-01

    Full Text Available Predicting the impact of climate change and human activities on river systems is imperative for effective management of aquatic ecosystems. Unique information can be derived that is critical to the survival of aquatic species under dynamic environmental conditions. Therefore, the response of a tropical river system under climate and land-use changes from the aspects of water temperature and dissolved oxygen concentration were evaluated. Nine designed projected climate change scenarios and three future land-use scenarios were integrated into the Hydrological Simulation Program FORTRAN (HSPF model to determine the impact of climate change and land-use on water temperature and dissolved oxygen (DO concentration using basin-wide simulation of river system in Malaysia. The model performance coefficients showed a good correlation between simulated and observed streamflow, water temperature, and DO concentration in a monthly time step simulation. The Nash–Sutcliffe Efficiency for streamflow was 0.88 for the calibration period and 0.82 for validation period. For water temperature and DO concentration, data from three stations were calibrated and the Nash–Sutcliffe Efficiency for both water temperature and DO ranged from 0.53 to 0.70. The output of the calibrated model under climate change scenarios show that increased rainfall and air temperature do not affects DO concentration and water temperature as much as the condition of a decrease in rainfall and increase in air temperature. The regression model on changes in streamflow, DO concentration, and water temperature under the climate change scenarios illustrates that scenarios that produce high to moderate streamflow, produce small predicted change in water temperatures and DO concentrations compared with the scenarios that produced a low streamflow. It was observed that climate change slightly affects the relationship between water temperatures and DO concentrations in the tropical rivers that we

  19. Transitional states in marine fisheries: adapting to predicted global change.

    Science.gov (United States)

    MacNeil, M Aaron; Graham, Nicholas A J; Cinner, Joshua E; Dulvy, Nicholas K; Loring, Philip A; Jennings, Simon; Polunin, Nicholas V C; Fisk, Aaron T; McClanahan, Tim R

    2010-11-27

    Global climate change has the potential to substantially alter the production and community structure of marine fisheries and modify the ongoing impacts of fishing. Fish community composition is already changing in some tropical, temperate and polar ecosystems, where local combinations of warming trends and higher environmental variation anticipate the changes likely to occur more widely over coming decades. Using case studies from the Western Indian Ocean, the North Sea and the Bering Sea, we contextualize the direct and indirect effects of climate change on production and biodiversity and, in turn, on the social and economic aspects of marine fisheries. Climate warming is expected to lead to (i) yield and species losses in tropical reef fisheries, driven primarily by habitat loss; (ii) community turnover in temperate fisheries, owing to the arrival and increasing dominance of warm-water species as well as the reduced dominance and departure of cold-water species; and (iii) increased diversity and yield in Arctic fisheries, arising from invasions of southern species and increased primary production resulting from ice-free summer conditions. How societies deal with such changes will depend largely on their capacity to adapt--to plan and implement effective responses to change--a process heavily influenced by social, economic, political and cultural conditions.

  20. Activity Level Change Detection for Persistent Surveillance

    National Research Council Canada - National Science Library

    Liu, F; Bush, L. A

    2004-01-01

    .... Instead of traditional target tracking, this approach utilizes GMTI data as moving spots on the ground to estimate the level of activities and detect unusual activities such as military deployments...

  1. Neural activity to a partner's facial expression predicts self-regulation after conflict

    Science.gov (United States)

    Hooker, Christine I.; Gyurak, Anett; Verosky, Sara; Miyakawa, Asako; Ayduk, Özlem

    2009-01-01

    Introduction Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to the regulation of emotional experience in response to lab-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk-factor for mood and behavior problems after an interpersonal stressor. However, it remains unclear whether LPFC activity to a lab-based affective challenge predicts self-regulation in real-life. Method We investigated whether LPFC activity to a lab-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During an fMRI scan, healthy, adult participants in committed, dating relationships (N = 27) viewed positive, negative, and neutral facial expressions of their partners. In an online daily-diary, participants reported conflict occurrence, level of negative mood, rumination, and substance-use. Results LPFC activity in response to the lab-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to the change in mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted the change in mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance-use. Conclusions Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. PMID:20004365

  2. Application of General Regression Neural Network to the Prediction of LOD Change

    Science.gov (United States)

    Zhang, Xiao-Hong; Wang, Qi-Jie; Zhu, Jian-Jun; Zhang, Hao

    2012-01-01

    Traditional methods for predicting the change in length of day (LOD change) are mainly based on some linear models, such as the least square model and autoregression model, etc. However, the LOD change comprises complicated non-linear factors and the prediction effect of the linear models is always not so ideal. Thus, a kind of non-linear neural network — general regression neural network (GRNN) model is tried to make the prediction of the LOD change and the result is compared with the predicted results obtained by taking advantage of the BP (back propagation) neural network model and other models. The comparison result shows that the application of the GRNN to the prediction of the LOD change is highly effective and feasible.

  3. Predicting the Response of Electricity Load to Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, Patrick [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Colman, Jesse [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kalendra, Eric [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2015-07-28

    Our purpose is to develop a methodology to quantify the impact of climate change on electric loads in the United States. We perform simple linear regression, assisted by geospatial smoothing, on paired temperature and load time-series to estimate the heating- and coolinginduced sensitivity to temperature across 300 transmission zones and 16 seasonal and diurnal time periods. The estimated load sensitivities can be coupled with climate scenarios to quantify the potential impact of climate change on load, with a primary application being long-term electricity scenarios. The method allows regional and seasonal differences in climate and load response to be reflected in the electricity scenarios. While the immediate product of this analysis was designed to mesh with the spatial and temporal resolution of a specific electricity model to enable climate change scenarios and analysis with that model, we also propose that the process could be applied for other models and purposes.

  4. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination

    Science.gov (United States)

    Ren, Zhoupeng; Wang, Duoquan; Ma, Aimin; Hwang, Jimee; Bennett, Adam; Sturrock, Hugh J. W.; Fan, Junfu; Zhang, Wenjie; Yang, Dian; Feng, Xinyu; Xia, Zhigui; Zhou, Xiao-Nong; Wang, Jinfeng

    2016-02-01

    Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

  5. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination.

    Science.gov (United States)

    Ren, Zhoupeng; Wang, Duoquan; Ma, Aimin; Hwang, Jimee; Bennett, Adam; Sturrock, Hugh J W; Fan, Junfu; Zhang, Wenjie; Yang, Dian; Feng, Xinyu; Xia, Zhigui; Zhou, Xiao-Nong; Wang, Jinfeng

    2016-02-12

    Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

  6. Nonlinear dynamical modeling and prediction of the terrestrial magnetospheric activity

    International Nuclear Information System (INIS)

    Vassiliadis, D.

    1992-01-01

    The irregular activity of the magnetosphere results from its complex internal dynamics as well as the external influence of the solar wind. The dominating self-organization of the magnetospheric plasma gives rise to repetitive, large-scale coherent behavior manifested in phenomena such as the magnetic substorm. Based on the nonlinearity of the global dynamics this dissertation examines the magnetosphere as a nonlinear dynamical system using time series analysis techniques. Initially the magnetospheric activity is modeled in terms of an autonomous system. A dimension study shows that its observed time series is self-similar, but the correlation dimension is high. The implication of a large number of degrees of freedom is confirmed by other state space techniques such as Poincare sections and search for unstable periodic orbits. At the same time a stability study of the time series in terms of Lyapunov exponents suggests that the series is not chaotic. The absence of deterministic chaos is supported by the low predictive capability of the autonomous model. Rather than chaos, it is an external input which is largely responsible for the irregularity of the magnetospheric activity. In fact, the external driving is so strong that the above state space techniques give results for magnetospheric and solar wind time series that are at least qualitatively similar. Therefore the solar wind input has to be included in a low-dimensional nonautonomous model. Indeed it is shown that such a model can reproduce the observed magnetospheric behavior up to 80-90 percent. The characteristic coefficients of the model show little variation depending on the external disturbance. The impulse response is consistent with earlier results of linear prediction filters. The model can be easily extended to contain nonlinear features of the magnetospheric activity and in particular the loading-unloading behavior of substorms

  7. Improving models to predict phenological responses to global change

    Energy Technology Data Exchange (ETDEWEB)

    Richardson, Andrew D. [Harvard College, Cambridge, MA (United States)

    2015-11-25

    The term phenology describes both the seasonal rhythms of plants and animals, and the study of these rhythms. Plant phenological processes, including, for example, when leaves emerge in the spring and change color in the autumn, are highly responsive to variation in weather (e.g. a warm vs. cold spring) as well as longer-term changes in climate (e.g. warming trends and changes in the timing and amount of rainfall). We conducted a study to investigate the phenological response of northern peatland communities to global change. Field work was conducted at the SPRUCE experiment in northern Minnesota, where we installed 10 digital cameras. Imagery from the cameras is being used to track shifts in plant phenology driven by elevated carbon dioxide and elevated temperature in the different SPRUCE experimental treatments. Camera imagery and derived products (“greenness”) is being posted in near-real time on a publicly available web page (http://phenocam.sr.unh.edu/webcam/gallery/). The images will provide a permanent visual record of the progression of the experiment over the next 10 years. Integrated with other measurements collected as part of the SPRUCE program, this study is providing insight into the degree to which phenology may mediate future shifts in carbon uptake and storage by peatland ecosystems. In the future, these data will be used to develop improved models of vegetation phenology, which will be tested against ground observations collected by a local collaborator.

  8. Parietal operculum and motor cortex activities predict motor recovery in moderate to severe stroke

    Directory of Open Access Journals (Sweden)

    Firdaus Fabrice Hannanu

    2017-01-01

    In subacute stroke, fMRI brain activity related to passive movement measured in a sensorimotor network defined by activity during voluntary movement predicted motor recovery better than baseline motor-FMS alone. Furthermore, fMRI sensorimotor network activity measures considered alone allowed excellent clinical recovery prediction and may provide reliable biomarkers for assessing new therapies in clinical trial contexts. Our findings suggest that neural reorganization related to motor recovery from moderate to severe stroke results from balanced changes in ipsilesional MI (BA4a and a set of phylogenetically more archaic sensorimotor regions in the ventral sensorimotor trend, in which OP1 and OP4 processes may complement the ipsilesional dorsal motor cortex in achieving compensatory sensorimotor recovery.

  9. Thermal and hydrologic responses to climate change predict marked alterations in boreal stream invertebrate assemblages.

    Science.gov (United States)

    Mustonen, Kaisa-Riikka; Mykrä, Heikki; Marttila, Hannu; Sarremejane, Romain; Veijalainen, Noora; Sippel, Kalle; Muotka, Timo; Hawkins, Charles P

    2018-06-01

    Air temperature at the northernmost latitudes is predicted to increase steeply and precipitation to become more variable by the end of the 21st century, resulting in altered thermal and hydrological regimes. We applied five climate scenarios to predict the future (2070-2100) benthic macroinvertebrate assemblages at 239 near-pristine sites across Finland (ca. 1200 km latitudinal span). We used a multitaxon distribution model with air temperature and modeled daily flow as predictors. As expected, projected air temperature increased the most in northernmost Finland. Predicted taxonomic richness also increased the most in northern Finland, congruent with the predicted northwards shift of many species' distributions. Compositional changes were predicted to be high even without changes in richness, suggesting that species replacement may be the main mechanism causing climate-induced changes in macroinvertebrate assemblages. Northern streams were predicted to lose much of the seasonality of their flow regimes, causing potentially marked changes in stream benthic assemblages. Sites with the highest loss of seasonality were predicted to support future assemblages that deviate most in compositional similarity from the present-day assemblages. Macroinvertebrate assemblages were also predicted to change more in headwaters than in larger streams, as headwaters were particularly sensitive to changes in flow patterns. Our results emphasize the importance of focusing protection and mitigation on headwater streams with high-flow seasonality because of their vulnerability to climate change. © 2018 John Wiley & Sons Ltd.

  10. A Quantum Annealing Computer Team Addresses Climate Change Predictability

    Science.gov (United States)

    Halem, M. (Principal Investigator); LeMoigne, J.; Dorband, J.; Lomonaco, S.; Yesha, Ya.; Simpson, D.; Clune, T.; Pelissier, C.; Nearing, G.; Gentine, P.; hide

    2016-01-01

    The near confluence of the successful launch of the Orbiting Carbon Observatory2 on July 2, 2014 and the acceptance on August 20, 2015 by Google, NASA Ames Research Center and USRA of a 1152 qubit D-Wave 2X Quantum Annealing Computer (QAC), offered an exceptional opportunity to explore the potential of this technology to address the scientific prediction of global annual carbon uptake by land surface processes. At UMBC,we have collected and processed 20 months of global Level 2 light CO2 data as well as fluorescence data. In addition we have collected ARM data at 2sites in the US and Ameriflux data at more than 20 stations. J. Dorband has developed and implemented a multi-hidden layer Boltzmann Machine (BM) algorithm on the QAC. Employing the BM, we are calculating CO2 fluxes by training collocated OCO-2 level 2 CO2 data with ARM ground station tower data to infer to infer measured CO2 flux data. We generate CO2 fluxes with a regression analysis using these BM derived weights on the level 2 CO2 data for three Ameriflux sites distinct from the ARM stations. P. Gentine has negotiated for the access of K34 Ameriflux data in the Amazon and is applying a neural net to infer the CO2 fluxes. N. Talik validated the accuracy of the BM performance on the QAC against a restricted BM implementation on the IBM Softlayer Cloud with the Nvidia co-processors utilizing the same data sets. G. Nearing and K. Harrison have extended the GSFC LIS model with the NCAR Noah photosynthetic parameterization and have run a 10 year global prediction of the net ecosystem exchange. C. Pellisier is preparing a BM implementation of the Kalman filter data assimilation of CO2 fluxes. At UMBC, R. Prouty is conducting OSSE experiments with the LISNoah model on the IBM iDataPlex to simulate the impact of CO2 fluxes to improve the prediction of global annual carbon uptake. J. LeMoigne and D. Simpson have developed a neural net image registration system that will be used for MODIS ENVI and will be

  11. Lateral prefrontal cortex activity during cognitive control of emotion predicts response to social stress in schizophrenia

    Directory of Open Access Journals (Sweden)

    Laura M. Tully, PhD

    2014-01-01

    Full Text Available LPFC dysfunction is a well-established neural impairment in schizophrenia and is associated with worse symptoms. However, how LPFC activation influences symptoms is unclear. Previous findings in healthy individuals demonstrate that lateral prefrontal cortex (LPFC activation during cognitive control of emotional information predicts mood and behavior in response to interpersonal conflict, thus impairments in these processes may contribute to symptom exacerbation in schizophrenia. We investigated whether schizophrenia participants show LPFC deficits during cognitive control of emotional information, and whether these LPFC deficits prospectively predict changes in mood and symptoms following real-world interpersonal conflict. During fMRI, 23 individuals with schizophrenia or schizoaffective disorder and 24 healthy controls completed the Multi-Source Interference Task superimposed on neutral and negative pictures. Afterwards, schizophrenia participants completed a 21-day online daily-diary in which they rated the extent to which they experienced mood and schizophrenia-spectrum symptoms, as well as the occurrence and response to interpersonal conflict. Schizophrenia participants had lower dorsal LPFC activity (BA9 during cognitive control of task-irrelevant negative emotional information. Within schizophrenia participants, DLPFC activity during cognitive control of emotional information predicted changes in positive and negative mood on days following highly distressing interpersonal conflicts. Results have implications for understanding the specific role of LPFC in response to social stress in schizophrenia, and suggest that treatments targeting LPFC-mediated cognitive control of emotion could promote adaptive response to social stress in schizophrenia.

  12. Prediction of antibacterial activity from physicochemical properties of antimicrobial peptides.

    Directory of Open Access Journals (Sweden)

    Manuel N Melo

    Full Text Available Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM, which conciliates the two types of observations.

  13. The sequential structure of brain activation predicts skill.

    Science.gov (United States)

    Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

    2016-01-29

    In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Improving the reliability of fishery predictions under climate change

    DEFF Research Database (Denmark)

    Brander, Keith

    2015-01-01

    The increasing number of publications assessing impacts of climate change on marine ecosystems and fisheries attests to rising scientific and public interest. A selection of recent papers, dealing more with biological than social and economic aspects, is reviewed here, with particular attention...... to the reliability of projections of climate impacts on future fishery yields. The 2014 Intergovernmental Panel on Climate Change (IPCC) report expresses high confidence in projections that mid- and high-latitude fish catch potential will increase by 2050 and medium confidence that low-latitude catch potential...... understanding of climate impacts, such as how to improve coupled models from physics to fish and how to strengthen confidence in analysis of time series...

  15. How the cerebral serotonin homeostasis predicts environmental changes

    DEFF Research Database (Denmark)

    Kalbitzer, Jan; Kalbitzer, Urs; Knudsen, Gitte Moos

    2013-01-01

    Molecular imaging studies with positron emission tomography have revealed that the availability of serotonin transporter (5-HTT) in the human brain fluctuates over the course of the year. This effect is most pronounced in carriers of the short allele of the 5-HTT promoter region (5-HTTLPR), which...... has in several previous studies been linked to an increased risk to develop mood disorders. We argue that long-lasting fluctuations in the cerebral serotonin transmission, which is regulated via the 5-HTT, are responsible for mediating responses to environmental changes based on an assessment...... of cerebral serotonin transmission to seasonal and other forms of environmental change imparts greater behavioral flexibility, at the expense of increased vulnerability to stress. This model may explain the somewhat higher prevalence of the s-allele in some human populations dwelling at geographic latitudes...

  16. Stages of Change or Changes of Stage? Predicting Transitions in Transtheoretical Model Stages in Relation to Healthy Food Choice

    Science.gov (United States)

    Armitage, Christopher J.; Sheeran, Paschal; Conner, Mark; Arden, Madelynne A.

    2004-01-01

    Relatively little research has examined factors that account for transitions between transtheoretical model (TTM) stages of change. The present study (N=787) used sociodemographic, TTM, and theory of planned behavior (TPB) variables, as well as theory-driven interventions to predict changes in stage. Longitudinal analyses revealed that…

  17. Predicting active school travel: The role of planned behavior and habit strength

    Science.gov (United States)

    2012-01-01

    Background Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model’s predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children’s active school travel. Method Participants (N = 126 children aged 8–9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. Results The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. Conclusions The TPB significantly predicts children’s active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children’s intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these

  18. Predicting behavior change from persuasive messages using neural representational similarity and social network analyses.

    Science.gov (United States)

    Pegors, Teresa K; Tompson, Steven; O'Donnell, Matthew Brook; Falk, Emily B

    2017-08-15

    Neural activity in medial prefrontal cortex (MPFC), identified as engaging in self-related processing, predicts later health behavior change. However, it is unknown to what extent individual differences in neural representation of content and lived experience influence this brain-behavior relationship. We examined whether the strength of content-specific representations during persuasive messaging relates to later behavior change, and whether these relationships change as a function of individuals' social network composition. In our study, smokers viewed anti-smoking messages while undergoing fMRI and we measured changes in their smoking behavior one month later. Using representational similarity analyses, we found that the degree to which message content (i.e. health, social, or valence information) was represented in a self-related processing MPFC region was associated with later smoking behavior, with increased representations of negatively valenced (risk) information corresponding to greater message-consistent behavior change. Furthermore, the relationship between representations and behavior change depended on social network composition: smokers who had proportionally fewer smokers in their network showed increases in smoking behavior when social or health content was strongly represented in MPFC, whereas message-consistent behavior (i.e., less smoking) was more likely for those with proportionally more smokers in their social network who represented social or health consequences more strongly. These results highlight the dynamic relationship between representations in MPFC and key outcomes such as health behavior change; a complete understanding of the role of MPFC in motivation and action should take into account individual differences in neural representation of stimulus attributes and social context variables such as social network composition. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Linear filters as a method of real-time prediction of geomagnetic activity

    International Nuclear Information System (INIS)

    McPherron, R.L.; Baker, D.N.; Bargatze, L.F.

    1985-01-01

    Important factors controlling geomagnetic activity include the solar wind velocity, the strength of the interplanetary magnetic field (IMF), and the field orientation. Because these quantities change so much in transit through the solar wind, real-time monitoring immediately upstream of the earth provides the best input for any technique of real-time prediction. One such technique is linear prediction filtering which utilizes past histories of the input and output of a linear system to create a time-invariant filter characterizing the system. Problems of nonlinearity or temporal changes of the system can be handled by appropriate choice of input parameters and piecewise approximation in various ranges of the input. We have created prediction filters for all the standard magnetic indices and tested their efficiency. The filters show that the initial response of the magnetosphere to a southward turning of the IMF peaks in 20 minutes and then again in 55 minutes. After a northward turning, auroral zone indices and the midlatitude ASYM index return to background within 2 hours, while Dst decays exponentially with a time constant of about 8 hours. This paper describes a simple, real-time system utilizing these filters which could predict a substantial fraction of the variation in magnetic activity indices 20 to 50 minutes in advance

  20. Fire behavior potential in central Saskatchewan under predicted climate change : summary document

    International Nuclear Information System (INIS)

    Parisien, M.; Hirsch, K.; Todd, B.; Flannigan, M.; Kafka, V.; Flynn, N.

    2005-01-01

    This study assesses fire danger and fire behaviour potential in central Saskatchewan using simulated climate scenarios produced by the Canadian Regional Climate Model (CRCM), including scenario analysis of base, double and triple level carbon dioxide in the atmosphere and uses available forest fuels to develop an absolute measure of fire behaviour. For each of these climate scenarios, the CRCM-generated weather was used as input variables into the Canadian Forest Fire Behavior Prediction (FBP) System. Fire behavior potential was quantified using head fire intensity, a measure of the fire's energy output because it can be related to fire behavior characteristics, suppression effectiveness, and fire effects. The report discusses the implications of fire behavior potential changes for fire and forest management. Preliminary results suggest a large increase in area burned in the study area by the end of the twenty-first century. Some of the possible fire management activities for long-term prediction include: pre-positioning of resources, preparedness planning, prioritization of fire and forest management activities and fire threat evaluation. 16 refs., 1 tab, 7 figs

  1. Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

    Science.gov (United States)

    Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

    2013-11-01

    The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

  2. Cultural Change, Human Activity, and Cognitive Development

    Science.gov (United States)

    Gauvain, Mary; Munroe, Robert L.

    2012-01-01

    Differential cognitive performance across cultural contexts has been a standard result in comparative research. Here we discuss how societal changes occurring when a small-scale traditional community incorporates elements from industrialized society may contribute to cognitive development, and we illustrate this with an analysis of the cognitive…

  3. Integration of climate change in flood prediction: application to the Somme river (France)

    Science.gov (United States)

    Pinault, J.-L.; Amraoui, N.; Noyer, M.-L.

    2003-04-01

    Exceptional floods that have occurred for the last two years in western and central Europe were very unlikely. The concomitance of such rare events shows that they might be imputable to climate change. The statistical analysis of long rainfall series confirms that both the cumulated annual height and the temporal variability have increased for the last decade. This paper is devoted to the analysis of climate change impact on flood prediction applied to the Somme river. The exceptional pluviometry that occurred from October 2000 to April 2001, about the double of the mean value, entailed catastrophic flood between the high Somme and Abbeville. The flow reached a peak at the beginning of May 2001, involving damages in numerous habitations and communication routes, and economical activity of the region had been flood-bound for more than 2 months. The flood caught unaware the population and caused deep traumas in France since it was the first time such a sudden event was recognized as resulting from groundwater discharge. Mechanisms of flood generation were studied tightly in order to predict the behavior of the Somme catchment and other urbanized basins when the pluviometry is exceptional in winter or in spring, which occurs more and more frequently in the northern part of Europe. The contribution of groundwater in surface water flow was calculated by inverse modeling from piezometers that are representative of aquifers in valleys. They were found on the slopes and near the edge of plateaus in order to characterize the drainage processes of the watertable to the surface water network. For flood prediction, a stochastic process is used, consisting in the generation of both rainfall and PET time series. The precipitation generator uses Markov chain Monte Carlo and simulated annealing from the Hastings -- Metropolis algorithm. Coupling of rainfall and PET generators with transfer enables a new evaluation of the probability of occurrence of floods, taking into account

  4. Search predicts and changes patience in intertemporal choice

    Science.gov (United States)

    Johnson, Eric J.

    2017-01-01

    Intertemporal choice impacts many important outcomes, such as decisions about health, education, wealth, and the environment. However, the psychological processes underlying decisions involving outcomes at different points in time remain unclear, limiting opportunities to intervene and improve people’s patience. This research examines information-search strategies used during intertemporal choice and their impact on decisions. In experiment 1, we demonstrate that search strategies vary substantially across individuals. We subsequently identify two distinct search strategies across individuals. Comparative searchers, who compare features across options, discount future options less and are more susceptible to acceleration versus delay framing than integrative searchers, who integrate the features of an option. Experiment 2 manipulates search using an unobtrusive method to establish a causal relationship between strategy and choice, randomly assigning participants to conditions promoting either comparative or integrative search. Again, comparative search promotes greater patience than integrative search. Additionally, when participants adopt a comparative search strategy, they also exhibit greater effects of acceleration versus delay framing. Although most participants reported that the manipulation did not change their behavior, promoting comparative search decreased discounting of future rewards substantially and speeded patient choices. These findings highlight the central role that heterogeneity in psychological processes plays in shaping intertemporal choice. Importantly, these results indicate that theories that ignore variability in search strategies may be inadvertently aggregating over different subpopulations that use very different processes. The findings also inform interventions in choice architecture to increase patience and improve consumer welfare. PMID:29078303

  5. Search predicts and changes patience in intertemporal choice.

    Science.gov (United States)

    Reeck, Crystal; Wall, Daniel; Johnson, Eric J

    2017-11-07

    Intertemporal choice impacts many important outcomes, such as decisions about health, education, wealth, and the environment. However, the psychological processes underlying decisions involving outcomes at different points in time remain unclear, limiting opportunities to intervene and improve people's patience. This research examines information-search strategies used during intertemporal choice and their impact on decisions. In experiment 1, we demonstrate that search strategies vary substantially across individuals. We subsequently identify two distinct search strategies across individuals. Comparative searchers, who compare features across options, discount future options less and are more susceptible to acceleration versus delay framing than integrative searchers, who integrate the features of an option. Experiment 2 manipulates search using an unobtrusive method to establish a causal relationship between strategy and choice, randomly assigning participants to conditions promoting either comparative or integrative search. Again, comparative search promotes greater patience than integrative search. Additionally, when participants adopt a comparative search strategy, they also exhibit greater effects of acceleration versus delay framing. Although most participants reported that the manipulation did not change their behavior, promoting comparative search decreased discounting of future rewards substantially and speeded patient choices. These findings highlight the central role that heterogeneity in psychological processes plays in shaping intertemporal choice. Importantly, these results indicate that theories that ignore variability in search strategies may be inadvertently aggregating over different subpopulations that use very different processes. The findings also inform interventions in choice architecture to increase patience and improve consumer welfare. Copyright © 2017 the Author(s). Published by PNAS.

  6. Burrowing behavior of a deposit feeding bivalve predicts change in intertidal ecosystem state

    Directory of Open Access Journals (Sweden)

    Tanya Joan Compton

    2016-03-01

    Full Text Available Behavior has a predictive power that is often underutilized as a tool for signaling ecological change. The burrowing behavior of the deposit feeding bivalve Macoma balthica reflects a typical food-safety trade-off. The choice to live close to the sediment surface comes at a risk of predation and is a decision made when predation danger, food intake rates or future fitness prospects are low. In parts of the Dutch Wadden Sea, Macoma populations declined by 90% in the late 1990s, in parallel with large-scale mechanical cockle-dredging activities. During this decline, the burrowing depth of Macoma became shallow and was correlated with the population decline in the following year, indicating that it forecasted population change. Recently, there has been a series of large recruitment events in Macoma. According to the food-safety trade-off, we expected that Macoma should now live deeper, and have a higher body condition in association with this change in depth of living. Indeed, we observed that Macoma now lives deeper and that living depth in a given year forecasted population growth to the next year, especially in individuals larger than 14 mm. As living depth and body condition were strongly correlated in individuals larger than 14 mm, larger Macoma could be living deeper to protect their reproductive assets. Our results confirmed that burrowing depth signals impending population change and, together with body condition, can provide an early warning signal of ecological change. We suggest that population recovery is being driven by improved intertidal habitat quality in the Dutch Wadden Sea, rather than by the proposed climate-change related effects. This shift in ecosystem state is suggested to include the recovery of diatom habitat in the top layer of the sediment after cockle-dredging ended.

  7. Behind the stage of deliberate self-persuasion: When changes in valence of associations to an attitude object predict attitude change.

    Science.gov (United States)

    Lu, Tong; Lord, Charles G; Yoke, Kristin

    2015-12-01

    Modern theory and research on evaluative processes, combined with a comprehensive review of deliberate self-persuasion (Maio & Thomas, 2007, Pers. Soc. Psychol. Bull., 11, 46), suggest two types of strategies people can use to construct new, more desired attitudes. Epistemic strategies change the perceived valence of associations activated by the attitude object. Teleologic strategies, in contrast, keep undesired associations from being activated in the first place, thus obviating the need to change their perceived valence. Change in perceived valence of associations therefore might predict attitude change better when people pursue epistemic than teleologic strategies for deliberate self-persuasion. This hypothesis gained convergent support from three studies in which use of epistemic versus teleologic strategies was measured as an individual difference (Study 1) and manipulated (studies 2 and 3). The results of these studies supported the theoretical distinction between the two strategies and suggested further research directions. © 2015 The British Psychological Society.

  8. Early changes in socioeconomic status do not predict changes in body mass in the first decade of life.

    Science.gov (United States)

    Starkey, Leighann; Revenson, Tracey A

    2015-04-01

    Many studies link childhood socioeconomic status (SES) to body mass index (BMI), but few account for the impact of socioeconomic mobility throughout the lifespan. This study aims to investigate the impact of socioeconomic mobility on changes in BMI in childhood. Analyses tested whether [1] socioeconomic status influences BMI, [2] changes in socioeconomic status impact changes in BMI, and [3] timing of socioeconomic status mobility impacts BMI. Secondary data spanning birth to age 9 were analyzed. SES and BMI were investigated with gender, birth weight, maternal race/ethnicity, and maternal nativity as covariates. Autoregressive structural equation modeling and latent growth modeling were used. Socioeconomic status in the first year of life predicted body mass index. Child covariates were consistently associated with body mass index. Rate of change in socioeconomic status did not predict change in body mass index. The findings suggest that early socioeconomic status may most influence body mass in later childhood.

  9. Predicting and preventing the future: actively managing multiple sclerosis.

    LENUS (Irish Health Repository)

    Hutchinson, Michael

    2012-02-01

    Relapsing-remitting multiple sclerosis (MS) has a highly variable clinical course but a number of demographic, clinical and MRI features can guide the clinician in the assessment of disease activity and likely disability outcome. It is also clear that the inflammatory activity in the first five years of relapsing-remitting MS results in the neurodegenerative changes seen in secondary progressive MS 10-15 years later. While conventional first-line disease modifying therapy has an effect on relapses, about one third of patients have a suboptimal response to treatment. With the advent of highly active second-line therapies with their evident marked suppression of inflammation, the clinician now has the tools to manage the course of relapsing-remitting MS more effectively. The development of treatment optimisation recommendations based on the clinical response to first-line therapies can guide the neurologist in more active management of the early course of relapsing-remitting MS, with the aim of preventing both acute inflammatory axonal injury and the neurodegenerative process which leads to secondary progressive MS.

  10. Juvenile Obesity, Physical Activity, and Lifestyle Changes.

    Science.gov (United States)

    Bar-Or, Oded

    2000-01-01

    Because many obese children become obese adults, the recent rapid increase in juvenile obesity poses a major public health challenge. Enhanced physical activity is a cornerstone in a multidisciplinary approach to preventing and treating juvenile obesity. Giving exercise recommendations focused for obese youth is critical. Cutting down on sedentary…

  11. Medium- and Long-term Prediction of LOD Change by the Leap-step Autoregressive Model

    Science.gov (United States)

    Wang, Qijie

    2015-08-01

    The accuracy of medium- and long-term prediction of length of day (LOD) change base on combined least-square and autoregressive (LS+AR) deteriorates gradually. Leap-step autoregressive (LSAR) model can significantly reduce the edge effect of the observation sequence. Especially, LSAR model greatly improves the resolution of signals’ low-frequency components. Therefore, it can improve the efficiency of prediction. In this work, LSAR is used to forecast the LOD change. The LOD series from EOP 08 C04 provided by IERS is modeled by both the LSAR and AR models. The results of the two models are analyzed and compared. When the prediction length is between 10-30 days, the accuracy improvement is less than 10%. When the prediction length amounts to above 30 day, the accuracy improved obviously, with the maximum being around 19%. The results show that the LSAR model has higher prediction accuracy and stability in medium- and long-term prediction.

  12. Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

    Science.gov (United States)

    Zou, Qihong; Ross, Thomas J; Gu, Hong; Geng, Xiujuan; Zuo, Xi-Nian; Hong, L Elliot; Gao, Jia-Hong; Stein, Elliot A; Zang, Yu-Feng; Yang, Yihong

    2013-12-01

    Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance. Copyright © 2012 Wiley Periodicals, Inc.

  13. Contextual remapping in visual search after predictable target-location changes.

    Science.gov (United States)

    Conci, Markus; Sun, Luning; Müller, Hermann J

    2011-07-01

    Invariant spatial context can facilitate visual search. For instance, detection of a target is faster if it is presented within a repeatedly encountered, as compared to a novel, layout of nontargets, demonstrating a role of contextual learning for attentional guidance ('contextual cueing'). Here, we investigated how context-based learning adapts to target location (and identity) changes. Three experiments were performed in which, in an initial learning phase, observers learned to associate a given context with a given target location. A subsequent test phase then introduced identity and/or location changes to the target. The results showed that contextual cueing could not compensate for target changes that were not 'predictable' (i.e. learnable). However, for predictable changes, contextual cueing remained effective even immediately after the change. These findings demonstrate that contextual cueing is adaptive to predictable target location changes. Under these conditions, learned contextual associations can be effectively 'remapped' to accommodate new task requirements.

  14. Cortical activity patterns predict robust speech discrimination ability in noise

    Science.gov (United States)

    Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

    2012-01-01

    The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

  15. Bi-directional SIFT predicts a subset of activating mutations.

    Directory of Open Access Journals (Sweden)

    William Lee

    Full Text Available Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer.

  16. The use of specialisation indices to predict vulnerability of coral-feeding butterflyfishes to environmental change

    KAUST Repository

    Lawton, Rebecca J.; Pratchett, Morgan S.; Berumen, Michael L.

    2011-01-01

    , the utility of these different indices to predict vulnerability to future environmental change is unknown. Here we compare the performance of specialisation indices using coral-feeding butterflyfishes as a model group. Our aims were to 1) quantify the dietary

  17. New England observed and predicted August stream/river temperature maximum daily rate of change points

    Data.gov (United States)

    U.S. Environmental Protection Agency — The shapefile contains points with associated observed and predicted August stream/river temperature maximum negative rate of change in New England based on a...

  18. prediction of the impacts of climate changes on the stream flow

    African Journals Online (AJOL)

    HOD

    Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed ... Climate is the synthesis of atmospheric conditions characteristic of a .... generator available in the SWAT model.

  19. Predicting Effects of Water Regime Changes on Waterbirds: Insights from Staging Swans

    NARCIS (Netherlands)

    Nolet, Bart A.; Gyimesi, Abel; Krimpen, Van Roderick R.D.; Boer, de Fred; Stillman, Richard A.; Green, Andy J.

    2016-01-01

    Predicting the environmental impact of a proposed development is notoriously difficult,
    especially when future conditions fall outside the current range of conditions. Individualbased
    approaches have been developed and applied to predict the impact of environmental
    changes on wintering

  20. Predicting effects of water regime changes on waterbirds : insights from staging swans

    NARCIS (Netherlands)

    Nolet, B.A.; Gyimesi, A.; van Krimpen, R.R.D.; de Boer, W.F.; Stillman, R.A.

    2016-01-01

    Predicting the environmental impact of a proposed development is notoriously difficult, especially when future conditions fall outside the current range of conditions. Individual-based approaches have been developed and applied to predict the impact of environmental changes on wintering and staging

  1. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    Science.gov (United States)

    Lawrence N. Hudson; Joseph Wunderle M.; And Others

    2016-01-01

    The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to...

  2. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    NARCIS (Netherlands)

    Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Alhusseini, Tamera I; Bedford, Felicity E; Bennett, Dominic J; Booth, Hollie; Burton, Victoria J; Chng, Charlotte W T; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Emerson, Susan R; Gao, Di; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; Pask-Hale, Gwilym D; Pynegar, Edwin L; Robinson, Alexandra N; Sanchez-Ortiz, Katia; Senior, Rebecca A; Simmons, Benno I; White, Hannah J; Zhang, Hanbin; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Albertos, Belén; Alcala, E L; Del Mar Alguacil, Maria; Alignier, Audrey; Ancrenaz, Marc; Andersen, Alan N; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Arroyo-Rodríguez, Víctor; Aumann, Tom; Axmacher, Jan C; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Bakayoko, Adama; Báldi, András; Banks, John E; Baral, Sharad K; Barlow, Jos; Barratt, Barbara I P; Barrico, Lurdes; Bartolommei, Paola; Barton, Diane M; Basset, Yves; Batáry, Péter; Bates, Adam J; Baur, Bruno; Bayne, Erin M; Beja, Pedro; Benedick, Suzan; Berg, Åke; Bernard, Henry; Berry, Nicholas J; Bhatt, Dinesh; Bicknell, Jake E; Bihn, Jochen H; Blake, Robin J; Bobo, Kadiri S; Bóçon, Roberto; Boekhout, Teun; Böhning-Gaese, Katrin; Bonham, Kevin J; Borges, Paulo A V; Borges, Sérgio H; Boutin, Céline; Bouyer, Jérémy; Bragagnolo, Cibele; Brandt, Jodi S; Brearley, Francis Q; Brito, Isabel; Bros, Vicenç; Brunet, Jörg; Buczkowski, Grzegorz; Buddle, Christopher M; Bugter, Rob; Buscardo, Erika; Buse, Jörn; Cabra-García, Jimmy; Cáceres, Nilton C; Cagle, Nicolette L; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Caparrós, Rut; Cardoso, Pedro; Carpenter, Dan; Carrijo, Tiago F; Carvalho, Anelena L; Cassano, Camila R; Castro, Helena; Castro-Luna, Alejandro A; Rolando, Cerda B; Cerezo, Alexis; Chapman, Kim Alan; Chauvat, Matthieu; Christensen, Morten; Clarke, Francis M; Cleary, Daniel F R; Colombo, Giorgio; Connop, Stuart P; Craig, Michael D; Cruz-López, Leopoldo; Cunningham, Saul A; D'Aniello, Biagio; D'Cruze, Neil; da Silva, Pedro Giovâni; Dallimer, Martin; Danquah, Emmanuel; Darvill, Ben; Dauber, Jens; Davis, Adrian L V; Dawson, Jeff; de Sassi, Claudio; de Thoisy, Benoit; Deheuvels, Olivier; Dejean, Alain; Devineau, Jean-Louis; Diekötter, Tim; Dolia, Jignasu V; Domínguez, Erwin; Dominguez-Haydar, Yamileth; Dorn, Silvia; Draper, Isabel; Dreber, Niels; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Eggleton, Paul; Eigenbrod, Felix; Elek, Zoltán; Entling, Martin H; Esler, Karen J; de Lima, Ricardo F; Faruk, Aisyah; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Fensham, Roderick J; Fernandez, Ignacio C; Ferreira, Catarina C; Ficetola, Gentile F; Fiera, Cristina; Filgueiras, Bruno K C; Fırıncıoğlu, Hüseyin K; Flaspohler, David; Floren, Andreas; Fonte, Steven J; Fournier, Anne; Fowler, Robert E; Franzén, Markus; Fraser, Lauchlan H; Fredriksson, Gabriella M; Freire, Geraldo B; Frizzo, Tiago L M; Fukuda, Daisuke; Furlani, Dario; Gaigher, René; Ganzhorn, Jörg U; García, Karla P; Garcia-R, Juan C; Garden, Jenni G; Garilleti, Ricardo; Ge, Bao-Ming; Gendreau-Berthiaume, Benoit; Gerard, Philippa J; Gheler-Costa, Carla; Gilbert, Benjamin; Giordani, Paolo; Giordano, Simonetta; Golodets, Carly; Gomes, Laurens G L; Gould, Rachelle K; Goulson, Dave; Gove, Aaron D; Granjon, Laurent; Grass, Ingo; Gray, Claudia L; Grogan, James; Gu, Weibin; Guardiola, Moisès; Gunawardene, Nihara R; Gutierrez, Alvaro G; Gutiérrez-Lamus, Doris L; Haarmeyer, Daniela H; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hassan, Shombe N; Hatfield, Richard G; Hawes, Joseph E; Hayward, Matt W; Hébert, Christian; Helden, Alvin J; Henden, John-André; Henschel, Philipp; Hernández, Lionel; Herrera, James P; Herrmann, Farina; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Höfer, Hubert; Hoffmann, Anke; Horgan, Finbarr G; Hornung, Elisabeth; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishida, Hiroaki; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Hernández, F Jiménez; Johnson, McKenzie F; Jolli, Virat; Jonsell, Mats; Juliani, S Nur; Jung, Thomas S; Kapoor, Vena; Kappes, Heike; Kati, Vassiliki; Katovai, Eric; Kellner, Klaus; Kessler, Michael; Kirby, Kathryn R; Kittle, Andrew M; Knight, Mairi E; Knop, Eva; Kohler, Florian; Koivula, Matti; Kolb, Annette; Kone, Mouhamadou; Kőrösi, Ádám; Krauss, Jochen; Kumar, Ajith; Kumar, Raman; Kurz, David J; Kutt, Alex S; Lachat, Thibault; Lantschner, Victoria; Lara, Francisco; Lasky, Jesse R; Latta, Steven C; Laurance, William F; Lavelle, Patrick; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Lehouck, Valérie; Lencinas, María V; Lentini, Pia E; Letcher, Susan G; Li, Qi; Litchwark, Simon A; Littlewood, Nick A; Liu, Yunhui; Lo-Man-Hung, Nancy; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Luskin, Matthew S; MacSwiney G, M Cristina; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Malone, Louise A; Malonza, Patrick K; Malumbres-Olarte, Jagoba; Mandujano, Salvador; Måren, Inger E; Marin-Spiotta, Erika; Marsh, Charles J; Marshall, E J P; Martínez, Eliana; Martínez Pastur, Guillermo; Moreno Mateos, David; Mayfield, Margaret M; Mazimpaka, Vicente; McCarthy, Jennifer L; McCarthy, Kyle P; McFrederick, Quinn S; McNamara, Sean; Medina, Nagore G; Medina, Rafael; Mena, Jose L; Mico, Estefania; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Miranda-Esquivel, Daniel R; Moir, Melinda L; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Mudri-Stojnic, Sonja; Munira, A Nur; Muoñz-Alonso, Antonio; Munyekenye, B F; Naidoo, Robin; Naithani, A; Nakagawa, Michiko; Nakamura, Akihiro; Nakashima, Yoshihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Navarro-Iriarte, Luis; Ndang'ang'a, Paul K; Neuschulz, Eike L; Ngai, Jacqueline T; Nicolas, Violaine; Nilsson, Sven G; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Norton, David A; Nöske, Nicole M; Nowakowski, A Justin; Numa, Catherine; O'Dea, Niall; O'Farrell, Patrick J; Oduro, William; Oertli, Sabine; Ofori-Boateng, Caleb; Oke, Christopher Omamoke; Oostra, Vicencio; Osgathorpe, Lynne M; Otavo, Samuel Eduardo; Page, Navendu V; Paritsis, Juan; Parra-H, Alejandro; Parry, Luke; Pe'er, Guy; Pearman, Peter B; Pelegrin, Nicolás; Pélissier, Raphaël; Peres, Carlos A; Peri, Pablo L; Persson, Anna S; Petanidou, Theodora; Peters, Marcell K; Pethiyagoda, Rohan S; Phalan, Ben; Philips, T Keith; Pillsbury, Finn C; Pincheira-Ulbrich, Jimmy; Pineda, Eduardo; Pino, Joan; Pizarro-Araya, Jaime; Plumptre, A J; Poggio, Santiago L; Politi, Natalia; Pons, Pere; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Rader, Romina; Ramesh, B R; Ramirez-Pinilla, Martha P; Ranganathan, Jai; Rasmussen, Claus; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Rey Benayas, José M; Rey-Velasco, Juan Carlos; Reynolds, Chevonne; Ribeiro, Danilo Bandini; Richards, Miriam H; Richardson, Barbara A; Richardson, Michael J; Ríos, Rodrigo Macip; Robinson, Richard; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rös, Matthias; Rosselli, Loreta; Rossiter, Stephen J; Roth, Dana S; Roulston, T'ai H; Rousseau, Laurent; Rubio, André V; Ruel, Jean-Claude; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Sam, Katerina; Samnegård, Ulrika; Santana, Joana; Santos, Xavier; Savage, Jade; Schellhorn, Nancy A; Schilthuizen, Menno; Schmiedel, Ute; Schmitt, Christine B; Schon, Nicole L; Schüepp, Christof; Schumann, Katharina; Schweiger, Oliver; Scott, Dawn M; Scott, Kenneth A; Sedlock, Jodi L; Seefeldt, Steven S; Shahabuddin, Ghazala; Shannon, Graeme; Sheil, Douglas; Sheldon, Frederick H; Shochat, Eyal; Siebert, Stefan J; Silva, Fernando A B; Simonetti, Javier A; Slade, Eleanor M; Smith, Jo; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Soto Quiroga, Grimaldo; St-Laurent, Martin-Hugues; Starzomski, Brian M; Stefanescu, Constanti; Steffan-Dewenter, Ingolf; Stouffer, Philip C; Stout, Jane C; Strauch, Ayron M; Struebig, Matthew J; Su, Zhimin; Suarez-Rubio, Marcela; Sugiura, Shinji; Summerville, Keith S; Sung, Yik-Hei; Sutrisno, Hari; Svenning, Jens-Christian; Teder, Tiit; Threlfall, Caragh G; Tiitsaar, Anu; Todd, Jacqui H; Tonietto, Rebecca K; Torre, Ignasi; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Uehara-Prado, Marcio; Urbina-Cardona, Nicolas; Vallan, Denis; Vanbergen, Adam J; Vasconcelos, Heraldo L; Vassilev, Kiril; Verboven, Hans A F; Verdasca, Maria João; Verdú, José R; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Virgilio, Massimiliano; Vu, Lien Van; Waite, Edward M; Walker, Tony R; Wang, Hua-Feng; Wang, Yanping; Watling, James I; Weller, Britta; Wells, Konstans; Westphal, Catrin; Wiafe, Edward D; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Wolters, Volkmar; Woodcock, Ben A; Wu, Jihua; Wunderle, Joseph M; Yamaura, Yuichi; Yoshikura, Satoko; Yu, Douglas W; Zaitsev, Andrey S; Zeidler, Juliane; Zou, Fasheng; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

    The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of

  3. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    DEFF Research Database (Denmark)

    Hudson, Lawrence N; Newbold, Tim; Contu, Sara

    2017-01-01

    The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity ...

  4. Environmental change and hydrological responses in the interior of western Canada: Towards improved understanding, diagnosis, and prediction by the Changing Cold Regions Network

    Science.gov (United States)

    DeBeer, C. M.; Wheater, H. S.; Carey, S. K.; Pomeroy, J. W.; Stewart, R. E.

    2016-12-01

    The past several decades have been a period of rapid climatic and environmental change. In western Canada, as in other areas globally, warming and changes in precipitation have led to vast reductions in seasonal snowcover and freshwater ice cover, retreating glaciers, thawing permafrost, changing forest composition and structure, increasing northern shrub coverage, and earlier timing of river flows in spring. Yet streamflow volume has exhibited a variety of responses across the region and over different time scales, and patterns of change are not easily generalizable. Improved understanding, diagnosis, and prediction of the rapidly changing components of the Earth system are key to managing uncertain water futures, but this is challenging due to complex system behavior and sometimes compensatory responses. The Changing Cold Regions Network (CCRN) is a Canadian research network and GEWEX Regional Hydroclimate Project that is addressing these issues, with a geographic focus on the Saskatchewan and Mackenzie River basins. This paper will present examples of the changes that have been observed at a set of long-term and well-studied headwater research basins, and highlight how various processes confound hydrological responses here, pointing to the need for careful diagnosis. We will discuss some recent CCRN activities and progress toward improving conceptual understanding and developing scenarios of change for the 21st century, which can then be applied within process-based hydrological models for future prediction. Several priority research areas that will be a focus of continued work in CCRN will be recommended.

  5. Prediction of Land Use Change Based on Markov and GM(1,1 Models

    Directory of Open Access Journals (Sweden)

    SUN Yi-yang

    2016-05-01

    Full Text Available In order to explore the law of land use change in Laiwu City, Markov and GM(1,1 were respectively employed in the prediction of land use change in Laiwu from 2015 to 2050, after which the results were analyzed and discussed. The results showed that:(1The variational trends of all kinds of land use change predicted by the two models were consistent and the goodness of fit of the predictive value in corresponding years in the near future was high, illustrating that the predicted results in the near future were credible and the trend predicted in mid long term could be used as reference. (2The cultivated land would remanin almost no change from 2015 to 2020, and then gradually decreaseed in a small range from 2020 to 2050. The garden, the woodland, the grassland always reducing and the decreare range of the grassland was the largest. The urban village and industrial and mining land, the transportation land would be continuously increased and the range of urban village and industrial and mining land was the largest. The water and water conservancy facilities land and the other land would be always reduced in a very small range. It could be concluded that the results predicted by the two models in the near future were credible and could provide scientific basis for land use planning of Laiwu, while the method could provide reference for the prediction of land use change.

  6. Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments.

    Science.gov (United States)

    Gorter, Florien A; Aarts, Mark G M; Zwaan, Bas J; de Visser, J Arjan G M

    2018-01-01

    The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change. Copyright © 2018 by the Genetics Society of America.

  7. Who will increase their physical activity? Predictors of change in objectively measured physical activity over 12 months in the ProActive cohort

    Directory of Open Access Journals (Sweden)

    Sutton Stephen

    2010-04-01

    Full Text Available Abstract Background The aim was to identify predictors of change in objectively measured physical activity over 12 months in the ProActive cohort to improve understanding of factors influencing change in physical activity. Methods ProActive is a physical activity promotion trial that took place in Eastern England (1999-2004. 365 offspring of people with type 2 diabetes underwent measurement of physical activity energy expenditure (PAEE using heart rate monitoring, fitness, and anthropometric and biochemical status at baseline and 1 year (n = 321. Linear regression was used to quantify the associations between baseline demographic, clinical, psychosocial and behavioural variables and change in PAEE over 12 months. This study is registered as ISRCTN61323766. Results ProActive participants significantly increased their PAEE by 0.6 kj/min (SD 4.2, p = 0.006 over one year, the equivalent of around 20 minutes brisk walking/day. Male sex and higher fitness at baseline predicted increase in PAEE. No significant associations were found for any other variables. Very few baseline demographic, clinical, psychosocial and behavioural predictors were associated with change in objectively measured physical activity. Conclusions Traditional baseline determinants of self-reported physical activity targeted by behavioural interventions may be relatively weak predictors of change in objectively measured physical activity. Further research is needed to improve our understanding of factors influencing change in physical activity to inform the development and targeting of interventions.

  8. Seismic activity prediction using computational intelligence techniques in northern Pakistan

    Science.gov (United States)

    Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

    2017-10-01

    Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

  9. Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

    Science.gov (United States)

    Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

    2016-01-01

    Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

  10. Prediction of Active Site and Distal Residues in E. coli DNA Polymerase III alpha Polymerase Activity.

    Science.gov (United States)

    Parasuram, Ramya; Coulther, Timothy A; Hollander, Judith M; Keston-Smith, Elise; Ondrechen, Mary Jo; Beuning, Penny J

    2018-02-20

    The process of DNA replication is carried out with high efficiency and accuracy by DNA polymerases. The replicative polymerase in E. coli is DNA Pol III, which is a complex of 10 different subunits that coordinates simultaneous replication on the leading and lagging strands. The 1160-residue Pol III alpha subunit is responsible for the polymerase activity and copies DNA accurately, making one error per 10 5 nucleotide incorporations. The goal of this research is to determine the residues that contribute to the activity of the polymerase subunit. Homology modeling and the computational methods of THEMATICS and POOL were used to predict functionally important amino acid residues through their computed chemical properties. Site-directed mutagenesis and biochemical assays were used to validate these predictions. Primer extension, steady-state single-nucleotide incorporation kinetics, and thermal denaturation assays were performed to understand the contribution of these residues to the function of the polymerase. This work shows that the top 15 residues predicted by POOL, a set that includes the three previously known catalytic aspartate residues, seven remote residues, plus five previously unexplored first-layer residues, are important for function. Six previously unidentified residues, R362, D405, K553, Y686, E688, and H760, are each essential to Pol III activity; three additional residues, Y340, R390, and K758, play important roles in activity.

  11. Predicting adult weight change in the real world: a systematic review and meta-analysis accounting for compensatory changes in energy intake or expenditure.

    Science.gov (United States)

    Dhurandhar, E J; Kaiser, K A; Dawson, J A; Alcorn, A S; Keating, K D; Allison, D B

    2015-08-01

    Public health and clinical interventions for obesity in free-living adults may be diminished by individual compensation for the intervention. Approaches to predict weight outcomes do not account for all mechanisms of compensation, so they are not well suited to predict outcomes in free-living adults. Our objective was to quantify the range of compensation in energy intake or expenditure observed in human randomized controlled trials (RCTs). We searched multiple databases (PubMed, CINAHL, SCOPUS, Cochrane, ProQuest, PsycInfo) up to 1 August 2012 for RCTs evaluating the effect of dietary and/or physical activity interventions on body weight/composition. subjects per treatment arm ≥5; ≥1 week intervention; a reported outcome of body weight/body composition; the intervention was either a prescribed amount of over- or underfeeding and/or supervised or monitored physical activity was prescribed; ≥80% compliance; and an objective method was used to verify compliance with the intervention (for example, observation and electronic monitoring). Data were independently extracted and analyzed by multiple reviewers with consensus reached by discussion. We compared observed weight change with predicted weight change using two models that predict weight change accounting only for metabolic compensation. Twenty-eight studies met inclusion criteria. Overfeeding studies indicate 96% less weight gain than expected if no compensation occurred. Dietary restriction and exercise studies may result in up to 12-44% and 55-64% less weight loss than expected, respectively, under an assumption of no behavioral compensation. Compensation is substantial even in high-compliance conditions, resulting in far less weight change than would be expected. The simple algorithm we report allows for more realistic predictions of intervention effects in free-living populations by accounting for the significant compensation that occurs.

  12. Predicting future changes in Muskegon River Watershed game fish distributions under future land cover alteration and climate change scenarios

    Science.gov (United States)

    Steen, Paul J.; Wiley, Michael J.; Schaeffer, Jeffrey S.

    2010-01-01

    Future alterations in land cover and climate are likely to cause substantial changes in the ranges of fish species. Predictive distribution models are an important tool for assessing the probability that these changes will cause increases or decreases in or the extirpation of species. Classification tree models that predict the probability of game fish presence were applied to the streams of the Muskegon River watershed, Michigan. The models were used to study three potential future scenarios: (1) land cover change only, (2) land cover change and a 3°C increase in air temperature by 2100, and (3) land cover change and a 5°C increase in air temperature by 2100. The analysis indicated that the expected change in air temperature and subsequent change in water temperatures would result in the decline of coldwater fish in the Muskegon watershed by the end of the 21st century while cool- and warmwater species would significantly increase their ranges. The greatest decline detected was a 90% reduction in the probability that brook trout Salvelinus fontinalis would occur in Bigelow Creek. The greatest increase was a 276% increase in the probability that northern pike Esox lucius would occur in the Middle Branch River. Changes in land cover are expected to cause large changes in a few fish species, such as walleye Sander vitreus and Chinook salmon Oncorhynchus tshawytscha, but not to drive major changes in species composition. Managers can alter stream environmental conditions to maximize the probability that species will reside in particular stream reaches through application of the classification tree models. Such models represent a good way to predict future changes, as they give quantitative estimates of the n-dimensional niches for particular species.

  13. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates.

    Science.gov (United States)

    Glazier, Douglas S; Hirst, Andrew G; Atkinson, David

    2015-03-07

    Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  14. Activism or "Slacktivism?": Digital Media and Organizing for Social Change

    Science.gov (United States)

    Glenn, Cerise L.

    2015-01-01

    The influence of social media and technological developments has changed how groups and organizations advocating for social change generate awareness and participation in their causes. In this single class activity students will (a) analyze notions of activism and "slacktivism" from scholarly and popular sources to apply these concepts…

  15. Fire activity increasing as climate changes

    Science.gov (United States)

    Balcerak, Ernie; Showstack, Randy

    2013-01-01

    Analysis of images from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellites shows that more than 2.5 million hectares were burned in 2012 from January through August in the United States. The amount is less than a record 3.2 million hectares in 2011 but greater than the area burned in 12 of 15 years since satellite monitoring began, scientists reported at the AGU Fall Meeting. With satellites "we can detect fires as they're actively burning," said Louis Giglio of the University of Maryland, College Park, at a press conference on 4 December. "We can also map the cumulative area burned on the landscape after the fire's over." He noted that "2012 has been a particularly big fire year" in the United States.

  16. Within-person changes in salivary testosterone and physical characteristics of puberty predict boys' daily affect.

    Science.gov (United States)

    Klipker, Kathrin; Wrzus, Cornelia; Rauers, Antje; Boker, Steven M; Riediger, Michaela

    2017-09-01

    Recent investigations highlighted the role of within-person pubertal changes for adolescents' behavior. Yet, little is known about effects on adolescents' daily affect, particularly regarding the hormonal changes underlying physical changes during puberty. In a study with 148 boys aged 10 to 20years, we tested whether within-person physical and hormonal changes over eight months predicted everyday affect fluctuations, measured with experience sampling. As expected, greater within-person changes in testosterone (but not in dehydroepiandrosterone) were associated with higher affect fluctuations in daily life. Additionally, greater physical changes predicted higher affect fluctuations for individuals in the beginning of puberty. The findings demonstrate the relevance of physical and hormonal changes in boys' affective (in)stability. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Development of METAL-ACTIVE SITE and ZINCCLUSTER tool to predict active site pockets.

    Science.gov (United States)

    Ajitha, M; Sundar, K; Arul Mugilan, S; Arumugam, S

    2018-03-01

    The advent of whole genome sequencing leads to increasing number of proteins with known amino acid sequences. Despite many efforts, the number of proteins with resolved three dimensional structures is still low. One of the challenging tasks the structural biologists face is the prediction of the interaction of metal ion with any protein for which the structure is unknown. Based on the information available in Protein Data Bank, a site (METALACTIVE INTERACTION) has been generated which displays information for significant high preferential and low-preferential combination of endogenous ligands for 49 metal ions. User can also gain information about the residues present in the first and second coordination sphere as it plays a major role in maintaining the structure and function of metalloproteins in biological system. In this paper, a novel computational tool (ZINCCLUSTER) is developed, which can predict the zinc metal binding sites of proteins even if only the primary sequence is known. The purpose of this tool is to predict the active site cluster of an uncharacterized protein based on its primary sequence or a 3D structure. The tool can predict amino acids interacting with a metal or vice versa. This tool is based on the occurrence of significant triplets and it is tested to have higher prediction accuracy when compared to that of other available techniques. © 2017 Wiley Periodicals, Inc.

  18. Medium- and Long-term Prediction of LOD Change with the Leap-step Autoregressive Model

    Science.gov (United States)

    Liu, Q. B.; Wang, Q. J.; Lei, M. F.

    2015-09-01

    It is known that the accuracies of medium- and long-term prediction of changes of length of day (LOD) based on the combined least-square and autoregressive (LS+AR) decrease gradually. The leap-step autoregressive (LSAR) model is more accurate and stable in medium- and long-term prediction, therefore it is used to forecast the LOD changes in this work. Then the LOD series from EOP 08 C04 provided by IERS (International Earth Rotation and Reference Systems Service) is used to compare the effectiveness of the LSAR and traditional AR methods. The predicted series resulted from the two models show that the prediction accuracy with the LSAR model is better than that from AR model in medium- and long-term prediction.

  19. Extremely Randomized Machine Learning Methods for Compound Activity Prediction

    Directory of Open Access Journals (Sweden)

    Wojciech M. Czarnecki

    2015-11-01

    Full Text Available Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called ‘extremely randomized methods’—Extreme Entropy Machine and Extremely Randomized Trees—for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their ‘non-extreme’ competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  20. Electrophysiological correlates of competitor activation predict retrieval-induced forgetting.

    Science.gov (United States)

    Hellerstedt, Robin; Johansson, Mikael

    2014-06-01

    The very act of retrieval modifies the accessibility of memory for knowledge and past events and can also cause forgetting. A prominent theory of such retrieval-induced forgetting (RIF) holds that retrieval recruits inhibition to overcome interference from competing memories, rendering these memories inaccessible. The present study tested a fundamental tenet of the inhibitory-control account: The competition-dependence assumption. Event-related potentials (ERPs) were recorded while participants engaged in a competitive retrieval task. Competition levels were manipulated within the retrieval task by varying the cue-item associative strength of competing items. In order to temporally separate ERP correlates of competitor activation and target retrieval, memory was probed with the sequential presentation of 2 cues: A category cue, to reactivate competitors, and a target cue. As predicted by the inhibitory-control account, competitors with strong compared with weak cue-competitor association were more susceptible to forgetting. Furthermore, competition-sensitive ERP modulations, elicited by the category cue, were observed over anterior regions and reflected individual differences in ensuing forgetting. The present study demonstrates ERP correlates of the reactivation of tightly bound associated memories (the competitors) and provides support for the inhibitory-control account of RIF.

  1. Temperature modelling and prediction for activated sludge systems.

    Science.gov (United States)

    Lippi, S; Rosso, D; Lubello, C; Canziani, R; Stenstrom, M K

    2009-01-01

    Temperature is an important factor affecting biomass activity, which is critical to maintain efficient biological wastewater treatment, and also physiochemical properties of mixed liquor as dissolved oxygen saturation and settling velocity. Controlling temperature is not normally possible for treatment systems but incorporating factors impacting temperature in the design process, such as aeration system, surface to volume ratio, and tank geometry can reduce the range of temperature extremes and improve the overall process performance. Determining how much these design or up-grade options affect the tank temperature requires a temperature model that can be used with existing design methodologies. This paper presents a new steady state temperature model developed by incorporating the best aspects of previously published models, introducing new functions for selected heat exchange paths and improving the method for predicting the effects of covering aeration tanks. Numerical improvements with embedded reference data provide simpler formulation, faster execution, easier sensitivity analyses, using an ordinary spreadsheet. The paper presents several cases to validate the model.

  2. Changing relationships between land use and environmental characteristics and their consequences for spatially explicit land-use change prediction

    NARCIS (Netherlands)

    Bakker, M.; Veldkamp, A.

    2012-01-01

    Spatially explicit land-use change prediction is often based on environmental characteristics of land-use types, such as soil type and slope, as observed at one time instant. This approach presumes that relationships between land use and environment are constant over time. We argue that such

  3. Is Personality Fixed? Personality Changes as Much as "Variable" Economic Factors and More Strongly Predicts Changes to Life Satisfaction

    Science.gov (United States)

    Boyce, Christopher J.; Wood, Alex M.; Powdthavee, Nattavudh

    2013-01-01

    Personality is the strongest and most consistent cross-sectional predictor of high subjective well-being. Less predictive economic factors, such as higher income or improved job status, are often the focus of applied subjective well-being research due to a perception that they can change whereas personality cannot. As such there has been limited…

  4. Structure prediction and activity analysis of human heme oxygenase-1 and its mutant.

    Science.gov (United States)

    Xia, Zhen-Wei; Zhou, Wen-Pu; Cui, Wen-Jun; Zhang, Xue-Hong; Shen, Qing-Xiang; Li, Yun-Zhu; Yu, Shan-Chang

    2004-08-15

    To predict wild human heme oxygenase-1 (whHO-1) and hHO-1 His25Ala mutant (delta hHO-1) structures, to clone and express them and analyze their activities. Swiss-PdbViewer and Antheprot 5.0 were used for the prediction of structure diversity and physical-chemical changes between wild and mutant hHO-1. hHO-1 His25Ala mutant cDNA was constructed by site-directed mutagenesis in two plasmids of E. coli DH5alpha. Expression products were purified by ammonium sulphate precipitation and Q-Sepharose Fast Flow column chromatography, and their activities were measured. rHO-1 had the structure of a helical fold with the heme sandwiched between heme-heme oxygenase-1 helices. Bond angle, dihedral angle and chemical bond in the active pocket changed after Ala25 was replaced by His25, but Ala25 was still contacting the surface and the electrostatic potential of the active pocket was negative. The mutated enzyme kept binding activity to heme. Two vectors pBHO-1 and pBHO-1(M) were constructed and expressed. Ammonium sulphate precipitation and column chromatography yielded 3.6-fold and 30-fold higher purities of whHO-1, respectively. The activity of delta hHO-1 was reduced 91.21% after mutation compared with whHO-1. Proximal His25 ligand is crucial for normal hHO-1 catalytic activity. delta hHO-1 is deactivated by mutation but keeps the same binding site as whHO-1. delta hHO-1 might be a potential inhibitor of whHO-1 for preventing neonatal hyperbilirubinemia.

  5. Changes in income predict change in social trust : A longitudinal analysis

    NARCIS (Netherlands)

    Brandt, M.J.; Wetherell, G.A.; Henry, P.J.

    2015-01-01

    Social trust is a psychological variable important to politics, the community, and health. Theorists have predicted that socioeconomic status determines social trust, but also that social trust determines socioeconomic status. The current study tested the viability of both causal directions using

  6. Short-Term changes on MRI predict long-Term changes on radiography in rheumatoid arthritis

    DEFF Research Database (Denmark)

    Peterfy, Charles; Strand, Vibeke; Tian, Lu

    2017-01-01

    Objective In rheumatoid arthritis (RA), MRI provides earlier detection of structural damage than radiography (X-ray) and more sensitive detection of intra-Articular inflammation than clinical examination. This analysis was designed to evaluate the ability of early MRI findings to predict subsequent...

  7. The predictive skill of species distribution models for plankton in a changing climate

    DEFF Research Database (Denmark)

    Brun, Philipp Georg; Kiørboe, Thomas; Licandro, Priscilla

    2016-01-01

    Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real-world are rare. Here, we use data from the Continuous Plankton Recorder program, one...... null models, is essential to assess the robustness of projections of marine planktonic species under climate change...

  8. Forest processes and global environmental change: predicting the effects of individual and multiple stressors

    Science.gov (United States)

    John Aber; Ronald P. Neilson; Steve McNulty; James M. Lenihan; Dominque Bachelet; Raymond J. Drapek

    2001-01-01

    The purpose of this article is to review the state of prediction of forest ecosystem response to envisioned changes in the physical and chemical climate. These results are offered as one part of the forest sector analysis of the National Assessment of the Potential Consequences of Climate Variability and Change. This article has three sections. The first offers a very...

  9. An Application to the Prediction of LOD Change Based on General Regression Neural Network

    Science.gov (United States)

    Zhang, X. H.; Wang, Q. J.; Zhu, J. J.; Zhang, H.

    2011-07-01

    Traditional prediction of the LOD (length of day) change was based on linear models, such as the least square model and the autoregressive technique, etc. Due to the complex non-linear features of the LOD variation, the performances of the linear model predictors are not fully satisfactory. This paper applies a non-linear neural network - general regression neural network (GRNN) model to forecast the LOD change, and the results are analyzed and compared with those obtained with the back propagation neural network and other models. The comparison shows that the performance of the GRNN model in the prediction of the LOD change is efficient and feasible.

  10. Validation of Quantitative Structure-Activity Relationship (QSAR Model for Photosensitizer Activity Prediction

    Directory of Open Access Journals (Sweden)

    Sharifuddin M. Zain

    2011-11-01

    Full Text Available Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value and r2 prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC50 values ranging from 0.39 µM to 7.04 µM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r2 prediction for external test set of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.

  11. Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task

    Science.gov (United States)

    Laubach, Mark; Wessberg, Johan; Nicolelis, Miguel A. L.

    2000-06-01

    When an animal learns to make movements in response to different stimuli, changes in activity in the motor cortex seem to accompany and underlie this learning. The precise nature of modifications in cortical motor areas during the initial stages of motor learning, however, is largely unknown. Here we address this issue by chronically recording from neuronal ensembles located in the rat motor cortex, throughout the period required for rats to learn a reaction-time task. Motor learning was demonstrated by a decrease in the variance of the rats' reaction times and an increase in the time the animals were able to wait for a trigger stimulus. These behavioural changes were correlated with a significant increase in our ability to predict the correct or incorrect outcome of single trials based on three measures of neuronal ensemble activity: average firing rate, temporal patterns of firing, and correlated firing. This increase in prediction indicates that an association between sensory cues and movement emerged in the motor cortex as the task was learned. Such modifications in cortical ensemble activity may be critical for the initial learning of motor tasks.

  12. The motivation to be sedentary predicts weight change when sedentary behaviors are reduced

    OpenAIRE

    Epstein, Leonard H; Roemmich, James N; Cavanaugh, Meghan D; Paluch, Rocco A

    2011-01-01

    Abstract Background Obesity is correlated with a sedentary lifestyle, and the motivation to be active or sedentary is correlated with obesity. The present study tests the hypothesis that the motivation to be active or sedentary is correlated with weight change when children reduce their sedentary behavior. Methods The motivation to be active or sedentary, changes in weight, and accelerometer assessed physical activity were collected for 55 families with overweight/obese children who participa...

  13. Path dependent models to predict property changes in graphite irradiated at changing irradiation temperatures

    CSIR Research Space (South Africa)

    Kok, S

    2010-10-01

    Full Text Available Property changes occur in materials subjected to irradiation. The bulk of experimental data and associated empirical models are for isothermal irradiation. The form that these isothermal models take is usually closed form expressions in terms...

  14. Analysis Of The Method Of Predictive Control Applicable To Active Magnetic Suspension Systems Of Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Kurnyta-Mazurek Paulina

    2015-12-01

    Full Text Available Conventional controllers are usually synthesized on the basis of already known parameters associated with the model developed for the object to be controlled. However, sometimes it proves extremely difficult or even infeasible to find out these parameters, in particular when they subject to changes during the exploitation lifetime. If so, much more sophisticated control methods have to be applied, e.g. the method of predictive control. Thus, the paper deals with application of the predictive control approach to follow-up tracking of an active magnetic suspension where the mathematical and simulation models for such a control system are disclosed with preliminary results from simulation investigations of the control system in question.

  15. Traction force dynamics predict gap formation in activated endothelium

    Energy Technology Data Exchange (ETDEWEB)

    Valent, Erik T.; Nieuw Amerongen, Geerten P. van; Hinsbergh, Victor W.M. van; Hordijk, Peter L., E-mail: p.hordijk@vumc.nl

    2016-09-10

    In many pathological conditions the endothelium becomes activated and dysfunctional, resulting in hyperpermeability and plasma leakage. No specific therapies are available yet to control endothelial barrier function, which is regulated by inter-endothelial junctions and the generation of acto-myosin-based contractile forces in the context of cell-cell and cell-matrix interactions. However, the spatiotemporal distribution and stimulus-induced reorganization of these integral forces remain largely unknown. Traction force microscopy of human endothelial monolayers was used to visualize contractile forces in resting cells and during thrombin-induced hyperpermeability. Simultaneously, information about endothelial monolayer integrity, adherens junctions and cytoskeletal proteins (F-actin) were captured. This revealed a heterogeneous distribution of traction forces, with nuclear areas showing lower and cell-cell junctions higher traction forces than the whole-monolayer average. Moreover, junctional forces were asymmetrically distributed among neighboring cells. Force vector orientation analysis showed a good correlation with the alignment of F-actin and revealed contractile forces in newly formed filopodia and lamellipodia-like protrusions within the monolayer. Finally, unstable areas, showing high force fluctuations within the monolayer were prone to form inter-endothelial gaps upon stimulation with thrombin. To conclude, contractile traction forces are heterogeneously distributed within endothelial monolayers and force instability, rather than force magnitude, predicts the stimulus-induced formation of intercellular gaps. - Highlights: • Endothelial monolayers exert dynamic- and heterogeneous traction forces. • High traction forces correlate with junctional areas and the F-actin cytoskeleton. • Newly formed inter-endothelial gaps are characterized by opposing traction forces. • Force stability is a key feature controlling endothelial permeability.

  16. Traction force dynamics predict gap formation in activated endothelium

    International Nuclear Information System (INIS)

    Valent, Erik T.; Nieuw Amerongen, Geerten P. van; Hinsbergh, Victor W.M. van; Hordijk, Peter L.

    2016-01-01

    In many pathological conditions the endothelium becomes activated and dysfunctional, resulting in hyperpermeability and plasma leakage. No specific therapies are available yet to control endothelial barrier function, which is regulated by inter-endothelial junctions and the generation of acto-myosin-based contractile forces in the context of cell-cell and cell-matrix interactions. However, the spatiotemporal distribution and stimulus-induced reorganization of these integral forces remain largely unknown. Traction force microscopy of human endothelial monolayers was used to visualize contractile forces in resting cells and during thrombin-induced hyperpermeability. Simultaneously, information about endothelial monolayer integrity, adherens junctions and cytoskeletal proteins (F-actin) were captured. This revealed a heterogeneous distribution of traction forces, with nuclear areas showing lower and cell-cell junctions higher traction forces than the whole-monolayer average. Moreover, junctional forces were asymmetrically distributed among neighboring cells. Force vector orientation analysis showed a good correlation with the alignment of F-actin and revealed contractile forces in newly formed filopodia and lamellipodia-like protrusions within the monolayer. Finally, unstable areas, showing high force fluctuations within the monolayer were prone to form inter-endothelial gaps upon stimulation with thrombin. To conclude, contractile traction forces are heterogeneously distributed within endothelial monolayers and force instability, rather than force magnitude, predicts the stimulus-induced formation of intercellular gaps. - Highlights: • Endothelial monolayers exert dynamic- and heterogeneous traction forces. • High traction forces correlate with junctional areas and the F-actin cytoskeleton. • Newly formed inter-endothelial gaps are characterized by opposing traction forces. • Force stability is a key feature controlling endothelial permeability.

  17. Prediction of residual metabolic activity after treatment in NSCLC patients

    International Nuclear Information System (INIS)

    Rios Velazquez, Emmanuel; Aerts, Hugo J.W.L.; Oberije, Cary; Ruysscher, Dirk De; Lambin, Philippe

    2010-01-01

    Purpose. Metabolic response assessment is often used as a surrogate of local failure and survival. Early identification of patients with residual metabolic activity is essential as this enables selection of patients who could potentially benefit from additional therapy. We report on the development of a pre-treatment prediction model for metabolic response using patient, tumor and treatment factors. Methods. One hundred and one patients with inoperable NSCLC (stage I-IV), treated with 3D conformal radical (chemo)-radiotherapy were retrospectively included in this study. All patients received a pre and post-radiotherapy fluorodeoxyglucose positron emission tomography-computed tomography FDG-PET-CT scan. The electronic medical record system and the medical patient charts were reviewed to obtain demographic, clinical, tumor and treatment data. Primary outcome measure was examined using a metabolic response assessment on a post-radiotherapy FDG-PET-CT scan. Radiotherapy was delivered in fractions of 1.8 Gy, twice a day, with a median prescribed dose of 60 Gy. Results. Overall survival was worse in patients with residual metabolic active areas compared with the patients with a complete metabolic response (p=0.0001). In univariate analysis, three variables were significantly associated with residual disease: larger primary gross tumor volume (GTVprimary, p=0.002), higher pre-treatment maximum standardized uptake value (SUV max , p=0.0005) in the primary tumor and shorter overall treatment time (OTT, p=0.046). A multivariate model including GTVprimary, SUV max , equivalent radiation dose at 2 Gy corrected for time (EQD2, T) and OTT yielded an area under the curve assessed by the leave-one-out cross validation of 0.71 (95% CI, 0.65-0.76). Conclusion. Our results confirmed the validity of metabolic response assessment as a surrogate of survival. We developed a multivariate model that is able to identify patients at risk of residual disease. These patients may benefit from

  18. Contributions of climate change and human activities to runoff change in seven typical catchments across China.

    Science.gov (United States)

    Zhai, Ran; Tao, Fulu

    2017-12-15

    Climate change and human activities are two major factors affecting water resource change. It is important to understand the roles of the major factors in affecting runoff change in different basins for watershed management. Here, we investigated the trends in climate and runoff in seven typical catchments in seven basins across China from 1961 to 2014. Then we attributed the runoff change to climate change and human activities in each catchment and in three time periods (1980s, 1990s and 2000s), using the VIC model and long-term runoff observation data. During 1961-2014, temperature increased significantly, while the trends in precipitation were insignificant in most of the catchments and inconsistent among the catchments. The runoff in most of the catchments showed a decreasing trend except the Yingluoxia catchment in the northwestern China. The contributions of climate change and human activities to runoff change varied in different catchments and time periods. In the 1980s, climate change contributed more to runoff change than human activities, which was 84%, 59%, -66%, -50%, 59%, 94%, and -59% in the Nianzishan, Yingluoxia, Xiahui, Yangjiaping, Sanjiangkou, Xixian, and Changle catchment, respectively. After that, human activities had played a more essential role in runoff change. In the 1990s and 2000s, human activities contributed more to runoff change than in the 1980s. The contribution by human activities accounted for 84%, -68%, and 67% in the Yingluoxia, Xiahui, and Sanjiangkou catchment, respectively, in the 1990s; and -96%, -67%, -94%, and -142% in the Nianzishan, Yangjiaping, Xixian, and Changle catchment, respectively, in the 2000s. It is also noted that after 2000 human activities caused decrease in runoff in all catchments except the Yingluoxia. Our findings highlight that the effects of human activities, such as increase in water withdrawal, land use/cover change, operation of dams and reservoirs, should be well managed. Copyright © 2017 Elsevier

  19. Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

    Science.gov (United States)

    Naik, P K; Singh, T; Singh, H

    2009-07-01

    Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

  20. Using the Change Manager Model for the Hippocampal System to Predict Connectivity and Neurophysiological Parameters in the Perirhinal Cortex

    Science.gov (United States)

    Coward, L. Andrew; Gedeon, Tamas D.

    2016-01-01

    Theoretical arguments demonstrate that practical considerations, including the needs to limit physiological resources and to learn without interference with prior learning, severely constrain the anatomical architecture of the brain. These arguments identify the hippocampal system as the change manager for the cortex, with the role of selecting the most appropriate locations for cortical receptive field changes at each point in time and driving those changes. This role results in the hippocampal system recording the identities of groups of cortical receptive fields that changed at the same time. These types of records can also be used to reactivate the receptive fields active during individual unique past events, providing mechanisms for episodic memory retrieval. Our theoretical arguments identify the perirhinal cortex as one important focal point both for driving changes and for recording and retrieving episodic memories. The retrieval of episodic memories must not drive unnecessary receptive field changes, and this consideration places strong constraints on neuron properties and connectivity within and between the perirhinal cortex and regular cortex. Hence the model predicts a number of such properties and connectivity. Experimental test of these falsifiable predictions would clarify how change is managed in the cortex and how episodic memories are retrieved. PMID:26819594

  1. Predicting mountain lion activity using radiocollars equipped with mercury tip-sensors

    Science.gov (United States)

    Janis, Michael W.; Clark, Joseph D.; Johnson, Craig

    1999-01-01

    Radiotelemetry collars with tip-sensors have long been used to monitor wildlife activity. However, comparatively few researchers have tested the reliability of the technique on the species being studied. To evaluate the efficacy of using tip-sensors to assess mountain lion (Puma concolor) activity, we radiocollared 2 hand-reared mountain lions and simultaneously recorded their behavior and the associated telemetry signal characteristics. We noted both the number of pulse-rate changes and the percentage of time the transmitter emitted a fast pulse rate (i.e., head up) within sampling intervals ranging from 1-5 minutes. Based on 27 hours of observations, we were able to correctly distinguish between active and inactive behaviors >93% of the time using a logistic regression model. We present several models to predict activity of mountain lions; the selection of which to us would depend on study objectives and logistics. Our results indicate that field protocols that use only pulse-rate changes to indicate activity can lead to significant classification errors.

  2. NASA's Earth Observing System: The Transition from Climate Monitoring to Climate Change Prediction

    Science.gov (United States)

    King, Michael D.; Herring, David D.

    1998-01-01

    Earth's 4.5 billion year history is a study in change. Natural geological forces have been rearranging the surface features and climatic conditions of our planet since its beginning. There is scientific evidence that some of these natural changes have not only led to mass extinctions of species (e.g., dinosaurs), but have also severely impacted human civilizations. For instance, there is evidence that a relatively sudden climate change caused a 300-year drought that contributed to the downfall of Akkadia, one of the most powerful empires in the Middle-East region around 2200 BC. More recently, the "little ice age" from 1200-1400 AD forced the Vikings to abandon Greenland when temperatures there dropped by about 1.5 C, rendering it too difficult to grow enough crops to sustain the population. Today, there is compelling scientific evidence that human activities have attained the magnitude of a geological force and are speeding up the rate of global change. For example, carbon dioxide levels have risen 30 percent since the industrial revolution and about 40 percent of the world's land surface has been transformed by humans. We don't understand the cause-and-effect relationships among Earth's land, ocean, and atmosphere well enough to predict what, if any, impacts these rapid changes will have on future climate conditions. We need to make many measurements all over the world, over a long period of time, in order to assemble the information needed to construct accurate computer models that will enable us to forecast climate change. In 1988, the Earth System Sciences Committee, sponsored by NASA, issued a report calling for an integrated, long-term strategy for measuring the vital signs of Earth's climate system. The report urged that the measurements must all be intimately coupled with focused process studies, they must facilitate development of Earth system models, and they must be stored in an information system that ensures open access to consistent, long-term data

  3. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    OpenAIRE

    Hudson, LN; Newbold, T; Contu, S; Hill, SLL; Lysenko, I; De Palma, A; Phillips, HRP; Alhusseini, TI; Bedford, FE; Bennett, DJ; Booth, H; Burton, VJ; Chng, CWT; Choimes, A; Correia, DLP

    2017-01-01

    The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make free...

  4. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    OpenAIRE

    Hudson, L. N.; Newbold, T.; Contu, S.; Hill, S. L.; Lysenko, I.; De Palma, A.; Phillips, H. R.; Alhusseini, T. I.; Bedford, F. E.; Bennett, D. J.; Booth, H.; Burton, V. J.; Chng, C. W.; Choimes, A.; Correia, D. L.

    2017-01-01

    The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make free...

  5. Woody plants and the prediction of climate-change impacts on bird diversity

    DEFF Research Database (Denmark)

    Kissling, W. Daniel; Field, R.; Korntheuer, H.

    2010-01-01

    Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant...... species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change...... suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically...

  6. A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

    Directory of Open Access Journals (Sweden)

    M Irfan Ashraf

    Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence

  7. Inter-decadal change in potential predictability of the East Asian summer monsoon

    Science.gov (United States)

    Li, Jiao; Ding, Ruiqiang; Wu, Zhiwei; Zhong, Quanjia; Li, Baosheng; Li, Jianping

    2018-05-01

    The significant inter-decadal change in potential predictability of the East Asian summer monsoon (EASM) has been investigated using the signal-to-noise ratio method. The relatively low potential predictability appears from the early 1950s through the late 1970s and during the early 2000s, whereas the potential predictability is relatively high from the early 1980s through the late 1990s. The inter-decadal change in potential predictability of the EASM can be attributed mainly to variations in the external signal of the EASM. The latter is mostly caused by the El Niño-Southern Oscillation (ENSO) inter-decadal variability. As a major external signal of the EASM, the ENSO inter-decadal variability experiences phase transitions from negative to positive phases in the late 1970s, and to negative phases in the late 1990s. Additionally, ENSO is generally strong (weak) during a positive (negative) phase of the ENSO inter-decadal variability. The strong ENSO is expected to have a greater influence on the EASM, and vice versa. As a result, the potential predictability of the EASM tends to be high (low) during a positive (negative) phase of the ENSO inter-decadal variability. Furthermore, a suite of Pacific Pacemaker experiments suggests that the ENSO inter-decadal variability may be a key pacemaker of the inter-decadal change in potential predictability of the EASM.

  8. Changes in acetylcholinesterase activities in the developing and ...

    African Journals Online (AJOL)

    Changes in acetylcholinesterase activities in the developing and aging pig brain and hypophyses. ... International Journal of Agriculture and Rural Development. Journal Home · ABOUT ... Open Access DOWNLOAD FULL TEXT Subscription ...

  9. Changing word usage predicts changing word durations in New Zealand English.

    Science.gov (United States)

    Sóskuthy, Márton; Hay, Jennifer

    2017-09-01

    This paper investigates the emergence of lexicalized effects of word usage on word duration by looking at parallel changes in usage and duration over 130years in New Zealand English. Previous research has found that frequent words are shorter, informative words are longer, and words in utterance-final position are also longer. It has also been argued that some of these patterns are not simply online adjustments, but are incorporated into lexical representations. While these studies tend to focus on the synchronic aspects of such patterns, our corpus shows that word-usage patterns and word durations are not static over time. Many words change in duration and also change with respect to frequency, informativity and likelihood of occurring utterance-finally. Analysis of changing word durations over this time period shows substantial patterns of co-adaptation between word usage and word durations. Words that are increasing in frequency are becoming shorter. Words that are increasing/decreasing in informativity show a change in the same direction in duration (e.g. increasing informativity is associated with increasing duration). And words that are increasingly appearing utterance-finally are lengthening. These effects exist independently of the local effects of the predictors. For example, words that are increasing utterance-finally lengthen in all positions, including utterance-medially. We show that these results are compatible with a number of different views about lexical representations, but they cannot be explained without reference to a production-perception loop that allows speakers to update their representations dynamically on the basis of their experience. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  10. Horticultural activity predicts later localized limb status in a contemporary pre-industrial population.

    Science.gov (United States)

    Stieglitz, Jonathan; Trumble, Benjamin C; Kaplan, Hillard; Gurven, Michael

    2017-07-01

    Modern humans may have gracile skeletons due to low physical activity levels and mechanical loading. Tests using pre-historic skeletons are limited by the inability to assess behavior directly, while modern industrialized societies possess few socio-ecological features typical of human evolutionary history. Among Tsimane forager-horticulturalists, we test whether greater activity levels and, thus, increased loading earlier in life are associated with greater later-life bone status and diminished age-related bone loss. We used quantitative ultrasonography to assess radial and tibial status among adults aged 20+ years (mean ± SD age = 49 ± 15; 52% female). We conducted systematic behavioral observations to assess earlier-life activity patterns (mean time lag between behavioural observation and ultrasound = 12 years). For a subset of participants, physical activity was again measured later in life, via accelerometry, to determine whether earlier-life time use is associated with later-life activity levels. Anthropometric and demographic data were collected during medical exams. Structural decline with age is reduced for the tibia (female: -0.25 SDs/decade; male: 0.05 SDs/decade) versus radius (female: -0.56 SDs/decade; male: -0.20 SDs/decade), which is expected if greater loading mitigates bone loss. Time allocation to horticulture, but not hunting, positively predicts later-life radial status (β Horticulture  = 0.48, p = 0.01), whereas tibial status is not significantly predicted by subsistence or sedentary leisure participation. Patterns of activity- and age-related change in bone status indicate localized osteogenic responses to loading, and are generally consistent with the logic of bone functional adaptation. Nonmechanical factors related to subsistence lifestyle moderate the association between activity patterns and bone structure. © 2017 Wiley Periodicals, Inc.

  11. Predicting daily physical activity in a lifestyle intervention program

    NARCIS (Netherlands)

    Long, Xi; Pauws, S.C.; Pijl, M.; Lacroix, J.; Goris, A.H.C.; Aarts, R.M.; Gottfried, B.; Aghajan, H.

    2011-01-01

    The growing number of people adopting a sedentary lifestyle these days creates a serious need for effective physical activity promotion programs. Often, these programs monitor activity, provide feedback about activity and offer coaching to increase activity. Some programs rely on a human coach who

  12. Stochastic Change Detection based on an Active Fault Diagnosis Approach

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2007-01-01

    The focus in this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow to obtain a fast change detection/isolation by considering the output or an err...

  13. Effects of climate change on income generating activities of farmers ...

    African Journals Online (AJOL)

    The need to examine the changes that the effect of climate change brings about on the income generating activities of farmers necessitated this study. Two local government areas (LGAs) were randomly selected and simple random sampling was used to sample 160 farmers from the 2 LGAs. Chi-square and Pearson ...

  14. Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle.

    Science.gov (United States)

    Borchers, M R; Chang, Y M; Proudfoot, K L; Wadsworth, B A; Stone, A E; Bewley, J M

    2017-07-01

    The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (lying bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine-learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sensitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was

  15. Leisure Activities and Change in Cognitive Stability: A Multivariate Approach

    Directory of Open Access Journals (Sweden)

    Nathalie Mella

    2017-03-01

    Full Text Available Aging is traditionally associated with cognitive decline, attested by slower reaction times and poorer performance in various cognitive tasks, but also by an increase in intraindividual variability (IIV in cognitive performance. Results concerning how lifestyle activities protect from cognitive decline are mixed in the literature and all focused on how it affects mean performance. However, IIV has been proven to be an index more sensitive to age differences, and very little is known about the relationships between lifestyle activities and change in IIV in aging. This longitudinal study explores the association between frequency of physical, social, intellectual, artistic, or cultural activities and age-related change in various cognitive abilities, considering both mean performance and IIV. Ninety-six participants, aged 64–93 years, underwent a battery of cognitive tasks at four measurements over a seven-year period, and filled out a lifestyle activity questionnaire. Linear multilevel models were used to analyze the associations between change in cognitive performance and five types of activities. Results showed that the practice of leisure activities was more strongly associated with IIV than with mean performance, both when considering overall level and change in performance. Relationships with IIV were dependent of the cognitive tasks considered and overall results showed protective effects of cultural, physical and intellectual activities on IIV. These results underline the need for considering IIV in the study of age-related cognitive change.

  16. Six-month changes in spirituality and religiousness in alcoholics predict drinking outcomes at nine months.

    Science.gov (United States)

    Robinson, Elizabeth A R; Krentzman, Amy R; Webb, Jon R; Brower, Kirk J

    2011-07-01

    Although spiritual change is hypothesized to contribute to recovery from alcohol dependence, few studies have used prospective data to investigate this hypothesis. Prior studies have also been limited to treatment-seeking and Alcoholics Anonymous (AA) samples. This study included alcohol-dependent individuals, both in treatment and not, to investigate the effect of spiritual and religious (SR) change on subsequent drinking outcomes, independent of AA involvement. Alcoholics (N = 364) were recruited for a panel study from two abstinence-based treatment centers, a moderation drinking program, and untreated individuals from the local community. Quantitative measures of SR change between baseline and 6 months were used to predict 9-month drinking outcomes, controlling for baseline drinking and AA involvement. Significant 6-month changes in 8 of 12 SR measures were found, which included private SR practices, beliefs, daily spiritual experiences, three measures of forgiveness, negative religious coping, and purpose in life. Increases in private SR practices and forgiveness of self were the strongest predictors of improvements in drinking outcomes. Changes in daily spiritual experiences, purpose in life, a general measure of forgiveness, and negative religious coping also predicted favorable drinking outcomes. SR change predicted good drinking outcomes in alcoholics, even when controlling for AA involvement. SR variables, broadly defined, deserve attention in fostering change even among those who do not affiliate with AA or religious institutions. Last, future research should include SR variables, particularly various types of forgiveness, given the strong effects found for forgiveness of self.

  17. Higher frequency network activity flow predicts lower frequency node activity in intrinsic low-frequency BOLD fluctuations.

    Science.gov (United States)

    Bajaj, Sahil; Adhikari, Bhim Mani; Dhamala, Mukesh

    2013-01-01

    The brain remains electrically and metabolically active during resting conditions. The low-frequency oscillations (LFO) of the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI) coherent across distributed brain regions are known to exhibit features of this activity. However, these intrinsic oscillations may undergo dynamic changes in time scales of seconds to minutes during resting conditions. Here, using wavelet-transform based time-frequency analysis techniques, we investigated the dynamic nature of default-mode networks from intrinsic BOLD signals recorded from participants maintaining visual fixation during resting conditions. We focused on the default-mode network consisting of the posterior cingulate cortex (PCC), the medial prefrontal cortex (mPFC), left middle temporal cortex (LMTC) and left angular gyrus (LAG). The analysis of the spectral power and causal flow patterns revealed that the intrinsic LFO undergo significant dynamic changes over time. Dividing the frequency interval 0 to 0.25 Hz of LFO into four intervals slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz), we further observed significant positive linear relationships of slow-4 in-out flow of network activity with slow-5 node activity, and slow-3 in-out flow of network activity with slow-4 node activity. The network activity associated with respiratory related frequency (slow-2) was found to have no relationship with the node activity in any of the frequency intervals. We found that the net causal flow towards a node in slow-3 band was correlated with the number of fibers, obtained from diffusion tensor imaging (DTI) data, from the other nodes connecting to that node. These findings imply that so-called resting state is not 'entirely' at rest, the higher frequency network activity flow can predict the lower frequency node activity, and the network activity flow can reflect underlying structural

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

    Science.gov (United States)

    Levy-Tzedek, Shelly

    2017-01-01

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

  19. Bureaucratic Activism and Radical School Change in Tamil Nadu, India

    Science.gov (United States)

    Niesz, Tricia; Krishnamurthy, Ramchandar

    2013-01-01

    In 2007, Activity Based Learning (ABL), a child-centered, activity-based method of pedagogical practice, transformed classrooms in all of the over 37,000 primary-level government schools in Tamil Nadu, India. The large scale, rapid pace, and radical nature of educational change sets the ABL initiative apart from most school reform efforts.…

  20. Factors affecting perceived change in physical activity in pregnancy

    NARCIS (Netherlands)

    Astrid Merkx; Marlein Ausems; Luc Budé; Raymond de Vries; Marianne J. Nieuwenhuijze

    2017-01-01

    Objective reduction of physical activity (PA) during pregnancy is common but undesirable, as it is associated with negative outcomes, including excessive gestational weight gain. Our objective was to explore changes in five types of activity that occurred during pregnancy and the behavioural

  1. Sexual selection predicts advancement of avian spring migration in response to climate change

    DEFF Research Database (Denmark)

    Spottiswoode, Claire N; Tøttrup, Anders P; Coppack, Timothy

    2006-01-01

    Global warming has led to earlier spring arrival of migratory birds, but the extent of this advancement varies greatly among species, and it remains uncertain to what degree these changes are phenotypically plastic responses or microevolutionary adaptations to changing environmental conditions. We...... suggest that sexual selection could help to understand this variation, since early spring arrival of males is favoured by female choice. Climate change could weaken the strength of natural selection opposing sexual selection for early migration, which would predict greatest advancement in species...... in the timing of first-arriving individuals, suggesting that selection has not only acted on protandrous males. These results suggest that sexual selection may have an impact on the responses of organisms to climate change, and knowledge of a species' mating system might help to inform attempts at predicting...

  2. Modeling and Predicting the Daily Equatorial Plasma Bubble Activity Using the Tiegcm

    Science.gov (United States)

    Carter, B. A.; Retterer, J. M.; Yizengaw, E.; Wiens, K. C.; Wing, S.; Groves, K. M.; Caton, R. G.; Bridgwood, C.; Francis, M. J.; Terkildsen, M. B.; Norman, R.; Zhang, K.

    2014-12-01

    Describing and understanding the daily variability of Equatorial Plasma Bubble (EPB) occurrence has remained a significant challenge over recent decades. In this study we use the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM), which is driven by solar (F10.7) and geomagnetic (Kp) activity indices, to study daily variations of the linear Rayleigh-Taylor (R-T) instability growth rate in relation to the measured scintillation strength at five longitudinally distributed stations. For locations characterized by generally favorable conditions for EPB growth (i.e., within the scintillation season for that location) we find that the TIEGCM is capable of identifying days when EPB development, determined from the calculated R-T growth rate, is suppressed as a result of geomagnetic activity. Both observed and modeled upward plasma drift indicate that the pre-reversal enhancement scales linearly with Kp from several hours prior, from which it is concluded that even small Kp changes cause significant variations in daily EPB growth. This control of Kp variations on EPB growth prompted an investigation into the use of predicted Kp values from the Wing Kp model over a 2-month equinoctial campaign in 2014. It is found that both the 1-hr and 4-hr predicted Kp values can be reliably used as inputs into the TIEGCM to forecast the EPB growth conditions during scintillation season, when daily EPB variability is governed by the suppression of EPBs on days with increased, but not necessarily high, geomagnetic activity.

  3. Time and activity sequence prediction of business process instances

    DEFF Research Database (Denmark)

    Polato, Mirko; Sperduti, Alessandro; Burattin, Andrea

    2018-01-01

    The ability to know in advance the trend of running process instances, with respect to different features, such as the expected completion time, would allow business managers to timely counteract to undesired situations, in order to prevent losses. Therefore, the ability to accurately predict...... future features of running business process instances would be a very helpful aid when managing processes, especially under service level agreement constraints. However, making such accurate forecasts is not easy: many factors may influence the predicted features. Many approaches have been proposed...

  4. Predicting of Physiological Changes through Personality Traits and Decision Making Styles

    Directory of Open Access Journals (Sweden)

    Saeed Imani

    2016-12-01

    Full Text Available Background and Objective: One of the important concepts of social psychology is cognitive dissonance. When our practice is in conflict with our previous attitudes often change our attitude so that we will operate in concert with; this is cognitive dissonance. The aim of this study was evaluation of relation between decision making styles, personality traits and physiological components of cognitive dissonance and also offering a statistical model about them.Materials and Methods: In this correlation study, 130 students of Elmi-Karbordi University of Safadasht were invited and they were asked to complete Scott & Bruce Decision-Making Styles Questionnaire and Gray-Wilson Personality Questionnaire. Before and after distributing those questionnaires, their physiological conditions were receded. Cognitive dissonance was induced by writing about reducing amount of budget which deserved to orphans and rating the reduction of interest of lovely character that ignore his or her fans. Data analysis conducted through regression and multi vitiate covariance.Results: There were correlation between cognitive styles (Avoidant, dependent, logical and intuitive and also personality variables (Flight and Approach, active avoidance, Fight and Extinction with cognitive dissonance. The effect of cognitive (decision making styles and personality variables on physiological components was mediate indirectly through cognitive dissonance, in levels of P=0.01 and P=0.05 difference, was significant. Conclusion: Decision making styles and personality traits are related to cognitive dissonance and its physiological components, and also predict physiological components of cognitive dissonance.

  5. Detection of cardiac activity changes from human speech

    Science.gov (United States)

    Tovarek, Jaromir; Partila, Pavol; Voznak, Miroslav; Mikulec, Martin; Mehic, Miralem

    2015-05-01

    Impact of changes in blood pressure and pulse from human speech is disclosed in this article. The symptoms of increased physical activity are pulse, systolic and diastolic pressure. There are many methods of measuring and indicating these parameters. The measurements must be carried out using devices which are not used in everyday life. In most cases, the measurement of blood pressure and pulse following health problems or other adverse feelings. Nowadays, research teams are trying to design and implement modern methods in ordinary human activities. The main objective of the proposal is to reduce the delay between detecting the adverse pressure and to the mentioned warning signs and feelings. Common and frequent activity of man is speaking, while it is known that the function of the vocal tract can be affected by the change in heart activity. Therefore, it can be a useful parameter for detecting physiological changes. A method for detecting human physiological changes by speech processing and artificial neural network classification is described in this article. The pulse and blood pressure changes was induced by physical exercises in this experiment. The set of measured subjects was formed by ten healthy volunteers of both sexes. None of the subjects was a professional athlete. The process of the experiment was divided into phases before, during and after physical training. Pulse, systolic, diastolic pressure was measured and voice activity was recorded after each of them. The results of this experiment describe a method for detecting increased cardiac activity from human speech using artificial neural network.

  6. Physical activity is associated with changes in knee cartilage microstructure.

    Science.gov (United States)

    Halilaj, E; Hastie, T J; Gold, G E; Delp, S L

    2018-06-01

    The purpose of this study was to determine if there is an association between objectively measured physical activity and longitudinal changes in knee cartilage microstructure. We used accelerometry and T 2 -weighted magnetic resonance imaging (MRI) data from the Osteoarthritis Initiative, restricting the analysis to men aged 45-60 years, with a body mass index (BMI) of 25-27 kg/m 2 and no radiographic evidence of knee osteoarthritis. After computing 4-year changes in mean T 2 relaxation time for six femoral cartilage regions and mean daily times spent in the sedentary, light, moderate, and vigorous activity ranges, we performed canonical correlation analysis (CCA) to find a linear combination of times spent in different activity intensity ranges (Activity Index) that was maximally correlated with a linear combination of regional changes in cartilage microstructure (Cartilage Microstructure Index). We used leave-one-out pre-validation to test the robustness of the model on new data. Nineteen subjects satisfied the inclusion criteria. CCA identified an Activity Index and a Cartilage Microstructure Index that were significantly correlated (r = .82, P microstructural changes in different cartilage regions than it is with univariate or cumulative changes, likely because this index separates the effect of activity, which is greater in the medial loadbearing region, from that of patient-specific natural aging. Copyright © 2018 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

  7. Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

    Science.gov (United States)

    Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

    2018-01-01

    Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

  8. [Effects of sampling plot number on tree species distribution prediction under climate change].

    Science.gov (United States)

    Liang, Yu; He, Hong-Shi; Wu, Zhi-Wei; Li, Xiao-Na; Luo, Xu

    2013-05-01

    Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.

  9. The motivation to be sedentary predicts weight change when sedentary behaviors are reduced

    Directory of Open Access Journals (Sweden)

    Paluch Rocco A

    2011-02-01

    Full Text Available Abstract Background Obesity is correlated with a sedentary lifestyle, and the motivation to be active or sedentary is correlated with obesity. The present study tests the hypothesis that the motivation to be active or sedentary is correlated with weight change when children reduce their sedentary behavior. Methods The motivation to be active or sedentary, changes in weight, and accelerometer assessed physical activity were collected for 55 families with overweight/obese children who participated in a nine-week field study to examine behavior and weight change as a function of reducing sedentary behavior. Children were studied in three 3-week phases, baseline, reduce targeted sedentary behaviors by 25% and reduce targeted sedentary behaviors by 50%. The targeted sedentary behaviors included television, video game playing, video watching, and computer use. Results The reinforcing value of sedentary behavior but not physical activity, was correlated with weight change, as losing weight was associated with lower reinforcing value of sedentary behaviors. Reducing sedentary behavior was not associated with a significant change in objectively measured physical activity, suggesting the main way in which reducing sedentary behavior influenced weight change is by complementary changes in energy intake. Estimated energy intake supported the hypothesis that reducing sedentary behaviors influences weight by reducing energy intake. Conclusions These data show that the motivation to be sedentary limits the effects of reducing sedentary behavior on weight change in obese children. Trial registration ClinicalTrials.gov: NCT00962247

  10. The motivation to be sedentary predicts weight change when sedentary behaviors are reduced.

    Science.gov (United States)

    Epstein, Leonard H; Roemmich, James N; Cavanaugh, Meghan D; Paluch, Rocco A

    2011-02-22

    Obesity is correlated with a sedentary lifestyle, and the motivation to be active or sedentary is correlated with obesity. The present study tests the hypothesis that the motivation to be active or sedentary is correlated with weight change when children reduce their sedentary behavior. The motivation to be active or sedentary, changes in weight, and accelerometer assessed physical activity were collected for 55 families with overweight/obese children who participated in a nine-week field study to examine behavior and weight change as a function of reducing sedentary behavior. Children were studied in three 3-week phases, baseline, reduce targeted sedentary behaviors by 25% and reduce targeted sedentary behaviors by 50%. The targeted sedentary behaviors included television, video game playing, video watching, and computer use. The reinforcing value of sedentary behavior but not physical activity, was correlated with weight change, as losing weight was associated with lower reinforcing value of sedentary behaviors. Reducing sedentary behavior was not associated with a significant change in objectively measured physical activity, suggesting the main way in which reducing sedentary behavior influenced weight change is by complementary changes in energy intake. Estimated energy intake supported the hypothesis that reducing sedentary behaviors influences weight by reducing energy intake. These data show that the motivation to be sedentary limits the effects of reducing sedentary behavior on weight change in obese children. © 2011 Epstein et al; licensee BioMed Central Ltd.

  11. GABAA receptors in visual and auditory cortex and neural activity changes during basic visual stimulation

    Directory of Open Access Journals (Sweden)

    Pengmin eQin

    2012-12-01

    Full Text Available Recent imaging studies have demonstrated that levels of resting GABA in the visual cortex predict the degree of stimulus-induced activity in the same region. These studies have used the presentation of discrete visual stimulus; the change from closed eyes to open also represents a simple visual stimulus, however, and has been shown to induce changes in local brain activity and in functional connectivity between regions. We thus aimed to investigate the role of the GABA system, specifically GABAA receptors, in the changes in brain activity between the eyes closed (EC and eyes open (EO state in order to provide detail at the receptor level to complement previous studies of GABA concentrations. We conducted an fMRI study involving two different modes of the change from EC to EO: An EO and EC block design, allowing the modelling of the haemodynamic response, followed by longer periods of EC and EO to allow the measuring of functional connectivity. The same subjects also underwent [18F]Flumazenil PET measure GABAA receptor binding potentials. It was demonstrated that the local-to-global ratio of GABAA receptor binding potential in the visual cortex predicted the degree of changes in neural activity from EC to EO. This same relationship was also shown in the auditory cortex. Furthermore, the local-to-global ratio of GABAA receptor binding potential in the visual cortex also predicts the change of functional connectivity between visual and auditory cortex from EC to EO. These findings contribute to our understanding of the role of GABAA receptors in stimulus-induced neural activity in local regions and in inter-regional functional connectivity.

  12. Responsiveness of a simple tool for assessing change in behavioral intention after continuing professional development activities.

    Science.gov (United States)

    Légaré, France; Freitas, Adriana; Turcotte, Stéphane; Borduas, Francine; Jacques, André; Luconi, Francesca; Godin, Gaston; Boucher, Andrée; Sargeant, Joan; Labrecque, Michel

    2017-01-01

    Continuing professional development (CPD) activities are one way that new knowledge can be translated into changes in practice. However, few tools are available for evaluating the extent to which these activities change health professionals' behavior. We developed a questionnaire called CPD-Reaction for assessing the impact of CPD activities on health professionals' clinical behavioral intentions. We evaluated its responsiveness to change in behavioral intention and verified its acceptability among stakeholders. We enrolled 376 health professionals who completed CPD-Reaction before and immediately after attending a CPD activity. We contacted them three months later and asked them to self-report on any behavior change. We compared the mean rankings on each CPD-Reaction construct before and immediately after CPD activities. To estimate its predictive validity, we compared the median behavioral intention score (post-activity) of health professionals reporting a behavior change three months later with the median behavioral intention score of physicians who reported no change. We explored stakeholders' views on CPD-Reaction in semi-structured interviews. Participants were mostly family physicians (62.2%), with an average of 19 years of clinical practice. Post-activity, we observed an increase in intention-related scores for all constructs (P behavior change. We observed no statistically significant difference in intention between health professionals who later reported a behavior change and those who reported no change (P = 0.30). Overall, CPD stakeholders found the CPD-Reaction questionnaire of interest and suggested potential solutions to perceived barriers to its implementation. The CPD-Reaction questionnaire seems responsive to change in behavioral intention. Although CPD stakeholders found it interesting, future implementation will require addressing barriers they identified.

  13. Improving sub-pixel imperviousness change prediction by ensembling heterogeneous non-linear regression models

    Science.gov (United States)

    Drzewiecki, Wojciech

    2016-12-01

    In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels) was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques. The results proved that in case of sub-pixel evaluation the most accurate prediction of change may not necessarily be based on the most accurate individual assessments. When single methods are considered, based on obtained results Cubist algorithm may be advised for Landsat based mapping of imperviousness for single dates. However, Random Forest may be endorsed when the most reliable evaluation of imperviousness change is the primary goal. It gave lower accuracies for individual assessments, but better prediction of change due to more correlated errors of individual predictions. Heterogeneous model ensembles performed for individual time points assessments at least as well as the best individual models. In case of imperviousness change assessment the ensembles always outperformed single model approaches. It means that it is possible to improve the accuracy of sub-pixel imperviousness change assessment using ensembles of heterogeneous non-linear regression models.

  14. Predicting enhancer activity and variant impact using gkm-SVM.

    Science.gov (United States)

    Beer, Michael A

    2017-09-01

    We participated in the Critical Assessment of Genome Interpretation eQTL challenge to further test computational models of regulatory variant impact and their association with human disease. Our prediction model is based on a discriminative gapped-kmer SVM (gkm-SVM) trained on genome-wide chromatin accessibility data in the cell type of interest. The comparisons with massively parallel reporter assays (MPRA) in lymphoblasts show that gkm-SVM is among the most accurate prediction models even though all other models used the MPRA data for model training, and gkm-SVM did not. In addition, we compare gkm-SVM with other MPRA datasets and show that gkm-SVM is a reliable predictor of expression and that deltaSVM is a reliable predictor of variant impact in K562 cells and mouse retina. We further show that DHS (DNase-I hypersensitive sites) and ATAC-seq (assay for transposase-accessible chromatin using sequencing) data are equally predictive substrates for training gkm-SVM, and that DHS regions flanked by H3K27Ac and H3K4me1 marks are more predictive than DHS regions alone. © 2017 Wiley Periodicals, Inc.

  15. Predicting the effects of climate change on marine communities and the consequences for fisheries

    DEFF Research Database (Denmark)

    Jennings, Simon; Brander, Keith

    2010-01-01

    for the community under the same climate scenario. The main weakness of the community approach is that the methods predict abundance and production by size-class rather than taxonomic group, and society would be particularly concerned if climate driven changes had a strong effect on the relative production...... of fishable and non-fishable species in the community. The main strength of the community approach is that it provides widely applicable ‘null’ models for assessing the biological effects of climate change and a baseline for model comparisons.......Climate effects on the structure and function of marine communities have received scant attention. The few existing approaches for predicting climate effects suggest that community responses might be predicted from the responses of component populations. These approaches require a very complex...

  16. Landscape genomic prediction for restoration of a Eucalyptus foundation species under climate change.

    Science.gov (United States)

    Supple, Megan Ann; Bragg, Jason G; Broadhurst, Linda M; Nicotra, Adrienne B; Byrne, Margaret; Andrew, Rose L; Widdup, Abigail; Aitken, Nicola C; Borevitz, Justin O

    2018-04-24

    As species face rapid environmental change, we can build resilient populations through restoration projects that incorporate predicted future climates into seed sourcing decisions. Eucalyptus melliodora is a foundation species of a critically endangered community in Australia that is a target for restoration. We examined genomic and phenotypic variation to make empirical based recommendations for seed sourcing. We examined isolation by distance and isolation by environment, determining high levels of gene flow extending for 500 km and correlations with climate and soil variables. Growth experiments revealed extensive phenotypic variation both within and among sampling sites, but no site-specific differentiation in phenotypic plasticity. Model predictions suggest that seed can be sourced broadly across the landscape, providing ample diversity for adaptation to environmental change. Application of our landscape genomic model to E. melliodora restoration projects can identify genomic variation suitable for predicted future climates, thereby increasing the long term probability of successful restoration. © 2018, Supple et al.

  17. Nonlinear model predictive control of a passenger vehicle for automated lane changes

    NARCIS (Netherlands)

    Acosta, A.F.; Marquez-Ruiz, A.; Espinosa, J.J.

    2017-01-01

    This article presents a nonlinear Model Predictive Control (MPC) for lane changes, based on a simplified Single Track Model (STM) of the vehicle. The STM includes the position of the vehicle in global coordinates as a state so that the position of the target lane can be specified to the MPC for

  18. LANDIS PRO: a landscape model that predicts forest composition and structure changes at regional scales

    Science.gov (United States)

    Wen J. Wang; Hong S. He; Jacob S. Fraser; Frank R. Thompson; Stephen R. Shifley; Martin A. Spetich

    2014-01-01

    LANDIS PRO predicts forest composition and structure changes incorporating species-, stand-, and landscape-scales processes at regional scales. Species-scale processes include tree growth, establishment, and mortality. Stand-scale processes contain density- and size-related resource competition that regulates self-thinning and seedling establishment. Landscapescale...

  19. Fat or lean: adjustment of endogenous energy stores to predictable and unpredictable changes in allostatic load

    Science.gov (United States)

    Schultner, Jannik; Kitaysky, Alexander S.; Welcker, Jorg; Hatch, Scott

    2013-01-01

    1. The ability to store energy endogenously is an important ecological mechanism that allows animals to buffer predictable and unpredictable variation in allostatic load. The secretion of glucocorticoids, which reflects changes in allostatic load, is suggested to play a major role in the adjustment of endogenous stores to these varying conditions.

  20. Prediction of the impacts of climate changes on the stream flow of ...

    African Journals Online (AJOL)

    Abstract. Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed, Aguobu-Umumba, Ezeagu, Enugu State, Nigeria. The model was first used to simulate stream flow using observed data. After model run, parameterization, sensitivity analysis, the monthly ...

  1. Burrowing Behavior of a Deposit Feeding Bivalve Predicts Change in Intertidal Ecosystem State

    NARCIS (Netherlands)

    Compton, T.J.; Bodnar, W.; Koolhaas, A.; Dekinga, A.; Holthuijsen, S.; Ten Horn, J.; McSweeney, N.; van Gils, J.A.; Piersma, T.

    2016-01-01

    Behavior has a predictive power that is often underutilized as a tool for signaling ecological change. The burrowing behavior of the deposit feeding bivalve Macoma balthica reflects a typical food-safety trade-off. The choice to live close to the sediment surface comes at a risk of predation and is

  2. Burrowing behavior of a deposit feeding bivalve predicts change in intertidal ecosystem state

    NARCIS (Netherlands)

    Compton, Tanya J.; Bodnar, Wanda; Koolhaas, Anita; Dekinga, Anne; Holthuijsen, Sander; ten Horn, Job; McSweeney, Niamh; van Gils, Jan; Piersma, Theunis

    2016-01-01

    Behavior has a predictive power that is often underutilized as a tool for signaling ecological change. The burrowing behavior of the deposit feeding bivalve Macoma balthica reflects a typical food-safety trade-off. The choice to live close to the sediment surface comes at a risk of predation and is

  3. Gianluigi Zenti, President, Academia Barilla SpA - The Changing Consumer: Demanding but Predictable

    OpenAIRE

    Hartl, Jochen

    2006-01-01

    It is crucial to understand and predict consumers' behaviour to meet future consumer demands. This report contributes to the discussion by giving an insight into consumers' behaviour from the perspective of Gianluigi Zenti, executive director of Academia Barilla. It is discussed how consumers' choice has changed in particular with regard to Italian food in the US and how Barilla has responded to that challenge.

  4. The Predictive Utility of Hypnotizability: The Change in Suggestibility Produced by Hypnosis

    Science.gov (United States)

    Milling, Leonard S.; Coursen, Elizabeth L.; Shores, Jessica S.; Waszkiewicz, Jolanta A.

    2010-01-01

    Objective: The predictive utility of hypnotizability, conceptualized as the change in suggestibility produced by a hypnotic induction, was investigated in the suggested reduction of experimental pain. Method: One hundred and seventy-three participants were assessed for nonhypnotic imaginative suggestibility. Thereafter, participants experienced…

  5. Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

    Science.gov (United States)

    Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh

    2017-01-01

    The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...

  6. Factors predicting physical activity among children with special needs.

    Science.gov (United States)

    Yazdani, Shahram; Yee, Chu Tang; Chung, Paul J

    2013-07-18

    Obesity is especially prevalent among children with special needs. Both lack of physical activity and unhealthful eating are major contributing factors. The objective of our study was to investigate barriers to physical activity among these children. We surveyed parents of the 171 children attending Vista Del Mar School in Los Angeles, a nonprofit school serving a socioeconomically diverse group of children with special needs from kindergarten through 12th grade. Parents were asked about their child's and their own physical activity habits, barriers to their child's exercise, and demographics. The response rate was 67%. Multivariate logistic regression was used to examine predictors of children being physically active at least 3 hours per week. Parents reported that 45% of the children were diagnosed with attention deficit hyperactivity disorder, 38% with autism, and 34% with learning disabilities; 47% of children and 56% of parents were physically active less than 3 hours per week. The top barriers to physical activity were reported as child's lack of interest (43%), lack of developmentally appropriate programs (33%), too many behavioral problems (32%), and parents' lack of time (29%). However, child's lack of interest was the only parent-reported barrier independently associated with children's physical activity. Meanwhile, children whose parents were physically active at least 3 hours per week were 4.2 times as likely to be physically active as children whose parents were less physically active (P = .01). In this group of students with special needs, children's physical activity was strongly associated with parental physical activity; parent-reported barriers may have had less direct effect. Further studies should examine the importance of parental physical activity among children with special needs.

  7. Predictive modelling of the spatial pattern of past and future forest cover changes in India

    Science.gov (United States)

    Reddy, C. Sudhakar; Singh, Sonali; Dadhwal, V. K.; Jha, C. S.; Rao, N. Rama; Diwakar, P. G.

    2017-02-01

    This study was carried out to simulate the forest cover changes in India using Land Change Modeler. Classified multi-temporal long-term forest cover data was used to generate the forest covers of 1880 and 2025. The spatial data were overlaid with variables such as the proximity to roads, settlements, water bodies, elevation and slope to determine the relationship between forest cover change and explanatory variables. The predicted forest cover in 1880 indicates an area of 10,42,008 km2, which represents 31.7% of the geographical area of India. About 40% of the forest cover in India was lost during the time interval of 1880-2013. Ownership of majority of forest lands by non-governmental agencies and large scale shifting cultivation are responsible for higher deforestation rates in the Northeastern states. The six states of the Northeast (Assam, Manipur, Meghalaya, Mizoram, Nagaland, Tripura) and one union territory (Andaman & Nicobar Islands) had shown an annual gross rate of deforestation of >0.3 from 2005 to 2013 and has been considered in the present study for the prediction of future forest cover in 2025. The modelling results predicted widespread deforestation in Northeast India and in Andaman & Nicobar Islands and hence is likely to affect the remaining forests significantly before 2025. The multi-layer perceptron neural network has predicted the forest cover for the period of 1880 and 2025 with a Kappa statistic of >0.70. The model predicted a further decrease of 2305 km2 of forest area in the Northeast and Andaman & Nicobar Islands by 2025. The majority of the protected areas are successful in the protection of the forest cover in the Northeast due to management practices, with the exception of Manas, Sonai-Rupai, Nameri and Marat Longri. The predicted forest cover scenario for the year 2025 would provide useful inputs for effective resource management and help in biodiversity conservation and for mitigating climate change.

  8. Predicting human activities in sequences of actions in RGB-D videos

    Science.gov (United States)

    Jardim, David; Nunes, Luís.; Dias, Miguel

    2017-03-01

    In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.

  9. Predicting physical activity in adolescents: the role of compensatory health beliefs within the Health Action Process Approach.

    Science.gov (United States)

    Berli, Corina; Loretini, Philipp; Radtke, Theda; Hornung, Rainer; Scholz, Urte

    2014-01-01

    Compensatory health beliefs (CHBs), defined as beliefs that healthy behaviours can compensate for unhealthy behaviours, may be one possible factor hindering people in adopting a healthier lifestyle. This study examined the contribution of CHBs to the prediction of adolescents' physical activity within the theoretical framework of the Health Action Process Approach (HAPA). The study followed a prospective survey design with assessments at baseline (T1) and two weeks later (T2). Questionnaire data on physical activity, HAPA variables and CHBs were obtained twice from 430 adolescents of four different Swiss schools. Multilevel modelling was applied. CHBs added significantly to the prediction of intentions and change in intentions, in that higher CHBs were associated with lower intentions to be physically active at T2 and a reduction in intentions from T1 to T2. No effect of CHBs emerged for the prediction of self-reported levels of physical activity at T2 and change in physical activity from T1 to T2. Findings emphasise the relevance of examining CHBs in the context of an established health behaviour change model and suggest that CHBs are of particular importance in the process of intention formation.

  10. Predictive Active Set Selection Methods for Gaussian Processes

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2012-01-01

    We propose an active set selection framework for Gaussian process classification for cases when the dataset is large enough to render its inference prohibitive. Our scheme consists of a two step alternating procedure of active set update rules and hyperparameter optimization based upon marginal...... high impact to the classifier decision process while removing those that are less relevant. We introduce two active set rules based on different criteria, the first one prefers a model with interpretable active set parameters whereas the second puts computational complexity first, thus a model...... with active set parameters that directly control its complexity. We also provide both theoretical and empirical support for our active set selection strategy being a good approximation of a full Gaussian process classifier. Our extensive experiments show that our approach can compete with state...

  11. The predicted influence of climate change on lesser prairie-chicken reproductive parameters

    Science.gov (United States)

    Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

    2013-01-01

    The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

  12. Ventromedial Prefrontal Cortex Activation Is Associated with Memory Formation for Predictable Rewards

    Science.gov (United States)

    Bialleck, Katharina A.; Schaal, Hans-Peter; Kranz, Thorsten A.; Fell, Juergen; Elger, Christian E.; Axmacher, Nikolai

    2011-01-01

    During reinforcement learning, dopamine release shifts from the moment of reward consumption to the time point when the reward can be predicted. Previous studies provide consistent evidence that reward-predicting cues enhance long-term memory (LTM) formation of these items via dopaminergic projections to the ventral striatum. However, it is less clear whether memory for items that do not precede a reward but are directly associated with reward consumption is also facilitated. Here, we investigated this question in an fMRI paradigm in which LTM for reward-predicting and neutral cues was compared to LTM for items presented during consumption of reliably predictable as compared to less predictable rewards. We observed activation of the ventral striatum and enhanced memory formation during reward anticipation. During processing of less predictable as compared to reliably predictable rewards, the ventral striatum was activated as well, but items associated with less predictable outcomes were remembered worse than items associated with reliably predictable outcomes. Processing of reliably predictable rewards activated the ventromedial prefrontal cortex (vmPFC), and vmPFC BOLD responses were associated with successful memory formation of these items. Taken together, these findings show that consumption of reliably predictable rewards facilitates LTM formation and is associated with activation of the vmPFC. PMID:21326612

  13. Efficient and Effective Change Principles in Active Videogames.

    Science.gov (United States)

    Straker, Leon M; Fenner, Ashley A; Howie, Erin K; Feltz, Deborah L; Gray, Cindy M; Lu, Amy Shirong; Mueller, Florian Floyd; Simons, Monique; Barnett, Lisa M

    2015-02-01

    Active videogames have the potential to enhance population levels of physical activity but have not been successful in achieving this aim to date. This article considers a range of principles that may be important to the design of effective and efficient active videogames from diverse discipline areas, including behavioral sciences (health behavior change, motor learning, and serious games), business production (marketing and sales), and technology engineering and design (human-computer interaction/ergonomics and flow). Both direct and indirect pathways to impact on population levels of habitual physical activity are proposed, along with the concept of a game use lifecycle. Examples of current active and sedentary electronic games are used to understand how such principles may be applied. Furthermore, limitations of the current usage of theoretical principles are discussed. A suggested list of principles for best practice in active videogame design is proposed along with suggested research ideas to inform practice to enhance physical activity.

  14. Efficient and Effective Change Principles in Active Videogames

    Science.gov (United States)

    Fenner, Ashley A.; Howie, Erin K.; Feltz, Deborah L.; Gray, Cindy M.; Lu, Amy Shirong; Mueller, Florian “Floyd”; Simons, Monique; Barnett, Lisa M.

    2015-01-01

    Abstract Active videogames have the potential to enhance population levels of physical activity but have not been successful in achieving this aim to date. This article considers a range of principles that may be important to the design of effective and efficient active videogames from diverse discipline areas, including behavioral sciences (health behavior change, motor learning, and serious games), business production (marketing and sales), and technology engineering and design (human–computer interaction/ergonomics and flow). Both direct and indirect pathways to impact on population levels of habitual physical activity are proposed, along with the concept of a game use lifecycle. Examples of current active and sedentary electronic games are used to understand how such principles may be applied. Furthermore, limitations of the current usage of theoretical principles are discussed. A suggested list of principles for best practice in active videogame design is proposed along with suggested research ideas to inform practice to enhance physical activity. PMID:26181680

  15. Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm ...... controller is shown very reliable keeping the comfort levels in the two considered seasons and shifting the load away from peak hours in order to achieve the desired flexible electricity consumption.......Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm...

  16. Examining Changes in Radioxenon Isotope Activity Ratios during Subsurface Transport

    Science.gov (United States)

    Annewandter, R.

    2013-12-01

    The Non-Proliferation Experiment (NPE) has demonstrated and modelled the usefulness of barometric pumping induced soil gas sampling during On-Site inspections. Gas transport has been widely studied with different numerical codes. However, gas transport of all radioxenons in the post-detonation regime and their possible fractionation is still neglected in the open literature. Atmospheric concentrations of the radioxenons Xe-135, Xe-133m, Xe-133 and Xe-131m can be used to discriminate between civilian releases (nuclear power plants or medical isotope facilities), and nuclear explosion sources. It is based on the isotopic activity ratio method. Yet it is not clear whether subsurface migration of the radioxenons, with eventual release into the atmosphere, can affect the activity ratios due to fractionation. Fractionation can be caused by different diffusivities due to mass differences between the radioxenons. A previous study showed surface arrival time of a chemically inert gaseous tracer is affected by its diffusivity. They observed detectable amount for SF6 50 days after detonation and 375 days for He-3. They predict 50 and 80 days for Xe-133 and Ar-37 respectively. Cyclical changes in atmospheric pressure can drive subsurface gas transport. This barometric pumping phenomenon causes an oscillatoric flow in upward trending fractures which, combined with diffusion into the porous matrix, leads to a net transport of gaseous components - a ratcheting effect. We use a general purpose reservoir simulator (Complex System Modelling Platform, CSMP++) which has been applied in a range of fields such as deep geothermal systems, three-phase black oil simulations , fracture propagation in fractured, porous media, Navier-Stokes pore-scale modelling among others. It is specifically designed to account for structurally complex geologic situation of fractured, porous media. Parabolic differential equations are solved by a continuous Galerkin finite-element method, hyperbolic

  17. Seasonal prediction of lightning activity in North Western Venezuela: Large-scale versus local drivers

    Science.gov (United States)

    Muñoz, Á. G.; Díaz-Lobatón, J.; Chourio, X.; Stock, M. J.

    2016-05-01

    The Lake Maracaibo Basin in North Western Venezuela has the highest annual lightning rate of any place in the world (~ 200 fl km- 2 yr- 1), whose electrical discharges occasionally impact human and animal lives (e.g., cattle) and frequently affect economic activities like oil and natural gas exploitation. Lightning activity is so common in this region that it has a proper name: Catatumbo Lightning (plural). Although short-term lightning forecasts are now common in different parts of the world, to the best of the authors' knowledge, seasonal prediction of lightning activity is still non-existent. This research discusses the relative role of both large-scale and local climate drivers as modulators of lightning activity in the region, and presents a formal predictability study at seasonal scale. Analysis of the Catatumbo Lightning Regional Mode, defined in terms of the second Empirical Orthogonal Function of monthly Lightning Imaging Sensor (LIS-TRMM) and Optical Transient Detector (OTD) satellite data for North Western South America, permits the identification of potential predictors at seasonal scale via a Canonical Correlation Analysis. Lightning activity in North Western Venezuela responds to well defined sea-surface temperature patterns (e.g., El Niño-Southern Oscillation, Atlantic Meridional Mode) and changes in the low-level meridional wind field that are associated with the Inter-Tropical Convergence Zone migrations, the Caribbean Low Level Jet and tropical cyclone activity, but it is also linked to local drivers like convection triggered by the topographic configuration and the effect of the Maracaibo Basin Nocturnal Low Level Jet. The analysis indicates that at seasonal scale the relative contribution of the large-scale drivers is more important than the local (basin-wide) ones, due to the synoptic control imposed by the former. Furthermore, meridional CAPE transport at 925 mb is identified as the best potential predictor for lightning activity in the Lake

  18. Prediction of crack density and electrical resistance changes in indium tin oxide/polymer thin films under tensile loading

    KAUST Repository

    Mora Cordova, Angel; Khan, Kamran; El Sayed, Tamer

    2014-01-01

    We present unified predictions for the crack onset strain, evolution of crack density, and changes in electrical resistance in indium tin oxide/polymer thin films under tensile loading. We propose a damage mechanics model to quantify and predict

  19. Changes in vigorous physical activity and incident diabetes inmale runners

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Paul T.

    2007-04-30

    Health Study [11-19] is unique among population cohorts in its focus on the health impact of higher doses of vigorously intense physical activity (i.e., {ge} 6-fold metabolic rate). The study was specifically designed to evaluate the dose-response relationship between vigorous physical activity and health for intensities and durations that exceed current physical activity recommendations [20-22]. One specific hypothesis is whether changes in vigorous physical activity affect the risk for becoming diabetic. Although women were surveyed and followed-up, only 23 developed diabetes so there is limited statistical power to establish their significance. Our analyses of diabetes and vigorous exercise are therefore restricted to men. This paper relates running distance at baseline and at the end of follow-up to self-reported, physician diagnosed diabetes in vigorously active men who were generally lean and ostensibly at low diabetic risk The benefits of greater doses of more vigorous exercise are relevant to the 27% of U.S. women and 34% of U.S. men meet or exceed the more general exercise recommendations for health benefits [23]. Specific issues to be addressed are: (1) whether maintenance of the same level of vigorous exercise over time reduces the risk of incident diabetes in relation to the exercise dose; (2) whether men who decrease their activity increase their risk for becoming diabetic; and (3) whether end of follow-up running distances are more predictive of diabetes than baseline distances, suggesting a causal, acute effect. Elsewhere we have shown that greater body weight is related to a lack of vigorous exercise [12-14] and increases the risk for diabetes even among generally lean vigorously active men [11]. In runners, leanness may be due to the exercise or due to initially lean men choosing to run further [17]. Therefore we also test whether body weight mediates the effects of vigorous exercise on diabetes, and whether this may be due to self-selection.

  20. Prediction of active control of subsonic centrifugal compressor rotating stall

    Science.gov (United States)

    Lawless, Patrick B.; Fleeter, Sanford

    1993-01-01

    A mathematical model is developed to predict the suppression of rotating stall in a centrifugal compressor with a vaned diffuser. This model is based on the employment of a control vortical waveform generated upstream of the impeller inlet to damp weak potential disturbances that are the early stages of rotating stall. The control system is analyzed by matching the perturbation pressure in the compressor inlet and exit flow fields with a model for the unsteady behavior of the compressor. The model was effective at predicting the stalling behavior of the Purdue Low Speed Centrifugal Compressor for two distinctly different stall patterns. Predictions made for the effect of a controlled inlet vorticity wave on the stability of the compressor show that for minimum control wave magnitudes, on the order of the total inlet disturbance magnitude, significant damping of the instability can be achieved. For control waves of sufficient amplitude, the control phase angle appears to be the most important factor in maintaining a stable condition in the compressor.

  1. THE DEVELOPMENT AND USE OF A MODEL TO PREDICT SUSTAINABILITY OF CHANGE IN HEALTH CARE SETTINGS.

    Science.gov (United States)

    Molfenter, Todd; Ford, James H; Bhattacharya, Abhik

    2011-01-01

    Innovations adopted through organizational change initiatives are often not sustained leading to diminished quality, productivity, and consumer satisfaction. Research explaining variance in the use of adopted innovations in health care settings is sparse, suggesting the need for a theoretical model to guide research and practice. In this article, we describe the development of a hybrid conjoint decision theoretic model designed to predict the sustainability of organizational change in health care settings. An initial test of the model's predictive validity using expert scored hypothetic profiles resulted in an r-squared value of .77. The test of this model offers a theoretical base for future research on the sustainability of change in health care settings.

  2. Prediction of anticancer activity of aliphatic nitrosoureas using ...

    African Journals Online (AJOL)

    Design and development of new anticancer drugs with low toxicity is a very challenging task and computer aided methods are being increasingly used to solve this problem. In this study, we investigated the anticancer activity of aliphatic nitrosoureas using quantum chemical quantitative structure activity relation (QSAR) ...

  3. PASS-GP: Predictive active set selection for Gaussian processes

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2010-01-01

    available in GPs to make a common ranking for both active and inactive points, allowing points to be removed again from the active set. This is important for keeping the complexity down and at the same time focusing on points close to the decision boundary. We lend both theoretical and empirical support...

  4. Ideologically motivated activism: How activist groups influence corporate social change activities

    NARCIS (Netherlands)

    den Hond, F.; de Bakker, F.G.A.; Hickman, G. R.

    2010-01-01

    Using insights from the social movement literature and institutional change theory, we explore how activism influences corporate social change activities. As the responsibility for addressing a variety of social issues is transferred from the state to the private sector, activist groups increasingly

  5. Predictive analytics on evolving data streams anticipating and adapting to changes in known and unknown contexts

    NARCIS (Netherlands)

    Pechenizkiy, M.

    2015-01-01

    Ever increasing volumes of sensor readings, transactional records, web data and event logs call for next generation of big data mining technology providing effective and efficient tools for making use of the streaming data. Predictive analytics on data streams is actively studied in research

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

    Science.gov (United States)

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

    2015-07-24

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

  7. Life history and spatial traits predict extinction risk due to climate change

    Science.gov (United States)

    Pearson, Richard G.; Stanton, Jessica C.; Shoemaker, Kevin T.; Aiello-Lammens, Matthew E.; Ersts, Peter J.; Horning, Ned; Fordham, Damien A.; Raxworthy, Christopher J.; Ryu, Hae Yeong; McNees, Jason; Akçakaya, H. Reşit

    2014-03-01

    There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change based on the expectation that established assessments such as the IUCN Red List need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

  8. Cross-modal prediction changes the timing of conscious access during the motion-induced blindness.

    Science.gov (United States)

    Chang, Acer Y C; Kanai, Ryota; Seth, Anil K

    2015-01-01

    Despite accumulating evidence that perceptual predictions influence perceptual content, the relations between these predictions and conscious contents remain unclear, especially for cross-modal predictions. We examined whether predictions of visual events by auditory cues can facilitate conscious access to the visual stimuli. We trained participants to learn associations between auditory cues and colour changes. We then asked whether congruency between auditory cues and target colours would speed access to consciousness. We did this by rendering a visual target subjectively invisible using motion-induced blindness and then gradually changing its colour while presenting congruent or incongruent auditory cues. Results showed that the visual target gained access to consciousness faster in congruent than in incongruent trials; control experiments excluded potentially confounding effects of attention and motor response. The expectation effect was gradually established over blocks suggesting a role for extensive training. Overall, our findings show that predictions learned through cross-modal training can facilitate conscious access to visual stimuli. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. An Improved Optimal Slip Ratio Prediction considering Tyre Inflation Pressure Changes

    Directory of Open Access Journals (Sweden)

    Guoxing Li

    2015-01-01

    Full Text Available The prediction of optimal slip ratio is crucial to vehicle control systems. Many studies have verified there is a definitive impact of tyre pressure change on the optimal slip ratio. However, the existing method of optimal slip ratio prediction has not taken into account the influence of tyre pressure changes. By introducing a second-order factor, an improved optimal slip ratio prediction considering tyre inflation pressure is proposed in this paper. In order to verify and evaluate the performance of the improved prediction, a cosimulation platform is developed by using MATLAB/Simulink and CarSim software packages, achieving a comprehensive simulation study of vehicle braking performance cooperated with an ABS controller. The simulation results show that the braking distances and braking time under different tyre pressures and initial braking speeds are effectively shortened with the improved prediction of optimal slip ratio. When the tyre pressure is slightly lower than the nominal pressure, the difference of braking performances between original optimal slip ratio and improved optimal slip ratio is the most obvious.

  10. Adults' future time perspective predicts engagement in physical activity.

    Science.gov (United States)

    Stahl, Sarah T; Patrick, Julie Hicks

    2012-07-01

    Our aim was to examine how the relations among known predictors of physical activity, such as age, sex, and body mass index, interact with future time perspective (FTP) and perceived functional limitation to explain adults' engagement in physical activity. Self-report data from 226 adults (range 20-88 years) were collected to examine the hypothesis that a more expansive FTP is associated with engagement in physical activity. Results indicated a good fit of the data to the model χ(2) (4, N = 226) = 7.457, p = .14 and accounted for a moderate amount of variance in adults' physical activity (R(2) = 15.7). Specifically, results indicated that perceived functional limitation (β = -.140) and FTP (β = .162) were directly associated with physical activity. Age was indirectly associated with physical activity through its association with perceived functional limitation (β = -.264) and FTP (β = .541). Results indicate that FTP may play an important role in explaining engagement in health promoting behaviors across the life span. Researchers should consider additional constructs and perhaps adopt socioemotional selectivity theory when explaining adults' engagement in physical activity.

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

    Science.gov (United States)

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

    2018-04-30

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

  12. Get Active Orlando: changing the built environment to increase physical activity.

    Science.gov (United States)

    McCreedy, Malisa; Leslie, Jill G

    2009-12-01

    Active Living by Design's Get Active Orlando partnership (GAO) focused on downtown Orlando's Community Redevelopment Area, including the Parramore Heritage District, home to many low-income and ethnically diverse residents, including many seniors. The area had undergone substantial development, and GAO aimed to incorporate active living considerations into the city's changing landscape. Get Active Orlando conducted a baseline survey of all streets, sidewalks, and bicycle lanes in the project area and identified a sequence of plans and policies in which to incorporate changes identified in the assessment. To create more immediate opportunities for active living, the partnership initiated a senior walking program, a bicycle refurbishment and giveaway program, and community bicycle-riding events, and led a social-marketing campaign that emphasized simple lifestyle changes. Get Active Orlando influenced adoption of public policies supporting active living in Orlando, including the Downtown Transportation Plan, Streetscape Guidelines, Design Standards Review Checklist, and growth management policies. Establishment of the Mayor's Advisory Council on Active Living is testament to the heightened significance of active living in Orlando. Initial assessment data served as a strong platform for policy change. Creating connections across disciplines including land-use planning, transportation, public health, and economic development allowed GAO to secure substantial policy change to influence design of the built environment. Engaging community members, including youth, as leaders was an important factor in program success. The physical environment in Orlando's Community Redevelopment Area is beginning to change as a reflection of a new policy framework designed to support active living.

  13. A rapid method of predicting radiocaesium concentrations in sheep from activity levels in faeces

    International Nuclear Information System (INIS)

    McGee, E.J.; Synnott, H.J.; Colgan, P.A.; Keatinge, M.J.

    1994-01-01

    The use of faecal samples taken from sheep flocks as a means of predicting radiocaesium concentrations in live animals was studied. Radiocaesium levels in 1726 sheep from 29 flocks were measured using in vivo techniques and a single faecal sample taken from each flock was also analysed. A highly significant relationship was found to exist between mean flock activity and activity in the corresponding faecal samples. Least-square regression yielded a simple model for predicting mean flock radiocaesium concentrations based on activity levels in faecal samples. A similar analysis of flock maxima and activity levels in faeces provides an alternative model for predicting the expected within-flock maximum radiocaesium concentration. (Author)

  14. Predicting protein folding rate change upon point mutation using residue-level coevolutionary information.

    Science.gov (United States)

    Mallik, Saurav; Das, Smita; Kundu, Sudip

    2016-01-01

    Change in folding kinetics of globular proteins upon point mutation is crucial to a wide spectrum of biological research, such as protein misfolding, toxicity, and aggregations. Here we seek to address whether residue-level coevolutionary information of globular proteins can be informative to folding rate changes upon point mutations. Generating residue-level coevolutionary networks of globular proteins, we analyze three parameters: relative coevolution order (rCEO), network density (ND), and characteristic path length (CPL). A point mutation is considered to be equivalent to a node deletion of this network and respective percentage changes in rCEO, ND, CPL are found linearly correlated (0.84, 0.73, and -0.61, respectively) with experimental folding rate changes. The three parameters predict the folding rate change upon a point mutation with 0.031, 0.045, and 0.059 standard errors, respectively. © 2015 Wiley Periodicals, Inc.

  15. Physics-Based Predictions for Coherent Change Detection Using X-Band Synthetic Aperture Radar

    Directory of Open Access Journals (Sweden)

    Mark Preiss

    2005-12-01

    Full Text Available A theoretical model is developed to describe the interferometric coherency between pairs of SAR images of rough soil surfaces. The model is derived using a dyadic form for surface reflectivity in the Kirchhoff approximation. This permits the combination of Kirchhoff theory and spotlight synthetic aperture radar (SAR image formation theory. The resulting model is used to describe the interferometric coherency between pairs of SAR images of rough soil surfaces. The theoretical model is applied to SAR images formed before and after surface changes observed by a repeat-pass SAR system. The change in surface associated with a tyre track following vehicle passage is modelled and SAR coherency estimates are obtained. Predicted coherency distributions for both the change and no-change scenarios are used to estimate receiver operator curves for the detection of the changes using a high-resolution, X-band SAR system.

  16. Comparison of an Imaging Software and Manual Prediction of Soft Tissue Changes after Orthognathic Surgery

    Directory of Open Access Journals (Sweden)

    M. S. Ahmad Akhoundi

    2012-01-01

    Full Text Available Objective: Accurate prediction of the surgical outcome is important in treating dentofacial deformities. Visualized treatment objectives usually involve manual surgical simulation based on tracing of cephalometric radiographs. Recent technical advancements have led to the use of computer assisted imaging systems in treatment planning for orthognathic surgical cases. The purpose of this study was to examine and compare the ability and reliability of digitization using Dolphin Imaging Software with traditional manual techniques and to compare orthognathic prediction with actual outcomes.Materials and Methods: Forty patients consisting of 35 women and 5 men (32 class III and 8 class II with no previous surgery were evaluated by manual tracing and indirect digitization using Dolphin Imaging Software. Reliability of each method was assessed then the two techniques were compared using paired t test.Result: The nasal tip presented the least predicted error and higher reliability. The least accurate regions in vertical plane were subnasal and upper lip, and subnasal and pogonion in horizontal plane. There were no statistically significant differences between the predictions of groups with and without genioplasty.Conclusion: Computer-generated image prediction was suitable for patient education and communication. However, efforts are still needed to improve accuracy and reliability of the prediction program and to include changes in soft tissue tension and muscle strain.

  17. Using decadal climate prediction to characterize and manage changing drought and flood risks in Colorado

    Science.gov (United States)

    Lazrus, H.; Done, J.; Morss, R. E.

    2017-12-01

    A new branch of climate science, known as decadal prediction, seeks to predict the time-varying trajectory of climate over the next 3-30 years and not just the longer-term trends. Decadal predictions bring climate information into the time horizon of decision makers, particularly those tasked with managing water resources and floods whose master planning is often on the timescale of decades. Information from decadal predictions may help alleviate some aspects of vulnerability by helping to inform decisions that reduce drought and flood exposure and increase adaptive capacities including preparedness, response, and recovery. This presentation will highlight an interdisciplinary project - involving atmospheric and social scientists - on the development of decadal climate information and its use in decision making. The presentation will explore the skill and utility of decadal drought and flood prediction along Colorado's Front Range, an area experiencing rapid population growth and uncertain climate variability and climate change impacts. Innovative statistical and dynamical atmospheric modeling techniques explore the extent to which Colorado precipitation can be predicted on decadal scales using remote Pacific Ocean surface temperature patterns. Concurrently, stakeholder interviews with flood managers in Colorado are being used to explore the potential utility of decadal climate information. Combining the modeling results with results from the stakeholder interviews shows that while there is still significant uncertainty surrounding precipitation on decadal time scales, relevant and well communicated decadal information has potential to be useful for drought and flood management.

  18. Predicting CD4 count changes among patients on antiretroviral treatment: Application of data mining techniques.

    Science.gov (United States)

    Kebede, Mihiretu; Zegeye, Desalegn Tigabu; Zeleke, Berihun Megabiaw

    2017-12-01

    To monitor the progress of therapy and disease progression, periodic CD4 counts are required throughout the course of HIV/AIDS care and support. The demand for CD4 count measurement is increasing as ART programs expand over the last decade. This study aimed to predict CD4 count changes and to identify the predictors of CD4 count changes among patients on ART. A cross-sectional study was conducted at the University of Gondar Hospital from 3,104 adult patients on ART with CD4 counts measured at least twice (baseline and most recent). Data were retrieved from the HIV care clinic electronic database and patients` charts. Descriptive data were analyzed by SPSS version 20. Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology was followed to undertake the study. WEKA version 3.8 was used to conduct a predictive data mining. Before building the predictive data mining models, information gain values and correlation-based Feature Selection methods were used for attribute selection. Variables were ranked according to their relevance based on their information gain values. J48, Neural Network, and Random Forest algorithms were experimented to assess model accuracies. The median duration of ART was 191.5 weeks. The mean CD4 count change was 243 (SD 191.14) cells per microliter. Overall, 2427 (78.2%) patients had their CD4 counts increased by at least 100 cells per microliter, while 4% had a decline from the baseline CD4 value. Baseline variables including age, educational status, CD8 count, ART regimen, and hemoglobin levels predicted CD4 count changes with predictive accuracies of J48, Neural Network, and Random Forest being 87.1%, 83.5%, and 99.8%, respectively. Random Forest algorithm had a superior performance accuracy level than both J48 and Artificial Neural Network. The precision, sensitivity and recall values of Random Forest were also more than 99%. Nearly accurate prediction results were obtained using Random Forest algorithm. This algorithm could be

  19. Visual short term memory related brain activity predicts mathematical abilities.

    Science.gov (United States)

    Boulet-Craig, Aubrée; Robaey, Philippe; Lacourse, Karine; Jerbi, Karim; Oswald, Victor; Krajinovic, Maja; Laverdière, Caroline; Sinnett, Daniel; Jolicoeur, Pierre; Lippé, Sarah

    2017-07-01

    Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities are significantly related. Moreover, both processes activate similar brain regions within the parietal cortex, in particular, the intraparietal sulcus; however, it is still unclear whether the neuronal underpinnings of VSTM directly correlate with mathematical operation and reasoning abilities. The main objective was to investigate the association between parieto-occipital brain activity during the retention period of a VSTM task and performance in mathematics. The authors measured mathematical abilities and VSTM capacity as well as brain activity during memory maintenance using magnetoencephalography (MEG) in 19 healthy adult participants. Event-related magnetic fields (ERFs) were computed on the MEG data. Linear regressions were used to estimate the strength of the relation between VSTM related brain activity and mathematical abilities. The amplitude of parieto-occipital cerebral activity during the retention of visual information was related to performance in 2 standardized mathematical tasks: mathematical reasoning and calculation fluency. The findings show that brain activity during retention period of a VSTM task is associated with mathematical abilities. Contributions of VSTM processes to numerical cognition should be considered in cognitive interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  20. Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

    Science.gov (United States)

    Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

    2014-08-01

    Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Structure-based prediction of free energy changes of binding of PTP1B inhibitors

    Science.gov (United States)

    Wang, Jing; Ling Chan, Shek; Ramnarayan, Kal

    2003-08-01

    The goals were (1) to understand the driving forces in the binding of small molecule inhibitors to the active site of PTP1B and (2) to develop a molecular mechanics-based empirical free energy function for compound potency prediction. A set of compounds with known activities was docked onto the active site. The related energy components and molecular surface areas were calculated. The bridging water molecules were identified and their contributions were considered. Linear relationships were explored between the above terms and the binding free energies of compounds derived based on experimental inhibition constants. We found that minimally three terms are required to give rise to a good correlation (0.86) with predictive power in five-group cross-validation test (q2 = 0.70). The dominant terms are the electrostatic energy and non-electrostatic energy stemming from the intra- and intermolecular interactions of solutes and from those of bridging water molecules in complexes.

  2. Decline in physical activity during adolescence is not associated with changes in mental health

    Directory of Open Access Journals (Sweden)

    Martin L. Van Dijk

    2016-04-01

    Full Text Available Abstract Background The majority of studies investigating associations between physical activity and mental health in adolescents have been cross-sectional in design. Potential associations between physical activity and mental health may be better examined longitudinally as physical activity levels tend to decrease in adolescence. Few studies have investigated these associations longitudinally in adolescents and none by measuring physical activity objectively. Methods A total of 158 Dutch adolescents (mean age 13.6 years, 38.6 % boys, grades 7 and 9 at baseline participated in this longitudinal study. Physical activity, depressive symptoms and self-esteem were measured at baseline and at the 1-year follow-up. Physical activity was objectively measured with an ActivPAL3™ accelerometer during one full week. Depressive symptoms were measured with the Center for Epidemiologic Studies Depression Scale (CES-D and self-esteem was assessed with the Rosenberg Self-Esteem Scale (RSE. Results were analysed using structural equation modelling. Results Physical activity levels decreased 15.3 % over a 1-year period (p < .001, with significantly (p = .001 greater decreases during grade 7 (-20.7 % than during grade 9 (-5.0 %. Overall, depressive symptoms decreased (-12.1 %, p < .001 over a 1-year period, while self-esteem did not change significantly (+2.9 %, p = .066. Higher levels of depressive symptoms at baseline predicted a greater decline in depressive symptoms (β = -.51, p < .001 and higher levels of self-esteem at baseline predicted a smaller increase in self-esteem (β = -.48, p < .001. The decline in physical activity did not appear to predict any change in depressive symptoms and self-esteem. Conclusion The decline in physical activity over a 1-year period during adolescence is not associated with a change in mental health. Further studies in adolescents aiming to investigate whether a change in physical

  3. On the importance of paleoclimate modelling for improving predictions of future climate change

    Directory of Open Access Journals (Sweden)

    J. C. Hargreaves

    2009-12-01

    Full Text Available We use an ensemble of runs from the MIROC3.2 AGCM with slab-ocean to explore the extent to which mid-Holocene simulations are relevant to predictions of future climate change. The results are compared with similar analyses for the Last Glacial Maximum (LGM and pre-industrial control climate. We suggest that the paleoclimate epochs can provide some independent validation of the models that is also relevant for future predictions. Considering the paleoclimate epochs, we find that the stronger global forcing and hence larger climate change at the LGM makes this likely to be the more powerful one for estimating the large-scale changes that are anticipated due to anthropogenic forcing. The phenomena in the mid-Holocene simulations which are most strongly correlated with future changes (i.e., the mid to high northern latitude land temperature and monsoon precipitation do, however, coincide with areas where the LGM results are not correlated with future changes, and these are also areas where the paleodata indicate significant climate changes have occurred. Thus, these regions and phenomena for the mid-Holocene may be useful for model improvement and validation.

  4. Are climate-related changes to the character of global-mean precipitation predictable?

    International Nuclear Information System (INIS)

    Stephens, Graeme L; Hu, Yongxiang

    2010-01-01

    The physical basis for the change in global-mean precipitation projected to occur with the warming associated with increased greenhouse gases is discussed. The expected increases to column water vapor W control the rate of increase of global precipitation accumulation through its affect on the planet's energy balance. The key role played by changes to downward longwave radiation controlled by this changing water vapor is emphasized. The basic properties of molecular absorption by water vapor dictate that the fractional rate of increase of global-mean precipitation must be significantly less that the fractional rate of increase in water vapor and it is further argued that this reduced rate of precipitation increase implies that the timescale for water re-cycling is increased in the global mean. This further implies less frequent precipitation over a fixed period of time, and the intensity of these less frequent precipitating events must subsequently increase in the mean to realize the increased global accumulation. These changes to the character of global-mean precipitation, predictable consequences of equally predictable changes to W, apply only to the global-mean state and not to the regional or local scale changes in precipitation.

  5. Ensembles-based predictions of climate change impacts on bioclimatic zones in Northeast Asia

    Science.gov (United States)

    Choi, Y.; Jeon, S. W.; Lim, C. H.; Ryu, J.

    2017-12-01

    Biodiversity is rapidly declining globally and efforts are needed to mitigate this continually increasing loss of species. Clustering of areas with similar habitats can be used to prioritize protected areas and distribute resources for the conservation of species, selection of representative sample areas for research, and evaluation of impacts due to environmental changes. In this study, Northeast Asia (NEA) was classified into 14 bioclimatic zones using statistical techniques, which are correlation analysis and principal component analysis (PCA), and the iterative self-organizing data analysis technique algorithm (ISODATA). Based on these bioclimatic classification, we predicted shift of bioclimatic zones due to climate change. The input variables include the current climatic data (1960-1990) and the future climatic data of the HadGEM2-AO model (RCP 4.5(2050, 2070) and 8.5(2050, 2070)) provided by WorldClim. Using these data, multi-modeling methods including maximum likelihood classification, random forest, and species distribution modelling have been used to project the impact of climate change on the spatial distribution of bioclimatic zones within NEA. The results of various models were compared and analyzed by overlapping each result. As the result, significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward and some zones were predicted to disappear. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.

  6. Factors affecting perceived change in physical activity in pregnancy.

    Science.gov (United States)

    Merkx, Astrid; Ausems, Marlein; Budé, Luc; de Vries, Raymond; Nieuwenhuijze, Marianne J

    2017-08-01

    reduction of physical activity (PA) during pregnancy is common but undesirable, as it is associated with negative outcomes, including excessive gestational weight gain. Our objective was to explore changes in five types of activity that occurred during pregnancy and the behavioural determinants of the reported changes in PA. we performed a secondary analysis of a cross sectional survey that was constructed using the ASE-Model - an approach to identifying the factors that drive behaviour change that focuses on Attitude, Social influence, and self-Efficacy. 455 healthy pregnant women of all gestational ages, receiving prenatal care from midwifery practices in the Netherlands. more than half of our respondents reported a reduction in their PA during pregnancy. The largest reduction occurred in sports and brief rigorous activities, but other types of PA were reduced as well. Reduction of PA was more likely in women who considered themselves as active before pregnancy, women who experienced pregnancy-related barriers, women who were advised to reduce their PA, and multiparous women. Fewer than 5% increased their PA. Motivation to engage in PA was positively associated with enjoying PA. all pregnant women should be informed about the positive effects of staying active and should be encouraged to engage in, or to continue, moderately intensive activities like walking, biking or swimming. Our findings concerning the predictors of PA reduction can be used to develop an evidence-based intervention aimed at encouraging healthy PA during pregnancy. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Modelling changes to electricity demand load duration curves as a consequence of predicted climate change for Australia

    International Nuclear Information System (INIS)

    Thatcher, Marcus J.

    2007-01-01

    In this paper, we describe a method for constructing regional electricity demand data sets at 30 min intervals, which are consistent with climate change scenarios. Specifically, we modify a commonly used linear regression model between regional electricity demand and climate to also describe intraday variability in demand so that regional load duration curves (LDCs) can be predicted. The model is evaluated for four different Australian states that are participants in the Australian National Electricity Market (NEM) and the resultant data sets are found to reproduce each state's LDCs with reasonable accuracy. We also apply the demand model to CSIRO's Mk 3 global climate model data sets that have been downscaled to 60 km resolution using CSIRO's conformal-cubic atmospheric model to estimate how LDCs change as a consequence of a 1 C increase in the average temperature of Australian state capital cities. These regional electricity demand data sets are then useful for economic modelling of electricity markets such as the NEM. (author)

  8. Prediction of BMI by impulsivity, eating behavior and activity level

    Directory of Open Access Journals (Sweden)

    Jiang Xiaxia

    2016-01-01

    Full Text Available Objective: Discuss the relationship between the impulsivity, eating behavior and activity level and the body mass index (BMI. Method: Test 147 female college students with the impulsivity questionnaire (BIS-11 and BIS/BAS, Dutch Eating Behavior Questionnaire (DBEQ, Sitting Time Scale (STS and Exercising Time Scale (ETS. Results: (1 The correlation analysis indicates that BMI and impulsivity (r = 0.43 and 0.52 have a significant positive correlation with the sitting time (r = 0.61 and a significant negative correlation with the activity level (r= −0.49. (2 The path analysis indicates that the reward sensitivity directly affects BMI and indirectly affects BMI through the activity level as well; the eating behavior has an insignificantly direct impact on BMI, because its impact is generated by the intermediary role of induced diet. Conclusion: (1 The impulsivity, eating behavior and activity level are closely related to BMI; (2 the activity level, sitting time and induced diet play an intermediary role between the impulsivity and BMI.

  9. Physical activity and epilepsy: proven and predicted benefits.

    Science.gov (United States)

    Arida, Ricardo M; Cavalheiro, Esper A; da Silva, Antonio C; Scorza, Fulvio A

    2008-01-01

    Epilepsy is a common disease found in 2% of the population, affecting people from all ages. Unfortunately, persons with epilepsy have previously been discouraged from participation in physical activity and sports for fear of inducing seizures or increasing seizure frequency. Despite a shift in medical recommendations toward encouraging rather than restricting participation, the stigma remains and persons with epilepsy continue to be less active than the general population. For this purpose, clinical and experimental studies have analysed the effect of physical exercise on epilepsy. Although there are rare cases of exercise-induced seizures, studies have shown that physical activity can decrease seizure frequency, as well as lead to improved cardiovascular and psychological health in people with epilepsy. The majority of physical activities or sports are safe for people with epilepsy to participate in with special attention to adequate seizure control, close monitoring of medications, and preparation of family or trainers. The evidence shows that patients with good seizure control can participate in both contact and non-contact sports without harmfully affecting seizure frequency. This article reviews the risks and benefits of physical activity in people with epilepsy, discusses sports in which persons with epilepsy may participate, and describes the positive effect of physical exercise in experimental models of epilepsy.

  10. Biological Activity Predictions and Hydrogen Bonding Analysis in Quinolines

    Science.gov (United States)

    Gupta, Palvi; Kamni

    The paper has been designed to make a comprehensive review of a particular series of organic molecular assembly in the form of compendium. An overview of general description of fifteen quinoline derivatives has been given. The biological activity spectra of quinoline derivatives have been correlated on structure activity relationships base which provides the different Pa (possibility of activity) and Pi (possibility of inactivity) values. Expositions of the role of intermolecular interactions in the identified derivatives have been discussed with the standard distance and angle cut-off criteria criteria as proposed by Desiraju and Steiner (1999) in an International monogram on crystallography. Distance-angle scatter plots for intermolecular interactions are presented for a better understanding of the packing interactions which exist in quinoline derivatives.

  11. Predicting Child Physical Activity and Screen Time: Parental Support for Physical Activity and General Parenting Styles

    Science.gov (United States)

    Crain, A. Lauren; Senso, Meghan M.; Levy, Rona L.; Sherwood, Nancy E.

    2014-01-01

    Objective: To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Methods: Participants were children (6.9 ± 1.8 years) with a body mass index in the 70–95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Results: Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Conclusions: Parenting practices and styles should be considered jointly, offering implications for tailored interventions. PMID:24812256

  12. Predicting child physical activity and screen time: parental support for physical activity and general parenting styles.

    Science.gov (United States)

    Langer, Shelby L; Crain, A Lauren; Senso, Meghan M; Levy, Rona L; Sherwood, Nancy E

    2014-07-01

    To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Participants were children (6.9 ± 1.8 years) with a body mass index in the 70-95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Parenting practices and styles should be considered jointly, offering implications for tailored interventions. © The Author 2014. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  13. Social Networking Site Use Predicts Changes in Young Adults’ Psychological Adjustment

    Science.gov (United States)

    Szwedo, David E.; Mikami, Amori Yee; Allen, Joseph P.

    2012-01-01

    This study examined youths’ friendships and posted pictures on social networking sites as predictors of changes in their adjustment over time. Observational, self-report, and peer report data were obtained from a community sample of 89 young adults interviewed at age 21 and again at age 22. Findings were consistent with a leveling effect for online friendships, predicting decreases in internalizing symptoms for youth with lower initial levels of social acceptance, but increases in symptoms for youth with higher initial levels over the following year. Across the entire sample, deviant behavior in posted photos predicted increases in young adults’ problematic alcohol use over time. The importance of considering the interplay between online and offline social factors for predicting adjustment is discussed. PMID:23109797

  14. Associations between initial change in physical activity level and subsequent change in regional body fat distributions

    DEFF Research Database (Denmark)

    Ezekwe, Kelechi A; Adegboye, Amanda R A; Gamborg, Michael

    2013-01-01

    examination, while waist circumference (WC) and hip circumference (HC) were measured at both follow-ups. RESULTS: Among men, WC increased in the constant active group to a lesser extent than in the non-constant active group (3.4 vs. 4.1 cm; p = 0.03) concerning leisure time physical activities (LTPA......). A similar pattern was observed for both WC and HC in relation to occupational physical activities (OPA) (p = 0.02). Among women, the results went in the same direction for LTPA, whereas the associations with OPA were in the opposite direction (p = 0.001). CONCLUSION: LTPA and OPA were associated......BACKGROUND: Few studies have examined which lifestyle factors relate to the development of fat distribution. Therefore, the identification of the determinants of changes in fat deposition is highly relevant. METHODS: The association between the change in physical activity (PA) and the subsequent...

  15. Assessing debris flow activity in a changing climate : open access

    NARCIS (Netherlands)

    Turkington, T.; Remaitre, A.; Ettema, J.; Hussin, H.Y.; van Westen, C.J.

    2016-01-01

    Future trends in debris flow activity are constructed based on bias-corrected climate change projections using two meteorological proxies: daily precipitation and Convective Available Potential Energy (CAPE) combined with specific humidity for two Alpine areas. Along with a comparison between

  16. Changes in erythrocyte ATPase activity under different pathological ...

    African Journals Online (AJOL)

    Changes in erythrocyte ATPase activity under different pathological conditions. Ali A Kherd, Nawal Helmi, Khadijah Saeed Balamash, Taha A Kumosani, Shareefa A AL-Ghamdi, Qari M, Etimad A Huwait, Soonham S Yaghmoor, Alaama Nabil, Maryam A AL-Ghamdi, Said S Moselhy ...

  17. Videogames, Tools for Change: A Study Based on Activity Theory

    Science.gov (United States)

    Méndez, Laura; Lacasa, Pilar

    2015-01-01

    Introduction: The purpose of this study is to provide a framework for analysis from which to interpret the transformations that take place, as perceived by the participants, when commercial video games are used in the classroom. We will show how Activity Theory (AT) is able to explain and interpret these changes. Method: Case studies are…

  18. Weight gain, physical activity and dietary changes during the seven ...

    African Journals Online (AJOL)

    Objective: The objective of the study was to assess weight gain, physical activity and dietary changes during the first year of university life in Malawi. Setting: The setting was Bunda College of Agriculture, University of Malawi. Subjects: The subjects were first-year students (n = 47) enrolled for the 2008/2009 academic year.

  19. Spatial relationship between climatologies and changes in global vegetation activity.

    Science.gov (United States)

    de Jong, Rogier; Schaepman, Michael E; Furrer, Reinhard; de Bruin, Sytze; Verburg, Peter H

    2013-06-01

    Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land-cover and climate-related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature. However, little remains known about the processes underlying these changes at large spatial scales. In this study, we aimed at quantifying the spatial relationship between changes in potential climatic growth constraints (i.e. temperature, precipitation and incident solar radiation) and changes in vegetation activity (1982-2008). We demonstrate an additive spatial model with 0.5° resolution, consisting of a regression component representing climate-associated effects and a spatially correlated field representing the combined influence of other factors, including land-use change. Little over 50% of the spatial variance could be attributed to changes in climatologies; conspicuously, many greening trends and browning hotspots in Argentina and Australia. The nonassociated model component may contain large-scale human interventions, feedback mechanisms or natural effects, which were not captured by the climatologies. Browning hotspots in this component were especially found in subequatorial Africa. On the scale of land-cover types, strongest relationships between climatologies and vegetation activity were found in forests, including indications for browning under warming conditions (analogous to the divergence issue discussed in dendroclimatology). © 2013 Blackwell Publishing Ltd.

  20. Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing.

    Science.gov (United States)

    Tulabandhula, Theja; Rudin, Cynthia

    2014-06-01

    Our goal is to design a prediction and decision system for real-time use during a professional car race. In designing a knowledge discovery process for racing, we faced several challenges that were overcome only when domain knowledge of racing was carefully infused within statistical modeling techniques. In this article, we describe how we leveraged expert knowledge of the domain to produce a real-time decision system for tire changes within a race. Our forecasts have the potential to impact how racing teams can optimize strategy by making tire-change decisions to benefit their rank position. Our work significantly expands previous research on sports analytics, as it is the only work on analytical methods for within-race prediction and decision making for professional car racing.

  1. Prediction of Positions of Active Compounds Makes It Possible To Increase Activity in Fragment-Based Drug Development

    Directory of Open Access Journals (Sweden)

    Yoshifumi Fukunishi

    2011-05-01

    Full Text Available We have developed a computational method that predicts the positions of active compounds, making it possible to increase activity as a fragment evolution strategy. We refer to the positions of these compounds as the active position. When an active fragment compound is found, the following lead generation process is performed, primarily to increase activity. In the current method, to predict the location of the active position, hydrogen atoms are replaced by small side chains, generating virtual compounds. These virtual compounds are docked to a target protein, and the docking scores (affinities are examined. The hydrogen atom that gives the virtual compound with good affinity should correspond to the active position and it should be replaced to generate a lead compound. This method was found to work well, with the prediction of the active position being 2 times more efficient than random synthesis. In the current study, 15 examples of lead generation were examined. The probability of finding active positions among all hydrogen atoms was 26%, and the current method accurately predicted 60% of the active positions.

  2. Validity of predicting left ventricular end systolic pressure changes following an acute bout of exercise.

    Science.gov (United States)

    Kappus, Rebecca M; Ranadive, Sushant M; Yan, Huimin; Lane, Abbi D; Cook, Marc D; Hall, Grenita; Harvey, I Shevon; Wilund, Kenneth R; Woods, Jeffrey A; Fernhall, Bo

    2013-01-01

    Left ventricular end systolic pressure (LV ESP) is important in assessing left ventricular performance and is usually derived from prediction equations. It is unknown whether these equations are accurate at rest or following exercise in a young, healthy population. Measured LV ESP vs. LV ESP values from the prediction equations were compared at rest, 15 min and 30 min following peak aerobic exercise in 60 participants. LV ESP was obtained by applanation tonometry at rest, 15 min post and 30 min post peak cycle exercise. Measured LV ESP was significantly lower (p<0.05) at all time points in comparison to the two calculated values. Measured LV ESP decreased significantly from rest at both the post15 and post30 time points (p<0.05) and changed differently in comparison to the calculated values (significant interaction; p<0.05). The two LV ESP equations were also significantly different from each other (p<0.05) and changed differently over time (significant interaction; p<0.05). The two commonly used prediction equations did not accurately predict either resting or post exercise LV ESP in a young, healthy population. Thus, LV ESP needs to be individually determined in young, healthy participants. Non-invasive measurement through applanation tonometry appears to allow for a more accurate determination of LV ESP. Copyright © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  3. Transitioning to adolescence: how changes in child personality and overreactive parenting predict adolescent adjustment problems.

    Science.gov (United States)

    van den Akker, Alithe L; Deković, Maja; Prinzie, Peter

    2010-01-01

    The present study examined how changes in child Big Five personality characteristics and overreactive parenting during the transition from childhood to adolescence predict adolescent adjustment problems. The sample included 290 children, aged 8-9 years. At three moments, with 2-year intervals, mothers, fathers, and a teacher reported on the child's personality, and mothers and fathers reported on their parenting behavior. At the third measurement moment, mothers, fathers, and children reported on the child's adjustment problems. Rank-order stability of the personality dimensions and overreactive parenting were high. Univariate latent growth models revealed mean-level decreases for extraversion, conscientiousness, and imagination. Mean levels of benevolence, emotional stability, and overreactive parenting were stable. Multivariate latent growth models revealed that decreases in extraversion and emotional stability predicted internalizing problems, whereas decreases in benevolence, conscientiousness, and emotional stability predicted externalizing problems. Increases in overreactive parenting predicted externalizing, but not internalizing problems. The associations were similar for boys and girls. The results indicate that changes in child personality and overreactive parenting during the transition to adolescence are associated with adolescent adjustment problems. Overall, child personality was more important than overreactive parenting, and children were more likely to "act out" than to "withdraw" in reaction to overreactive parenting.

  4. Cross-Layer Active Predictive Congestion Control Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yinfeng Wu

    2009-10-01

    Full Text Available In wireless sensor networks (WSNs, there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node‟s neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  5. Cross-layer active predictive congestion control protocol for wireless sensor networks.

    Science.gov (United States)

    Wan, Jiangwen; Xu, Xiaofeng; Feng, Renjian; Wu, Yinfeng

    2009-01-01

    In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.

  6. Body-Related Shame and Guilt Predict Physical Activity in Breast Cancer Survivors Over Time.

    Science.gov (United States)

    Castonguay, Andrée L; Wrosch, Carsten; Pila, Eva; Sabiston, Catherine M

    2017-07-01

    To test body-related shame and guilt as predictors of breast cancer survivors' (BCS') moderate to vigorous intensity physical activity (MVPA) during six months and to examine motivational regulations as mediators of this association.
. Prospective study.
. Survivors were recruited through advertisements and oncologist referrals from medical clinics and hospitals in Montreal, Quebec, Canada.
. 149 female BCS.
. Self-reports of body-related shame and guilt, motivational regulations, and MVPA were measured among BCS at baseline. MVPA was assessed a second time six months later. Residual change scores were used.
. Body-related shame and guilt; external, introjected, and autonomous (identified and intrinsic) motivational regulations; MVPA.
. In the multiple mediation models, body-related shame was associated with low levels of MVPA, as well as external, introjected, and autonomous motivational regulations. Guilt was related to high levels of MVPA and introjected and autonomous motivational regulations. Indirect effects linked shame, guilt, and MVPA via autonomous motivation. Only body-related shame was a significant predictor of six-month changes in MVPA.
. Based on these results, the specific emotions of shame and guilt contextualized to the body differentially predict BCS' health motivations and behavior over time.
. Survivorship programs may benefit from integrating intervention strategies aimed at reducing body-related shame and helping women manage feelings of guilt to improve physical activity.

  7. Connectivity changes underlying neurofeedback training of visual cortex activity.

    Directory of Open Access Journals (Sweden)

    Frank Scharnowski

    Full Text Available Neurofeedback based on real-time functional magnetic resonance imaging (fMRI is a new approach that allows training of voluntary control over regionally specific brain activity. However, the neural basis of successful neurofeedback learning remains poorly understood. Here, we assessed changes in effective brain connectivity associated with neurofeedback training of visual cortex activity. Using dynamic causal modeling (DCM, we found that training participants to increase visual cortex activity was associated with increased effective connectivity between the visual cortex and the superior parietal lobe. Specifically, participants who learned to control activity in their visual cortex showed increased top-down control of the superior parietal lobe over the visual cortex, and at the same time reduced bottom-up processing. These results are consistent with efficient employment of top-down visual attention and imagery, which were the cognitive strategies used by participants to increase their visual cortex activity.

  8. Climate change impact on economical and industrial activities

    Science.gov (United States)

    Parey, Sylvie; Bernardara, Pietro; Donat, Markus G.

    2010-05-01

    Climate change is underway and even if mitigation measures are successfully implemented, societies will have to adapt to new climatic conditions in the near future and further. This session had been proposed to gather different studies dedicated to the climate change impact on some human activities, and discuss the possible ways of adaptation. Climate change is often presented in terms of global mean temperature evolutions, but what is important for adaptation concerns the local evolutions, and rather of the variability and extremes than of the mean of the involved meteorological parameters. In the session, studies and applications will be presented, covering different economical and industrial activities, such as energy production, (re-) insurance and risk assessment, water management or tourism.

  9. Tolerance and potential for adaptation of a Baltic Sea rockweed under predicted climate change conditions.

    Science.gov (United States)

    Rugiu, Luca; Manninen, Iita; Rothäusler, Eva; Jormalainen, Veijo

    2018-03-01

    Climate change is threating species' persistence worldwide. To predict species responses to climate change we need information not just on their environmental tolerance but also on its adaptive potential. We tested how the foundation species of rocky littoral habitats, Fucus vesiculosus, responds to combined hyposalinity and warming projected to the Baltic Sea by 2070-2099. We quantified responses of replicated populations originating from the entrance, central, and marginal Baltic regions. Using replicated individuals, we tested for the presence of within-population tolerance variation. Future conditions hampered growth and survival of the central and marginal populations whereas the entrance populations fared well. Further, both the among- and within-population variation in responses to climate change indicated existence of genetic variation in tolerance. Such standing genetic variation provides the raw material necessary for adaptation to a changing environment, which may eventually ensure the persistence of the species in the inner Baltic Sea. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Predicting the change of child’s behavior problems: sociodemographic and maternal parenting stress factors

    OpenAIRE

    Viduolienė, Evelina

    2013-01-01

    Purpose: evaluate 1) whether child’s externalizing problems increase or decrease within 12 months period; 2) the change of externalizing problems with respect to child gender and age, and 3) which maternal parenting stress factors and family sociodemographic characteristics can predict the increase and decrease of child’s externalizing problems. Design/methodology/approach: participants were evaluated 2 times (with the interval of 12 months) with the Parenting Stress Index (Abidin, 1990) and ...

  11. Evaluating Transcription Factor Activity Changes by Scoring Unexplained Target Genes in Expression Data.

    Directory of Open Access Journals (Sweden)

    Evi Berchtold

    Full Text Available Several methods predict activity changes of transcription factors (TFs from a given regulatory network and measured expression data. But available gene regulatory networks are incomplete and contain many condition-dependent regulations that are not relevant for the specific expression measurement. It is not known which combination of active TFs is needed to cause a change in the expression of a target gene. A method to systematically evaluate the inferred activity changes is missing. We present such an evaluation strategy that indicates for how many target genes the observed expression changes can be explained by a given set of active TFs. To overcome the problem that the exact combination of active TFs needed to activate a gene is typically not known, we assume a gene to be explained if there exists any combination for which the predicted active TFs can possibly explain the observed change of the gene. We introduce the i-score (inconsistency score, which quantifies how many genes could not be explained by the set of activity changes of TFs. We observe that, even for these minimal requirements, published methods yield many unexplained target genes, i.e. large i-scores. This holds for all methods and all expression datasets we evaluated. We provide new optimization methods to calculate the best possible (minimal i-score given the network and measured expression data. The evaluation of this optimized i-score on a large data compendium yields many unexplained target genes for almost every case. This indicates that currently available regulatory networks are still far from being complete. Both the presented Act-SAT and Act-A* methods produce optimal sets of TF activity changes, which can be used to investigate the difficult interplay of expression and network data. A web server and a command line tool to calculate our i-score and to find the active TFs associated with the minimal i-score is available from https://services.bio.ifi.lmu.de/i-score.

  12. Changing patterns of brain activation during maze learning.

    Science.gov (United States)

    Van Horn, J D; Gold, J M; Esposito, G; Ostrem, J L; Mattay, V; Weinberger, D R; Berman, K F

    1998-05-18

    Recent research has found that patterns of brain activation involving the frontal cortex during novel task performance change dramatically following practice and repeat performance. Evidence for differential left vs. right frontal lobe activation, respectively, during episodic memory encoding and retrieval has also been reported. To examine these potentially related issues regional cerebral blood flow (rCBF) was measured in 15 normal volunteers using positron emission tomography (PET) during the naive and practiced performance of a maze task paradigm. SPM analysis indicated a largely right-sided, frontal lobe activation during naive performance. Following training and practice, performance of the same maze task elicited a more posterior pattern of rCBF activation involving posterior cingulate and precuneus. The change in the pattern of rCBF activation between novel and practiced task conditions agrees with results found in previous studies using repeat task methodology, and indicates that the neural circuitry required for encoding novel task information differs from that required when the same task has become familiar and information is being recalled. The right-sided preponderance of activation during naive performance may relate to task novelty and the spatially-based nature of the stimuli, whereas posterior areas activated during repeat performance are those previously found to be associated with visuospatial memory recall. Activation of these areas, however, does not agree with previously reported findings of left-sided activation during verbal episodic memory encoding and right-sided activation during retrieval, suggesting different neural substrates for verbal and visuospatial processing within memory. Copyright 1998 Elsevier Science B.V.

  13. National Scale Prediction of Soil Carbon Sequestration under Scenarios of Climate Change

    Science.gov (United States)

    Izaurralde, R. C.; Thomson, A. M.; Potter, S. R.; Atwood, J. D.; Williams, J. R.

    2006-12-01

    Carbon sequestration in agricultural soils is gaining momentum as a tool to mitigate the rate of increase of atmospheric CO2. Researchers from the Pacific Northwest National Laboratory, Texas A&M University, and USDA-NRCS used the EPIC model to develop national-scale predictions of soil carbon sequestration with adoption of no till (NT) under scenarios of climate change. In its current form, the EPIC model simulates soil C changes resulting from heterotrophic respiration and wind / water erosion. Representative modeling units were created to capture the climate, soil, and management variability at the 8-digit hydrologic unit (USGS classification) watershed scale. The soils selected represented at least 70% of the variability within each watershed. This resulted in 7,540 representative modeling units for 1,412 watersheds. Each watershed was assigned a major crop system: corn, soybean, spring wheat, winter wheat, cotton, hay, alfalfa, corn-soybean rotation or wheat-fallow rotation based on information from the National Resource Inventory. Each representative farm was simulated with conventional tillage and no tillage, and with and without irrigation. Climate change scenarios for two future periods (2015-2045 and 2045-2075) were selected from GCM model runs using the IPCC SRES scenarios of A2 and B2 from the UK Hadley Center (HadCM3) and US DOE PCM (PCM) models. Changes in mean and standard deviation of monthly temperature and precipitation were extracted from gridded files and applied to baseline climate (1960-1990) for each of the 1,412 modeled watersheds. Modeled crop yields were validated against historical USDA NASS county yields (1960-1990). The HadCM3 model predicted the most severe changes in climate parameters. Overall, there would be little difference between the A2 and B2 scenarios. Carbon offsets were calculated as the difference in soil C change between conventional and no till. Overall, C offsets during the first 30-y period (513 Tg C) are predicted to

  14. Individual differences in decision making and reward processing predict changes in cannabis use: a prospective functional magnetic resonance imaging study.

    Science.gov (United States)

    Cousijn, Janna; Wiers, Reinout W; Ridderinkhof, K Richard; van den Brink, Wim; Veltman, Dick J; Porrino, Linda J; Goudriaan, Anna E

    2013-11-01

    Decision-making deficits are thought to play an important role in the development and persistence of substance use disorders. Individual differences in decision-making abilities and their underlying neurocircuitry may, therefore, constitute an important predictor for the course of substance use and the development of substance use disorders. Here, we investigate the predictive value of decision making and neural mechanisms underlying decision making for future cannabis use and problem severity in a sample of heavy cannabis users. Brain activity during a monetary decision-making task (Iowa gambling task) was compared between 32 heavy cannabis users and 41 matched non-using controls using functional magnetic resonance imaging. In addition, within the group of heavy cannabis users, associations were examined between task-related brain activations, cannabis use and cannabis use-related problems at baseline, and change in cannabis use and problem severity after a 6-month follow-up. Despite normal task performance, heavy cannabis users compared with controls showed higher activation during wins in core areas associated with decision making. Moreover, within the group of heavy cannabis users, win-related activity and activity anticipating loss outcomes in areas generally involved in executive functions predicted change in cannabis use after 6 months. These findings are consistent with previous studies and point to abnormal processing of motivational information in heavy cannabis users. A new finding is that individuals who are biased toward immediate rewards have a higher probability of increasing drug use, highlighting the importance of the relative balance between motivational processes and regulatory executive processes in the development of substance use disorders. © 2012 The Authors, Addiction Biology © 2012 Society for the Study of Addiction.

  15. Healthy work revisited: do changes in time strain predict well-being?

    Science.gov (United States)

    Moen, Phyllis; Kelly, Erin L; Lam, Jack

    2013-04-01

    Building on Karasek and Theorell (R. Karasek & T. Theorell, 1990, Healthy work: Stress, productivity, and the reconstruction of working life, New York, NY: Basic Books), we theorized and tested the relationship between time strain (work-time demands and control) and seven self-reported health outcomes. We drew on survey data from 550 employees fielded before and 6 months after the implementation of an organizational intervention, the results only work environment (ROWE) in a white-collar organization. Cross-sectional (wave 1) models showed psychological time demands and time control measures were related to health outcomes in expected directions. The ROWE intervention did not predict changes in psychological time demands by wave 2, but did predict increased time control (a sense of time adequacy and schedule control). Statistical models revealed increases in psychological time demands and time adequacy predicted changes in positive (energy, mastery, psychological well-being, self-assessed health) and negative (emotional exhaustion, somatic symptoms, psychological distress) outcomes in expected directions, net of job and home demands and covariates. This study demonstrates the value of including time strain in investigations of the health effects of job conditions. Results encourage longitudinal models of change in psychological time demands as well as time control, along with the development and testing of interventions aimed at reducing time strain in different populations of workers.

  16. Predicting short-term weight loss using four leading health behavior change theories

    Directory of Open Access Journals (Sweden)

    Barata José T

    2007-04-01

    Full Text Available Abstract Background This study was conceived to analyze how exercise and weight management psychosocial variables, derived from several health behavior change theories, predict weight change in a short-term intervention. The theories under analysis were the Social Cognitive Theory, the Transtheoretical Model, the Theory of Planned Behavior, and Self-Determination Theory. Methods Subjects were 142 overweight and obese women (BMI = 30.2 ± 3.7 kg/m2; age = 38.3 ± 5.8y, participating in a 16-week University-based weight control program. Body weight and a comprehensive psychometric battery were assessed at baseline and at program's end. Results Weight decreased significantly (-3.6 ± 3.4%, p Conclusion The present models were able to predict 20–30% of variance in short-term weight loss and changes in weight management self-efficacy accounted for a large share of the predictive power. As expected from previous studies, exercise variables were only moderately associated with short-term outcomes; they are expected to play a larger explanatory role in longer-term results.

  17. Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China

    Directory of Open Access Journals (Sweden)

    Huiran Han

    2015-04-01

    Full Text Available Land use and land cover (LULC models are essential for analyzing LULC change and predicting land use requirements and are valuable for guiding reasonable land use planning and management. However, each LULC model has its own advantages and constraints. In this paper, we explore the characteristics of LULC change and simulate future land use demand by combining a CLUE-S model with a Markov model to deal with some shortcomings of existing LULC models. Using Beijing as a case study, we describe the related driving factors from land-adaptive variables, regional spatial variables and socio-economic variables and then simulate future land use scenarios from 2010 to 2020, which include a development scenario (natural development and rapid development and protection scenarios (ecological and cultivated land protection. The results indicate good consistency between predicted results and actual land use situations according to a Kappa statistic. The conversion of cultivated land to urban built-up land will form the primary features of LULC change in the future. The prediction for land use demand shows the differences under different scenarios. At higher elevations, the geographical environment limits the expansion of urban built-up land, but the conversion of cultivated land to built-up land in mountainous areas will be more prevalent by 2020; Beijing, however, still faces the most pressure in terms of ecological and cultivated land protection.

  18. Comparison of clinical utility between diaphragm excursion and thickening change using ultrasonography to predict extubation success

    Science.gov (United States)

    Yoo, Jung-Wan; Lee, Seung Jun; Lee, Jong Deog; Kim, Ho Cheol

    2018-01-01

    Background/Aims Both diaphragmatic excursion and change in muscle thickening are measured using ultrasonography (US) to assess diaphragm function and mechanical ventilation weaning outcomes. However, which parameter can better predict successful extubation remains to be determined. The aim of this study was to compare the clinical utility of these two diaphragmatic parameters to predict extubation success. Methods This study included patients subjected to extubation trial in the medical or surgical intensive care unit of a university-affiliated hospital from May 2015 through February 2016. Diaphragm excursion and percent of thickening change (Δtdi%) were measured using US within 24 hours before extubation. Results Sixty patients were included, and 78.3% (47/60) of these patients were successfully extubated, whereas 21.7% (13/60) were not. The median degree of excursion was greater in patients with extubation success than in those with extubation failure (1.65 cm vs. 0.8 cm, p success had a greater Δtdi% than those with extubation failure (42.1% vs. 22.5%, p = 0.03). The areas under the receiver operating curve for excursion and Δtdi% were 0.836 (95% confidence interval [CI], 0.717 to 0.919) and 0.698 (95% CI, 0.566 to 0.810), respectively (p = 0.017). Conclusions Diaphragm excursion seems more accurate than a change in the diaphragm thickness to predict extubation success. PMID:29050461

  19. Application of Artificial Neural Network to Predict Colour Change, Shrinkage and Texture of Osmotically Dehydrated Pumpkin

    Science.gov (United States)

    Tang, S. Y.; Lee, J. S.; Loh, S. P.; Tham, H. J.

    2017-06-01

    The objectives of this study were to use Artificial Neural Network (ANN) to predict colour change, shrinkage and texture of osmotically dehydrated pumpkin slices. The effects of process variables such as concentration of osmotic solution, immersion temperature and immersion time on the above mentioned physical properties were studied. The colour of the samples was measured using a colorimeter and the net colour difference changes, ΔE were determined. The texture was measured in terms of hardness by using a Texture Analyzer. As for the shrinkage, displacement of volume method was applied and percentage of shrinkage was obtained in terms of volume changes. A feed-forward backpropagation network with sigmoidal function was developed and best network configuration was chosen based on the highest correlation coefficients between the experimental values versus predicted values. As a comparison, Response Surface Methodology (RSM) statistical analysis was also employed. The performances of both RSM and ANN modelling were evaluated based on absolute average deviation (AAD), correlation of determination (R2) and root mean square error (RMSE). The results showed that ANN has higher prediction capability as compared to RSM. The relative importance of the variables on the physical properties were also determined by using connection weight approach in ANN. It was found that solution concentration showed the highest influence on all three physical properties.

  20. Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J. [Iowa State Univ., Ames, IA (United States)

    2017-12-28

    This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASM can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes

  1. Prediction of changes in memory performance by plasma homovanillic acid levels in clozapine-treated patients with schizophrenia.

    Science.gov (United States)

    Sumiyoshi, Tomiki; Roy, A; Kim, C-H; Jayathilake, K; Lee, M A; Sumiyoshi, C; Meltzer, H Y

    2004-12-01

    Cognitive dysfunction in schizophrenia has been demonstrated to be dependent, in part, on dopaminergic activity. Clozapine has been found to improve some domains of cognition, including verbal memory, in patients with schizophrenia. This study tested the hypothesis that plasma homovanillic acid (pHVA) levels, a peripheral measure of central dopaminergic activity, would predict the change in memory performance in patients with schizophrenia treated with clozapine. Twenty-seven male patients with schizophrenia received clozapine treatment for 6 weeks. Verbal list learning (VLL)-Delayed Recall (VLL-DR), a test of secondary verbal memory, was administered before and after clozapine treatment. Blood samples to measure pHVA levels were collected at baseline. Baseline pHVA levels were negatively correlated with change in performance on VLL-DR; the lower baseline pHVA level was associated with greater improvement in performance on VLL-DR during treatment with clozapine. Baseline pHVA levels in subjects who showed improvement in verbal memory during clozapine treatment ( n=13) were significantly lower than those in subjects whose memory performance did not improve ( n=14). The results of this study indicate that baseline pHVA levels predict the ability of clozapine to improve memory performance in patients with schizophrenia.

  2. Analysis and prediction of daily physical activity level data using autoregressive integrated moving average models

    NARCIS (Netherlands)

    Long, Xi; Pauws, S.C.; Pijl, M.; Lacroix, J.; Goris, A.H.C.; Aarts, R.M.

    2009-01-01

    Results are provided on predicting daily physical activity level (PAL) data from past data of participants of a physical activity lifestyle program aimed at promoting a healthier lifestyle consisting of more physical exercise. The PAL data quantifies the level of a person’s daily physical activity

  3. Has growth mixture modeling improved our understanding of how early change predicts psychotherapy outcome?

    Science.gov (United States)

    Koffmann, Andrew

    2017-03-02

    Early change in psychotherapy predicts outcome. Seven studies have used growth mixture modeling [GMM; Muthén, B. (2001). Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class-latent growth modeling. In L. M. Collins & A. G. Sawyers (Eds.), New methods for the analysis of change (pp. 291-322). Washington, DC: American Psychological Association] to identify patient classes based on early change but have yielded conflicting results. Here, we review the earlier studies and apply GMM to a new data set. In a university-based training clinic, 251 patients were administered the Outcome Questionnaire-45 [Lambert, M. J., Hansen, N. B., Umphress, V., Lunnen, K., Okiishi, J., Burlingame, G., … Reisinger, C. W. (1996). Administration and scoring manual for the Outcome Questionnaire (OQ 45.2). Wilmington, DE: American Professional Credentialing Services] at each psychotherapy session. We used GMM to identify class structure based on change in the first six sessions and examined trajectories as predictors of outcome. The sample was best described as a single class. There was no evidence of autoregressive trends in the data. We achieved better fit to the data by permitting latent variables some degree of kurtosis, rather than to assume multivariate normality. Treatment outcome was predicted by the amount of early improvement, regardless of initial level of distress. The presence of sudden early gains or losses did not further improve outcome prediction. Early improvement is an easily computed, powerful predictor of psychotherapy outcome. The use of GMM to investigate the relationship between change and outcome is technically complex and computationally intensive. To date, it has not been particularly informative.

  4. Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions.

    Science.gov (United States)

    Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudrot, Lydia; Zarnetske, Phoebe; Belmaker, Jonathan; Gerstner, Beth

    2018-01-01

    There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species' responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. We systematically reviewed SDM studies published from 2003-2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis.

  5. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    Energy Technology Data Exchange (ETDEWEB)

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A [Duke University Medical Center, Durham, NC (United States); Ge, Y [University of North Carolina at Charlotte, Charlotte, NC (United States)

    2014-06-15

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

  6. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    International Nuclear Information System (INIS)

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

    2014-01-01

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

  7. Early prediction of outcome of activities of daily living after stroke: a systematic review

    OpenAIRE

    Veerbeek, J.M.; Kwakkel, G.; Wegen, van, E.E.H.; Ket, J.C.F.; Heijmans, M.W.

    2011-01-01

    BACKGROUND AND PURPOSE-Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables that are predictive or not predictive for outcome of ADL after stroke. METHODS-PubMed, Ebsco/Cinahl and Embase were systematically searched for prognostic studies in which stroke patients were inclu...

  8. Associations between initial change in physical activity level and subsequent change in regional body fat distributions.

    Science.gov (United States)

    Ezekwe, Kelechi A; Adegboye, Amanda R A; Gamborg, Michael; Heitmann, Berit L

    2013-01-01

    Few studies have examined which lifestyle factors relate to the development of fat distribution. Therefore, the identification of the determinants of changes in fat deposition is highly relevant. The association between the change in physical activity (PA) and the subsequent changes in regional body fat distributions was examined. In total, 1,236 men and 1,201 women were included at baseline and participated in the Danish MONICA (MONItoring Trends and Determinants in CArdiovascular Disease) study. A questionnaire was used to assess PA at 5 and 11 years after baseline examination, while waist circumference (WC) and hip circumference (HC) were measured at both follow-ups. Among men, WC increased in the constant active group to a lesser extent than in the non-constant active group (3.4 vs. 4.1 cm; p = 0.03) concerning leisure time physical activities (LTPA). A similar pattern was observed for both WC and HC in relation to occupational physical activities (OPA) (p = 0.02). Among women, the results went in the same direction for LTPA, whereas the associations with OPA were in the opposite direction (p = 0.001). LTPA and OPA were associated with reduced subsequent 6-year changes in regional fat distribution for men. For women, no associations were observed in relation to WC; however, OPA seemed to increase HC among women. © 2013 S. Karger GmbH, Freiburg.

  9. CHANGES IN QUADRICEPS MUSCLE ACTIVITY DURING SUSTAINED RECREATIONAL ALPINE SKIING

    Directory of Open Access Journals (Sweden)

    Josef Kröll

    2011-03-01

    Full Text Available During a day of skiing thousands of repeated contractions take place. Previous research on prolonged recreational alpine skiing show that physiological changes occur and hence some level of fatigue is inevitable. In the present paper the effect of prolonged skiing on the recruitment and coordination of the muscle activity was investigated. Six subjects performed 24 standardized runs. Muscle activity during the first two (PREskiing and the last two (POSTskiing runs was measured from the vastus lateralis (VL and rectus femoris (RF using EMG and quantified using wavelet and principal component analysis. The frequency content of the EMG signal shifted in seven out of eight cases significantly towards lower frequencies with highest effects observed for RF on outside leg. A significant pronounced outside leg loading occurred during POSTskiing and the timing of muscle activity peaks occurred more towards turn completion. Specific EMG frequency changes were observed at certain time points throughout the time windows and not over the whole double turn. It is suggested that general muscular fatigue, where additional specific muscle fibers have to be recruited due to the reduced power output of other fibers did not occur. The EMG frequency decrease and intensity changes for RF and VL are caused by altered timing (coordination within the turn towards a most likely more uncontrolled skiing technique. Hence, these data provide evidence to suggest recreational skiers alter their skiing technique before a potential change in muscle fiber recruitment occurs

  10. Do symptom-specific stages of change predict eating disorder treatment outcome?

    Science.gov (United States)

    Ackard, Diann M; Cronemeyer, Catherine L; Richter, Sara; Egan, Amber

    2015-03-01

    Interview methods to assess stages of change (SOC) in eating disorders (ED) indicate that SOC are positively correlated with symptom improvement over time. However, interviews require significant time and staff training and global measures of SOC do not capture varying levels of motivation across ED symptoms. This study used a self-report, ED symptom-specific SOC measure to determine prevalence of stages across symptoms and identify if SOC predict treatment outcome. Participants [N = 182; age 13-58 years; 92% Caucasian; 96% female; average BMI 21.7 (SD = 5.9); 50% ED not otherwise specified (EDNOS), 30.8% bulimia nervosa (BN), 19.2% anorexia nervosa (AN)] seeking ED treatment at a diverse-milieu multi-disciplinary facility in the United States completed stages of change, behavioral (ED symptom use and frequency) and psychological (ED concerns, anxiety, depression) measures at intake assessment and at 3, 6 and 12 months thereafter. Descriptive summaries were generated using ANOVA or Kruskal-Wallis (continuous) and χ (2) (categorical) tests. Repeated measures linear regression models with autoregressive correlation structure predicted treatment outcome. At intake assessment, 53.3% of AN, 34.0% of BN and 18.1% of EDNOS patients were in Preparation/Action. Readiness to change specific symptoms was highest for binge-eating (57.8%) and vomiting (56.5%). Frequency of fasting and restricting behaviors, and scores on all eating disorder and psychological measures improved over time regardless of SOC at intake assessment. Symptom-specific SOC did not predict reductions in ED symptom frequency. Overall SOC predicted neither improvement in Eating Disorder Examination Questionnaire (EDE-Q) scores nor reduction in depression or trait anxiety; however, higher overall SOC predicted lower state anxiety across follow-up. Readiness to change ED behaviors varies considerably. Most patients reduced eating disorder behaviors and increased psychological functioning regardless of stages

  11. Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches.

    Science.gov (United States)

    Memarian, Negar; Torre, Jared B; Haltom, Kate E; Stanton, Annette L; Lieberman, Matthew D

    2017-09-01

    Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. © The Author (2017). Published by Oxford University Press.

  12. The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems

    Directory of Open Access Journals (Sweden)

    Wilfredo Blanco

    2017-09-01

    Full Text Available Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the “intermediate neurons.” We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes

  13. When activation changes, what else changes? the relationship between change in patient activation measure (PAM) and employees' health status and health behaviors.

    Science.gov (United States)

    Harvey, Lisa; Fowles, Jinnet Briggs; Xi, Min; Terry, Paul

    2012-08-01

    To test whether changes in the patient activation measure (PAM) are related to changes in health status and healthy behaviors. Data for this secondary analysis were taken from a group-randomized, controlled trial comparing a traditional health promotion program for employees with an activated consumer program and a control program. The study population included 320 employees (with and without chronic disease) from two U.S. companies: a large, integrated health care system and a national airline. Survey and biometric data were collected in Spring 2005 (baseline) and Spring 2007 (follow-up). Change in PAM was associated with changes in health behaviors at every level (1-4), especially at level 4. Changes related to overall risk score and many of its components: aerobic exercise, safety, cancer risk, stress and mental health. Other changes included frequency of eating breakfast and the likelihood of knowing about health plans and how they compare. Level 4 of patient activation is not an end-point. People are capable of continuing to make significant change within this level. Interventions should be designed to encourage movement from lower to higher levels of activation. Even people at the most activated level improve health behaviors. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  14. Tools for Consumer Rights Protection in the Prediction of Electronic Virtual Market and Technological Changes

    Directory of Open Access Journals (Sweden)

    Mikuláš Gangur

    2014-05-01

    Full Text Available Electronic virtual markets can serve as an alternative tool for collecting information that is spread among numerous experts. This is the principal market functionality from the operators’ point of view. On the other hand it is profits that are the main interest of the market participants. What they expect from the market is liquidity as high as possible and the opportunity for unrestricted trading. Both the operator and the electronic market participant can be considered consumers of this particular market with reference to the requirements for the accuracy of its outputs but also for the market liquidity. Both the above mentioned groups of consumers (the operators and the participants themselves expect protection of their specific consumer rights, i.e. securing the two above mentioned functionalities of the market. These functionalities of the electronic market are, however, influenced by many factors, among others by participants’ activity. The article deals with the motivation tools that may improve the quality of the prediction market. In the prediction electronic virtual market there may be situations in which the commonly used tools for increasing business activities described in the published literature are not significantly effective. For such situations we suggest a new type of motivation incentive consisting in penalizing the individual market participants whose funds are not placed in the market. The functionality of the proposed motivation incentive is presented on the example of the existing data gained from the electronic virtual prediction market which is actively operated.

  15. The importance of biotic factors in predicting global change effects on decomposition of temperate forest leaf litter.

    Science.gov (United States)

    Rouifed, Soraya; Handa, I Tanya; David, Jean-François; Hättenschwiler, Stephan

    2010-05-01

    Increasing atmospheric CO(2) and temperature are predicted to alter litter decomposition via changes in litter chemistry and environmental conditions. The extent to which these predictions are influenced by biotic factors such as litter species composition or decomposer activity, and in particular how these different factors interact, is not well understood. In a 5-week laboratory experiment we compared the decomposition of leaf litter from four temperate tree species (Fagus sylvatica, Quercus petraea, Carpinus betulus and Tilia platyphyllos) in response to four interacting factors: elevated CO(2)-induced changes in litter quality, a 3 degrees C warmer environment during decomposition, changes in litter species composition, and presence/absence of a litter-feeding millipede (Glomeris marginata). Elevated CO(2) and temperature had much weaker effects on decomposition than litter species composition and the presence of Glomeris. Mass loss of elevated CO(2)-grown leaf litter was reduced in Fagus and increased in Fagus/Tilia mixtures, but was not affected in any other leaf litter treatment. Warming increased litter mass loss in Carpinus and Tilia, but not in the other two litter species and in none of the mixtures. The CO(2)- and temperature-related differences in decomposition disappeared completely when Glomeris was present. Overall, fauna activity stimulated litter mass loss, but to different degrees depending on litter species composition, with a particularly strong effect on Fagus/Tilia mixtures (+58%). Higher fauna-driven mass loss was not followed by higher C mineralization over the relatively short experimental period. Apart from a strong interaction between litter species composition and fauna, the tested factors had little or no interactive effects on decomposition. We conclude that if global change were to result in substantial shifts in plant community composition and macrofauna abundance in forest ecosystems, these interacting biotic factors could have

  16. Microgravity change as a precursor to volcanic activity

    Science.gov (United States)

    Rymer, Hazel

    1994-07-01

    In recent decades, systematic microgravity studies over some 20 active volcanoes in Central America, Iceland, Italy, Japan, Papua New Guinea and the USA have provided valuable data on sub-surface mass redistribution associated with volcanic activity. Concurrent data on ground deformation are essential to the unambiguous interpretation of gravity changes. In some instances, gravity and elevation vary along the free-air or Bouguer gradients, implying that there has been no sub-surface mass or density change, respectively. Where there are residual gravity changes after correction for elevation changes, magma movements in sub-surface chambers, feeder systems, vents and fissures (dykes) or water table variations are proposed. Although detailed interpretations depend on local circumstances and the calculations depend on source geometry, in general, the smallest residual gravity changes are associated with eruptions from volatile-poor basaltic vents and at extensional rift zones, whereas the highest residual values occur at explosive, subduction-related stratocones built from volatile-rich andesitic magma. The most intriguing, yet difficult, data to interpret derive from large-volume, infrequently erupting volcanic systems where caldera unrest is now becoming well documented and the ultimate hazards are most severe. Mass increases during inflation followed by limited mass loss during subsequent deflation typify these structures.

  17. Predicting the initial freezing point and water activity of meat products from composition data

    NARCIS (Netherlands)

    Sman, van der R.G.M.; Boer, E.P.J.

    2005-01-01

    In this paper we predict the water activity and initial freezing point of food products (meat and fish) based on their composition. The prediction is based on thermodynamics (the Clausius-Clapeyron equation, the Ross equation and an approximation of the Pitzer equation). Furthermore, we have taken

  18. Using Social Cognitive Theory to Predict Physical Activity and Fitness in Underserved Middle School Children

    Science.gov (United States)

    Martin, Jeffrey J.; McCaughtry, Nate; Flory, Sara; Murphy, Anne; Wisdom, Kimberlydawn

    2011-01-01

    Few researchers have used social cognitive theory and environment-based constructs to predict physical activity (PA) and fitness in underserved middle-school children. Hence, we evaluated social cognitive variables and perceptions of the school environment to predict PA and fitness in middle school children (N = 506, ages 10-14 years). Using…

  19. Workplace exercise for changing health behavior related to physical activity.

    Science.gov (United States)

    Grande, Antonio José; Cieslak, Fabrício; Silva, Valter

    2015-01-01

    Physical Activity in the workplace has received special attention from researchers who are looking to promote lifelong health and well-being. The workplace is being investigated as a possible place to assess and create strategies to help people to become healthier. The transtheoretical model and stages of change has been adapted as a tool to assess the stages of behavioral change towards exercising. To assess the change in health behavior following a three-month exercise program based in the workplace. A quasi-experimental study design was used in which 165 employees participated in the study. An intervention program of workplace exercise was applied for three months. Participants were assessed through the transtheoretical model and stages of change questionnaire before and after intervention to understand changes in their position on the behavioral change continuum. The number of employees who were physically active increased after the workplace exercise intervention (13.9% , 95% CI 9.5 to 20.1; P = 0.009). There was a significant decrease in the proportion of employees in the pre-contemplation stage (-6.1% , 95% CI 3.3 to 10.8; P = 0.045) and contemplation stage (-11.5% , 95% CI 7.5 to 17.3; P = 0.017), and a significant increase in the action stage (10.9% , 95% CI 7.0 to 16.6; P = 0.003). Engaging in workplace exercise has a significant positive effect on health behavior and willingness to become more physically active.

  20. Changes in event-related potential functional networks predict traumatic brain injury in piglets.

    Science.gov (United States)

    Atlan, Lorre S; Lan, Ingrid S; Smith, Colin; Margulies, Susan S

    2018-06-01

    Traumatic brain injury is a leading cause of cognitive and behavioral deficits in children in the US each year. None of the current diagnostic tools, such as quantitative cognitive and balance tests, have been validated to identify mild traumatic brain injury in infants, adults and animals. In this preliminary study, we report a novel, quantitative tool that has the potential to quickly and reliably diagnose traumatic brain injury and which can track the state of the brain during recovery across multiple ages and species. Using 32 scalp electrodes, we recorded involuntary auditory event-related potentials from 22 awake four-week-old piglets one day before and one, four, and seven days after two different injury types (diffuse and focal) or sham. From these recordings, we generated event-related potential functional networks and assessed whether the patterns of the observed changes in these networks could distinguish brain-injured piglets from non-injured. Piglet brains exhibited significant changes after injury, as evaluated by five network metrics. The injury prediction algorithm developed from our analysis of the changes in the event-related potentials functional networks ultimately produced a tool with 82% predictive accuracy. This novel approach is the first application of auditory event-related potential functional networks to the prediction of traumatic brain injury. The resulting tool is a robust, objective and predictive method that offers promise for detecting mild traumatic brain injury, in particular because collecting event-related potentials data is noninvasive and inexpensive. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. The Metabolic Syndrome Predicts Longitudinal Changes in Clock Drawing Test Performance in Older Nondemented Hypertensive Individuals.

    Science.gov (United States)

    Viscogliosi, Giovanni; Chiriac, Iulia Maria; Andreozzi, Paola; Ettorre, Evaristo

    2016-05-01

    The present study evaluated the metabolic syndrome (MetS) as independent predictor of 1-year longitudinal changes in cognitive function. 104 stroke- and dementia-free older hypertensive subjects were studied. MetS was defined by NCEP ATP-III criteria. Cognitive function was assessed by the Clock Drawing Test (CDT); 1-year changes in cognitive function were expressed as annual changes in CDT performance. Brain magnetic resonance imaging studies (1.5T) were performed. Participants with MetS exhibited greater cognitive decline than those without (-1.78 ± 1.47 versus -0.74 ± 1.44 CDT points, t = 3.348, df = 102, p < 0.001). MetS predicted cognitive decline (β = -0.327, t = -3.059, df = 96, p = 0.003) independently of its components, age, baseline cognition, neuroimaging findings, blood pressure levels, and duration of hypertension. With the exception of systolic blood pressure, none of the individual components of MetS explained 1-year changes in CDT performance. MetS as an entity predicted accelerated 1-year decline in cognitive function, assessed by CDT, in a sample of older hypertensive subjects. Copyright © 2016 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  2. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms.

    Science.gov (United States)

    Ripszam, M; Gallampois, C M J; Berglund, Å; Larsson, H; Andersson, A; Tysklind, M; Haglund, P

    2015-06-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15°C and 4 mg DOCL(-1) and, within ranges of predicted increases, 18°C and 6 mg DOCL(-1), respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Diverse models for the prediction of CDK4 inhibitory activity of ...

    Indian Academy of Sciences (India)

    employed for development of models for the prediction of CDK4 inhibitory activity using a dataset comprising of 52 analogues of ... index; molecular connectivity index; connective eccentricity topochemical index. 1. ... 80% of human cancers.

  4. Optimism predicts sustained vigorous physical activity in postmenopausal women

    Directory of Open Access Journals (Sweden)

    Ana M. Progovac

    2017-12-01

    Full Text Available Optimism and cynical hostility are associated with health behaviors and health outcomes, including morbidity and mortality. This analysis assesses their association with longitudinal vigorous physical activity (PA in postmenopausal women of the Women's Health Initiative (WHI. Subjects include 73,485 women nationwide without history of cancer or cardiovascular disease (CVD, and no missing baseline optimism, cynical hostility, or PA data. The Life Orientation Test-Revised Scale measured optimism. A Cook Medley questionnaire subscale measured cynical hostility. Scale scores were divided into quartiles. Vigorous PA three times or more per week was assessed via self-report at study baseline (1994–1998 and through follow-up year 6. Descriptive analysis mapped lifetime trajectories of vigorous PA (recalled at ages 18, 25, 50; prospectively assessed at baseline, and 3 and 6years later. Hierarchical generalized linear mixed models examined the prospective association between optimism, cynical hostility, and vigorous PA over 6years. Models adjusted for baseline sociodemographic variables, psychosocial characteristics, and health conditions and behaviors. Vigorous PA rates were highest for most optimistic women, but fell for all women by approximately 60% between age 50 and study baseline. In adjusted models from baseline through year 6, most vs. least optimistic women were 15% more likely to exercise vigorously (p<0.001. Cynical hostility was not associated with lower odds of longitudinal vigorous PA after adjustment. Results did not differ by race/ethnicity or socioeconomic status. Higher optimism is associated with maintaining vigorous PA over time in post-menopausal women, and may protect women's health over the lifespan. Keywords: Physical activity, Aging, Optimism, Cynical hostility, women's health

  5. Predicting the impact of climate change on threatened species in UK waters.

    Directory of Open Access Journals (Sweden)

    Miranda C Jones

    Full Text Available Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis and angelshark (Squatina squatina.

  6. Predicting earthquakes by analyzing accelerating precursory seismic activity

    Science.gov (United States)

    Varnes, D.J.

    1989-01-01

    During 11 sequences of earthquakes that in retrospect can be classed as foreshocks, the accelerating rate at which seismic moment is released follows, at least in part, a simple equation. This equation (1) is {Mathematical expression},where {Mathematical expression} is the cumulative sum until time, t, of the square roots of seismic moments of individual foreshocks computed from reported magnitudes;C and n are constants; and tfis a limiting time at which the rate of seismic moment accumulation becomes infinite. The possible time of a major foreshock or main shock, tf,is found by the best fit of equation (1), or its integral, to step-like plots of {Mathematical expression} versus time using successive estimates of tfin linearized regressions until the maximum coefficient of determination, r2,is obtained. Analyzed examples include sequences preceding earthquakes at Cremasta, Greece, 2/5/66; Haicheng, China 2/4/75; Oaxaca, Mexico, 11/29/78; Petatlan, Mexico, 3/14/79; and Central Chile, 3/3/85. In 29 estimates of main-shock time, made as the sequences developed, the errors in 20 were less than one-half and in 9 less than one tenth the time remaining between the time of the last data used and the main shock. Some precursory sequences, or parts of them, yield no solution. Two sequences appear to include in their first parts the aftershocks of a previous event; plots using the integral of equation (1) show that the sequences are easily separable into aftershock and foreshock segments. Synthetic seismic sequences of shocks at equal time intervals were constructed to follow equation (1), using four values of n. In each series the resulting distributions of magnitudes closely follow the linear Gutenberg-Richter relation log N=a-bM, and the product n times b for each series is the same constant. In various forms and for decades, equation (1) has been used successfully to predict failure times of stressed metals and ceramics, landslides in soil and rock slopes, and volcanic

  7. Approaches to predicting potential impacts of climate change on forest disease: An example with Armillaria root disease

    Science.gov (United States)

    Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist

    2011-01-01

    Climate change will likely have dramatic impacts on forest health because many forest trees could become maladapted to climate. Furthermore, climate change will have additional impacts on forest health through changes in the distribution and severity of forest disease. Methods are needed to predict the influence of climate change on forest disease so that appropriate...

  8. Changes in external conditions and activity in the petroleum industry

    International Nuclear Information System (INIS)

    1999-01-01

    Tax reductions in the petroleum industry are conductive to increased activity and makes the respective provinces more attractive for investments compared with other regions. Changes in taxation in Great Britain and the Gulf of Mexico, which has been analyzed by ECON, show that reducing taxes on gross income has rendered marginal investments more profitable and that reducing the tax on profits may have advanced investments and cut the costs. The examples also show that it is possible to protect the public tax revenue under taxation rearrangements by essentially limiting the tax reductions to new activities

  9. Failure Rate Prediction of Active Component Using PM Basis Database

    International Nuclear Information System (INIS)

    Kim, J. S.; Kim, H. W.; Park, J. S.; Jung, S. G.

    2011-01-01

    The safety security and efficient management of NPPs (Nuclear Power Plants) have been increased after the accident of TEPCO's Fukushima nuclear power stations. The needs for the safety and efficiency are becoming more important because about 90 percent of the NPPs all over the world are more than 20 operation years old. The preventive maintenance criteria need to be flexible, considering long-term development of the equipment performance and preventive maintenance. The PMBD (Preventive Maintenance Basis Database) program was widely used for optimization of the preventive maintenance criteria. PMBD program contains all kinds of failure mechanisms for each equipment that may occur in the power plant based on RCM(Reliability-Centered Maintenance) and numerically calculate the variation of reliability and failure rate based on PM interval changes. In this study, propriety evaluation of preventive maintenance task, cycle, technical basis for cost effective preventive maintenance strategy and an appropriate evaluation were suggested by the case application of PMBD for major components in the NPPs

  10. Changes in Leisure Activities and Dimensions of Depressive Symptoms in Later Life: A 12-Year Follow-Up.

    Science.gov (United States)

    Chao, Shiau-Fang

    2016-06-01

    Although leisure activities benefit the mental health of the elderly population, the effect of changes in leisure activities on dimensions of depressive symptoms remains unclear. This investigation examined the influences of changes in intellectual, social, and physical activities between waves on four dimensions of depressive symptoms at follow-up. Random effects modeling was utilized with data from a nationwide longitudinal study conducted in Taiwan. The study data comprised 6,942 observations from 2,660 older adults over a 12-year period. The results suggested that changes in physical activities contributed to depressive symptoms which reflected positive affect in the later wave. Increased social activities between waves predicted higher positive affect and lower interpersonal difficulties scores at follow-up. Increased intellectual activities between waves did not substantially affect any domain of depressive symptoms. In contrast, declines in intellectual activities between waves predicted higher scores in three depressive symptoms domains, including depressed mood, somatic symptoms, and interpersonal difficulties. Engagement in a varied range of activities benefits mental health among elders more than participation in any single type of activity among elders. Reducing physical activities can lower positive affect, while the adverse effect may be balanced by increasing social activities. Also, the impact of decreasing intellectual activities on the interpersonal difficulties domain of depressive symptoms may be offset by increasing social activities. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  11. Chaos and the (un)predictability of evolution in a changing environment.

    Science.gov (United States)

    Rego-Costa, Artur; Débarre, Florence; Chevin, Luis-Miguel

    2018-02-01

    Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

  12. Structural integrity of frontostriatal connections predicts longitudinal changes in self-esteem.

    Science.gov (United States)

    Chavez, Robert S; Heatherton, Todd F

    2017-06-01

    Diverse neurological and psychiatric conditions are marked by a diminished sense of positive self-regard, and reductions in self-esteem are associated with risk for these disorders. Recent evidence has shown that the connectivity of frontostriatal circuitry reflects individual differences in self-esteem. However, it remains an open question as to whether the integrity of these connections can predict self-esteem changes over larger timescales. Using diffusion magnetic resonance imaging and probabilistic tractography, we demonstrate that the integrity of white matter pathways linking the medial prefrontal cortex to the ventral striatum predicts changes in self-esteem 8 months after initial scanning in a sample of 30 young adults. Individuals with greater integrity of this pathway during the scanning session at Time 1 showed increased levels of self-esteem at follow-up, whereas individuals with lower integrity showed stifled or decreased levels of self-esteem. These results provide evidence that frontostriatal white matter integrity predicts the trajectory of self-esteem development in early adulthood, which may contribute to blunted levels of positive self-regard seen in multiple psychiatric conditions, including depression and anxiety.

  13. Hydrological responses to climatic changes in the Yellow River basin, China: Climatic elasticity and streamflow prediction

    Science.gov (United States)

    Zhang, Qiang; Liu, Jianyu; Singh, Vijay P.; Shi, Peijun; Sun, Peng

    2017-11-01

    Prediction of streamflow of the Yellow River basin was done using downscaled precipitation and temperature based on outputs of 12 GCMs under RCP2.6 and RCP8.5 scenarios. Streamflow changes of 37 tributaries of the Yellow River basin during 2070-2099 were predicted related to different GCMs and climatic scenarios using Budyko framework. The results indicated that: (1) When compared to precipitation and temperature during 1960-1979, increasing precipitation and temperature are dominant during 2070-2099. Particularly, under RCP8.5, increase of 10% and 30% can be detected for precipitation and temperature respectively; (2) Precipitation changes have larger fractional contribution to streamflow changes than temperature changes, being the major driver for spatial and temporal patterns of water resources across the Yellow River basin; (3) 2070-2099 period will witness increased streamflow depth and decreased streamflow can be found mainly in the semi-humid regions and headwater regions of the Yellow River basin, which can be attributed to more significant increase of temperature than precipitation in these regions; (4) Distinctly different picture of streamflow changes can be observed with consideration of different outputs of GCMs which can be attributed to different outputs of GCMs under different scenarios. Even so, under RCP2.6 and RCP8.5 scenarios, 36.8% and 71.1% of the tributaries of the Yellow River basin are dominated by increasing streamflow. The results of this study are of theoretical and practical merits in terms of management of water resources and also irrigated agriculture under influences of changing climate.

  14. Color vision predicts processing modes of goal activation during action cascading.

    Science.gov (United States)

    Jongkees, Bryant J; Steenbergen, Laura; Colzato, Lorenza S

    2017-09-01

    One of the most important functions of cognitive control is action cascading: the ability to cope with multiple response options when confronted with various task goals. A recent study implicates a key role for dopamine (DA) in this process, suggesting higher D1 efficiency shifts the action cascading strategy toward a more serial processing mode, whereas higher D2 efficiency promotes a shift in the opposite direction by inducing a more parallel processing mode (Stock, Arning, Epplen, & Beste, 2014). Given that DA is found in high concentration in the retina and modulation of retinal DA release displays characteristics of D2-receptors (Peters, Schweibold, Przuntek, & Müller, 2000), color vision discrimination might serve as an index of D2 efficiency. We used color discrimination, assessed with the Lanthony Desaturated Panel D-15 test, to predict individual differences (N = 85) in a stop-change paradigm that provides a well-established measure of action cascading. In this task it is possible to calculate an individual slope value for each participant that estimates the degree of overlap in task goal activation. When the stopping process of a previous task goal has not finished at the time the change process toward a new task goal is initiated (parallel processing), the slope value becomes steeper. In case of less overlap (more serial processing), the slope value becomes flatter. As expected, participants showing better color vision were more prone to activate goals in a parallel manner as indicated by a steeper slope. Our findings suggest that color vision might represent a predictor of D2 efficiency and the predisposed processing mode of goal activation during action cascading. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Global Change. Teaching Activities on Global Change for Grades 4-6.

    Science.gov (United States)

    Geological Survey (Dept. of Interior), Reston, VA.

    This packet contains a series of teaching guides on global change. The series includes lessons on dendrochronology; land, air, and water; and island living. Included is information such as : laws of straws; where land, air, and water meet; and Earth as home. Each section provides an introductory description of the activity, the purpose of the…

  16. Endosulfan induces changes in spontaneous swimming activity and acetylcholinesterase activity of Jenynsia multidentata (Anablepidae, Cyprinodontiformes)

    Energy Technology Data Exchange (ETDEWEB)

    Ballesteros, M.L. [Facultad de Ciencias Exactas, Fisicas y Naturales, Catedra Diversidad Animal II, Universidad Nacional de Cordoba, Av. Velez Sarsfield 299, 5000 Cordoba (Argentina); Durando, P.E. [Facultad de Ciencias Exactas, Fisicas y Naturales, Departamento de Biologia, Catedra de Fisiologia Animal, Universidad Nacional de San Juan, Complejo ' Islas Malvinas' , Av. Jose I. de la Roza y Meglioli, Rivadavia, San Juan (Argentina); Nores, M.L. [Facultad de Ciencias Medicas, Universidad Nacional de Cordoba-CONICET, Ciudad Universitaria, Cordoba (Argentina); Diaz, M.P. [Facultad de Ciencias Medicas, Catedra de Estadistica y Bioestadistica, Escuela de Nutricion, Universidad Nacional de Cordoba, Pabellon Chile, Ciudad Universitaria, 5000 Cordoba (Argentina); Bistoni, M.A., E-mail: mbistoni@com.uncor.ed [Facultad de Ciencias Exactas, Fisicas y Naturales, Catedra Diversidad Animal II, Universidad Nacional de Cordoba, Av. Velez Sarsfield 299, 5000 Cordoba (Argentina); Wunderlin, D.A. [Facultad de Ciencias Quimicas, Dto. Bioquimica Clinica-CIBICI, Universidad Nacional de Cordoba-CONICET, Haya de la Torre esq. Medina Allende, Ciudad Universitaria, 5000 Cordoba (Argentina)

    2009-05-15

    We assessed changes in spontaneous swimming activity and acetylcholinesterase (AchE) activity of Jenynsia multidentata exposed to Endosulfan (EDS). Females of J. multidentata were exposed to 0.072 and 1.4 mug L{sup -1} EDS. Average speed and movement percentage were recorded during 48 h. We also exposed females to EDS at five concentrations between 0.072 and 1.4 mug L{sup -1} during 24 h, and measured the AchE activity in brain and muscle. At 0.072 mug L{sup -1} EDS swimming motility decreased relative to the control group after 45 h, while at 1.4 mug L{sup -1} EDS swimming motility decreased after 24 h. AchE activity significantly decreased in muscle when J. multidentata were exposed to EDS above 0.072 mug L{sup -1}, while no significant changes were observed in brain. Thus, changes in swimming activity and AchE activity in muscle are good biomarkers of exposure to EDS in J. multidentata. - This work reports changes observed in spontaneous swimming activity and AchE activity of Jenynsia multidentata exposed to sublethal concentrations of Endosulfan.

  17. Endosulfan induces changes in spontaneous swimming activity and acetylcholinesterase activity of Jenynsia multidentata (Anablepidae, Cyprinodontiformes)

    International Nuclear Information System (INIS)

    Ballesteros, M.L.; Durando, P.E.; Nores, M.L.; Diaz, M.P.; Bistoni, M.A.; Wunderlin, D.A.

    2009-01-01

    We assessed changes in spontaneous swimming activity and acetylcholinesterase (AchE) activity of Jenynsia multidentata exposed to Endosulfan (EDS). Females of J. multidentata were exposed to 0.072 and 1.4 μg L -1 EDS. Average speed and movement percentage were recorded during 48 h. We also exposed females to EDS at five concentrations between 0.072 and 1.4 μg L -1 during 24 h, and measured the AchE activity in brain and muscle. At 0.072 μg L -1 EDS swimming motility decreased relative to the control group after 45 h, while at 1.4 μg L -1 EDS swimming motility decreased after 24 h. AchE activity significantly decreased in muscle when J. multidentata were exposed to EDS above 0.072 μg L -1 , while no significant changes were observed in brain. Thus, changes in swimming activity and AchE activity in muscle are good biomarkers of exposure to EDS in J. multidentata. - This work reports changes observed in spontaneous swimming activity and AchE activity of Jenynsia multidentata exposed to sublethal concentrations of Endosulfan.

  18. Promoting physical activity and reducing climate change : Opportunities to replace short car trips with active transportation

    NARCIS (Netherlands)

    Maibach, E.; Steg, L.; Anable, J.

    2009-01-01

    Automobile use is a significant contributor to climate change, local air pollution, pedestrian injuries and deaths, declines in physical activity and obesity. A significant proportion of car use is for short trips that can relatively easily be taken with active transportation options - walking or

  19. Wave climate change, coastline response and hazard prediction in New South Wales, Australia

    International Nuclear Information System (INIS)

    Goodwin, Ian D.; Verdon, Danielle; Cowell, Peter

    2007-01-01

    Full text: Full text: Considerable research effort has been directed towards understanding and the gross prediction of shoreline response to sea level rise (eg. Cowell ef a/. 2003a, b). In contrast, synoptic prediction of changes in the planform configuration of shorelines in response to changes in wind and wave climates over many decades has been limited by the lack of geohistorical data on shoreline alignment evolution and long time series of wave climate. This paper presents new data sets on monthly mean wave direction variability based on: a. Waverider buoy data; b. a reconstruction of monthly mid-shelf wave direction, 1877 to 2002 AD from historical MSLP data (Goodwin 2005); and c. a multi-decadal reconstruction of wave direction, in association with the Interdecadal Pacific Oscillation and the Southern Annular Mode of climate variability, covering the past millennium. A model of coastline response to the wave climate variability is presented for northern and central New South Wales (NSW) for decadal to multi-decadal time scales, and is based on instrumental and geohistorical data. The sensitivity of the coastline position and alignment, and beach state to mean and extreme wave climate changes is demonstrated (e.g. Goodwin et al. 2006). State changes in geometric shoreline alignment rotation, sand volume (progradation/recession) for NSW and mean wave direction, are shown to be in agreement with the low-frequency change in Pacific-wide climate. Synoptic typing of climate patterns using Self Organised Mapping methods is used to downscale CSIRO GCM output for this century. The synoptic types are correlated to instrumental wave climate data and coastal behaviour. The shifts in downscaled synoptic types for 2030 and 2070 AD are then used as the basis for predicting mean wave climate changes, coastal behaviour and hazards along the NSW coastline. The associated coastal hazards relate to the definition of coastal land loss through rising sea levels and shoreline

  20. Performance of a process-based hydrodynamic model in predicting shoreline change

    Science.gov (United States)

    Safak, I.; Warner, J. C.; List, J. H.

    2012-12-01

    Shoreline change is controlled by a complex combination of processes that include waves, currents, sediment characteristics and availability, geologic framework, human interventions, and sea level rise. A comprehensive data set of shoreline position (14 shorelines between 1978-2002) along the continuous and relatively non-interrupted North Carolina Coast from Oregon Inlet to Cape Hatteras (65 km) reveals a spatial pattern of alternating erosion and accretion, with an erosional average shoreline change rate of -1.6 m/yr and up to -8 m/yr in some locations. This data set gives a unique opportunity to study long-term shoreline change in an area hit by frequent storm events while relatively uninfluenced by human interventions and the effects of tidal inlets. Accurate predictions of long-term shoreline change may require a model that accurately resolves surf zone processes and sediment transport patterns. Conventional methods for predicting shoreline change such as one-line models and regression of shoreline positions have been designed for computational efficiency. These methods, however, not only have several underlying restrictions (validity for small angle of wave approach, assuming bottom contours and shoreline to be parallel, depth of closure, etc.) but also their empirical estimates of sediment transport rates in the surf zone have been shown to vary greatly from the calculations of process-based hydrodynamic models. We focus on hind-casting long-term shoreline change using components of the process-based, three-dimensional coupled-ocean-atmosphere-wave-sediment transport modeling system (COAWST). COAWST is forced with historical predictions of atmospheric and oceanographic data from public-domain global models. Through a method of coupled concurrent grid-refinement approach in COAWST, the finest grid with resolution of O(10 m) that covers the surf zone along the section of interest is forced at its spatial boundaries with waves and currents computed on the grids

  1. Changes in mitochondrial electron transport chain activity during insect metamorphosis.

    Science.gov (United States)

    Chamberlin, M E

    2007-02-01

    The midgut of the tobacco hornworm (Manduca sexta) is a highly aerobic tissue that is destroyed by programmed cell death during larval-pupal metamorphosis. The death of the epithelium begins after commitment to pupation, and the oxygen consumption of isolated midgut mitochondria decreases soon after commitment. To assess the role of the electron transport chain in this decline in mitochondrial function, the maximal activities of complexes I-IV of the respiratory chain were measured in isolated midgut mitochondria. Whereas there were no developmental changes in the activity of complex I or III, activities of complexes II and IV [cytochrome c oxidase (COX)] were higher in mitochondria from precommitment than postcommitment larvae. This finding is consistent with a higher rate of succinate oxidation in mitochondria isolated from precommitment larvae and reveals that the metamorphic decline in mitochondrial respiration is due to the targeted destruction or inactivation of specific sites within the mitochondria, rather than the indiscriminate destruction of the organelles. The COX turnover number (e- x s(-1) x cytochrome aa3(-1)) was greater for the enzyme from precommitment than postcommitment larvae, indicating a change in the enzyme structure and/or its lipid environment during the early stages of metamorphosis. The turnover number of COX in the intact mitochondria (in organello COX) was also lower in postcommitment larvae. In addition to changes in the protein or membrane phospholipids, the metamorphic decline in this rate constant may be a result of the observed loss of endogenous cytochrome c.

  2. Continuously Growing Rodent Molars Result from a Predictable Quantitative Evolutionary Change over 50 Million Years

    Directory of Open Access Journals (Sweden)

    Vagan Tapaltsyan

    2015-05-01

    Full Text Available The fossil record is widely informative about evolution, but fossils are not systematically used to study the evolution of stem-cell-driven renewal. Here, we examined evolution of the continuous growth (hypselodonty of rodent molar teeth, which is fuelled by the presence of dental stem cells. We studied occurrences of 3,500 North American rodent fossils, ranging from 50 million years ago (mya to 2 mya. We examined changes in molar height to determine whether evolution of hypselodonty shows distinct patterns in the fossil record, and we found that hypselodont taxa emerged through intermediate forms of increasing crown height. Next, we designed a Markov simulation model, which replicated molar height increases throughout the Cenozoic and, moreover, evolution of hypselodonty. Thus, by extension, the retention of the adult stem cell niche appears to be a predictable quantitative rather than a stochastic qualitative process. Our analyses predict that hypselodonty will eventually become the dominant phenotype.

  3. Phase change predictions for liquid fuel in contact with steel structure using the heat conduction equation

    Energy Technology Data Exchange (ETDEWEB)

    Brear, D.J. [Power Reactor and Nuclear Fuel Development Corp., Oarai, Ibaraki (Japan). Oarai Engineering Center

    1998-01-01

    When liquid fuel makes contact with steel structure the liquid can freeze as a crust and the structure can melt at the surface. The melting and freezing processes that occur can influence the mode of fuel freezing and hence fuel relocation. Furthermore the temperature gradients established in the fuel and steel phases determine the rate at which heat is transferred from fuel to steel. In this memo the 1-D transient heat conduction equations are applied to the case of initially liquid UO{sub 2} brought into contact with solid steel using up-to-date materials properties. The solutions predict criteria for fuel crust formation and steel melting and provide a simple algorithm to determine the interface temperature when one or both of the materials is undergoing phase change. The predicted steel melting criterion is compared with available experimental results. (author)

  4. Phase change predictions for liquid fuel in contact with steel structure using the heat conduction equation

    International Nuclear Information System (INIS)

    Brear, D.J.

    1998-01-01

    When liquid fuel makes contact with steel structure the liquid can freeze as a crust and the structure can melt at the surface. The melting and freezing processes that occur can influence the mode of fuel freezing and hence fuel relocation. Furthermore the temperature gradients established in the fuel and steel phases determine the rate at which heat is transferred from fuel to steel. In this memo the 1-D transient heat conduction equations are applied to the case of initially liquid UO 2 brought into contact with solid steel using up-to-date materials properties. The solutions predict criteria for fuel crust formation and steel melting and provide a simple algorithm to determine the interface temperature when one or both of the materials is undergoing phase change. The predicted steel melting criterion is compared with available experimental results. (author)

  5. Changes in economic activity: The role of age and education

    Directory of Open Access Journals (Sweden)

    Elke Loichinger

    2017-04-01

    Full Text Available Background: Between 2000 and 2010, the labor force participation (LFP of European men stayed mostly constant, whereas the participation of women continued to increase. Participation rates of people close to normal retirement ages rose almost universally. At the same time, the education composition shifted toward higher levels of educational attainment and education-specific differentials in economic activity persisted. Objective: The aim of the paper is to understand the extent to which developments of LFP rates between 2000 and 2010 in selected European countries can be explained by age-specific and education-specific changes in participation rates, as compared to changes in populations' structural composition by age and education. Methods: We apply a decomposition methodology that allows us to disentangle changes in age- and education-specific LFP rates from changes in the age and educational structure of the population. Results: Our results show that LFP rates of adult women would have increased even more, had it not been for the downward pressure from the shift in the age composition toward older age groups with relatively lower levels of participation. This downward pressure also depressed male participation. The increase in participation among older people is mainly explained by participation increases among those with nontertiary education and is reinforced by a general shift toward higher levels of educational attainment. Contribution: Beyond changes in the age structure, we quantify the role of compositional changes by educational attainment. Our results indicate that labor supply may not decrease to the extent expected due to population aging, given educational expansion and education-specific patterns of economic activity.

  6. Can phenological models predict tree phenology accurately under climate change conditions?

    Science.gov (United States)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  7. Post-anoxic quantitative MRI changes may predict emergence from coma and functional outcomes at discharge.

    Science.gov (United States)

    Reynolds, Alexandra S; Guo, Xiaotao; Matthews, Elizabeth; Brodie, Daniel; Rabbani, Leroy E; Roh, David J; Park, Soojin; Claassen, Jan; Elkind, Mitchell S V; Zhao, Binsheng; Agarwal, Sachin

    2017-08-01

    Traditional predictors of neurological prognosis after cardiac arrest are unreliable after targeted temperature management. Absence of pupillary reflexes remains a reliable predictor of poor outcome. Diffusion-weighted imaging has emerged as a potential predictor of recovery, and here we compare imaging characteristics to pupillary exam. We identified 69 patients who had MRIs within seven days of arrest and used a semi-automated algorithm to perform quantitative volumetric analysis of apparent diffusion coefficient (ADC) sequences at various thresholds. Area under receiver operating characteristic curves (ROC-AUC) were estimated to compare predictive values of quantitative MRI with pupillary exam at days 3, 5 and 7 post-arrest, for persistence of coma and functional outcomes at discharge. Cerebral Performance Category scores of 3-4 were considered poor outcome. Excluding patients where life support was withdrawn, ≥2.8% diffusion restriction of the entire brain at an ADC of ≤650×10 -6 m 2 /s was 100% specific and 68% sensitive for failure to wake up from coma before discharge. The ROC-AUC of ADC changes at ≤450×10 -6 mm 2 /s and ≤650×10 -6 mm 2 /s were significantly superior in predicting failure to wake up from coma compared to bilateral absence of pupillary reflexes. Among survivors, >0.01% of diffusion restriction of the entire brain at an ADC ≤450×10 -6 m 2 /s was 100% specific and 46% sensitive for poor functional outcome at discharge. The ROC curve predicting poor functional outcome at ADC ≤450×10 -6 mm 2 /s had an AUC of 0.737 (0.574-0.899, p=0.04). Post-anoxic diffusion changes using quantitative brain MRI may aid in predicting persistent coma and poor functional outcomes at hospital discharge. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Switch region for pathogenic structural change in conformational disease and its prediction.

    Directory of Open Access Journals (Sweden)

    Xin Liu

    2010-01-01

    Full Text Available Many diseases are believed to be related to abnormal protein folding. In the first step of such pathogenic structural changes, misfolding occurs in regions important for the stability of the native structure. This destabilizes the normal protein conformation, while exposing the previously hidden aggregation-prone regions, leading to subsequent errors in the folding pathway. Sites involved in this first stage can be deemed switch regions of the protein, and can represent perfect binding targets for drugs to block the abnormal folding pathway and prevent pathogenic conformational changes. In this study, a prediction algorithm for the switch regions responsible for the start of pathogenic structural changes is introduced. With an accuracy of 94%, this algorithm can successfully find short segments covering sites significant in triggering conformational diseases (CDs and is the first that can predict switch regions for various CDs. To illustrate its effectiveness in dealing with urgent public health problems, the reason of the increased pathogenicity of H5N1 influenza virus is analyzed; the mechanisms of the pandemic swine-origin 2009 A(H1N1 influenza virus in overcoming species barriers and in infecting large number of potential patients are also suggested. It is shown that the algorithm is a potential tool useful in the study of the pathology of CDs because: (1 it can identify the origin of pathogenic structural conversion with high sensitivity and specificity, and (2 it provides an ideal target for clinical treatment.

  9. Prediction of hospital mortality by changes in the estimated glomerular filtration rate (eGFR).

    LENUS (Irish Health Repository)

    Berzan, E

    2015-03-01

    Deterioration of physiological or laboratory variables may provide important prognostic information. We have studied whether a change in estimated glomerular filtration rate (eGFR) value calculated using the (Modification of Diet in Renal Disease (MDRD) formula) over the hospital admission, would have predictive value. An analysis was performed on all emergency medical hospital episodes (N = 61964) admitted between 1 January 2002 and 31 December 2011. A stepwise logistic regression model examined the relationship between mortality and change in renal function from admission to discharge. The fully adjusted Odds Ratios (OR) for 5 classes of GFR deterioration showed a stepwise increased risk of 30-day death with OR\\'s of 1.42 (95% CI: 1.20, 1.68), 1.59 (1.27, 1.99), 2.71 (2.24, 3.27), 5.56 (4.54, 6.81) and 11.9 (9.0, 15.6) respectively. The change in eGFR during a clinical episode, following an emergency medical admission, powerfully predicts the outcome.

  10. Land use change and prediction in the Baimahe Basin using GIS and CA-Markov model

    International Nuclear Information System (INIS)

    Wang, Shixu; Zhang, Zulu; Wang, Xue

    2014-01-01

    Using ArcGIS and IDRISI, land use dynamics and Shannon entropy information were applied in this paper to analyze the quantity and structure change in the Baimahe Basin from 1996 to 2008. A CA-Markov model was applied to predict the land use patterns in 2020. Results showed that farmland, forest and construction land are the dominant land use types in the Baimahe Basin. From 1996 to 2008, areas of farmland and forest decreased and other land use types increased, with construction land increasing the most. The prediction results showed that the changes in land use patterns from 2008 to 2020 would be the same with those from 1996 to 2008. Main changes are the transiting out of farmland and forest and the transiting in of construction land. The order degree of the whole basin goes on decreasing. Measures of farmland protection and grain for green projects should be adopted to enhance the stability of land use system in the Baimahe Basin in order to promote regional sustainable development

  11. Dynamic changes in brain activity during prism adaptation.

    Science.gov (United States)

    Luauté, Jacques; Schwartz, Sophie; Rossetti, Yves; Spiridon, Mona; Rode, Gilles; Boisson, Dominique; Vuilleumier, Patrik

    2009-01-07

    Prism adaptation does not only induce short-term sensorimotor plasticity, but also longer-term reorganization in the neural representation of space. We used event-related fMRI to study dynamic changes in brain activity during both early and prolonged exposure to visual prisms. Participants performed a pointing task before, during, and after prism exposure. Measures of trial-by-trial pointing errors and corrections allowed parametric analyses of brain activity as a function of performance. We show that during the earliest phase of prism exposure, anterior intraparietal sulcus was primarily implicated in error detection, whereas parieto-occipital sulcus was implicated in error correction. Cerebellum activity showed progressive increases during prism exposure, in accordance with a key role for spatial realignment. This time course further suggests that the cerebellum might promote neural changes in superior temporal cortex, which was selectively activated during the later phase of prism exposure and could mediate the effects of prism adaptation on cognitive spatial representations.

  12. Professional activity. How is family physicians' work time changing?

    Science.gov (United States)

    Woodward, C A; Ferrier, B; Cohen, M; Brown, J

    2001-07-01

    To examine hours worked professionally, work preferences, and changes in both of these and their correlates. Repeated surveys done in 1993 and 1999. Ontario family practices. Cohort of physicians certified in family medicine between 1989 and 1991 after family medicine residency who were surveyed in 1993 when they resided in Ontario. Self-reported hours spent weekly on professional activities, desired hours of professional work, and balance between work and other activities. Fifty-three percent (293) of 553 physicians responded to the 1999 survey; 91% had remained family physicians; 85% of these had participated in the 1993 survey. The difference between the hours that family physicians preferred to work professionally and their actual hours of work had increased since 1993. Childless physicians, women physicians with preschool children, and women physicians married to other physicians worked fewer hours professionally than other physicians in 1999. Female physicians and physicians without children worked closer to their preferred hours than other physicians. Reporting a preference to work fewer hours professionally in 1993 was linked with a reduction in professional activities by 1999. Greater attention should be paid in physician resource planning to the family life cycle of female physicians. Lifestyle changes could lead to a reduction in professional activity among these physicians.

  13. Online communication predicts Belgian adolescents' initiation of romantic and sexual activity.

    Science.gov (United States)

    Vandenbosch, Laura; Beyens, Ine; Vangeel, Laurens; Eggermont, Steven

    2016-04-01

    Online communication is associated with offline romantic and sexual activity among college students. Yet, it is unknown whether online communication is associated with the initiation of romantic and sexual activity among adolescents. This two-wave panel study investigated whether chatting, visiting dating websites, and visiting erotic contact websites predicted adolescents' initiation of romantic and sexual activity. We analyzed two-wave panel data from 1163 Belgian adolescents who participated in the MORES Study. We investigated the longitudinal impact of online communication on the initiation of romantic relationships and sexual intercourse using logistic regression analyses. The odds ratios of initiating a romantic relationship among romantically inexperienced adolescents who frequently used chat rooms, dating websites, or erotic contact websites were two to three times larger than those of non-users. Among sexually inexperienced adolescents who frequently used chat rooms, dating websites, or erotic contact websites, the odds ratios of initiating sexual intercourse were two to five times larger than that among non-users, even after a number of other relevant factors were introduced. This is the first study to demonstrate that online communication predicts the initiation of offline sexual and romantic activity as early as adolescence. Practitioners and parents need to consider the role of online communication in adolescents' developing sexuality. • Adolescents increasingly communicate online with peers. • Online communication predicts romantic and sexual activity among college students. What is New: • Online communication predicts adolescents' offline romantic activity over time. • Online communication predicts adolescents' offline sexual activity over time.

  14. Cognitive emotion regulation enhances aversive prediction error activity while reducing emotional responses.

    Science.gov (United States)

    Mulej Bratec, Satja; Xie, Xiyao; Schmid, Gabriele; Doll, Anselm; Schilbach, Leonhard; Zimmer, Claus; Wohlschläger, Afra; Riedl, Valentin; Sorg, Christian

    2015-12-01

    Cognitive emotion regulation is a powerful way of modulating emotional responses. However, despite the vital role of emotions in learning, it is unknown whether the effect of cognitive emotion regulation also extends to the modulation of learning. Computational models indicate prediction error activity, typically observed in the striatum and ventral tegmental area, as a critical neural mechanism involved in associative learning. We used model-based fMRI during aversive conditioning with and without cognitive emotion regulation to test the hypothesis that emotion regulation would affect prediction error-related neural activity in the striatum and ventral tegmental area, reflecting an emotion regulation-related modulation of learning. Our results show that cognitive emotion regulation reduced emotion-related brain activity, but increased prediction error-related activity in a network involving ventral tegmental area, hippocampus, insula and ventral striatum. While the reduction of response activity was related to behavioral measures of emotion regulation success, the enhancement of prediction error-related neural activity was related to learning performance. Furthermore, functional connectivity between the ventral tegmental area and ventrolateral prefrontal cortex, an area involved in regulation, was specifically increased during emotion regulation and likewise related to learning performance. Our data, therefore, provide first-time evidence that beyond reducing emotional responses, cognitive emotion regulation affects learning by enhancing prediction error-related activity, potentially via tegmental dopaminergic pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Ligand-induced conformational changes: Improved predictions of ligand binding conformations and affinities

    DEFF Research Database (Denmark)

    Frimurer, T.M.; Peters, Günther H.J.; Iversen, L.F.

    2003-01-01

    tyrosine phosphatase 1 B (PTP1B) are known. To obtain a quantitative measure of the impact of conformational changes induced by the inhibitors, these were docked to the active site region of various structures of PTP1B using the docking program FlexX. Firstly, the inhibitors were docked to a PTP1B crystal...

  16. Utilizing change effort prediction to analyze modifiability of business rule architectures at the NHS

    NARCIS (Netherlands)

    dr. Martijn Zoet; Koen Smit

    2016-01-01

    From the article: Abstract Business rules (BR’s) play a critical role in an organization’s daily activities. With the increased use of BR (solutions) and ever increasing change frequency of BR’s the interest in modifiability guidelines that address the manageability of BR’s has increased as well.

  17. Body image and body change: predictive factors in an Iranian population.

    Science.gov (United States)

    Garrusi, Behshid; Garousi, Saeide; Baneshi, Mohammad R

    2013-08-01

    Body concerns and its health consequences such as eating disorders and harmful body change activities are mentioned in Asian countries. This study evaluates factors contributing to body image/shape changes in an Iranian population. In this cross-sectional study we focused on four main body change activity (diet, exercise, substance use, and surgery) and their risk factors such as demographic variables, Body Mass Index (BMI), Media, Body-Esteem, Perceived Socio-cultural Pressure, Body dissatisfaction and, Self-Esteem. Approximately, 1,200 individuals between 14-55 years old participated in this study. We used a multistage sampling method. In each region, the first household was selected at random. The probability of outcomes was estimated from logistic models. About 54.3% of respondents were females. The mean (SD) of age was 31.06 (10.24) years. Variables such as gender, age, BMI, use of media and socio cultural factors as, body dissatisfaction, body-esteem and pressure by relatives were the main factors that influenced body change methods. In particular we have seen that male are 53% less likely to follow surgical treatments, but 125% were more likely to use substances. Investigation of body concern and its health related problem should be assessed in cultural context. For effectiveness of interventional programs and reducing harmful body image/shape changes activities, socio-cultural background should be noted.

  18. Body image and body change: Predictive factors in an Iranian population

    Directory of Open Access Journals (Sweden)

    Behshid Garrusi

    2013-01-01

    Full Text Available Background: Body concerns and its health consequences such as eating disorders and harmful body change activities are mentioned in Asian countries. This study evaluates factors contributing to body image/shape changes in an Iranian population. Methods: In this cross-sectional study we focused on four main body change activity (diet, exercise, substance use, and surgery and their risk factors such as demographic variables, Body Mass Index (BMI, Media, Body-Esteem, Perceived Socio-cultural Pressure, Body dissatisfaction and, Self-Esteem. Approximately, 1,200 individuals between 14-55 years old participated in this study. We used a multistage sampling method. In each region, the first household was selected at random. The probability of outcomes was estimated from logistic models. Results: About 54.3% of respondents were females. The mean (SD of age was 31.06 (10.24 years. Variables such as gender, age, BMI, use of media and socio cultural factors as, body dissatisfaction, body-esteem and pressure by relatives were the main factors that influenced body change methods. In particular we have seen that male are 53% less likely to follow surgical treatments, but 125% were more likely to use substances. Conclusions: Investigation of body concern and its health related problem should be assessed in cultural context. For effectiveness of interventional programs and reducing harmful body image/shape changes activities, socio-cultural background should be noted.

  19. Body Image and Body Change: Predictive Factors in an Iranian Population

    Science.gov (United States)

    Garrusi, Behshid; Garousi, Saeide; Baneshi, Mohammad R.

    2013-01-01

    Background: Body concerns and its health consequences such as eating disorders and harmful body change activities are mentioned in Asian countries. This study evaluates factors contributing to body image/shape changes in an Iranian population. Methods: In this cross-sectional study we focused on four main body change activity (diet, exercise, substance use, and surgery) and their risk factors such as demographic variables, Body Mass Index (BMI), Media, Body-Esteem, Perceived Socio-cultural Pressure, Body dissatisfaction and, Self-Esteem. Approximately, 1,200 individuals between 14-55 years old participated in this study. We used a multistage sampling method. In each region, the first household was selected at random. The probability of outcomes was estimated from logistic models. Results: About 54.3% of respondents were females. The mean (SD) of age was 31.06 (10.24) years. Variables such as gender, age, BMI, use of media and socio cultural factors as, body dissatisfaction, body-esteem and pressure by relatives were the main factors that influenced body change methods. In particular we have seen that male are 53% less likely to follow surgical treatments, but 125% were more likely to use substances. Conclusions: Investigation of body concern and its health related problem should be assessed in cultural context. For effectiveness of interventional programs and reducing harmful body image/shape changes activities, socio-cultural background should be noted. PMID:24049621

  20. Predictive capabilities of the specific activity hypothesis for Cs and Zn in freshwater systems

    International Nuclear Information System (INIS)

    Seelye, J.G.

    1975-01-01

    Predictions of radioisotope concentrations in components of aquatic systems have been attempted using the specific activity concept, an approach that seems theoretically sound. A comprehensive examination of the specific activities of 134 Cs and 65 Zn in the components of a freshwater system, over a 10 month period, was conducted to evaluate the specific activity hypothesis under applied conditions. This study was designed to provide comparisons of predicted and observed specific activities and to test the equivalence of specific activities between all components of the system. One dose of radioisotopes was added to the system in this study and even after 10 months these radioisotopes were not distributed similarly to the stable isotopes. This suggests that the time necessary to reach a specific activity equilibrium might be a matter of years rather than months. More importantly, in natural systems, where the radioisotope addition is continuous a specific activity equilibrium may never be achieved. These things plus the non-conservative nature of the 134 Cs and 65 Zn predicted concentrations indicates that the use of the specific activity concept for predicting radioisotope concentrations of Cs and Zn in freshwater systems is questionable. A more rigorous approach must be used, considering isotope transfer rates between components and the complexity of the system. Problems with statistical comparisons of derived variables, such as specific activities, are discussed and were considered in interpreting the results of this study

  1. A conceptual framework for effectively anticipating water-quality changes resulting from changes in agricultural activities

    Science.gov (United States)

    Capel, Paul D.; Wolock, David M.; Coupe, Richard H.; Roth, Jason L.

    2018-01-10

    Agricultural activities can affect water quality and the health of aquatic ecosystems; many water-quality issues originate with the movement of water, agricultural chemicals, and eroded soil from agricultural areas to streams and groundwater. Most agricultural activities are designed to sustain or increase crop production, while some are designed to protect soil and water resources. Numerous soil- and water-protection practices are designed to reduce the volume and velocity of runoff and increase infiltration. This report presents a conceptual framework that combines generalized concepts on the movement of water, the environmental behavior of chemicals and eroded soil, and the designed functions of various agricultural activities, as they relate to hydrology, to create attainable expectations for the protection of—with the goal of improving—water quality through changes in an agricultural activity.The framework presented uses two types of decision trees to guide decision making toward attainable expectations regarding the effectiveness of changing agricultural activities to protect and improve water quality in streams. One decision tree organizes decision making by considering the hydrologic setting and chemical behaviors, largely at the field scale. This decision tree can help determine which agricultural activities could effectively protect and improve water quality in a stream from the movement of chemicals, or sediment, from a field. The second decision tree is a chemical fate accounting tree. This decision tree helps set attainable expectations for the permanent removal of sediment, elements, and organic chemicals—such as herbicides and insecticides—through trapping or conservation tillage practices. Collectively, this conceptual framework consolidates diverse hydrologic settings, chemicals, and agricultural activities into a single, broad context that can be used to set attainable expectations for agricultural activities. This framework also enables

  2. Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

    Science.gov (United States)

    Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

    2017-09-01

    We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  3. A Bayesian Belief Network framework to predict SOC stock change: the Veneto region (Italy) case study

    Science.gov (United States)

    Dal Ferro, Nicola; Quinn, Claire Helen; Morari, Francesco

    2017-04-01

    A key challenge for soil scientists is predicting agricultural management scenarios that combine crop productions with high standards of environmental quality. In this context, reversing the soil organic carbon (SOC) decline in croplands is required for maintaining soil fertility and contributing to mitigate GHGs emissions. Bayesian belief networks (BBN) are probabilistic models able to accommodate uncertainty and variability in the predictions of the impacts of management and environmental changes. By linking multiple qualitative and quantitative variables in a cause-and-effect relationships, BBNs can be used as a decision support system at different spatial scales to find best management strategies in the agroecosystems. In this work we built a BBN to model SOC dynamics (0-30 cm layer) in the low-lying plain of Veneto region, north-eastern Italy, and define best practices leading to SOC accumulation and GHGs (CO2-equivalent) emissions reduction. Regional pedo-climatic, land use and management information were combined with experimental and modelled data on soil C dynamics as natural and anthropic key drivers affecting SOC stock change. Moreover, utility nodes were introduced to determine optimal decisions for mitigating GHGs emissions from croplands considering also three different IPCC climate scenarios. The network was finally validated with real field data in terms of SOC stock change. Results showed that the BBN was able to model real SOC stock changes, since validation slightly overestimated SOC reduction (+5%) at the expenses of its accumulation. At regional level, probability distributions showed 50% of SOC loss, while only 17% of accumulation. However, the greatest losses (34%) were associated with low reduction rates (100-500 kg C ha-1 y-1), followed by 33% of stabilized conditions (-100 < SOC < 100 kg ha-1 y-1). Land use management (especially tillage operations and soil cover) played a primary role to affect SOC stock change, while climate conditions

  4. Revisiting concepts of thermal physiology: Predicting responses of mammals to climate change.

    Science.gov (United States)

    Mitchell, Duncan; Snelling, Edward P; Hetem, Robyn S; Maloney, Shane K; Strauss, Willem Maartin; Fuller, Andrea

    2018-02-26

    The accuracy of predictive models (also known as mechanistic or causal models) of animal responses to climate change depends on properly incorporating the principles of heat transfer and thermoregulation into those models. Regrettably, proper incorporation of these principles is not always evident. We have revisited the relevant principles of thermal physiology and analysed how they have been applied in predictive models of large mammals, which are particularly vulnerable, to climate change. We considered dry heat exchange, evaporative heat transfer, the thermoneutral zone and homeothermy, and we examined the roles of size and shape in the thermal physiology of large mammals. We report on the following misconceptions in influential predictive models: underestimation of the role of radiant heat transfer, misassignment of the role and misunderstanding of the sustainability of evaporative cooling, misinterpretation of the thermoneutral zone as a zone of thermal tolerance or as a zone of sustainable energetics, confusion of upper critical temperature and critical thermal maximum, overestimation of the metabolic energy cost of evaporative cooling, failure to appreciate that the current advantages of size and shape will become disadvantageous as climate change advances, misassumptions about skin temperature and, lastly, misconceptions about the relationship between body core temperature and its variability with body mass in large mammals. Not all misconceptions invalidate the models, but we believe that preventing inappropriate assumptions from propagating will improve model accuracy, especially as models progress beyond their current typically static format to include genetic and epigenetic adaptation that can result in phenotypic plasticity. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

  5. Human activities and climate and environment changes: an inevitable relation

    International Nuclear Information System (INIS)

    Sanchez, Aretha

    2009-01-01

    The human interference in the environment and the consequent climate change is today a consensus. The climate change can be local, regional and global. The global climate change is mainly caused by the greenhouse gases, and consequently the climate change intervenes in the environment. The interference cycle emerges in several forms and results in several consequences. However, the Global Warming has certainly the most import global impact. The main cause of the increase in the temperature (Greenhouse Effect) is the intensive use of the fossil fuels. Thus, to minimize the climatic changes actions are necessary to reduce, to substitute and to use with more efficient the fossil fuels. Looking at the past, the old agriculturists may have released greenhouse gases since thousand years ago, thus, modifying slowly but in significant form the earth climate much before the Industrial Age. If this theory is confirmed, its consequences would be decisive for the man history in the planet. For example, in parts of the North America and Europe the current temperatures could be even four Celsius degrees smaller. This change in temperature is enough to hinder agricultural used of these regions and consequently to diminish the human development. The main focus of this work is to perform a retrospective in some of civilizations who collapse due to environmental problems and make a historical description of the human activities (agriculture and livestock) since the primordium of the man up to the Industrial Age, aiming at the man interference on the natural dynamics of the global climate and the environment. This work will show through data comparisons and inferences that the gases emissions from these activities had a significant magnitude comparatively by the emissions after the Industrial Age. It is also demonstrated that the climate and environment interference was inevitable because the human evolution was caused by these activities. Another important point of this work is to

  6. Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules

    Science.gov (United States)

    Ranganathan, Rajiv; Krishnan, Chandramouli; Dhaher, Yasin Y.; Rymer, William Z.

    2018-01-01

    The motor module hypothesis in motor control proposes that the nervous system can simplify the problem of controlling a large number of muscles in human movement by grouping muscles into a smaller number of modules. Here, we tested one prediction of the modular organization hypothesis by examining whether there is preferential exploration along these motor modules during the learning of a new gait pattern. Healthy college-aged participants learned a new gait pattern which required increased hip and knee flexion during the swing phase while walking in a lower-extremity robot (Lokomat). The new gait pattern was displayed as a foot trajectory in the sagittal plane and participants attempted to match their foot trajectory to this template. We recorded EMG from 8 lower-extremity muscles and we extracted motor modules during both baseline walking and target-tracking using non-negative matrix factorization (NMF). Results showed increased trajectory variability in the first block of learning, indicating that participants were engaged in exploratory behavior. Critically, when we examined the muscle activity during this exploratory phase, we found that the composition of motor modules changed significantly within the first few strides of attempting the new gait pattern. The lack of persistence of the motor modules under even short time scales suggests that motor modules extracted during locomotion may be more indicative of correlated muscle activity induced by the task constraints of walking, rather than reflecting a modular control strategy. PMID:26916510

  7. Graph-based representation of behavior in detection and prediction of daily living activities.

    Science.gov (United States)

    Augustyniak, Piotr; Ślusarczyk, Grażyna

    2018-04-01

    Various surveillance systems capture signs of human activities of daily living (ADLs) and store multimodal information as time line behavioral records. In this paper, we present a novel approach to the analysis of a behavioral record used in a surveillance system designed for use in elderly smart homes. The description of a subject's activity is first decomposed into elementary poses - easily detectable by dedicated intelligent sensors - and represented by the share coefficients. Then, the activity is represented in the form of an attributed graph, where nodes correspond to elementary poses. As share coefficients of poses are expressed as attributes assigned to graph nodes, their change corresponding to a subject's action is represented by flow in graph edges. The behavioral record is thus a time series of graphs, which tiny size facilitates storage and management of long-term monitoring results. At the system learning stage, the contribution of elementary poses is accumulated, discretized and probability-ordered leading to a finite list representing the possible transitions between states. Such a list is independently built for each room in the supervised residence, and employed for assessment of the current action in the context of subject's habits and a room purpose. The proposed format of a behavioral record, applied to an adaptive surveillance system, is particularly advantageous for representing new activities not known at the setup stage, for providing a quantitative measure of transitions between poses and for expressing the difference between a predicted and actual action in a numerical way. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

    Science.gov (United States)

    Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

    2017-01-01

    Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

  9. Distributional changes and range predictions of downy brome (Bromus tectorum) in Rocky Mountain National Park

    Science.gov (United States)

    Bromberg, J.E.; Kumar, S.; Brown, C.S.; Stohlgren, T.J.

    2011-01-01

    Downy brome (Bromus tectorum L.), an invasive winter annual grass, may be increasing in extent and abundance at high elevations in the western United States. This would pose a great threat to high-elevation plant communities and resources. However, data to track this species in high-elevation environments are limited. To address changes in the distribution and abundance of downy brome and the factors most associated with its occurrence, we used field sampling and statistical methods, and niche modeling. In 2007, we resampled plots from two vegetation surveys in Rocky Mountain National Park for presence and cover of downy brome. One survey was established in 1993 and had been resampled in 1999. The other survey was established in 1996 and had not been resampled until our study. Although not all comparisons between years demonstrated significant changes in downy brome abundance, its mean cover increased nearly fivefold from 1993 (0.7%) to 2007 (3.6%) in one of the two vegetation surveys (P = 0.06). Although the average cover of downy brome within the second survey appeared to be increasing from 1996 to 2007, this slight change from 0.5% to 1.2% was not statistically significant (P = 0.24). Downy brome was present in 50% more plots in 1999 than in 1993 (P = 0.02) in the first survey. In the second survey, downy brome was present in 30% more plots in 2007 than in 1996 (P = 0.08). Maxent, a species-environmental matching model, was generally able to predict occurrences of downy brome, as new locations were in the ranges predicted by earlier generated models. The model found that distance to roads, elevation, and vegetation community influenced the predictions most. The strong response of downy brome to interannual environmental variability makes detecting change challenging, especially with small sample sizes. However, our results suggest that the area in which downy brome occurs is likely increasing in Rocky Mountain National Park through increased frequency and cover

  10. Narrative Changes Predict a Decrease in Symptoms in CBT for Depression: An Exploratory Study.

    Science.gov (United States)

    Gonçalves, Miguel M; Silva, Joana Ribeiro; Mendes, Inês; Rosa, Catarina; Ribeiro, António P; Batista, João; Sousa, Inês; Fernandes, Carlos F

    2017-07-01

    Innovative moments (IMs) are new and more adjusted ways of thinking, acting, feeling and relating that emerge during psychotherapy. Previous research on IMs has provided sustainable evidence that IMs differentiate recovered from unchanged psychotherapy cases. However, studies with cognitive behavioural therapy (CBT) are so far absent. The present study tests whether IMs can be reliably identified in CBT and examines if IMs and symptoms' improvement are associated. The following variables were assessed in each session from a sample of six cases of CBT for depression (a total of 111 sessions): (a) symptomatology outcomes (Outcome Questionnaire-OQ-10) and (b) IMs. Two hierarchical linear models were used: one to test whether IMs predicted a symptom decrease in the next session and a second one to test whether symptoms in one session predicted the emergence of IMs in the next session. Innovative moments were better predictors of symptom decrease than the reverse. A higher proportion of a specific type of IMs-reflection 2-in one session predicted a decrease in symptoms in the next session. Thus, when clients further elaborated this type of IM (in which clients describe positive contrasts or elaborate on changes processes), a reduction in symptoms was observed in the next session. A higher expression and elaboration of reflection 2 IMs appear to have a facilitative function in the reduction of depressive symptoms in this sample of CBT. Copyright © 2016 John Wiley & Sons, Ltd. Elaborating innovative moments (IMs) that are new ways of thinking, feeling, behaving and relating, in the therapeutic dialogue, may facilitate change. IMs that are more predictive of amelioration of symptoms in CBT are the ones focused on contrasts between former problematic patterns and new adjusted ones; and the ones in which the clients elaborate on processes of change. Therapists may integrate these kinds of questions (centred on contrasts and centred on what allowed change from the client

  11. Changes in Quadriceps Muscle Activity During Sustained Recreational Alpine Skiing

    Science.gov (United States)

    Kröll, Josef; Müller, Erich; Seifert, John G.; Wakeling, James M.

    2011-01-01

    During a day of skiing thousands of repeated contractions take place. Previous research on prolonged recreational alpine skiing show that physiological changes occur and hence some level of fatigue is inevitable. In the present paper the effect of prolonged skiing on the recruitment and coordination of the muscle activity was investigated. Six subjects performed 24 standardized runs. Muscle activity during the first two (PREskiing) and the last two (POSTskiing) runs was measured from the vastus lateralis (VL) and rectus femoris (RF) using EMG and quantified using wavelet and principal component analysis. The frequency content of the EMG signal shifted in seven out of eight cases significantly towards lower frequencies with highest effects observed for RF on outside leg. A significant pronounced outside leg loading occurred during POSTskiing and the timing of muscle activity peaks occurred more towards turn completion. Specific EMG frequency changes were observed at certain time points throughout the time windows and not over the whole double turn. It is suggested that general muscular fatigue, where additional specific muscle fibers have to be recruited due to the reduced power output of other fibers did not occur. The EMG frequency decrease and intensity changes for RF and VL are caused by altered timing (coordination) within the turn towards a most likely more uncontrolled skiing technique. Hence, these data provide evidence to suggest recreational skiers alter their skiing technique before a potential change in muscle fiber recruitment occurs. Key points The frequency content of the EMG signal shifted in seven out of eight cases significantly towards lower frequencies with highest effects observed for RF. General muscular fatigue, where additional specific fibers have to be recruited due to the reduced power output of other fibers, did not occur. A modified skiing style towards a less functional and hence more uncontrolled skiing technique seems to be a key

  12. Alcohol-related problems and life satisfaction predict motivation to change among mandated college students.

    Science.gov (United States)

    Diulio, Andrea R; Cero, Ian; Witte, Tracy K; Correia, Christopher J

    2014-04-01

    The present study investigated the role specific types of alcohol-related problems and life satisfaction play in predicting motivation to change alcohol use. Participants were 548 college students mandated to complete a brief intervention following an alcohol-related policy violation. Using hierarchical multiple regression, we tested for the presence of interaction and quadratic effects on baseline data collected prior to the intervention. A significant interaction indicated that the relationship between a respondent's personal consequences and his/her motivation to change differs depending upon the level of concurrent social consequences. Additionally quadratic effects for abuse/dependence symptoms and life satisfaction were found. The quadratic probes suggest that abuse/dependence symptoms and poor life satisfaction are both positively associated with motivation to change for a majority of the sample; however, the nature of these relationships changes for participants with more extreme scores. Results support the utility of using a multidimensional measure of alcohol related problems and assessing non-linear relationships when assessing predictors of motivation to change. The results also suggest that the best strategies for increasing motivation may vary depending on the types of alcohol-related problems and level of life satisfaction the student is experiencing and highlight potential directions for future research. Copyright © 2014. Published by Elsevier Ltd.

  13. Heterogeneity in development of aspects of working memory predicts longitudinal attention deficit hyperactivity disorder symptom change.

    Science.gov (United States)

    Karalunas, Sarah L; Gustafsson, Hanna C; Dieckmann, Nathan F; Tipsord, Jessica; Mitchell, Suzanne H; Nigg, Joel T

    2017-08-01

    The role of cognitive mechanisms in the clinical course of neurodevelopmental disorders is poorly understood. Attention Deficit Hyperactivity Disorder (ADHD) is emblematic in that numerous alterations in cognitive development are apparent, yet how they relate to changes in symptom expression with age is unclear. To resolve the role of cognitive mechanisms in ADHD, a developmental perspective that takes into account expected within-group heterogeneity is needed. The current study uses an accelerated longitudinal design and latent trajectory growth mixture models in a sample of children ages 7-13 years carefully characterized as with (n = 437) and without (n = 297) ADHD to (a) identify heterogeneous developmental trajectories for response inhibition, visual spatial working memory maintenance, and delayed reward discounting and (b) to assess the relationships between these cognitive trajectories and ADHD symptom change. Best-fitting models indicated multiple trajectory classes in both the ADHD and typically developing samples, as well as distinct relationships between each cognitive process and ADHD symptom change. Developmental change in response inhibition and delayed reward discounting were unrelated to ADHD symptom change, while individual differences in the rate of visual spatial working memory maintenance improvement predicted symptom remission in ADHD. Characterizing heterogeneity in cognitive development will be crucial for clarifying mechanisms of symptom persistence and recovery. Results here suggest working memory maintenance may be uniquely related to ADHD symptom improvement. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  14. Vigorous physical activity predicts higher heart rate variability among younger adults.

    Science.gov (United States)

    May, Richard; McBerty, Victoria; Zaky, Adam; Gianotti, Melino

    2017-06-14

    Baseline heart rate variability (HRV) is linked to prospective cardiovascular health. We tested intensity and duration of weekly physical activity as predictors of heart rate variability in young adults. Time and frequency domain indices of HRV were calculated based on 5-min resting electrocardiograms collected from 82 undergraduate students. Hours per week of both moderate and vigorous activity were estimated using the International Physical Activity Questionnaire. In regression analyses, hours of vigorous physical activity, but not moderate activity, significantly predicted greater time domain and frequency domain indices of heart rate variability. Adjusted for weekly frequency, greater daily duration of vigorous activity failed to predict HRV indices. Future studies should test direct measurements of vigorous activity patterns as predictors of autonomic function in young adulthood.

  15. Health Impacts of Increased Physical Activity from Changes in Transportation Infrastructure: Quantitative Estimates for Three Communities

    Science.gov (United States)

    2015-01-01

    Recently, two quantitative tools have emerged for predicting the health impacts of projects that change population physical activity: the Health Economic Assessment Tool (HEAT) and Dynamic Modeling for Health Impact Assessment (DYNAMO-HIA). HEAT has been used to support health impact assessments of transportation infrastructure projects, but DYNAMO-HIA has not been previously employed for this purpose nor have the two tools been compared. To demonstrate the use of DYNAMO-HIA for supporting health impact assessments of transportation infrastructure projects, we employed the model in three communities (urban, suburban, and rural) in North Carolina. We also compared DYNAMO-HIA and HEAT predictions in the urban community. Using DYNAMO-HIA, we estimated benefit-cost ratios of 20.2 (95% C.I.: 8.7–30.6), 0.6 (0.3–0.9), and 4.7 (2.1–7.1) for the urban, suburban, and rural projects, respectively. For a 40-year time period, the HEAT predictions of deaths avoided by the urban infrastructure project were three times as high as DYNAMO-HIA's predictions due to HEAT's inability to account for changing population health characteristics over time. Quantitative health impact assessment coupled with economic valuation is a powerful tool for integrating health considerations into transportation decision-making. However, to avoid overestimating benefits, such quantitative HIAs should use dynamic, rather than static, approaches. PMID:26504832

  16. Using Prediction Markets to Generate Probability Density Functions for Climate Change Risk Assessment

    Science.gov (United States)

    Boslough, M.

    2011-12-01

    Climate-related uncertainty is traditionally presented as an error bar, but it is becoming increasingly common to express it in terms of a probability density function (PDF). PDFs are a necessary component of probabilistic risk assessments, for which simple "best estimate" values are insufficient. Many groups have generated PDFs for climate sensitivity using a variety of methods. These PDFs are broadly consistent, but vary significantly in their details. One axiom of the verification and validation community is, "codes don't make predictions, people make predictions." This is a statement of the fact that subject domain experts generate results using assumptions within a range of epistemic uncertainty and interpret them according to their expert opinion. Different experts with different methods will arrive at different PDFs. For effective decision support, a single consensus PDF would be useful. We suggest that market methods can be used to aggregate an ensemble of opinions into a single distribution that expresses the consensus. Prediction markets have been shown to be highly successful at forecasting the outcome of events ranging from elections to box office returns. In prediction markets, traders can take a position on whether some future event will or will not occur. These positions are expressed as contracts that are traded in a double-action market that aggregates price, which can be interpreted as a consensus probability that the event will take place. Since climate sensitivity cannot directly be measured, it cannot be predicted. However, the changes in global mean surface temperature are a direct consequence of climate sensitivity, changes in forcing, and internal variability. Viable prediction markets require an undisputed event outcome on a specific date. Climate-related markets exist on Intrade.com, an online trading exchange. One such contract is titled "Global Temperature Anomaly for Dec 2011 to be greater than 0.65 Degrees C." Settlement is based

  17. Betting and Belief: Modeling the Impact of Prediction Markets on Public Attribution of Climate Change

    Science.gov (United States)

    Gilligan, J. M.; Nay, J. J.; van der Linden, M.

    2016-12-01

    Despite overwhelming scientific evidence and an almost complete consensus among scientists, a large fraction of the American public is not convinced that global warming is anthropogenic. This doubt correlates strongly with political, ideological, and cultural orientation. [1] It has been proposed that people who do not trust climate scientists tend to trust markets, so prediction markets might be able to influence their beliefs about the causes of climate change. [2] We present results from an agent-based simulation of a prediction market in which traders invest based on their beliefs about what drives global temperature change (here, either CO2 concentration or total solar irradiance (TSI), which is a popular hypothesis among many who doubt the dominant role of CO2). At each time step, traders use historical and observed temperatures and projected future forcings (CO2 or TSI) to update Bayesian posterior probability distributions for future temperatures, conditional on their belief about what drives climate change. Traders then bet on future temperatures by trading in climate futures. Trading proceeds by a continuous double auction. Traders are randomly assigned initial beliefs about climate change, and they have some probability of changing their beliefs to match those of the most successful traders in their social network. We simulate two alternate realities in which the global temperature is controlled either by CO2 or by TSI, with stochastic noise. In both cases traders' beliefs converge, with a large majority reaching agreement on the actual cause of climate change. This convergence is robust, but the speed with which consensus emerges depends on characteristics of the traders' psychology and the structure of the market. Our model can serve as a test-bed for studying how beliefs might evolve under different market structures and different modes of decision-making and belief-change. We will report progress on studying alternate models of belief-change. This

  18. Are Remotely Sensed Trends in the Built Environment and Urban Vegetation Predictive of Changes in Metropolitan Housing Markets?

    Science.gov (United States)

    Endsley, K. A.

    2017-12-01

    In the midst of a global urbanization trend, residential neighborhoods are undergoing a variety of changes, including neighborhood turnover, the re-location of employment centers, and, recently, the increasing social and economic isolation of the suburbs. In the U.S., where residential lawns account for more area than any other irrigated crop (Polsky et al. 2014, in PNAS), coeval changes in residential populations, the built environment, and vegetation have serious implications for urban sustainability. To date, detailed studies of dynamic neighborhood changes have been hampered by the lack of fine time-series data on neighborhood composition. Most notably, the U.S. Census is conducted only once every decade leading to the likely inaccurate assumption of linear change between Census years. To the extent that human activities alter the built environment and urban ecology, can remotely sensed biophysical changes serve as a good proxy for neighborhood socio-economic changes? In this study, I apply time series data on spectral reflectance, spectral indices, and land-cover abundances from 15-to-25 years of Landsat data to fine-scale data on residential property transactions in two metropolitan areas with different regional economic and environmental contexts: Detroit and Los Angeles. The real estate record provides parcel-level, monthly data on sale prices and tax foreclosures; taken together, these provide a good description of the housing market and an acceptable proxy for neighborhood stability. By comparing lagged features from the remote sensing (RS) archive at different time scales in a non-parametric statistical learning algorithm, I identify which RS features best predict changes in the housing market and compare these associations between the two metropolitan areas and across multiple spatial and temporal scales along an urban to peri-urban gradient.

  19. Changes of resting cerebral activities in subacute ischemic stroke patients

    Directory of Open Access Journals (Sweden)

    Ping Wu

    2015-01-01

    Full Text Available This study aimed to detect the difference in resting cerebral activities between ischemic stroke patients and healthy participants, define the abnormal site, and provide new evidence for pathological mechanisms, clinical diagnosis, prognosis prediction and efficacy evaluation of ischemic stroke. At present, the majority of functional magnetic resonance imaging studies focus on the motor dysfunction and the acute stage of ischemic stroke. This study recruited 15 right-handed ischemic stroke patients at subacute stage (15 days to 11.5 weeks and 15 age-matched healthy participants. A resting-state functional magnetic resonance imaging scan was performed on each subject to detect cerebral activity. Regional homogeneity analysis was used to investigate the difference in cerebral activities between ischemic stroke patients and healthy participants. The results showed that the ischemic stroke patients had lower regional homogeneity in anterior cingulate and left cerebrum and higher regional homogeneity in cerebellum, left precuneus and left frontal lobe, compared with healthy participants. The experimental findings demonstrate that the areas in which regional homogeneity was different between ischemic stroke patients and healthy participants are in the cerebellum, left precuneus, left triangle inferior frontal gyrus, left inferior temporal gyrus and anterior cingulate. These locations, related to the motor, sensory and emotion areas, are likely potential targets for the neural regeneration of subacute ischemic stroke patients.

  20. A Trap Motion in Validating Muscle Activity Prediction from Musculoskeletal Model using EMG

    NARCIS (Netherlands)

    Wibawa, A. D.; Verdonschot, N.; Halbertsma, J.P.K.; Burgerhof, J.G.M.; Diercks, R.L.; Verkerke, G. J.

    2016-01-01

    Musculoskeletal modeling nowadays is becoming the most common tool for studying and analyzing human motion. Besides its potential in predicting muscle activity and muscle force during active motion, musculoskeletal modeling can also calculate many important kinetic data that are difficult to measure

  1. Predictive factors of unfavorable prostate cancer in patients who underwent prostatectomy but eligible for active surveillance

    Directory of Open Access Journals (Sweden)

    Seol Ho Choo

    2014-06-01

    Conclusions: A significant proportion of patients who were candidates for active surveillance had unfavorable prostate cancer. Age, PSA density, and two positive cores were independent significant predictive factors for unfavorable prostate cancer. These factors should be considered when performing active surveillance.

  2. New active drugs against liver stages of Plasmodium predicted by molecular topology.

    NARCIS (Netherlands)

    Mahmoudi, N.; Garcia-Domenech, R.; Galvez, J.; Farhati, K.; Franetich, J.F.; Sauerwein, R.W.; Hannoun, L.; Derouin, F.; Danis, M.; Mazier, D.

    2008-01-01

    We conducted a quantitative structure-activity relationship (QSAR) study based on a database of 127 compounds previously tested against the liver stage of Plasmodium yoelii in order to develop a model capable of predicting the in vitro antimalarial activities of new compounds. Topological indices

  3. Predicting Antitumor Activity of Peptides by Consensus of Regression Models Trained on a Small Data Sample

    Directory of Open Access Journals (Sweden)

    Ivanka Jerić

    2011-11-01

    Full Text Available Predicting antitumor activity of compounds using regression models trained on a small number of compounds with measured biological activity is an ill-posed inverse problem. Yet, it occurs very often within the academic community. To counteract, up to some extent, overfitting problems caused by a small training data, we propose to use consensus of six regression models for prediction of biological activity of virtual library of compounds. The QSAR descriptors of 22 compounds related to the opioid growth factor (OGF, Tyr-Gly-Gly-Phe-Met with known antitumor activity were used to train regression models: the feed-forward artificial neural network, the k-nearest neighbor, sparseness constrained linear regression, the linear and nonlinear (with polynomial and Gaussian kernel support vector machine. Regression models were applied on a virtual library of 429 compounds that resulted in six lists with candidate compounds ranked by predicted antitumor activity. The highly ranked candidate compounds were synthesized, characterized and tested for an antiproliferative activity. Some of prepared peptides showed more pronounced activity compared with the native OGF; however, they were less active than highly ranked compounds selected previously by the radial basis function support vector machine (RBF SVM regression model. The ill-posedness of the related inverse problem causes unstable behavior of trained regression models on test data. These results point to high complexity of prediction based on the regression models trained on a small data sample.

  4. M-ficolin levels reflect disease activity and predict remission in early rheumatoid arthritis

    DEFF Research Database (Denmark)

    Ammitzbøll, Christian Gytz; Thiel, Steffen; Jensenius, Jens Christian

    2013-01-01

    To assess plasma M-ficolin concentrations in disease-modifying antirheumatic drug (DMARD)-naive patients with early rheumatoid arthritis (RA), to investigate the correlation of M-ficolin concentrations with disease activity markers, and to determine the predictive value of M-ficolin with respect...... to the Disease Activity Score in 28 joints (DAS28)....

  5. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    Science.gov (United States)

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

  6. High serum ACE activity predicts severe hypoglycaemia over time in patients with type 1 diabetes

    DEFF Research Database (Denmark)

    Færch, Louise; Pedersen-Bjergaard, Ulrik; Thorsteinsson, Birger

    2011-01-01

    High serum angiotensin-converting enzyme (ACE) activity is associated with increased risk of severe hypoglycaemia (SH) within 1 year in type 1 diabetes. We wanted to find out whether ACE activity is stable over time and predicts SH beyond 1 year, and if gender differences exist in the association...

  7. Investigation of an alternative generic model for predicting pharmacokinetic changes during physiological stress.

    Science.gov (United States)

    Peng, Henry T; Edginton, Andrea N; Cheung, Bob

    2013-10-01

    Physiologically based pharmacokinetic models were developed using MATLAB Simulink® and PK-Sim®. We compared the capability and usefulness of these two models by simulating pharmacokinetic changes of midazolam under exercise and heat stress to verify the usefulness of MATLAB Simulink® as a generic PBPK modeling software. Although both models show good agreement with experimental data obtained under resting condition, their predictions of pharmacokinetics changes are less accurate in the stressful conditions. However, MATLAB Simulink® may be more flexible to include physiologically based processes such as oral absorption and simulate various stress parameters such as stress intensity, duration and timing of drug administration to improve model performance. Further work will be conducted to modify algorithms in our generic model developed using MATLAB Simulink® and to investigate pharmacokinetics under other physiological stress such as trauma. © The Author(s) 2013.

  8. Prediction of pressure induced structural phase transitions and internal mode frequency changes in solid N2+

    International Nuclear Information System (INIS)

    Etters, R.D.; Kobashi, K.; Chandrasekharan, V.

    1983-01-01

    A rhombohedral distortion of the Pm3n structure is introduced which shows that a low temperature phase transition occurs from P4 2 /mnm into the R3c calcite structure at P approx. = 19.2 kbar with a volume change of 0.125 cm 3 /mole. This transition agrees with recent Raman scattering measurements. Another transition from R3c into R3m is predicted at P approx. = 67.5 kbar, with a volume change of 0.1 cm 3 /mole. The pressure dependence of the intramolecular mode frequencies for the R3c structure is in reasonably good agreement with the two main branches observed experimentally

  9. Changes in CVD risk factors in the activity counseling trial

    Directory of Open Access Journals (Sweden)

    Meghan Baruth

    2011-01-01

    Full Text Available Meghan Baruth1, Sara Wilcox1, James F Sallis3, Abby C King4,5, Bess H Marcus6, Steven N Blair1,21Department of Exercise Science, 2Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Public Health Research Center, Columbia, SC, USA; 3Department of Psychology, San Diego State University, San Diego, CA, USA; 4Department of Health Research and Policy, 5Stanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA; 6Behavioral and Social Sciences Section, Brown University Program in Public Health, Providence, RI, USAAbstract: Primary care facilities may be a natural setting for delivering interventions that focus on behaviors that improve cardiovascular disease (CVD risk factors. The purpose of this study was to examine the 24-month effects of the Activity Counseling Trial (ACT on CVD risk factors, to examine whether changes in CVD risk factors differed according to baseline risk factor status, and to examine whether changes in fitness were associated with changes in CVD risk factors. ACT was a 24-month multicenter randomized controlled trial to increase physical activity. Participants were 874 inactive men and women aged 35–74 years. Participants were randomly assigned to one of three arms that varied by level of counseling, intensity, and resource requirements. Because there were no significant differences in change over time between arms on any of the CVD risk factors examined, all arms were combined, and the effects of time, independent of arm, were examined separately for men and women. Time × Baseline risk factor status interactions examined whether changes in CVD risk factors differed according to baseline risk factor status. Significant improvements in total cholesterol, high-density lipoprotein cholesterol (HDL-C and low-density lipoprotein cholesterol, the ratio of total cholesterol to HDL-C, and triglycerides were seen in

  10. Changes of spontaneous oscillatory activity to tonic heat pain.

    Science.gov (United States)

    Peng, Weiwei; Hu, Li; Zhang, Zhiguo; Hu, Yong

    2014-01-01

    Transient painful stimuli could induce suppression of alpha oscillatory activities and enhancement of gamma oscillatory activities that also could be greatly modulated by attention. Here, we attempted to characterize changes in cortical activities during tonic heat pain perception and investigated the influence of directed/distracted attention on these responses. We collected 5-minute long continuous Electroencephalography (EEG) data from 38 healthy volunteers during four conditions presented in a counterbalanced order: (A) resting condition; (B) innoxious-distracted condition; (C) noxious-distracted condition; (D) noxious-attended condition. The effects of tonic heat pain stimulation and selective attention on oscillatory activities were investigated by comparing the EEG power spectra among the four experimental conditions and assessing the relationship between spectral power difference and subjective pain intensity. The change of oscillatory activities in condition D was characterized by stable and persistent decrease of alpha oscillation power over contralateral-central electrodes and widespread increase of gamma oscillation power, which were even significantly correlated with subjective pain intensity. Since EEG responses in the alpha and gamma frequency band were affected by attention in different manners, they are likely related to different aspects of the multidimensional sensory experience of pain. The observed contralateral-central alpha suppression (conditions D vs. B and D vs. C) may reflect primarily a top-down cognitive process such as attention, while the widespread gamma enhancement (conditions D vs. A) may partly reflect tonic pain processing, representing the summary effects of bottom-up stimulus-related and top-down subject-driven cognitive processes.

  11. Changes of spontaneous oscillatory activity to tonic heat pain.

    Directory of Open Access Journals (Sweden)

    Weiwei Peng

    Full Text Available Transient painful stimuli could induce suppression of alpha oscillatory activities and enhancement of gamma oscillatory activities that also could be greatly modulated by attention. Here, we attempted to characterize changes in cortical activities during tonic heat pain perception and investigated the influence of directed/distracted attention on these responses. We collected 5-minute long continuous Electroencephalography (EEG data from 38 healthy volunteers during four conditions presented in a counterbalanced order: (A resting condition; (B innoxious-distracted condition; (C noxious-distracted condition; (D noxious-attended condition. The effects of tonic heat pain stimulation and selective attention on oscillatory activities were investigated by comparing the EEG power spectra among the four experimental conditions and assessing the relationship between spectral power difference and subjective pain intensity. The change of oscillatory activities in condition D was characterized by stable and persistent decrease of alpha oscillation power over contralateral-central electrodes and widespread increase of gamma oscillation power, which were even significantly correlated with subjective pain intensity. Since EEG responses in the alpha and gamma frequency band were affected by attention in different manners, they are likely related to different aspects of the multidimensional sensory experience of pain. The observed contralateral-central alpha suppression (conditions D vs. B and D vs. C may reflect primarily a top-down cognitive process such as attention, while the widespread gamma enhancement (conditions D vs. A may partly reflect tonic pain processing, representing the summary effects of bottom-up stimulus-related and top-down subject-driven cognitive processes.

  12. Predicted disappearance of Cephalantheropsis obcordata in Luofu Mountain due to changes in rainfall patterns.

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    Xin-Ju Xiao

    Full Text Available BACKGROUND: In the past century, the global average temperature has increased by approximately 0.74°C and extreme weather events have become prevalent. Recent studies have shown that species have shifted from high-elevation areas to low ones because the rise in temperature has increased rainfall. These outcomes challenge the existing hypothesis about the responses of species to climate change. METHODOLOGY/PRINCIPAL FINDINGS: With the use of data on the biological characteristics and reproductive behavior of Cephalantheropsis obcordata in Luofu Mountain, Guangdong, China, trends in the population size of the species were predicted based on several factors. The response of C. obcordata to climate change was verified by integrating it with analytical findings on meteorological data and an artificially simulated environment of water change. The results showed that C. obcordata can grow only in waterlogged streams. The species can produce fruit with many seeds by insect pollination; however, very few seeds can burgeon to become seedlings, with most of those seedlings not maturing into the sexually reproductive phase, and grass plants will die after reproduction. The current population's age pyramid is kettle-shaped; it has a Deevey type I survival curve; and its net reproductive rate, intrinsic rate of increase, as well as finite rate of increase are all very low. The population used in the artificial simulation perished due to seasonal drought. CONCLUSIONS: The change in rainfall patterns caused by climate warming has altered the water environment of C. obcordata in Luofu Mountain, thereby restricting seed burgeoning as well as seedling growth and shortening the life span of the plant. The growth rate of the C. obcordata population is in descending order, and models of population trend predict that the population in Luofu Mountain will disappear in 23 years.

  13. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms

    Energy Technology Data Exchange (ETDEWEB)

    Ripszam, M., E-mail: matyas.ripszam@chem.umu.se [Department of Chemistry, Umea University, 901 87 Umeå (Sweden); Gallampois, C.M.J. [Department of Chemistry, Umea University, 901 87 Umeå (Sweden); Berglund, Å. [Department of Ecology and Environmental Sciences, Umeå University, 901 87 Umeå (Sweden); Larsson, H. [Umeå Marine Sciences Centre, Umeå University, Norrbyn, 905 71 Hörnefors (Sweden); Andersson, A. [Department of Ecology and Environmental Sciences, Umeå University, 901 87 Umeå (Sweden); Tysklind, M.; Haglund, P. [Department of Chemistry, Umea University, 901 87 Umeå (Sweden)

    2015-06-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15 °C and 4 mg DOC L{sup −1} and, within ranges of predicted increases, 18 °C and 6 mg DOC L{sup −1}, respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. - Highlights: • More contaminants remained in the ecosystem at higher organic carbon levels. • More contaminants were lost in the higher temperature treatments. • The combined effects are competitive with respect to contaminant cycling. • The individual properties of each contaminant determine their respective fate.

  14. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms

    International Nuclear Information System (INIS)

    Ripszam, M.; Gallampois, C.M.J.; Berglund, Å.; Larsson, H.; Andersson, A.; Tysklind, M.; Haglund, P.

    2015-01-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15 °C and 4 mg DOC L −1 and, within ranges of predicted increases, 18 °C and 6 mg DOC L −1 , respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. - Highlights: • More contaminants remained in the ecosystem at higher organic carbon levels. • More contaminants were lost in the higher temperature treatments. • The combined effects are competitive with respect to contaminant cycling. • The individual properties of each contaminant determine their respective fate

  15. Design and implementation of predictive filtering system for current reference generation of active power filter

    Energy Technology Data Exchange (ETDEWEB)

    Kilic, Tomislav; Milun, Stanko; Petrovic, Goran [FESB University of Split, Faculty of Electrical Engineering, Machine Engineering and Naval Architecture, R. Boskovica bb, 21000, Split (Croatia)

    2007-02-15

    The shunt active power filters are used to attenuate the harmonic currents in power systems by injecting equal but opposite compensating currents. Successful control of the active filters requires an accurate current reference. In this paper the current reference determination based on predictive filtering structure is presented. Current reference was obtained by taking the difference of load current and its fundamental harmonic. For fundamental harmonic determination with no time delay a combination of digital predictive filter and low pass filter is used. The proposed method was implemented on a laboratory prototype of a three-phase active power filter. The algorithm for current reference determination was adapted and implemented on DSP controller. Simulation and experimental results show that the active power filter with implemented predictive filtering structure gives satisfactory performance in power system harmonic attenuation. (author)

  16. Activity Prediction of Schiff Base Compounds using Improved QSAR Models of Cinnamaldehyde Analogues and Derivatives

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2015-10-01

    Full Text Available In past work, QSAR (quantitative structure-activity relationship models of cinnamaldehyde analogues and derivatives (CADs have been used to predict the activities of new chemicals based on their mass concentrations, but these approaches are not without shortcomings. Therefore, molar concentrations were used instead of mass concentrations to determine antifungal activity. New QSAR models of CADs against Aspergillus niger and Penicillium citrinum were established, and the molecular design of new CADs was performed. The antifungal properties of the designed CADs were tested, and the experimental Log AR values were in agreement with the predicted Log AR values. The results indicate that the improved QSAR models are more reliable and can be effectively used for CADs molecular design and prediction of the activity of CADs. These findings provide new insight into the development and utilization of cinnamaldehyde compounds.

  17. Anthropogenic Changes in Mid-latitude Storm and Blocking Activities from Observations and Climate Models

    Science.gov (United States)

    Li, D.

    2017-12-01

    Fingerprints of anthropogenic climate change can be most readily detected in the high latitudes of Northern Hemisphere, where temperature has been rising faster than the rest of the globe and sea ice cover has shrunk dramatically over recent decades. Reducing the meridional temperature gradient, this amplified warming over the high latitudes influences weather in the middle latitudes by modulating the jet stream, storms, and atmospheric blocking activities. Whether observational records have revealed significant changes in mid-latitude storms and blocking activities, however, has remained a subject of much debate. Buried deep in strong year-to-year variations, the long-term dynamic responses of the atmosphere are more difficult to identify, compared with its thermodynamic responses. Variabilities of decadal and longer timescales further obscure any trends diagnosed from satellite observations, which are often shorter than 40 years. Here, new metrics reflecting storm and blocking activities are developed using surface air temperature and pressure records, and their variations and long-term trends are examined. This approach gives an inkling of the changes in storm and blocking activities since the Industrial Revolution in regions with abundant long-term observational records, e.g. Europe and North America. The relationship between Atlantic Multi-decadal Oscillation and variations in storm and blocking activities across the Atlantic is also scrutinized. The connection between observed centennial trends and anthropogenic forcings is investigated using a hierarchy of numerical tools, from highly idealized to fully coupled atmosphere-ocean models. Pre-industrial control simulations and a set of large ensemble simulations forced by increased CO2 are analyzed to evaluate the range of natural variabilities, which paves the way to singling out significant anthropogenic changes from observational records, as well as predicting future changes in mid-latitude storm and

  18. Longitudinal changes in sedentary time and physical activity during adolescence.

    Science.gov (United States)

    Harding, Sarah K; Page, Angie S; Falconer, Catherine; Cooper, Ashley R

    2015-04-01

    Low levels of physical activity and high time spent in sedentary activities have been associated with unfavourable health outcomes in adolescents. During adolescence, physical activity declines and sedentary time increases, however little is known about whether the magnitude of these changes differs within or between school-time, after-school time, or at weekends. Adolescents (n = 363) participating in the PEACH (Personal and Environmental Associations with Children's Health) project provided accelerometer data at 12 and 15 years of age. Data were collected in 2008/2009 and 2012/2013. Time spent sedentary (physical activity (LPA (100-2295 cpm) and in moderate to vigorous physical activity (MVPA: ≥ 2296 cpm) were generated for school-time, after-school time and for weekends using school-specific start and finish times. All data were analysed in 2014. The proportion of time spent sedentary significantly increased during school (+8.23%, 95% CI = 7.35 to 9.13), after-school (+6.99%, 95% CI = 5.91 to 8.07) and at weekends (+6.86%, 95% CI = 5.10 to 8.62). A parallel decrease was found in the proportion of time spent in LPA during school (-7.62%, 95% CI = -8.26 to -6.98), after-school (-7.01%, 95% CI = -7.74 to -6.28) and at weekends (-6.72%, 95% CI = -7.80 to -5.65). The proportion of time spent in MVPA remained relatively stable during school (-0.64, 95% CI = -1.11 to -0.18), after-school (0.04%, 95% CI = -0.58 to 0.67) and at weekends (-0.14%, 95% CI = -1.18 to 0.90). Objectively measured sedentary time increased between 12 and 15 years of age during-school, after-school, and at weekends, suggesting that interventions aiming to reduce the age-associated changes in sedentary time are needed in all three time contexts. Future work should identify which sedentary activities change more than others to inform interventions which aim to minimise the increase in time spent sedentary during adolescence.

  19. Prediction of Land Use Change in Long Island Sound Watersheds Using Nighttime Light Data

    Directory of Open Access Journals (Sweden)

    Ruiting Zhai

    2016-12-01

    Full Text Available The Long Island Sound Watersheds (LISW are experiencing significant land use/cover change (LUCC, which affects the environment and ecosystems in the watersheds through water pollution, carbon emissions, and loss of wildlife. LUCC modeling is an important approach to understanding what has happened in the landscape and what may change in the future. Moreover, prospective modeling can provide sustainable and efficient decision support for land planning and environmental management. This paper modeled the LUCCs between 1996, 2001 and 2006 in the LISW in the New England region, which experienced an increase in developed area and a decrease of forest. The low-density development pattern played an important role in the loss of forest and the expansion of urban areas. The key driving forces were distance to developed areas, distance to roads, and social-economic drivers, such as nighttime light intensity and population density. In addition, this paper compared and evaluated two integrated LUCC models—the logistic regression–Markov chain model and the multi-layer perception–Markov chain (MLP–MC model. Both models achieved high accuracy in prediction, but the MLP–MC model performed slightly better. Finally, a land use map for 2026 was predicted by using the MLP–MC model, and it indicates the continued loss of forest and increase of developed area.

  20. Space can substitute for time in predicting climate-change effects on biodiversity

    Science.gov (United States)

    Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

    2013-01-01

    “Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  1. Predicting the Potential Distribution of Polygala tenuifolia Willd. under Climate Change in China.

    Directory of Open Access Journals (Sweden)

    Hongjun Jiang

    Full Text Available Global warming has created opportunities and challenges for the survival and development of species. Determining how climate change may impact multiple ecosystem levels and lead to various species adaptations is necessary for both biodiversity conservation and sustainable biological resource utilization. In this study, we employed Maxent to predict changes in the habitat range and altitude of Polygala tenuifolia Willd. under current and future climate scenarios in China. Four representative concentration pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5 were modeled for two time periods (2050 and 2070. The model inputs included 732 presence points and nine sets of environmental variables under the current conditions and the four RCPs in 2050 and 2070. The area under the receiver-operating characteristic (ROC curve (AUC was used to evaluate model performance. All of the AUCs were greater than 0.80, thereby placing these models in the "very good" category. Using a jackknife analysis, the precipitation in the warmest quarter, annual mean temperature, and altitude were found to be the top three variables that affect the range of P. tenuifolia. Additionally, we found that the predicted highly suitable habitat was in reasonable agreement with its actual distribution. Furthermore, the highly suitable habitat area was slowly reduced over time.

  2. Predicting Effects of Water Regime Changes on Waterbirds: Insights from Staging Swans.

    Science.gov (United States)

    Nolet, Bart A; Gyimesi, Abel; van Krimpen, Roderick R D; de Boer, Willem F; Stillman, Richard A

    2016-01-01

    Predicting the environmental impact of a proposed development is notoriously difficult, especially when future conditions fall outside the current range of conditions. Individual-based approaches have been developed and applied to predict the impact of environmental changes on wintering and staging coastal bird populations. How many birds make use of staging sites is mostly determined by food availability and accessibility, which in the case of many waterbirds in turn is affected by water level. Many water systems are regulated and water levels are maintained at target levels, set by management authorities. We used an individual-based modelling framework (MORPH) to analyse how different target water levels affect the number of migratory Bewick's swans Cygnus columbianus bewickii staging at a shallow freshwater lake (Lauwersmeer, the Netherlands) in autumn. As an emerging property of the model, we found strong non-linear responses of swan usage to changes in water level, with a sudden drop in peak numbers as well as bird-days with a 0.20 m rise above the current target water level. Such strong non-linear responses are probably common and should be taken into account in environmental impact assessments.

  3. Predicting Effects of Water Regime Changes on Waterbirds: Insights from Staging Swans.

    Directory of Open Access Journals (Sweden)

    Bart A Nolet

    Full Text Available Predicting the environmental impact of a proposed development is notoriously difficult, especially when future conditions fall outside the current range of conditions. Individual-based approaches have been developed and applied to predict the impact of environmental changes on wintering and staging coastal bird populations. How many birds make use of staging sites is mostly determined by food availability and accessibility, which in the case of many waterbirds in turn is affected by water level. Many water systems are regulated and water levels are maintained at target levels, set by management authorities. We used an individual-based modelling framework (MORPH to analyse how different target water levels affect the number of migratory Bewick's swans Cygnus columbianus bewickii staging at a shallow freshwater lake (Lauwersmeer, the Netherlands in autumn. As an emerging property of the model, we found strong non-linear responses of swan usage to changes in water level, with a sudden drop in peak numbers as well as bird-days with a 0.20 m rise above the current target water level. Such strong non-linear responses are probably common and should be taken into account in environmental impact assessments.

  4. Space can substitute for time in predicting climate-change effects on biodiversity.

    Science.gov (United States)

    Blois, Jessica L; Williams, John W; Fitzpatrick, Matthew C; Jackson, Stephen T; Ferrier, Simon

    2013-06-04

    "Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  5. Sparse coding can predict primary visual cortex receptive field changes induced by abnormal visual input.

    Science.gov (United States)

    Hunt, Jonathan J; Dayan, Peter; Goodhill, Geoffrey J

    2013-01-01

    Receptive fields acquired through unsupervised learning of sparse representations of natural scenes have similar properties to primary visual cortex (V1) simple cell receptive fields. However, what drives in vivo development of receptive fields remains controversial. The strongest evidence for the importance of sensory experience in visual development comes from receptive field changes in animals reared with abnormal visual input. However, most sparse coding accounts have considered only normal visual input and the development of monocular receptive fields. Here, we applied three sparse coding models to binocular receptive field development across six abnormal rearing conditions. In every condition, the changes in receptive field properties previously observed experimentally were matched to a similar and highly faithful degree by all the models, suggesting that early sensory development can indeed be understood in terms of an impetus towards sparsity. As previously predicted in the literature, we found that asymmetries in inter-ocular correlation across orientations lead to orientation-specific binocular receptive fields. Finally we used our models to design a novel stimulus that, if present during rearing, is predicted by the sparsity principle to lead robustly to radically abnormal receptive fields.

  6. Void fraction prediction in two-phase flows independent of the liquid phase density changes

    International Nuclear Information System (INIS)

    Nazemi, E.; Feghhi, S.A.H.; Roshani, G.H.

    2014-01-01

    Gamma-ray densitometry is a frequently used non-invasive method to determine void fraction in two-phase gas liquid pipe flows. Performance of flow meters using gamma-ray attenuation depends strongly on the fluid properties. Variations of the fluid properties such as density in situations where temperature and pressure fluctuate would cause significant errors in determination of the void fraction in two-phase flows. A conventional solution overcoming such an obstacle is periodical recalibration which is a difficult task. This paper presents a method based on dual modality densitometry using Artificial Neural Network (ANN), which offers the advantage of measuring the void fraction independent of the liquid phase changes. An experimental setup was implemented to generate the required input data for training the network. ANNs were trained on the registered counts of the transmission and scattering detectors in different liquid phase densities and void fractions. Void fractions were predicted by ANNs with mean relative error of less than 0.45% in density variations range of 0.735 up to 0.98 gcm −3 . Applying this method would improve the performance of two-phase flow meters and eliminates the necessity of periodical recalibration. - Highlights: • Void fraction was predicted independent of density changes. • Recorded counts of detectors/void fraction were used as inputs/output of ANN. • ANN eliminated necessity of recalibration in changeable density of two-phase flows

  7. Photometric changes on Saturn's Titan: Evidence for active cryovolcanism

    Science.gov (United States)

    Nelson, R.M.; Kamp, L.W.; Lopes, R.M.C.; Matson, D.L.; Kirk, R.L.; Hapke, B.W.; Wall, S.D.; Boryta, M.D.; Leader, F.E.; Smythe, W.D.; Mitchell, K.L.; Baines, K.H.; Jaumann, R.; Sotin, Christophe; Clark, R.N.; Cruikshank, D.P.; Drossart, P.; Lunine, J.I.; Combes, M.; Bellucci, G.; Bibring, J.-P.; Capaccioni, F.; Cerroni, P.; Coradini, A.; Formisano, V.; Filacchione, G.; Langevin, Y.; McCord, T.B.; Mennella, V.; Nicholson, P.D.; Sicardy, B.; Irwin, P.G.J.; Pearl, J.C.

    2009-01-01

    We report infrared spectrophotometric variability on the surface of Saturn's moon Titan detected in images returned by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini Saturn Orbiter. The changes were observed at 7??S, 138??W and occurred between October 27, 2005 and January 15, 2006. After that date the surface was unchanged until the most recent observation, March 18, 2006. We previously reported spectrophotometric variability at another location (26??S, 78??W). Cassini Synthetic Aperture RADAR (SAR) images find that the surface morphology at both locations is consistent with surface flows possibly resulting from cryovolcanic activity (Wall et al., companion paper, this issue). The VIMS-reported time variability and SAR morphology results suggest that Titan currently exhibits intermittent surface changes consistent with present ongoing surface processes. We suggest that these processes involve material from Titan's interior being extruded or effiised and deposited on the surface, as might be expected from cryovolcanism. ?? 2009.

  8. Photonic crystals cause active colour change in chameleons

    Science.gov (United States)

    Teyssier, Jérémie; Saenko, Suzanne V.; van der Marel, Dirk; Milinkovitch, Michel C.

    2015-03-01

    Many chameleons, and panther chameleons in particular, have the remarkable ability to exhibit complex and rapid colour changes during social interactions such as male contests or courtship. It is generally interpreted t