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Sample records for activity change predict

  1. Predicting changes in volcanic activity through modelling magma ascent rate.

    Science.gov (United States)

    Thomas, Mark; Neuberg, Jurgen

    2013-04-01

    It is a simple fact that changes in volcanic activity happen and in retrospect they are easy to spot, the dissimilar eruption dynamics between an effusive and explosive event are not hard to miss. However to be able to predict such changes is a much more complicated process. To cause altering styles of activity we know that some part or combination of parts within the system must vary with time, as if there is no physical change within the system, why would the change in eruptive activity occur? What is unknown is which parts or how big a change is needed. We present the results of a suite of conduit flow models that aim to answer these questions by assessing the influence of individual model parameters such as the dissolved water content or magma temperature. By altering these variables in a systematic manner we measure the effect of the changes by observing the modelled ascent rate. We use the ascent rate as we believe it is a very important indicator that can control the style of eruptive activity. In particular, we found that the sensitivity of the ascent rate to small changes in model parameters surprising. Linking these changes to observable monitoring data in a way that these data could be used as a predictive tool is the ultimate goal of this work. We will show that changes in ascent rate can be estimated by a particular type of seismicity. Low frequency seismicity, thought to be caused by the brittle failure of melt is often linked with the movement of magma within a conduit. We show that acceleration in the rate of low frequency seismicity can correspond to an increase in the rate of magma movement and be used as an indicator for potential changes in eruptive activity.

  2. 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.

  3. 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.

  4. 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.

  5. Health Literacy Predicts Change in Physical Activity Self-efficacy Among Sedentary Latinas

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    Dunsiger, Shira I.; Pekmezi, Dorothy W.; Marcus, Bess H.

    2017-01-01

    Health literacy (HL) is associated with preventive health behaviors. Self-efficacy is a predictor of health behavior, including physical activity (PA); however, causal pathways between HL and self-efficacy for PA are unknown, especially among Latinas who are at risk for chronic disease. To explore this potential relationship, secondary analyses were conducted on data [Shortened Test of Functional Health Literacy in Adults (STOFHLA), PA self-efficacy, and socio-demographics] from a 6-month, randomized controlled trial of a print-based PA intervention (n = 89 Spanish-speaking Latinas). Linear regression models revealed associations between HL and baseline self-efficacy in addition to changes in self-efficacy at 6-months. After controlling for significant covariates, higher HL scores were associated with lower baseline PA self-efficacy. Regardless of treatment assignment, higher HL scores at baseline predicted greater changes in PA self-efficacy at 6-months. HL may contribute to Latinas’ improved PA self-efficacy, though further research is warranted. PMID:22733230

  6. Health literacy predicts change in physical activity self-efficacy among sedentary Latinas.

    Science.gov (United States)

    Dominick, Gregory M; Dunsiger, Shira I; Pekmezi, Dorothy W; Marcus, Bess H

    2013-06-01

    Health literacy (HL) is associated with preventive health behaviors. Self-efficacy is a predictor of health behavior, including physical activity (PA); however, causal pathways between HL and self-efficacy for PA are unknown, especially among Latinas who are at risk for chronic disease. To explore this potential relationship, secondary analyses were conducted on data [Shortened Test of Functional Health Literacy in Adults (STOFHLA), PA self-efficacy, and socio-demographics] from a 6-month, randomized controlled trial of a print-based PA intervention (n = 89 Spanish-speaking Latinas). Linear regression models revealed associations between HL and baseline self-efficacy in addition to changes in self-efficacy at 6-months. After controlling for significant covariates, higher HL scores were associated with lower baseline PA self-efficacy. Regardless of treatment assignment, higher HL scores at baseline predicted greater changes in PA self-efficacy at 6-months. HL may contribute to Latinas' improved PA self-efficacy, though further research is warranted.

  7. Participant adherence indicators predict changes in dietary, physical activity, and clinical outcomes in church-based, diet and supervised physical activity intervention: Delta Body and Soul III

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    This secondary analysis evaluated the utility of several participant adherence indicators for predicting health outcome changes in a 6-month, church-based, controlled, lifestyle intervention previously proven effective for improving diet quality, physical activity, and blood lipids. Descriptive ind...

  8. Positive experience, self-efficacy, and action control predict physical activity changes: a moderated mediation analysis.

    Science.gov (United States)

    Parschau, Linda; Fleig, Lena; Koring, Milena; Lange, Daniela; Knoll, Nina; Schwarzer, Ralf; Lippke, Sonia

    2013-05-01

    Experiencing positive consequences of one's physical activity is supposed to facilitate further activity. This motivational outcome might be generated by an increase in perceived self-efficacy. In addition to such a mediator effect, we examine whether this applies generally or only under conditions of volitional control. For this purpose, perceived action control was considered as a putative moderator. N = 193 students participated in a study with three measurement points in time. At baseline, positive experience with previous physical activity was measured as a predictor of physical activity. Two weeks later, self-efficacy and action control variables were assessed as putative mediator and moderator, respectively. After another 2 weeks, physical activity was measured as the outcome. A moderated mediation model was specified with baseline physical activity and sex as covariates. Self-efficacy was found to mediate between initial positive experience and later physical activity, and this mediation was moderated by action control. Participants' perceptions of positive experience were associated with their subsequent self-efficacy fostering physical activity. However, persons with low levels of action control did not translate positive experience into physical activity via self-efficacy. What is already known on this subject? Numerous studies have shown that exercise-specific self-efficacy predicts subsequent physical activity. Prior positive experience with physical activity is suggested to be associated with exercise-specific self-efficacy. Furthermore, action control was found to be beneficial for the maintenance of physical activity. What does this study add? This study unveils the mechanisms between these social-cognitive determinants: our longitudinal results suggest that the mediation of positive experience and subsequent physical activity via self-efficacy is moderated by action control. Persons with low levels of action control did not translate positive

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

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    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 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.

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

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    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

  11. Theory of planned behaviour cognitions do not predict self-reported or objective physical activity levels or change in the ProActive trial.

    Science.gov (United States)

    Hardeman, Wendy; Kinmonth, Ann Louise; Michie, Susan; Sutton, Stephen

    2011-02-01

    The objective was to test, in a trial cohort of sedentary adults at risk of Type 2 diabetes, whether theory of planned behaviour (TPB) cognitions about becoming more physically active predicted objective and self-reported activity levels and change. Participants of a randomized controlled trial underwent measurement at baseline, 6 and 12 months. Participants (N= 365, 30-50 years) were recruited via their parent or family history registers at 20 general practices in the UK. Energy expenditure was measured objectively at baseline and 1 year. Participants completed questionnaires assessing physical activity and beliefs about becoming more physically active over the next year at baseline, 6 and 12 months. Between baseline and 12 months, objective energy expenditure in the cohort increased by an average of 20 minutes of brisk walking per day. Based on the 252 participants who provided complete data, affective attitude and perceived behavioural control consistently predicted intention, but intention and perceived behavioural control failed to predict physical activity levels or change (p-values > .05). Failure of the theory to predict behaviour and behaviour change may be due to inapplicability of the theory to this at-risk population or to trial participation and intensive measurement facilitating behaviour change without affecting measured cognitions, or lack of correspondence between cognitive and behavioural measures. A wide range of potential personal and environmental mediators should be considered when designing physical activity interventions among at-risk groups. High-quality experimental tests of the theory are needed in clinical populations. ©2010 The British Psychological Society.

  12. The morphological changes of monocytes in peripheral blood as a potential indicator for predicting active pulmonary tuberculosis.

    Science.gov (United States)

    Shen, Tian; Cao, Xingjian; Shi, Junwei; Yu, Yu; Zhu, Yihua; Gu, Delin

    2018-03-16

    Monocytes play a crucial role in immune response against Mycobacterium tuberculosis infection. The purpose of this current study was to investigate the morphology present on monocytes in peripheral blood from patients with active pulmonary tuberculosis (APTB) and the laboratory performance of the changes for discriminating cases from normal healthy subjects (NHS). A total of 71 peripheral blood samples from patients with APTB, and 65 samples from NHS were analyzed. The mean monocyte volume with its distribution width and mean monocyte conductivity as well as monocyte light scatter were detected by VCS technology used on the LH750 hematology analyzer. Correlations of these changes with the serum cytokine level in the immune alterations were further evaluated. The Receiver operating characteristic curve (ROC) analysis was used to highlight the clinical implication. In APTB patients, the mean monocyte volume showed significant difference associated with an evident elevation in the mean monocyte volume distribution width compared to those in NHS. Furthermore, the mean monocyte volume had positive relationship with the serum level of interleukine-1β response to M. tuberculosis infection. Simultaneous measurement of the mean monocyte volume and its distribution width was able to distinguish active infection with an excellent sensitivity of 84.5% and specificity of 90.5% comparable to those obtained from pro-inflammatory cytokine interleukine-6 identifying APTB with great accuracy. The morphological changes of monocytes particular increased mean volume may be a potential indicator to predict active tuberculosis infection. Copyright © 2018. Published by Elsevier B.V.

  13. Health Literacy Predicts Change in Physical Activity Self-efficacy Among Sedentary Latinas

    OpenAIRE

    Dominick, Gregory M.; Dunsiger, Shira I.; Pekmezi, Dorothy W.; Marcus, Bess H.

    2013-01-01

    Health literacy (HL) is associated with preventive health behaviors. Self-efficacy is a predictor of health behavior, including physical activity (PA); however, causal pathways between HL and self-efficacy for PA are unknown, especially among Latinas who are at risk for chronic disease. To explore this potential relationship, secondary analyses were conducted on data [Shortened Test of Functional Health Literacy in Adults (STOFHLA), PA self-efficacy, and socio-demographics] from a 6-month, ra...

  14. 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

    BACKGROUND/AIMS: 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). METHODS: We performed a prospective, interventional, clinical...

  15. Predicting earth's dynamic changes

    Science.gov (United States)

    Rasool, S. I.

    1986-01-01

    Given a suitable strategy for conducting measurements, satellite-based remote sensing of the earth can furnish valuable information on the dynamic changes of such planetary characteristics as ocean surface temperatures and atmospheric CO2. Observations must be global and synoptic, quantitatively validated, and consistent over the long term. A program spanning 20 years will study such critical variables as solar flux, stratospheric temperature, aerosols and ozone, cloud cover, tropospheric gases and aerosols, radiation balance, surface temperature, albedo, precipitation, vegetation cover, moisture, snow and ice, as well as oceanic color, topography, and wind stress.

  16. Volcanic activity and climatic changes.

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    Bryson, R A; Goodman, B M

    1980-03-07

    Radiocarbon dates of volcanic activity suggest variations that appear to be related to climatic changes. Historical eruption records also show variations on the scale of years to centuries. These records can be combined with simple climatic models to estimate the impact of various volcanic activity levels. From this analysis it appears that climatic prediction in the range of 2 years to many decades requires broad-scale volcanic activity prediction. Statistical analysis of the volcanic record suggests that some predictability is possible.

  17. Predicting Changes in Physical Activity among Adolescents: The Role of Self-Efficacy, Intention, Action Planning and Coping Planning

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    Araujo-Soares, Vera; McIntyre, Teresa; Sniehotta, Falko F.

    2009-01-01

    This paper aims to test the direct predictors of the theory of planned behaviour (TPB), action planning and coping planning as predictors of changes in physical activity (PA) in 157 adolescents (mean age: 12). TPB measures, the Action Planning and Coping Planning Scales (APCPS) and the International Physical Activity Questionnaires were measured…

  18. 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

  19. The role of symptoms and self-efficacy in predicting physical activity change among older adults with arthritis.

    Science.gov (United States)

    Sperber, Nina; Hall, Katherine S; Allen, Kelli; DeVellis, Brenda M; Lewis, Megan; Callahan, Leigh F

    2014-03-01

    Physical and psychological symptoms limit physical activity for people with arthritis. This study examined if self-efficacy mediated a relationship between symptom and physical activity (PA) frequency change. This was a secondary analysis of older adults with arthritis and joint pain in a trial of a lifestyle PA program (n = 339). Measures were depressive symptoms, pain, fatigue, arthritis self-efficacy, PA self-efficacy, and PA frequency. A panel model was used to analyze relationships at baseline and changes at 20 weeks. The mean age was 68.8 years. At baseline, depression and fatigue were associated with arthritis self-efficacy (β = -.34 and -.24) and, in turn, PA self-efficacy (β = .63); PA self-efficacy was associated with PA (β = .15). Pain and depression changes were associated with arthritis self-efficacy change (β = -.20 and -.21) and, in turn, PA self-efficacy (β = .32) change; PA self-efficacy change was associated with PA change (β = .36). Change in symptom severity affected change in PA frequency. These relationships appeared to operate through self-efficacy. Over time, pain appeared to have a stronger relationship than fatigue with self-efficacy and PA. These findings support strategies to help people with arthritis strengthen their confidence for symptom coping and PA participation.

  20. Participant Adherence Indicators Predict Changes in Blood Pressure, Anthropometric Measures, and Self-Reported Physical Activity in a Lifestyle Intervention: HUB City Steps

    Science.gov (United States)

    Thomson, Jessica L.; Landry, Alicia S.; Zoellner, Jamie M.; Connell, Carol; Madson, Michael B.; Molaison, Elaine Fontenot; Yadrick, Kathy

    2015-01-01

    The objective of this secondary analysis was to evaluate the utility of several participant adherence indicators for predicting changes in clinical, anthropometric, dietary, fitness, and physical activity (PA) outcomes in a lifestyle intervention, HUB City Steps, conducted in a southern, African American cohort in 2010. HUB City Steps was a…

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

    Science.gov (United States)

    Montresor, Antonio; Deol, Arminder; À Porta, Natacha; Lethanh, Nam; Jankovic, Dina

    2016-04-01

    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 STH

  2. 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

  3. 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

  4. Predicting Fire-Regime Responses to Climate Change Over the Past Millennium: Implications of Paleodata-Model Comparisons for Future Projections of Fire Activity

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    Young, A. M.; Higuera, P.; Abatzoglou, J. T.; Duffy, P.; Hu, F.

    2016-12-01

    Statistical models of fire-climate relationships are an important tool for anticipating fire-regime responses to future climate change. An important limitation of this approach is the reliance on observations from recent decades. Understanding how well modern fire-climate relationships apply to periods outside of the observational record is thus critical for using these models to anticipate future fire activity. In previous work, we developed models that accurately predict the spatial distribution of fire in Alaskan boreal forest and tundra ecosystems, using empirical relationships with summer temperature and annual moisture availability from 1950-2009. Here, we inform these models with downscaled global climate model (GCM) output for the past millennium (850-1850 CE), and compared predictions to reconstructed levels of fire activity derived from 25 paleoecological records in Alaska. Statistical models accurately predicted fire activity over the past millennium in boreal forests. Predicted mean fire return intervals (MFIs) ranged from 95-125 yrs, compared to 71-179 yrs in the paleo records (mean bias = 10 yrs). In contrast, statistical models significantly underestimated fire activity in the most flammable region of Alaskan tundra, predicting MFIs at least twice as long as those based on paleodata (mean bias = -712 yrs). This mismatch is due to at least two reasons. First, based on modern fire-climate relationships, this tundra region sits near a temperature threshold to burning, such that small changes in temperature result in large changes in predicted fire activity. Second, downscaled GCM-estimated temperatures are cooler than paleo-temperature estimates suggest, placing this tundra region below the temperature threshold to burning. Past-millennium GCM temperatures need to be increased by 1.0-1.5 °C for model predictions to agree with paleo-estimates of fire activity (mean bias = -35 yrs), comparable to differences between GCM and paleo-temperature estimates

  5. Relative Importance of Baseline Pain, Fatigue, Sleep, and Physical Activity: Predicting Change in Depression in Adults With Multiple Sclerosis.

    Science.gov (United States)

    Edwards, Karlyn A; Molton, Ivan R; Smith, Amanda E; Ehde, Dawn M; Bombardier, Charles H; Battalio, Samuel L; Jensen, Mark P

    2016-08-01

    To determine whether baseline levels of pain, fatigue, sleep disturbance, and physical activity measured at the initial assessment predicted the development of or improvement of depression 3.5 years later, while controlling for sex, age, and disease severity. Observational, longitudinal survey study. A community-based population sample. Adults with multiple sclerosis (MS) (N=489). Not applicable. Primary outcome was classification of depression group measured using a Patient Health Questionnaire-9 cutoff score ≥10, indicating probable major depression. Fatigue severity (odds ratio, 1.19; 95% confidence interval, 1.12-1.26; Psleep disturbance (odds ratio, 1.06; 95% confidence interval, 1.02-1.10; P=.001) predicted probable major depression 3.5 years later among those not depressed at the initial assessment. An effect of age (odds ratio, .96; 95% confidence interval, .92-.99; P=.008) was found among those who developed depression, indicating that younger adults were more likely to develop depression. Pain, fatigue, sleep, and physical activity at baseline were not significantly associated with recovery from depression among those depressed at the initial assessment. Fatigue and sleep may contribute to the development of depression. Clinical trial research targeting these variables to determine their influence on depression is warranted. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  6. Bronchial thermoplasty: activations predict response.

    Science.gov (United States)

    Langton, David; Sha, Joy; Ing, Alvin; Fielding, David; Thien, Francis; Plummer, Virginia

    2017-07-04

    Bronchial thermoplasty (BT) is an emerging bronchoscopic intervention for the treatment of severe asthma. The predictive factors for clinical response to BT are unknown. We examined the relationship between the number of radiofrequency activations applied and the treatment response observed. Data were collected from 24 consecutive cases treated at three Australian centres from June 2014 to March 2016. The baseline characteristics were collated along with the activations delivered. The primary response measure was change in the Asthma Control Questionnaire-5 (ACQ-5) score measured at 6 months post BT. The relationship between change in outcome parameters and the number of activations delivered was explored. All patients met the ERS/ATS definition for severe asthma. At 6 months post treatment, mean ACQ-5 improved from 3.3 ± 1.1 to 1.5 ± 1.1, p < 0.001. The minimal clinically significant improvement in ACQ-5 of ≥0.5 was observed in 21 out of 24 patients. The only significant variable that differed between the 21 responders and the three non-responders was the number of activations delivered, with 139 ± 11 activations in the non-responders, compared to 221 ± 45 activations in the responders (p < 0.01). A significant inverse correlation was found between change in ACQ-5 score and the number of activations, r = -0.43 (p < 0.05). The number of activations delivered during BT has a role in determining clinical response to treatment.

  7. 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.

  8. Response Versus Nonresponse to Self-Regulatory Treatment Targets Is Not Discriminated by Personal Characteristics but Predicts Physical Activity, Eating Behavior, and Weight Changes in Women With Obesity.

    Science.gov (United States)

    Annesi, James J

    2018-01-01

    Background Results of behavioral weight-loss treatments vary widely, with mostly unsuccessful outcomes beyond the short term. Women with obesity participating in a new cognitive-behavioral weight-loss treatment were assessed on their responses to psychological targets. Methods Groups of responders ( n = 43) and nonresponders ( n = 48) were established post hoc. Results Age, race/ethnicity, education, income, body composition, physical activity, and eating behaviors at baseline were not discriminated between responders and nonresponders. Over both 6 and 24 months, responders improved significantly more in physical activity and fruit/vegetable consumption but not sweets intake. Weight loss over 6 and 24 months was significantly greater for the responder group at 8.1% and 8.6% versus nonresponders at 4.7% and 3.8%, respectively. Self-regulation change significantly predicted all behavioral changes, with mood change improving the predictive strength for only sweets intake. Discussion Although further research is required to determine the etiology of, and to maximize, positive responses, findings suggested prospects for treatment improvements.

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

    Science.gov (United States)

    Van Dyck, Delfien; Cardon, Greet; De Bourdeaudhuij, Ilse

    2017-01-01

    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. This longitudinal study was conducted in Flanders, Belgium. In total, 180 recently retired (>1 month, psychological, social and physical environmental characteristics. Multiple moderated hierarchic regression analyses were conducted in SPSS 22.0. Higher perceived residential density ( p  changes in active transportation and leisure-time physical activity. Few moderating effects were found, so health interventions at the start of retirement focusing on self-efficacy and specific walkability characteristics could be effective to increase physical activity in recently retired adults. No firm conclusions can be drawn on the importance of the examined predictors to explain change in car use and screen time, possibly other factors like the home environment, or automatic processes and habit strength are more important to explain sedentary behaviors.

  10. 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

  11. 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

  12. 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 deve...

  13. 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...

  14. 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

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

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

    2010-10-08

    Oct 8, 2010 ... Indigenous people in western Kenya have relied on the mystical abilities of the Nganyi rainmakers to predict the weather for generations. However, the erratic weather caused by climate change has made the signs rainmakers need for their forecast opaque. The Nganyi rainmakers have begun ...

  16. Does change in hostility predict sexual recidivism?

    Science.gov (United States)

    Pettersen, Cathrine; Nunes, Kevin L; Woods, Mandie; Maimone, Sacha; Hermann, Chantal A; Looman, Jan; Spape, Jessica

    2015-06-01

    The purpose of the study was to examine whether scores on a widely used measure of hostility--the Buss-Durkee Hostility Inventory (BDHI)--and change on this measure predicted sexual recidivism in a sample of 120 adult male incarcerated sexual offenders. Pre- and posttreatment scores, simple difference scores, and clinically significant change were examined. The majority of participants had functional scores on the BDHI prior to treatment. Of those who had dysfunctional pretreatment scores, the majority remained unchanged. Higher posttreatment scores on the Assault and Verbal Hostility subscales significantly predicted sexual recidivism. The remaining pre- and posttreatment scores as well as change scores and classifications did not significantly predict sexual recidivism. Our findings suggest that the Assault and Verbal Hostility subscales may be useful for predicting sexual recidivism but were not clearly consistent with the notion that the BDHI assesses a dynamic risk factor(s) for sexual recidivism. Due to a number of limitations of the current study, however, more rigorous research is needed before firm conclusions can be drawn. © The Author(s) 2014.

  17. Lipid profile of rheumatoid arthritis patients treated with anti-tumor necrosis factor-alpha drugs changes according to disease activity and predicts clinical response.

    Science.gov (United States)

    Cacciapaglia, Fabio; Anelli, Maria Grazia; Rinaldi, Angela; Serafino, Lucia; Covelli, Michele; Scioscia, Crescenzio; Iannone, Florenzo; Lapadula, Giovanni

    2014-11-01

    Patients with active rheumatoid arthritis (RA) frequently show an atherogenic lipid profile, which has been linked with the inflammatory reaction. Inflammatory cytokines, and particularly tumor necrosis factor-alpha (TNF-α), are implicated in the pathogenesis of both atherosclerosis and RA, and also involved in the development of the impaired lipid profile detected in active RA. Although anti-TNF-α agents have been proven effective in controlling joint damage and systemic inflammation, controversy remains about the effect of these drugs on the lipid profile; therefore, the aim of our study was to investigate the effect of anti-TNF-α treatment, in combination with disease-modifying anti-rheumatic drugs (DMARDs) and corticosteroid therapy, on the lipid profile of patients with active RA. Our data suggest that the combination anti-TNF-α/DMARDs/steroids do not significantly interfere with the lipid profile of RA patients. However, analysis of clinical response data showed that patients achieving low disease activity or remission seem to have a protective lipid profile, suggesting that better control of inflammation and disease activity can affect lipid metabolism. The available evidence indicates that high inflammation interferes with lipid metabolism, whereas good control of the chronic inflammatory state may positively influence the lipid profile and cardiovascular risk. Low cholesterol levels at baseline could predict a favorable outcome with anti-TNF-α treatment, but these data need to be confirmed by large prospective studies with long-term follow-up. © 2014 Wiley Periodicals, Inc.

  18. Prediction of change in borderline personality disorder.

    Science.gov (United States)

    Goldberg, S C

    1989-01-01

    Prediction of change in borderlines is an important effort because it may illuminate the character of this tentatively defined, complex disorder. In future years the disorder will be defined differently in light of its network of relationships with other variables. Presently, the strongest predictors of change in borderlines are receipt of neuroleptics and presence of target symptoms that are affected by these drugs. Other drugs and other treatments may also be found to have a selectively differential effect in which case receipt of these drugs will also predict change but perhaps on other target symptoms. Preliminary evidence implicates monoamine oxidase inhibitors (MAOIs), lithium, and carbamazepine. Response to thiothixene has been found to be related to the patient's Minnesota Multiphasic Personality Inventory (MMPI) profile prior to treatment. Biological predictor variables studied in other disorders have been found to be abnormal in borderlines, but how these variables might relate to change has not been studied. The program of research that is necessary includes other drug treatments, nonphysiological treatments, family history, and personality variables.

  19. 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. .

  20. 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

  1. Response to mTOR inhibition: activity of eIF4E predicts sensitivity in cell lines and acquired changes in eIF4E regulation in breast cancer

    Directory of Open Access Journals (Sweden)

    Bartlett John MS

    2011-02-01

    Full Text Available Abstract Background Inhibitors of the kinase mTOR, such as rapamycin and everolimus, have been used as cancer therapeutics with limited success since some tumours are resistant. Efforts to establish predictive markers to allow selection of patients with tumours likely to respond have centred on determining phosphorylation states of mTOR or its targets 4E-BP1 and S6K in cancer cells. In an alternative approach we estimated eIF4E activity, a key effector of mTOR function, and tested the hypothesis that eIF4E activity predicts sensitivity to mTOR inhibition in cell lines and in breast tumours. Results We found a greater than three fold difference in sensitivity of representative colon, lung and breast cell lines to rapamycin. Using an assay to quantify influences of eIF4E on the translational efficiency specified by structured 5'UTRs, we showed that this estimate of eIF4E activity was a significant predictor of rapamycin sensitivity, with higher eIF4E activities indicative of enhanced sensitivity. Surprisingly, non-transformed cell lines were not less sensitive to rapamycin and did not have lower eIF4E activities than cancer lines, suggesting the mTOR/4E-BP1/eIF4E axis is deregulated in these non-transformed cells. In the context of clinical breast cancers, we estimated eIF4E activity by analysing expression of eIF4E and its functional regulators within tumour cells and combining these scores to reflect inhibitory and activating influences on eIF4E. Estimates of eIF4E activity in cancer biopsies taken at diagnosis did not predict sensitivity to 11-14 days of pre-operative everolimus treatment, as assessed by change in tumour cell proliferation from diagnosis to surgical excision. However, higher pre-treatment eIF4E activity was significantly associated with dramatic post-treatment changes in expression of eIF4E and 4E-binding proteins, suggesting that eIF4E is further deregulated in these tumours in response to mTOR inhibition. Conclusions

  2. 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......) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. Methods: CERAPP combined multiple models developed in collaboration with 17 groups in the United......: 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...

  3. Activity Prediction: A Twitter-based Exploration

    NARCIS (Netherlands)

    Weerkamp, W.; de Rijke, M.

    2012-01-01

    Social media platforms allow users to share their messages with everyone else. In microblogs, e.g., Twitter, people mostly report on what they did, they talk about current activities, and mention things they plan to do in the near future. In this paper, we propose the task of activity prediction,

  4. 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

  5. Cortical Neural Activity Predicts Sensory Acuity Under Optogenetic Manipulation.

    Science.gov (United States)

    Briguglio, John J; Aizenberg, Mark; Balasubramanian, Vijay; Geffen, Maria N

    2018-02-21

    Excitatory and inhibitory neurons in the mammalian sensory cortex form interconnected circuits that control cortical stimulus selectivity and sensory acuity. Theoretical studies have predicted that suppression of inhibition in such excitatory-inhibitory networks can lead to either an increase or, paradoxically, a decrease in excitatory neuronal firing, with consequent effects on stimulus selectivity. We tested whether modulation of inhibition or excitation in the auditory cortex of male mice could evoke such a variety of effects in tone-evoked responses and in behavioral frequency discrimination acuity. We found that, indeed, the effects of optogenetic manipulation on stimulus selectivity and behavior varied in both magnitude and sign across subjects, possibly reflecting differences in circuitry or expression of optogenetic factors. Changes in neural population responses consistently predicted behavioral changes for individuals separately, including improvement and impairment in acuity. This correlation between cortical and behavioral change demonstrates that, despite the complex and varied effects that these manipulations can have on neuronal dynamics, the resulting changes in cortical activity account for accompanying changes in behavioral acuity. SIGNIFICANCE STATEMENT Excitatory and inhibitory interactions determine stimulus specificity and tuning in sensory cortex, thereby controlling perceptual discrimination acuity. Modeling has predicted that suppressing the activity of inhibitory neurons can lead to increased or, paradoxically, decreased excitatory activity depending on the architecture of the network. Here, we capitalized on differences between subjects to test whether suppressing/activating inhibition and excitation can in fact exhibit such paradoxical effects for both stimulus sensitivity and behavioral discriminability. Indeed, the same optogenetic manipulation in the auditory cortex of different mice could improve or impair frequency discrimination

  6. 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...

  7. Predicting Malaria's Changing Course | IDRC - International ...

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

    2010-12-09

    Dec 9, 2010 ... East Africa is experiencing outbreaks of malaria in highland areas where there is little experience with the disease. Researchers led by the Kenya Medical Research Institute are combining climate observation with medical research to predict highland malaria outbreaks in Kenya, Tanzania, and Uganda so ...

  8. 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.

  9. 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 ...

  10. 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

  11. Predicting Home and Community Walking Activity Poststroke.

    Science.gov (United States)

    Fulk, George D; He, Ying; Boyne, Pierce; Dunning, Kari

    2017-02-01

    Walking ability poststroke is commonly assessed using gait speed categories developed by Perry et al. The purpose of this study was to reexamine factors that predict home and community ambulators determined from real-world walking activity data using activity monitors. Secondary analyses of real-world walking activity from 2 stroke trials. Home (100-2499 steps/d), most limited community (2500-4499 steps/d), least limited community (5000-74 999), and full community (≥7500 steps/d) walking categories were developed based on normative data. Independent variables to predict walking categories were comfortable and fast gait speed, 6-minute walk test, Berg Balance Scale, Fugl Meyer, and Stroke Impact Scale. Data were analyzed using multivariate analyses to identify significant variables associated with walking categories, bootstrap method to select the most stable model and receiver-operating characteristic to identify cutoff values. Data from 441 individuals poststroke were analyzed. The 6-minute walk test, Fugl Meyer, and Berg Balance Scale combined were the strongest predictors of home versus community and limited versus unlimited community ambulators. The 6-minute walk test was the strongest individual variable in predicting home versus community (receiver-operating characteristic area under curve=0.82) and limited versus full community ambulators (receiver-operating characteristic area under curve=0.76). A comfortable gait speed of 0.49 m/s discriminated between home and community and a comfortable gait speed of 0.93 m/s discriminated between limited community and full community ambulators. The 6-minute walk test was better able to discriminate among home, limited community, and full community ambulators than comfortable gait speed. Gait speed values commonly used to distinguish between home and community walkers may overestimate walking activity. © 2017 American Heart Association, Inc.

  12. 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."

  13. Commitment to Change Statements Can Predict Actual Change in Practice

    Science.gov (United States)

    Wakefield, Jacqueline; Herbert, Carol P.; Maclure, Malcolm; Dormuth, Colin; Wright, James M.; Legare, Jeanne; Brett-MacLean, Pamela; Premi, John

    2003-01-01

    Introduction: Statements of commitment to change are advocated both to promote and to assess continuing education interventions. However, most studies of commitment to change have used self-reported outcomes, and self-reports may significantly overestimate actual performance. As part of an educational randomized controlled trial, this study…

  14. 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 imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance.

  15. Sensitivity to changing contingencies predicts social suc- cess.

    NARCIS (Netherlands)

    Ronay, R.D.; von Hippel, W.

    2015-01-01

    To adapt one’s behavior to suit changing social contingencies, it is necessary to be skillful at detecting such changing contingencies in the first place. As a consequence, the ability to detect changing contingencies (reversal learning) should predict social competence across both competitive and

  16. Changes in Memory Prediction Accuracy: Age and Performance Effects

    Science.gov (United States)

    Pearman, Ann; Trujillo, Amanda

    2013-01-01

    Memory performance predictions are subjective estimates of possible memory task performance. The purpose of this study was to examine possible factors related to changes in word list performance predictions made by younger and older adults. Factors included memory self-efficacy, actual performance, and perceptions of performance. The current study…

  17. 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.

  18. Neural predictive control for active buffet alleviation

    Science.gov (United States)

    Pado, Lawrence E.; Lichtenwalner, Peter F.; Liguore, Salvatore L.; Drouin, Donald

    1998-06-01

    The adaptive neural control of aeroelastic response (ANCAR) and the affordable loads and dynamics independent research and development (IRAD) programs at the Boeing Company jointly examined using neural network based active control technology for alleviating undesirable vibration and aeroelastic response in a scale model aircraft vertical tail. The potential benefits of adaptive control includes reducing aeroelastic response associated with buffet and atmospheric turbulence, increasing flutter margins, and reducing response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and thus loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Wind tunnel tests were undertaken on a rigid 15% scale aircraft in Boeing's mini-speed wind tunnel, which is used for testing at very low air speeds up to 80 mph. The model included a dynamically scaled flexible fail consisting of an aluminum spar with balsa wood cross sections with a hydraulically powered rudder. Neural predictive control was used to actuate the vertical tail rudder in response to strain gauge feedback to alleviate buffeting effects. First mode RMS strain reduction of 50% was achieved. The neural predictive control system was developed and implemented by the Boeing Company to provide an intelligent, adaptive control architecture for smart structures applications with automated synthesis, self-optimization, real-time adaptation, nonlinear control, and fault tolerance capabilities. It is designed to solve complex control problems though a process of automated synthesis, eliminating costly control design and surpassing it in many instances by accounting for real world non-linearities.

  19. 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-term...... period but show recent signs of rapid change. The observed regime shifts were difficult to anticipate, which compromises the validity of predictions of future land-system changes and the assessment of their impact on greenhouse gas emissions, hydrological processes, agriculture, biodiversity...

  20. 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.)

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

    African Journals Online (AJOL)

    The objectives of this study were to determine land use changes in upper Berg catchment using multi-temporal Landsat images from 1984, 1992, 2002, and 2008, and to predict the impact of these land use changes on groundwater recharge. For the simulation of groundwater recharge the distributed hydrological model ...

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

    African Journals Online (AJOL)

    2012-04-13

    Apr 13, 2012 ... images from 1984, 1992, 2002, and 2008, and to predict the impact of these land use changes on groundwater recharge. For ... Policy intention is to maintain a balance between demand, quantity and quality of groundwater. Land use change is a major factor affecting the .... tion in the channel network.

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

    International Nuclear Information System (INIS)

    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

  4. Beyond predictions: biodiversity conservation in a changing climate.

    Science.gov (United States)

    Dawson, Terence P; Jackson, Stephen T; House, Joanna I; Prentice, Iain Colin; Mace, Georgina M

    2011-04-01

    Climate change is predicted to become a major threat to biodiversity in the 21st century, but accurate predictions and effective solutions have proved difficult to formulate. Alarming predictions have come from a rather narrow methodological base, but a new, integrated science of climate-change biodiversity assessment is emerging, based on multiple sources and approaches. Drawing on evidence from paleoecological observations, recent phenological and microevolutionary responses, experiments, and computational models, we review the insights that different approaches bring to anticipating and managing the biodiversity consequences of climate change, including the extent of species' natural resilience. We introduce a framework that uses information from different sources to identify vulnerability and to support the design of conservation responses. Although much of the information reviewed is on species, our framework and conclusions are also applicable to ecosystems, habitats, ecological communities, and genetic diversity, whether terrestrial, marine, or fresh water.

  5. 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.

  6. Predicting effects of environmental change on a migratory herbivore

    Science.gov (United States)

    Stillman, R A; Wood, K A; Gilkerson, Whelan; Elkinton, E; Black, J. M.; Ward, David H.; Petrie, M.

    2015-01-01

    Changes in climate, food abundance and disturbance from humans threaten the ability of species to successfully use stopover sites and migrate between non-breeding and breeding areas. To devise successful conservation strategies for migratory species we need to be able to predict how such changes will affect both individuals and populations. Such predictions should ideally be process-based, focusing on the mechanisms through which changes alter individual physiological state and behavior. In this study we use a process-based model to evaluate how Black Brant (Branta bernicla nigricans) foraging on common eelgrass (Zostera marina) at a stopover site (Humboldt Bay, USA), may be affected by changes in sea level, food abundance and disturbance. The model is individual-based, with empirically based parameters, and incorporates the immigration of birds into the site, tidal changes in availability of eelgrass, seasonal and depth-related changes in eelgrass biomass, foraging behavior and energetics of the birds, and their mass-dependent decisions to emigrate. The model is validated by comparing predictions to observations across a range of system properties including the time birds spent foraging, probability of birds emigrating, mean stopover duration, peak bird numbers, rates of mass gain and distribution of birds within the site: all 11 predictions were within 35% of the observed value, and 8 within 20%. The model predicted that the eelgrass within the site could potentially support up to five times as many birds as currently use the site. Future predictions indicated that the rate of mass gain and mean stopover duration were relatively insensitive to sea level rise over the next 100 years, primarily because eelgrass habitat could redistribute shoreward into intertidal mudflats within the site to compensate for higher sea levels. In contrast, the rate of mass gain and mean stopover duration were sensitive to changes in total eelgrass biomass and the percentage of time

  7. 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

  8. Global perceived stress predicts cognitive change among older adults.

    Science.gov (United States)

    Munoz, Elizabeth; Sliwinski, Martin J; Scott, Stacey B; Hofer, Scott

    2015-09-01

    Research on stress and cognitive aging has primarily focused on examining the effects of biological and psychosocial indicators of stress, with little attention provided to examining the association between perceived stress and cognitive aging. We examined the longitudinal association between global perceived stress (GPS) and cognitive change among 116 older adults (M(age) = 80, SD = 6.40, range = 67-96) in a repeated measurement burst design. Bursts of 6 daily cognitive assessments were repeated every 6 months over a 2-year period, with self-reported GPS assessed at the start of every burst. Using a double-exponential learning model, 2 parameters were estimated: (a) asymptotic level (peak performance), and (b) asymptotic change (the rate at which peak performance changed across bursts). We hypothesized that greater GPS would predict slowed performance in tasks of attention, working memory, and speed of processing and that increases in GPS across time would predict cognitive slowing. Results from latent growth curve analyses were consistent with our first hypothesis and indicated that level of GPS predicted cognitive slowing across time. Changes in GPS did not predict cognitive slowing. This study extends previous findings by demonstrating a prospective association between level of GPS and cognitive slowing across a 2-year period, highlighting the role of psychological stress as a risk factor for poor cognitive function. (c) 2015 APA, all rights reserved).

  9. Global Perceived Stress Predicts Cognitive Change among Older Adults

    Science.gov (United States)

    Munoz, Elizabeth; Sliwinski, Martin J.; Scott, Stacey B.; Hofer, Scott

    2015-01-01

    Research on stress and cognitive aging has primarily focused on examining the effects of biological and psychosocial indicators of stress with little attention provided to examining the association between perceived stress and cognitive aging. We examined the longitudinal association between global perceived stress (GPS) and cognitive change among 116 older adults (Mage = 80, SD = 6.40, range: 67–96) in a repeated measurement burst design. Bursts of six daily cognitive assessments were repeated every six months over a two-year period with self-reported GPS assessed at the start of every burst. Using a double-exponential learning model, two parameters were estimated: 1) asymptotic level (peak performance), and 2) asymptotic change (the rate in which peak performance changed across bursts). We hypothesized that greater GPS would predict slowed performance in tasks of attention, working memory, and speed of processing and that increases in GPS across time would predict cognitive slowing. Results from latent growth curve analyses were consistent with our first hypothesis and indicated that level of GPS predicted cognitive slowing across time. Changes in GPS did not predict cognitive slowing. This study extends previous findings by demonstrating a prospective association between level of GPS and cognitive slowing across a two-year period highlighting the role of psychological stress as a risk factor for poor cognitive function. PMID:26121285

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

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Earth System Science; Volume 123; Issue 6. Forest cover change prediction using hybrid methodology of geoinformatics and Markov chain model: A case study on sub-Himalayan town Gangtok, India. Anirban Mukhopadhyay Arun Mondal Sandip Mukherjee Dipam Khatua Subhajit Ghosh ...

  11. Phylogeny Predicts Future Habitat Shifts Due to Climate Change

    Science.gov (United States)

    Kuntner, Matjaž; Năpăruş, Magdalena; Li, Daiqin; Coddington, Jonathan A.

    2014-01-01

    Background Taxa may respond differently to climatic changes, depending on phylogenetic or ecological effects, but studies that discern among these alternatives are scarce. Here, we use two species pairs from globally distributed spider clades, each pair representing two lifestyles (generalist, specialist) to test the relative importance of phylogeny versus ecology in predicted responses to climate change. Methodology We used a recent phylogenetic hypothesis for nephilid spiders to select four species from two genera (Nephilingis and Nephilengys) that match the above criteria, are fully allopatric but combined occupy all subtropical-tropical regions. Based on their records, we modeled each species niche spaces and predicted their ecological shifts 20, 40, 60, and 80 years into the future using customized GIS tools and projected climatic changes. Conclusions Phylogeny better predicts the species current ecological preferences than do lifestyles. By 2080 all species face dramatic reductions in suitable habitat (54.8–77.1%) and adapt by moving towards higher altitudes and latitudes, although at different tempos. Phylogeny and life style explain simulated habitat shifts in altitude, but phylogeny is the sole best predictor of latitudinal shifts. Models incorporating phylogenetic relatedness are an important additional tool to predict accurately biotic responses to global change. PMID:24892737

  12. 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.

  13. 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

  14. 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

  15. Drought Predictability and Prediction in a Changing Climate: Assessing Current Predictive Knowledge and Capabilities, User Requirements and Research Priorities

    Science.gov (United States)

    Schubert, Siegfried

    2011-01-01

    Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g., on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well. In order to make progress on these issues, the WCRP drought information group (DIG), with the support of WCRP, the Catalan Institute of Climate Sciences, the La Caixa Foundation, the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the National Science Foundation, has organized a workshop to focus on: 1. User requirements for drought prediction information on sub-seasonal to centennial time scales 2. Current understanding of the mechanisms and predictability of drought on sub-seasonal to centennial time scales 3. Current drought prediction/projection capabilities on sub-seasonal to centennial time scales 4. Advancing regional drought prediction capabilities for variables and scales most relevant to user needs on sub-seasonal to centennial time scales. This introductory talk provides an overview of these goals, and outlines the occurrence and mechanisms of drought world-wide.

  16. Predicting Responses to Contemporary Environmental Change Using Evolutionary Response Architectures.

    Science.gov (United States)

    Bay, Rachael A; Rose, Noah; Barrett, Rowan; Bernatchez, Louis; Ghalambor, Cameron K; Lasky, Jesse R; Brem, Rachel B; Palumbi, Stephen R; Ralph, Peter

    2017-05-01

    Rapid environmental change currently presents a major threat to global biodiversity and ecosystem functions, and understanding impacts on individual populations is critical to creating reliable predictions and mitigation plans. One emerging tool for this goal is high-throughput sequencing technology, which can now be used to scan the genome for signs of environmental selection in any species and any system. This explosion of data provides a powerful new window into the molecular mechanisms of adaptation, and although there has been some success in using genomic data to predict responses to selection in fields such as agriculture, thus far genomic data are rarely integrated into predictive frameworks of future adaptation in natural populations. Here, we review both theoretical and empirical studies of adaptation to rapid environmental change, focusing on areas where genomic data are poised to contribute to our ability to estimate species and population persistence and adaptation. We advocate for the need to study and model evolutionary response architectures, which integrate spatial information, fitness estimates, and plasticity with genetic architecture. Understanding how these factors contribute to adaptive responses is essential in efforts to predict the responses of species and ecosystems to future environmental change.

  17. "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.

  18. 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

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

    Indian Academy of Sciences (India)

    In the Himalayan states of India, with increasing population and activities, large areas of forested land are being converted into other land-use features. There is a definite cause and effect relationship between changing practice for development and changes in land use. So, an estimation of land use dynamics and a.

  20. Autonomic activity during sleep predicts memory consolidation in humans.

    Science.gov (United States)

    Whitehurst, Lauren N; Cellini, Nicola; McDevitt, Elizabeth A; Duggan, Katherine A; Mednick, Sara C

    2016-06-28

    Throughout history, psychologists and philosophers have proposed that good sleep benefits memory, yet current studies focusing on the relationship between traditionally reported sleep features (e.g., minutes in sleep stages) and changes in memory performance show contradictory findings. This discrepancy suggests that there are events occurring during sleep that have not yet been considered. The autonomic nervous system (ANS) shows strong variation across sleep stages. Also, increases in ANS activity during waking, as measured by heart rate variability (HRV), have been correlated with memory improvement. However, the role of ANS in sleep-dependent memory consolidation has never been examined. Here, we examined whether changes in cardiac ANS activity (HRV) during a daytime nap were related to performance on two memory conditions (Primed and Repeated) and a nonmemory control condition on the Remote Associates Test. In line with prior studies, we found sleep-dependent improvement in the Primed condition compared with the Quiet Wake control condition. Using regression analyses, we compared the proportion of variance in performance associated with traditionally reported sleep features (model 1) vs. sleep features and HRV during sleep (model 2). For both the Primed and Repeated conditions, model 2 (sleep + HRV) predicted performance significantly better (73% and 58% of variance explained, respectively) compared with model 1 (sleep only, 46% and 26% of variance explained, respectively). These findings present the first evidence, to our knowledge, that ANS activity may be one potential mechanism driving sleep-dependent plasticity.

  1. 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.

  2. 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…

  3. 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.

  4. 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

    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......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...

  5. Implication of global climate change on the distribution and activity of Phytophthora ramorum

    Science.gov (United States)

    Robert C. Venette

    2009-01-01

    Global climate change is predicted to alter the distribution and activity of several forest pathogens. Boland et al. (2004) suggested that climate change might affect pathogen establishment, rate of disease progress, and the duration of...

  6. 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.

  7. Institutional Constraints, Legislative Activism, and Policy Change

    DEFF Research Database (Denmark)

    Citi, Manuele; Justesen, Mogens Kamp

    of regulatory reform in the EU. The rise in the number of legislative proposal, in turn, is affected by the extent of gridlock between the EU’s legislative bodies. These findings show that the Commission steps up its legislative activity when the institutional opportunity space allows for greater policy change.......This paper studies how institutional constraints affect legislative activism, and how legislative activism affects policy change, analyzing the case of the European Union’s legislative process. Our argument revolves around the key role of the Commission in advancing policy change, and emphasizes...... that the Commission can successfully push for increased policy change by increasing its legislative activity when the institutional opportunity space widens. Using a novel panel dataset covering eight policy sectors from 1984--‐2012, we find that the number of legislative proposals significantly affects the extent...

  8. 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.

  9. 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.

  10. Predicting promoter activities of primary human DNA sequences

    Science.gov (United States)

    Irie, Takuma; Park, Sung-Joon; Yamashita, Riu; Seki, Masahide; Yada, Tetsushi; Sugano, Sumio; Nakai, Kenta; Suzuki, Yutaka

    2011-01-01

    We developed a computer program that can predict the intrinsic promoter activities of primary human DNA sequences. We observed promoter activity using a quantitative luciferase assay and generated a prediction model using multiple linear regression. Our program achieved a prediction accuracy correlation coefficient of 0.87 between the predicted and observed promoter activities. We evaluated the prediction accuracy of the program using massive sequencing analysis of transcriptional start sites in vivo. We found that it is still difficult to predict transcript levels in a strictly quantitative manner in vivo; however, it was possible to select active promoters in a given cell from the other silent promoters. Using this program, we analyzed the transcriptional landscape of the entire human genome. We demonstrate that many human genomic regions have potential promoter activity, and the expression of some previously uncharacterized putatively non-protein-coding transcripts can be explained by our prediction model. Furthermore, we found that nucleosomes occasionally formed open chromatin structures with RNA polymerase II recruitment where the program predicted significant promoter activities, although no transcripts were observed. PMID:21486745

  11. 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.

  12. Thermodynamic modeling of activity coefficient and prediction of solubility: Part 1. Predictive models.

    Science.gov (United States)

    Mirmehrabi, Mahmoud; Rohani, Sohrab; Perry, Luisa

    2006-04-01

    A new activity coefficient model was developed from excess Gibbs free energy in the form G(ex) = cA(a) x(1)(b)...x(n)(b). The constants of the proposed model were considered to be function of solute and solvent dielectric constants, Hildebrand solubility parameters and specific volumes of solute and solvent molecules. The proposed model obeys the Gibbs-Duhem condition for activity coefficient models. To generalize the model and make it as a purely predictive model without any adjustable parameters, its constants were found using the experimental activity coefficient and physical properties of 20 vapor-liquid systems. The predictive capability of the proposed model was tested by calculating the activity coefficients of 41 binary vapor-liquid equilibrium systems and showed good agreement with the experimental data in comparison with two other predictive models, the UNIFAC and Hildebrand models. The only data used for the prediction of activity coefficients, were dielectric constants, Hildebrand solubility parameters, and specific volumes of the solute and solvent molecules. Furthermore, the proposed model was used to predict the activity coefficient of an organic compound, stearic acid, whose physical properties were available in methanol and 2-butanone. The predicted activity coefficient along with the thermal properties of the stearic acid were used to calculate the solubility of stearic acid in these two solvents and resulted in a better agreement with the experimental data compared to the UNIFAC and Hildebrand predictive models.

  13. Institutional Constraints, Legislative Activism and Policy Change

    DEFF Research Database (Denmark)

    Citi, Manuele; Justesen, Mogens Kamp

    2016-01-01

    This article presents a study of how institutional constraints affect legislative activism and how legislative activism in turn affects policy change through an analysis of the European Union's legislative process. The argument revolves around the key role of the European Commission in advancing...... policy change, and emphasises that the Commission can successfully push for increased policy change by increasing its legislative activity when the institutional opportunity space widens. Using a novel panel dataset covering eight policy sectors from the period 1984–2012, the article shows...... that the number of legislative proposals significantly affects the extent of regulatory reform in the EU. The rise in the number of legislative proposals, in turn, is affected by the extent of gridlock between the EU's legislative bodies. These findings show that the Commission steps up its legislative activity...

  14. 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....

  15. Solar activity prediction studies and services in NAOC

    Science.gov (United States)

    He, Han; Wang, Huaning; Du, Zhanle; Li, Rong; Cui, Yanmei; Zhang, Liyun; He, Yulin

    2008-11-01

    Solar activity prediction services started in 1960’s in National Astronomical Observatories, Chinese Academy of Sciences (NAOC). As one of the members of the International Space Environment Service (ISES), Regional Warning Center of China (RWC-China) was set up in 1990’s. Solar Activity Prediction Center (SAPC), as one of the four sub-centers of RWC-China, is located in NAOC. Solar activity prediction studies and services in NAOC cover short-term, medium-term, and long-term forecast of solar activities. Nowadays, certain prediction models, such as solar X-ray flare model, solar proton event model, solar 10 cm radio flux model, have been established for the practical prediction services. Recently, more and more physical analyses are introduced in the studies of solar activity prediction, such as the magnetic properties of solar active regions and magnetic structure of solar atmosphere. Besides traditional statistics algorithms, Machine Learning and Artificial Intelligence techniques, such as Support Vector Machine (SVM) method, are employed in the establishment of forecast models. A Web-based integrated platform for solar activity data sharing and forecast distribution is under construction.

  16. Longitudinal change instead of baseline testosterone predicts depressive symptoms.

    Science.gov (United States)

    Kische, Hanna; Pieper, Lars; Venz, John; Klotsche, Jens; März, Winfried; Koch-Gromus, Uwe; Pittrow, David; Lehnert, Hendrik; Silber, Sigmund; Stalla, G K; Zeiher, Andreas M; Wittchen, Hans-Ulrich; Haring, Robin

    2018-03-01

    The association between total testosterone (T) and depression mostly relies on single sex hormone assessment and remains inconclusive. Thus, we investigated the comparative predictive performance of baseline T and change in T with development of depressive symptoms and incident depressive episodes. We used data from 6493 primary care patients (2653 men and 3840 women) of the DETECT study (Diabetes Cardiovascular Risk-Evaluation: Targets and Essential Data for Commitment of Treatment), including four-year follow-up, repeated immunoassay-based measurement of serum T and depressive symptoms assessed by the Depression Screening Questionnaire (DSQ). Cross-sectional and longitudinal associations of baseline T and one-year change in T with prevalent and incident depression were investigated using age- and multivariable-adjusted regression models. Baseline T showed no association with prevalent or incident depressive symptoms and episodes in both sexes. In men, a positive change in T (higher T at one-year follow-up compared to baseline) was associated with a lower burden of depressive symptoms (β-coefficient per unit change in T: -0.17; 95% CI: -0.31 to -0.04) and lower risk of incident depressive symptoms (odds ratio per unit change in T: 0.84; 95% CI: 0.72-0.98) at four-year follow-up. In women, the association of T change with incident depressive episodes was rendered non-significant after multivariable adjustment. The present study observed a sex-specific inverse association of T change, but not baseline T, with increased depressive symptom burden in men. Future studies should assess longitudinal changes in sex hormone status as predictor of adverse health outcomes related to low T. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Solar activities and Climate change hazards

    Science.gov (United States)

    Hady, A. A., II

    2014-12-01

    Throughout the geological history of Earth, climate change is one of the recurrent natural hazards. In recent history, the impact of man brought about additional climatic change. Solar activities have had notable effect on palaeoclimatic changes. Contemporary, both solar activities and building-up of green-house gases effect added to the climatic changes. This paper discusses if the global worming caused by the green-house gases effect will be equal or less than the global cooling resulting from the solar activities. In this respect, we refer to the Modern Dalton Minimum (MDM) which stated that starting from year 2005 for the next 40 years; the earth's surface temperature will become cooler than nowadays. However the degree of cooling, previously mentioned in old Dalton Minimum (c. 210 y ago), will be minimized by building-up of green-house gases effect during MDM period. Regarding to the periodicities of solar activities, it is clear that now we have a new solar cycle of around 210 years. Keywords: Solar activities; solar cycles; palaeoclimatic changes; Global cooling; Modern Dalton Minimum.

  18. 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...

  19. Analysis and Prediction of Changes in Coastline Morphology in the Bohai Sea, China, Using Remote Sensing

    Directory of Open Access Journals (Sweden)

    Ying Fu

    2017-05-01

    Full Text Available Coastline change reflects the dynamics of natural processes and human activity, and influences the ecology and environment of the coastal strip. This study researched the change in coastline and sea area of the Bohai Sea, China, over a 30-year period using Landsat TM and OLI remote sensing data. The total change in coastline length, sea area, and the centroid of the sea surface were quantified. Variations in the coastline morphology were measured using four shape indexes: fractal dimension, compact ratio, circularity, and square degree. Equations describing fit of the shape index, coastline length, and marine area were built. Then the marine area 10 years later was predicted using the model that had the highest prediction accuracy. The results showed that the highest prediction accuracy for the coastline length was obtained using a compound function. When a cubic function was used to predict the compact ratio, then the highest prediction accuracy was obtained using this compact ratio and a quadratic function to predict sea area. This study can provide theoretical support for the coastal development planning and ecological environment protection around the Bohai Sea.

  20. 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

  1. 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.

  2. Method of predicting a change in an economy

    Science.gov (United States)

    Pryor, Richard J [Albuquerque, NM; Basu, Nipa [Albany, NY

    2006-01-10

    An economy whose activity is to be predicted comprises a plurality of decision makers. Decision makers include, for example, households, government, industry, and banks. The decision makers are represented by agents, where an agent can represent one or more decision makers. Each agent has decision rules that determine the agent's actions. Each agent can affect the economy by affecting variable conditions characteristic of the economy or the internal state of other agents. Agents can communicate actions through messages. On a multiprocessor computer, the agents can be assigned to processing elements.

  3. Predicting the Impacts of Climate Change on Central American Agriculture

    Science.gov (United States)

    Winter, J. M.; Ruane, A. C.; Rosenzweig, C.

    2011-12-01

    Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.

  4. Do the transtheoretical processes of change predict transitions in stages of change for fruit intake?

    NARCIS (Netherlands)

    de Vet, E.W.M.L.; de Nooijer, J.; de Vries, N.K.; Brug, J.

    2008-01-01

    In a longitudinal study, it is examined whether the transtheoretical processes of change do predict stage transitions in fruit intake. A random sample of an existing Internet research panel resulted in a cohort of 735 adults, who were examined three times with electronic questionnaires assessing

  5. Examining a Ripple Effect: Do Spouses’ Behavior Changes Predict Each Other’s Weight Loss?

    Directory of Open Access Journals (Sweden)

    Anna E. Schierberl Scherr

    2013-01-01

    Full Text Available Background. Including spouses in obesity treatment has been found to promote weight loss. We assessed whether spouses’ diet and activity changes impacted each other’s weight loss when both members attended an active weight loss program (TOGETHER or only the primary participant attended treatment (ALONE. Methods. Heterosexual couples (N=132 enrolled in an 18-month randomized controlled weight loss trial were weighed and completed measures of dietary intake and physical activity at baseline and 6 months. We conducted dyadic data analyses using the Actor-Partner Interdependence Model. Results. Participants’ weight loss was not predicted by their partners’ behavior changes. However, partners’ weight loss was predicted by their participants’ changes in calorie and fat intake. When partners were coupled with a participant who did not reduce their own calorie and fat intake as much, these partners had higher weight loss when treated in the TOGETHER group but lower weight loss when they were untreated in the ALONE group. There were no reciprocal effects found with physical activity changes. Conclusions. Direct treatment had the greatest impact on participants and partners who were treated. Untreated partners’ weight losses were positively impacted by their spouses’ dietary changes, suggesting a ripple effect from treated spouses to their untreated partners.

  6. Predicting Physical Activity in Arab American School Children

    Science.gov (United States)

    Martin, Jeffrey J.; McCaughtry, Nate; Shen, Bo

    2008-01-01

    Theoretically grounded research on the determinants of Arab American children's physical activity is virtually nonexistent. Thus, the purpose of our investigation was to evaluate the ability of the theory of planned behavior (TPB) and social cognitive theory (SCT) to predict Arab American children's moderate-to-vigorous physical activity (MVPA).…

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

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2010-01-01

    We propose a new approximation method for Gaussian process (GP) learning for large data sets that combines inline active set selection with hyperparameter optimization. The predictive probability of the label is used for ranking the data points. We use the leave-one-out predictive probability...... to the active set selection strategy and marginal likelihood optimization on the active set. We make extensive tests on the USPS and MNIST digit classification databases with and without incorporating invariances, demonstrating that we can get state-of-the-art results (e.g.0.86% error on MNIST) with reasonable...

  8. Prediction Activities at NASA's Global Modeling and Assimilation Office

    Science.gov (United States)

    Schubert, Siegfried

    2010-01-01

    The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the

  9. 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

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

    Science.gov (United States)

    Brander, K M

    2010-11-01

    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 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 can push it into decline unless the level of fishing is reduced: the idea of a stable carrying capacity is a dangerous myth. Overexploitation can be avoided by keeping fishing mortality low and by monitoring and responding rapidly to changes in productivity. There are signs that this lesson has been learned and that G. morhua will continue to be a mainstay of the human diet. © 2010 The Author. Journal of Fish Biology © 2010 The Fisheries Society of the British Isles.

  11. Predicting reading and mathematics from neural activity for feedback learning.

    Science.gov (United States)

    Peters, Sabine; Van der Meulen, Mara; Zanolie, Kiki; Crone, Eveline A

    2017-01-01

    Although many studies use feedback learning paradigms to study the process of learning in laboratory settings, little is known about their relevance for real-world learning settings such as school. In a large developmental sample (N = 228, 8-25 years), we investigated whether performance and neural activity during a feedback learning task predicted reading and mathematics performance 2 years later. The results indicated that feedback learning performance predicted both reading and mathematics performance. Activity during feedback learning in left superior dorsolateral prefrontal cortex (DLPFC) predicted reading performance, whereas activity in presupplementary motor area/anterior cingulate cortex (pre-SMA/ACC) predicted mathematical performance. Moreover, left superior DLPFC and pre-SMA/ACC activity predicted unique variance in reading and mathematics ability over behavioral testing of feedback learning performance alone. These results provide valuable insights into the relationship between laboratory-based learning tasks and learning in school settings, and the value of neural assessments for prediction of school performance over behavioral testing alone. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  12. Neural Activity During Health Messaging Predicts Reductions in Smoking Above and Beyond Self-Report

    Science.gov (United States)

    Falk, Emily B.; Berkman, Elliot T.; Whalen, Danielle; Lieberman, Matthew D.

    2011-01-01

    Objective The current study tested whether neural activity in response to messages designed to help smokers quit could predict smoking reduction, above and beyond self-report. Design Using neural activity in an a priori region of interest (a subregion of medial prefrontal cortex [MPFC]), in response to ads designed to help smokers quit smoking, we prospectively predicted reductions in smoking in a community sample of smokers (N = 28) who were attempting to quit smoking. Smoking was assessed via expired carbon monoxide (CO; a biological measure of recent smoking) at baseline and 1 month following exposure to professionally developed quitting ads. Results A positive relationship was observed between activity in the MPFC region of interest and successful quitting (increased activity in MPFC was associated with a greater decrease in expired CO). The addition of neural activity to a model predicting changes in CO from self-reported intentions, self-efficacy, and ability to relate to the messages significantly improved model fit, doubling the variance explained ( Rself−report2=.15,Rself−report+neuralactivity2=.35,Rchange2=.20). Conclusion: Neural activity is a useful complement to existing self-report measures. In this investigation, we extend prior work predicting behavior change based on neural activity in response to persuasive media to an important health domain and discuss potential psychological interpretations of the brain–behavior link. Our results support a novel use of neuroimaging technology for understanding the psychology of behavior change and facilitating health promotion. PMID:21261410

  13. Prediction of fine-tuned promoter activity from DNA sequence.

    Science.gov (United States)

    Siwo, Geoffrey; Rider, Andrew; Tan, Asako; Pinapati, Richard; Emrich, Scott; Chawla, Nitesh; Ferdig, Michael

    2016-01-01

    The quantitative prediction of transcriptional activity of genes using promoter sequence is fundamental to the engineering of biological systems for industrial purposes and understanding the natural variation in gene expression. To catalyze the development of new algorithms for this purpose, the Dialogue on Reverse Engineering Assessment and Methods (DREAM) organized a community challenge seeking predictive models of promoter activity given normalized promoter activity data for 90 ribosomal protein promoters driving expression of a fluorescent reporter gene. By developing an unbiased modeling approach that performs an iterative search for predictive DNA sequence features using the frequencies of various k-mers, inferred DNA mechanical properties and spatial positions of promoter sequences, we achieved the best performer status in this challenge. The specific predictive features used in the model included the frequency of the nucleotide G, the length of polymeric tracts of T and TA, the frequencies of 6 distinct trinucleotides and 12 tetranucleotides, and the predicted protein deformability of the DNA sequence. Our method accurately predicted the activity of 20 natural variants of ribosomal protein promoters (Spearman correlation r = 0.73) as compared to 33 laboratory-mutated variants of the promoters (r = 0.57) in a test set that was hidden from participants. Notably, our model differed substantially from the rest in 2 main ways: i) it did not explicitly utilize transcription factor binding information implying that subtle DNA sequence features are highly associated with gene expression, and ii) it was entirely based on features extracted exclusively from the 100 bp region upstream from the translational start site demonstrating that this region encodes much of the overall promoter activity. The findings from this study have important implications for the engineering of predictable gene expression systems and the evolution of gene expression in naturally occurring

  14. 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.

  15. 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.

  16. Predicting Change in Marital Satisfaction Throughout Emotionally Focused Couple Therapy.

    Science.gov (United States)

    Dalgleish, Tracy L; Johnson, Susan M; Burgess Moser, Melissa; Lafontaine, Marie-France; Wiebe, Stephanie A; Tasca, Giorgio A

    2015-07-01

    Emotionally focused couple therapy (EFT) is an empirically validated approach to couple therapy that uses attachment theory to understand the needs and emotions of romantic partners. EFT is recognized as one of the most effective approaches to couple therapy, but to guide therapists in their use of EFT, a theoretically based model to predict change is needed. This study tested such a model by recruiting 32 couples, and 14 therapists who provided approximately 21 sessions of EFT. Couples completed self-report measures of marital satisfaction, attachment security, relationship trust, and emotional control at pre- and posttherapy and after each therapy session. Results of hierarchical linear modeling suggested that individuals higher on self-report attachment anxiety and higher levels of emotional control had greater change in marital satisfaction across EFT sessions. Assessing attachment security at the start of therapy will inform therapists of the emotion regulating strategies used by couples and may help couples achieve positive outcomes from EFT. © 2014 American Association for Marriage and Family Therapy.

  17. 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.

  18. How well do cognitive and environmental variables predict active commuting?

    Directory of Open Access Journals (Sweden)

    Godin Gaston

    2009-03-01

    Full Text Available Abstract Background In recent years, there has been growing interest in theoretical studies integrating cognitions and environmental variables in the prediction of behaviour related to the obesity epidemic. This is the approach adopted in the present study in reference to the theory of planned behaviour. More precisely, the aim of this study was to determine the contribution of cognitive and environmental variables in the prediction of active commuting to get to and from work or school. Methods A prospective study was carried out with 130 undergraduate and graduate students (93 females; 37 males. Environmental, cognitive and socio-demographic variables were evaluated at baseline by questionnaire. Two weeks later, active commuting (walking/bicycling to get to and from work or school was self-reported by questionnaire. Hierarchical multiple regression analyses were performed to predict intention and behaviour. Results The model predicting behaviour based on cognitive variables explained more variance than the model based on environmental variables (37.4% versus 26.8%; Z = 3.86, p p p Conclusion The results showed that cognitive variables play a more important role than environmental variables in predicting and explaining active commuting. When environmental variables were significant, they were mediated by cognitive variables. Therefore, individual cognitions should remain one of the main focuses of interventions promoting active commuting among undergraduate and graduate students.

  19. Changes in predicted muscle coordination with subject-specific muscle parameters for individuals after stroke.

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Brian A. Knarr

    2014-01-01

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

  1. A neural network model for olfactory glomerular activity prediction

    Science.gov (United States)

    Soh, Zu; Tsuji, Toshio; Takiguchi, Noboru; Ohtake, Hisao

    2012-12-01

    Recently, the importance of odors and methods for their evaluation have seen increased emphasis, especially in the fragrance and food industries. Although odors can be characterized by their odorant components, their chemical information cannot be directly related to the flavors we perceive. Biological research has revealed that neuronal activity related to glomeruli (which form part of the olfactory system) is closely connected to odor qualities. Here we report on a neural network model of the olfactory system that can predict glomerular activity from odorant molecule structures. We also report on the learning and prediction ability of the proposed model.

  2. Life-Space Mobility Change Predicts 6-Month Mortality.

    Science.gov (United States)

    Kennedy, Richard E; Sawyer, Patricia; Williams, Courtney P; Lo, Alexander X; Ritchie, Christine S; Roth, David L; Allman, Richard M; Brown, Cynthia J

    2017-04-01

    To examine 6-month change in life-space mobility as a predictor of subsequent 6-month mortality in community-dwelling older adults. Prospective cohort study. Community-dwelling older adults from five Alabama counties in the University of Alabama at Birmingham (UAB) Study of Aging. A random sample of 1,000 Medicare beneficiaries, stratified according to sex, race, and rural or urban residence, recruited between November 1999 and February 2001, followed by a telephone interview every 6 months for the subsequent 8.5 years. Mortality data were determined from informant contacts and confirmed using the National Death Index and Social Security Death Index. Life-space was measured at each interview using the UAB Life-Space Assessment, a validated instrument for assessing community mobility. Eleven thousand eight hundred seventeen 6-month life-space change scores were calculated over 8.5 years of follow-up. Generalized linear mixed models were used to test predictors of mortality at subsequent 6-month intervals. Three hundred fifty-four deaths occurred within 6 months of two sequential life-space assessments. Controlling for age, sex, race, rural or urban residence, and comorbidity, life-space score and life-space decline over the preceding 6-month interval predicted mortality. A 10-point decrease in life-space resulted in a 72% increase in odds of dying over the subsequent 6 months (odds ratio = 1.723, P space score at the beginning of a 6-month interval and change in life-space over 6 months were each associated with significant differences in subsequent 6-month mortality. Life-space assessment may assist clinicians in identifying older adults at risk of short-term mortality. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  3. 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

  4. 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.

  5. 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)

  6. 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.

  7. Transient Response of Aerobic and Anoxic Activated Sludge Activities to Sudden Substrate Concentration Changes

    DEFF Research Database (Denmark)

    Sin, G.; Vanrolleghem, P.A.; Gernaey, Krist

    2004-01-01

    The state-of-the-art understanding of activated sludge processes as summarized in activated sludge models (ASMs) predicts an instantaneous increase in the biomass activity (which is measured, e.g., by the corresponding respiration rate OUR, NUR, etc.) under sudden substrate concentration changes....... Experimental data (e.g., short-term batch respiration experiments under aerobic or anoxic conditions) collected for the calibration of the dynamic models (ASMs) often exhibit a transient phenomenon while attaining maximum activity, which cannot be explained by the current understanding of the activated sludge...... process. That transient phenomenon exhibits itself immediately upon addition of a substrate source to an endogenously respiring activated sludge sample and it usually takes a few minutes until the activated sludge reaches its maximum possible rate under given environmental conditions. This discrepancy...

  8. 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

  9. Functional and catalytic active sites prediction and docking analysis ...

    African Journals Online (AJOL)

    Bioinformatics

    2015-07-01

    Jul 1, 2015 ... African Journal of Biotechnology. Full Length Research Paper. Functional and catalytic active sites prediction and docking analysis of azoreductase enzyme in. Pseudomonas putida with a variety of commercially available azodyes. Bikash Thakuria, Chandra J Singha, Premchand Maisnam and Samrat ...

  10. 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

    A computational docking strategy using multiple conformations of the target protein is discussed and evaluated. A series of low molecular weight, competitive, nonpeptide protein tyrosine phosphatase inhibitors are considered for which the x-ray crystallographic structures in complex with protein...... 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...... predicted binding energy and a correct docking mode. Thirdly, to improve the predictability of the docking procedure in the general case, where only a single target protein structure is known, we evaluate an approach which takes possible protein side-chain conformational changes into account. Here, side...

  11. Misspecification in Latent Change Score Models: Consequences for Parameter Estimation, Model Evaluation, and Predicting Change.

    Science.gov (United States)

    Clark, D Angus; Nuttall, Amy K; Bowles, Ryan P

    2018-01-01

    Latent change score models (LCS) are conceptually powerful tools for analyzing longitudinal data (McArdle & Hamagami, 2001). However, applications of these models typically include constraints on key parameters over time. Although practically useful, strict invariance over time in these parameters is unlikely in real data. This study investigates the robustness of LCS when invariance over time is incorrectly imposed on key change-related parameters. Monte Carlo simulation methods were used to explore the impact of misspecification on parameter estimation, predicted trajectories of change, and model fit in the dual change score model, the foundational LCS. When constraints were incorrectly applied, several parameters, most notably the slope (i.e., constant change) factor mean and autoproportion coefficient, were severely and consistently biased, as were regression paths to the slope factor when external predictors of change were included. Standard fit indices indicated that the misspecified models fit well, partly because mean level trajectories over time were accurately captured. Loosening constraint improved the accuracy of parameter estimates, but estimates were more unstable, and models frequently failed to converge. Results suggest that potentially common sources of misspecification in LCS can produce distorted impressions of developmental processes, and that identifying and rectifying the situation is a challenge.

  12. The utility of an empirically derived co-activation ratio for muscle force prediction through optimization.

    Science.gov (United States)

    Brookham, Rebecca L; Middlebrook, Erin E; Grewal, Tej-jaskirat; Dickerson, Clark R

    2011-05-17

    Biomechanical optimization models that apply efficiency-based objective functions often underestimate or negate antagonist co-activation. Co-activation assists movement control, joint stabilization and limb stiffness and should be carefully incorporated into models. The purposes of this study were to mathematically describe co-activation relationships between elbow flexors and extensors during isometric exertions at varying intensity levels and postures, and secondly, to apply these co-activation relationships as constraints in an optimization muscle force prediction model of the elbow and assess changes in predictions made while including these constraints. Sixteen individuals performed 72 isometric exertions while holding a load in their right hand. Surface EMG was recorded from elbow flexors and extensors. A co-activation index provided a relative measure of flexor contribution to total activation about the elbow. Parsimonious models of co-activation during flexion and extension exertions were developed and added as constraints to a muscle force prediction model to enforce co-activation. Three different PCSA data sets were used. Elbow co-activation was sensitive to changes in posture and load. During flexion exertions the elbow flexors were activated about 75% MVC (this amount varied according to elbow angle, shoulder flexion and abduction angles, and load). During extension exertions the elbow flexors were activated about 11% MVC (this amount varied according to elbow angle, shoulder flexion angle and load). The larger PCSA values appeared to be more representative of the subject pool. Inclusion of these co-activation constraints improved the model predictions, bringing them closer to the empirically measured activation levels. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. 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.

  14. Predicting human brain activity associated with the meanings of nouns.

    Science.gov (United States)

    Mitchell, Tom M; Shinkareva, Svetlana V; Carlson, Andrew; Chang, Kai-Min; Malave, Vicente L; Mason, Robert A; Just, Marcel Adam

    2008-05-30

    The question of how the human brain represents conceptual knowledge has been debated in many scientific fields. Brain imaging studies have shown that different spatial patterns of neural activation are associated with thinking about different semantic categories of pictures and words (for example, tools, buildings, and animals). We present a computational model that predicts the functional magnetic resonance imaging (fMRI) neural activation associated with words for which fMRI data are not yet available. This model is trained with a combination of data from a trillion-word text corpus and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for thousands of other concrete nouns in the text corpus, with highly significant accuracies over the 60 nouns for which we currently have fMRI data.

  15. 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

  16. Predicting active users' personality based on micro-blogging behaviors.

    Science.gov (United States)

    Li, Lin; Li, Ang; Hao, Bibo; Guan, Zengda; Zhu, Tingshao

    2014-01-01

    Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 839 micro-blogging behavioral features, we first trained classification models utilizing Support Vector Machine (SVM), differentiating participants with high and low scores on each dimension of the Big Five Inventory [corrected]. The classification accuracy ranged from 84% to 92%. We also built regression models utilizing PaceRegression methods, predicting participants' scores on each dimension of the Big Five Inventory. The Pearson correlation coefficients between predicted scores and actual scores ranged from 0.48 to 0.54. Results indicated that active users' personality traits could be predicted by micro-blogging behaviors.

  17. Relevance of Self-reported Behavioral Changes Before Bariatric Surgery to Predict Success After Surgery.

    Science.gov (United States)

    Ledoux, Séverine; Sami, Ouidad; Breuil, Marie-Christine; Delapierre, Marie; Calabrese, Daniela; Msika, Simon; Coupaye, Muriel

    2017-06-01

    International guidelines emphasize the need for multidisciplinary preparation to improve the safety and effectiveness of bariatric surgery (BS), but whether the patient is ready for surgery is difficult to assess. The objective of this study was to explore whether inquiries on dietary habits and physical activity before surgery are predictive of postoperative weight loss. We prospectively assessed in 78 candidates for BS (age, 43 ± 12 years; M/F, 15/63; weight, 122 ± 17 kg; IMC, 44 ± 5 kg/m 2 ) anthropometric parameters, food intake, and physical activity (Baecke questionnaire) at the beginning and the end of a systematized preoperative preparation (7 ± 2 months) including consultations (mean number 7 ± 2) with a nutritionist, dietician, psychologist, and sports coach. During the preparation, weight change was zero (±5 kg). In contrast, self-reported caloric intake decreased from 2143 ± 640 to 1906 ± 564 kcal/24 h (p bariatric surgery, as illustrated by the absence of weight changes on average during the preoperative preparation. In contrast to dietary inquiry, self-reported changes in physical activity are predictive of postoperative weight loss after bariatric surgery.

  18. Metabolomic profiling of amines in sepsis predicts changes in NOS canonical pathways.

    Directory of Open Access Journals (Sweden)

    Abel Tesfai

    Full Text Available Nitric oxide synthase (NOS is a biomarker/target in sepsis. NOS activity is driven by amino acids, which cycle to regulate the substrate L-arginine in parallel with cycles which regulate the endogenous inhibitors ADMA and L-NMMA. The relationship between amines and the consequence of plasma changes on iNOS activity in early sepsis is not known.Our objective was to apply a metabolomics approach to determine the influence of sepsis on a full array of amines and what consequence these changes may have on predicted iNOS activity.34 amino acids were measured using ultra purification mass spectrometry in the plasma of septic patients (n = 38 taken at the time of diagnosis and 24-72 hours post diagnosis and of healthy volunteers (n = 21. L-arginine and methylarginines were measured using liquid-chromatography mass spectrometry and ELISA. A top down approach was also taken to examine the most changed metabolic pathways by Ingenuity Pathway Analysis. The iNOS supporting capacity of plasma was determined using a mouse macrophage cell-based bioassay.Of all the amines measured 22, including L-arginine and ADMA, displayed significant differences in samples from patients with sepsis. The functional consequence of increased ADMA and decreased L-arginine in context of all cumulative metabolic changes in plasma resulted in reduced iNOS supporting activity associated with sepsis.In early sepsis profound changes in amine levels were defined by dominant changes in the iNOS canonical pathway resulting in functionally meaningful changes in the ability of plasma to regulate iNOS activity ex vivo.

  19. Mandibular bone changes in 24 years and skeletal fracture prediction.

    Science.gov (United States)

    Jonasson, G; Sundh, V; Hakeberg, M; Hassani-Nejad, A; Lissner, L; Ahlqwist, M

    2013-03-01

    The objectives of the investigation were to describe changes in mandibular bone structure with aging and to compare the usefulness of cortical and trabecular bone for fracture prediction. From 1968 to 1993, 1,003 women were examined. With the help of panoramic radiographs, cortex thickness was measured and cortex was categorized as: normal, moderately, or severely eroded. The trabeculation was assessed as sparse, mixed, or dense. Visually, the mandibular compact and trabecular bone transformed gradually during the 24 years. The compact bone became more porous, the intertrabecular spaces increased, and the radiographic image of the trabeculae seemed less mineralized. Cortex thickness increased up to the age of 50 and decreased significantly thereafter. At all examinations, the sparse trabeculation group had more fractures (71-78 %) than the non-sparse group (27-31 %), whereas the severely eroded compact group showed more fractures than the less eroded groups only in 1992/1993, 24 years later. Sparse trabecular pattern was associated with future fractures both in perimenopausal and older women (relative risk (RR), 1.47-4.37) and cortical erosion in older women (RR, 1.35-1.55). RR for future fracture associated with a severely eroded cortex increased to 4.98 for cohort 1930 in 1992/1993. RR for future fracture associated with sparse trabeculation increased to 11.43 for cohort 1922 in 1992/1993. Dental radiographs contain enough information to identify women most at risk of future fracture. When observing sparse mandibular trabeculation, dentists can identify 40-69 % of women at risk for future fractures, depending on participant age at examination.

  20. Application of artificial neural network (ANN) and partial least-squares regression (PLSR) to predict the changes of anthocyanins, ascorbic acid, Total phenols, flavonoids, and antioxidant activity during storage of red bayberry juice based on fractal analysis and red, green, and blue (RGB) intensity values.

    Science.gov (United States)

    Zheng, Hong; Jiang, Lingling; Lou, Heqiang; Hu, Ya; Kong, Xuecheng; Lu, Hongfei

    2011-01-26

    Artificial neural network (ANN) and partial least-squares regression (PLSR) models were developed to predict the changes of anthocyanin (AC), ascorbic acid (AA), total phenols (TP), total flavonoid (TF), and DPPH radical scavenging activity (SA) in bayberry juice during storage based on fractal analysis (FA) and red, green, and blue (RGB) intensity values. The results show the root mean squared error (RMSE) of ANN-FA decreased 2.44 and 12.45% for AC (RMSE = 18.673 mg/100 mL, R(2) = 0.939) and AA (RMSE = 8.694 mg/100 mL, R(2) = 0.935) compared with PLSR-RGB, respectively. In addition, PLSR-FA (RMSE = 5.966%, R(2) = 0.958) showed a 12.01% decrease in the RMSE compared with PLSR-RGB for predicting SA. For the prediction of TP and TF, however, both models showed poor performances based on FA and RGB. Therefore, ANN and PLSR combined with FA may be a potential method for quality evaluation of bayberry juice during processing, storage, and distribution, but the selection of the most adequate model is of great importance to predict different nutritional components.

  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. 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.

  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. 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.)

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. PREDICTION OF CHANGES IN VEGETATION DISTRIBUTION UNDER CLIMATE CHANGE SCENARIOS USING MODIS DATASET

    Directory of Open Access Journals (Sweden)

    H. Hirayama

    2016-06-01

    Full Text Available The distribution of vegetation is expected to change under the influence of climate change. This study utilizes vegetation maps derived from Terra/MODIS data to generate a model of current climate conditions suitable to beech-dominated deciduous forests, which are the typical vegetation of Japan’s cool temperate zone. This model will then be coordinated with future climate change scenarios to predict the future distribution of beech forests. The model was developed by using the presence or absence of beech forest as the dependent variable. Four climatic variables; mean minimum daily temperature of the coldest month (TMC,warmth index (WI, winter precipitation (PRW and summer precipitation (PRS: and five geophysical variables; topography (TOPO, surface geology (GEOL, soil (SOIL, slope aspect (ASP, and inclination (INCL; were adopted as independent variables. Previous vegetation distribution studies used point data derived from field surveys. The remote sensing data utilized in this study, however, should permit collecting of greater amounts of data, and also frequent updating of data and distribution maps. These results will hopefully show that use of remote sensing data can provide new insights into our understanding of how vegetation distribution will be influenced by climate change.

  10. 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.

  11. 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

  12. 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…

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

    DEFF Research Database (Denmark)

    Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, D.

    2016-01-01

    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 ..., 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...

  14. 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.

  15. 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

  16. 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.

  17. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    Science.gov (United States)

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-01

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Köhler theory to predict the effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid-liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.

  18. 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

  19. 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.

  20. Predicting the Responses of Soil Nitrite-Oxidizers to Multi-Factorial Global Change: A Trait-Based Approach

    DEFF Research Database (Denmark)

    Le Roux, Xavier; Bouskill, Nicholas J.; Niboyet, Audrey

    2016-01-01

    Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil...... change scenarios for central California) on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB). Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting...... how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic Nitrobacter, rare under most treatments, became dominant under the 'High CO2+Nitrogen...

  1. Schizophrenia polygenic risk score predicts mnemonic hippocampal activity.

    Science.gov (United States)

    Chen, Qiang; Ursini, Gianluca; Romer, Adrienne L; Knodt, Annchen R; Mezeivtch, Karleigh; Xiao, Ena; Pergola, Giulio; Blasi, Giuseppe; Straub, Richard E; Callicott, Joseph H; Berman, Karen F; Hariri, Ahmad R; Bertolino, Alessandro; Mattay, Venkata S; Weinberger, Daniel R

    2018-02-03

    The use of polygenic risk scores has become a practical translational approach to investigating the complex genetic architecture of schizophrenia, but the link between polygenic risk scores and pathophysiological components of this disorder has been the subject of limited research. We investigated in healthy volunteers whether schizophrenia polygenic risk score predicts hippocampal activity during simple memory encoding, which has been proposed as a risk-associated intermediate phenotype of schizophrenia. We analysed the relationship between polygenic risk scores and hippocampal activity in a discovery sample of 191 unrelated healthy volunteers from the USA and in two independent replication samples of 76 and 137 healthy unrelated participants from Europe and the USA, respectively. Polygenic risk scores for each individual were calculated as the sum of the imputation probability of reference alleles weighted by the natural log of odds ratio from the recent schizophrenia genome-wide association study. We examined hippocampal activity during simple memory encoding of novel visual stimuli assessed using blood oxygen level-dependent functional MRI. Polygenic risk scores were significantly associated with hippocampal activity in the discovery sample [P = 0.016, family-wise error (FWE) corrected within Anatomical Automatic Labeling (AAL) bilateral hippocampal-parahippocampal mask] and in both replication samples (P = 0.033, FWE corrected within AAL right posterior hippocampal-parahippocampal mask in Bari sample, and P = 0.002 uncorrected in the Duke Neurogenetics Study sample). The relationship between polygenic risk scores and hippocampal activity was consistently negative, i.e. lower hippocampal activity in individuals with higher polygenic risk scores, consistent with previous studies reporting decreased hippocampal-parahippocampal activity during declarative memory tasks in patients with schizophrenia and in their healthy siblings. Polygenic risk scores accounted for

  2. 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.

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

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

    IDRC

    epidemic in areas not traditionally prone to the disease, and to manage it better.” Collaborators in this KEMRI-led research include Uganda's Ministry of Health;. Tanzania's National Institute for Medical. Research; IGAD's Climate Prediction and. Application Centre; the International. Centre for Insect Physiology and Ecology;.

  4. Dangerous Mindsets: How Beliefs about Intelligence Predict Motivational Change

    Science.gov (United States)

    Haimovitz, Kyla; Wormington, Stephanie V.; Corpus, Jennifer Henderlong

    2011-01-01

    The present study examined how beliefs about intelligence, as mediated by ability-validation goals, predicted whether students lost or maintained levels of intrinsic motivation over the course of a single academic year. 978 third- through eighth-grade students were surveyed in the fall about their theories concerning the malleability of…

  5. 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 ...

  6. Model prediction of maize yield responses to climate change in ...

    African Journals Online (AJOL)

    Observed data of the last three decades (1971 to 2000) from several climatological stations in north-eastern Zimbabwe and outputs from several global climate models were used. The downscaled model simulations consistently predicted a warming of between 1 and 2 ºC above the baseline period (1971-2000) at most of ...

  7. 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.

  8. 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...

  9. Toward the Prediction of FBPase Inhibitory Activity Using Chemoinformatic Methods

    Directory of Open Access Journals (Sweden)

    Shuwei Zhang

    2012-06-01

    Full Text Available Currently, Chemoinformatic methods are used to perform the prediction for FBPase inhibitory activity. A genetic algorithm-random forest coupled method (GA-RF was proposed to predict fructose 1,6-bisphosphatase (FBPase inhibitors to treat type 2 diabetes mellitus using the Mold2 molecular descriptors. A data set of 126 oxazole and thiazole analogs was used to derive the GA-RF model, yielding the significant non-cross-validated correlation coefficient r2ncv and cross-validated r2cv values of 0.96 and 0.67 for the training set, respectively. The statistically significant model was validated by a test set of 64 compounds, producing the prediction correlation coefficient r2pred of 0.90. More importantly, the building GA-RF model also passed through various criteria suggested by Tropsha and Roy with r2o and r2m values of 0.90 and 0.83, respectively. In order to compare with the GA-RF model, a pure RF model developed based on the full descriptors was performed as well for the same data set. The resulting GA-RF model with significantly internal and external prediction capacities is beneficial to the prediction of potential oxazole and thiazole series of FBPase inhibitors prior to chemical synthesis in drug discovery programs.

  10. Do temporal changes in vegetation structure additional to time since fire predict changes in bird occurrence?

    Science.gov (United States)

    Lindenmayer, David B; Candy, Steven G; MacGregor, Christopher I; Banks, Sam C; Westgate, Martin; Ikin, Karen; Pierson, Jennifer; Tulloch, Ayesha; Barton, Philip

    2016-10-01

    Fire is a major ecological process in ecosystems globally. Its impacts on fauna can be both direct (e.g., mortality) and indirect (e.g., altered habitat), resulting in population recovery being driven by several possible mechanisms. Separating direct from indirect impacts of fire on faunal population recovery can be valuable in guiding management of biodiversity in fire-prone environments. However, resolving the influence of direct and indirect processes remains a key challenge because many processes affecting fauna can change concomitantly with time since fire. We explore the mechanisms influencing bird response to fire by posing the question, can temporal changes in vegetation structure predict changes in bird occurrence on sites, and can these be separated from other temporal changes using the surrogate of time since fire? We conducted a 12-yr study of bird and vegetation responses to fire at 124 sites across six vegetation classes in Booderee National Park, Australia. Approximately half of these sites, established in 2002, were burned by a large (>3000 ha) wildfire in 2003. To disentangle collinear effects of temporal changes in vegetation and direct demographic effects on population recovery that are subsumed by time since fire, we incorporated both longitudinal and cross-sectional vegetation effects in addition to time since fire within logistic structural equation models. We identified temporal changes in vegetation structure and richness of plant and bird species that characterized burned and unburned sites in all vegetation classes. For nine bird species, a significant component of the year trend was driven by temporal trends in one of three vegetation variables (number of understory or midstory plant species, or midstory cover). By contrast, we could not separate temporal effects between time since fire and vegetation attributes for bird species richness, reporting rate, and the occurrence of 11 other bird species. Our findings help identify species for

  11. 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.…

  12. Abrupt climate change and thermohaline circulation: mechanisms and predictability.

    Science.gov (United States)

    Marotzke, J

    2000-02-15

    The ocean's thermohaline circulation has long been recognized as potentially unstable and has consequently been invoked as a potential cause of abrupt climate change on all timescales of decades and longer. However, fundamental aspects of thermohaline circulation changes remain poorly understood.

  13. Abrupt climate change and thermohaline circulation: Mechanisms and predictability

    OpenAIRE

    Marotzke, Jochem

    2000-01-01

    The ocean's thermohaline circulation has long been recognized as potentially unstable and has consequently been invoked as a potential cause of abrupt climate change on all timescales of decades and longer. However, fundamental aspects of thermohaline circulation changes remain poorly understood.

  14. And yet they correlate: psychophysiological activation predicts self-report outcomes of exposure therapy in claustrophobia.

    Science.gov (United States)

    Alpers, Georg W; Sell, Roxane

    2008-10-01

    The study examines whether self-reported fear and physiological activation are concordant when claustrophobic patients are exposed to small spaces, whether the measures change in synchrony for individual patients and whether initial activation of measures can predict the outcome of an exposure treatment. Ten patients with claustrophobia participated in six in-vivo exposure sessions with continuous monitoring of self-reported fear and their EKG. Partial pressure of carbon dioxide (pCO(2)), a measure of hyperventilation, was available in a subsample of patients. While evidence for concordance of self-reported fear and heart rate was limited, the measures changed synchronously within subjects. Most importantly, higher heart rate at the beginning of the first exposure session predicted better treatment outcome. Because self-reported fear turned out not to be a reliable predictor of the outcome, this is interpreted as evidence for the incremental validity of physiological measures of fear.

  15. 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

  16. Real-time Neural Network predictions of geomagnetic activity indices

    Science.gov (United States)

    Bala, R.; Reiff, P. H.

    2009-12-01

    The Boyle potential or the Boyle Index (BI), Φ (kV)=10-4 (V/(km/s))2 + 11.7 (B/nT) sin3(θ/2), is an empirically-derived formula that can characterize the Earth's polar cap potential, which is readily derivable in real time using the solar wind data from ACE (Advanced Composition Explorer). The BI has a simplistic form that utilizes a non-magnetic "viscous" and a magnetic "merging" component to characterize the magnetospheric behavior in response to the solar wind. We have investigated its correlation with two of conventional geomagnetic activity indices in Kp and the AE index. We have shown that the logarithms of both 3-hr and 1-hr averages of the BI correlate well with the subsequent Kp: Kp = 8.93 log10(BI) - 12.55 along with 1-hr BI correlating with the subsequent log10(AE): log10(AE) = 1.78 log10(BI) - 3.6. We have developed a new set of algorithms based on Artificial Neural Networks (ANNs) suitable for short term space weather forecasts with an enhanced lead-time and better accuracy in predicting Kp and AE over some leading models; the algorithms omit the time history of its targets to utilize only the solar wind data. Inputs to our ANN models benefit from the BI and its proven record as a forecasting parameter since its initiation in October, 2003. We have also performed time-sensitivity tests using cross-correlation analysis to demonstrate that our models are as efficient as those that incorporates the time history of the target indices in their inputs. Our algorithms can predict the upcoming full 3-hr Kp, purely from the solar wind data and achieve a linear correlation coefficient of 0.840, which means that it predicts the upcoming Kp value on average to within 1.3 step, which is approximately the resolution of the real-time Kp estimate. Our success in predicting Kp during a recent unexpected event (22 July ’09) is shown in the figure. Also, when predicting an equivalent "one hour Kp'', the correlation coefficient is 0.86, meaning on average a prediction

  17. Predicting bee community responses to land-use changes

    NARCIS (Netherlands)

    Palma, De Adriana; Abrahamczyk, Stefan; Aizen, Marcelo A.; Albrecht, Matthias; Basset, Yves; Bates, Adam; Blake, Robin J.; Boutin, Céline; Bugter, Rob; Connop, Stuart; Cruz-López, Leopoldo; Cunningham, Saul A.; Darvill, Ben; Diekötter, Tim; Dorn, Silvia; Downing, Nicola; Entling, Martin H.; Farwig, Nina; Felicioli, Antonio; Fonte, Steven J.; Fowler, Robert; Franzén, Markus; Goulson, Dave; Grass, Ingo; Hanley, Mick E.; Hendrix, Stephen D.; Herrmann, Farina; Herzog, Felix; Holzschuh, Andrea; Jauker, Birgit; Kessler, Michael; Knight, M.E.; Kruess, Andreas; Lavelle, Patrick; Féon, Le Violette; Lentini, Pia; Malone, Louise A.; Marshall, Jon; Pachón, Eliana Martínez; McFrederick, Quinn S.; Morales, Carolina L.; Mudri-Stojnic, Sonja; Nates-Parra, Guiomar; Nilsson, Sven G.; Öckinger, Erik; Osgathorpe, Lynne; Parra-H, Alejandro; Peres, Carlos A.; Persson, Anna S.; Petanidou, Theodora; Poveda, Katja; Power, Eileen F.; Quaranta, Marino; Quintero, Carolina; Rader, Romina; Richards, Miriam H.; Roulston, Tai; Rousseau, Laurent; Sadler, Jonathan P.; Samnegård, Ulrika; Schellhorn, Nancy A.; Schüepp, Christof; Schweiger, Oliver; Smith-Pardo, Allan H.; Steffan-Dewenter, Ingolf; Stout, Jane C.; Tonietto, Rebecca K.; Tscharntke, Teja; Tylianakis, Jason M.; Verboven, Hans A.F.; Vergara, Carlos H.; Verhulst, Jort; Westphal, Catrin; Yoon, Hyung Joo; Purvis, Andy

    2016-01-01

    Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically

  18. Limited predictability of extreme decadal changes in the Arctic Ocean freshwater content

    Science.gov (United States)

    Schmith, Torben; Olsen, Steffen M.; Ringgaard, Ida M.; May, Wilhelm

    2018-02-01

    Predictability of extreme changes in the Arctic Ocean freshwater content and the associated release into the subpolar North Atlantic up to one decade ahead is investigated using a CMIP5-type global climate model. The perfect-model setup consists of a 500 year control run, from which selected 10 year long segments are predicted by initialized, perturbed ensemble predictions. Initial conditions for these are selected from the control run to represent large positive or negative decadal changes in the total freshwater content in the Arctic Ocean. Two different classes of ensemble predictions are performed, one initialized with the `observed' ocean globally, and one initialized with the model climatology in the Arctic Ocean and with the observed ocean elsewhere. Analysis reveals that the former yields superior predictions 1 year ahead as regards both liquid freshwater content and sea ice volume in the Arctic Ocean. For prediction years two and above there is no overall gain in predictability from knowing the initial state in the Arctic Ocean and damped persistence predictions perform just as well as the ensemble predictions. Areas can be identified, mainly in the proper Canadian and Eurasian basins, where knowledge of the initial conditions gives a gain in predictability of liquid freshwater content beyond year two. Total freshwater export events from the Arctic Ocean into the subpolar North Atlantic have no predictability even 1 year ahead. This is a result of the sea ice component not being predictable and LFW being on the edge of being predictable for prediction time 1 year.

  19. 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.

  20. 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.

  1. NMME-based hybrid prediction of Atlantic hurricane season activity

    Science.gov (United States)

    Harnos, Daniel S.; Schemm, Jae-Kyung E.; Wang, Hui; Finan, Christina A.

    2017-09-01

    A hybrid dynamical-statistical model is pursued for prediction of Atlantic seasonal hurricane activity driven by output of the North American Multimodel Ensemble (NMME). This is an updated version of a proven multiple linear regression method conditioned on forecast vertical wind shear from the Climate Forecast System and observed sea surface temperatures (SSTs). The method pursued for prediction utilizes August-October (ASO) Main Development Region (MDR; 10-20°N, 20-80°W) vertical wind shear and observed North Atlantic (NATL; 55-65°N, 30-60°W) SST averaged over the 3 months preceding the forecast in conjunction with the full hurricane climatology. NMME forecasts improve upon representations relative to individual members. The NMME multi-model mean better reproduces vertical wind shear distributions over the MDR and captures the observed relationships between SST and vertical wind shear with hurricane trend and interannual variability despite occasionally poor reproductions by individual members. Cross-validation reveals the multi-model average of the hybrid model outputs from the individual NMME members yields forecast errors 10-30% less than the individual members, while correlations with observed hurricane-related activity typically improve. The NMME methodology is shown to be competitive with official outlooks from Colorado State University and the National Oceanic and Atmospheric Administration over recent years.

  2. Thermodynamic prediction of active ingredient loading in polymeric microparticles.

    Science.gov (United States)

    Tse, G; Blankschtein, D; Shefer, A; Shefer, S

    1999-06-28

    The growing use of microparticles as a controlled-delivery system for pharmaceutical and non-pharmaceutical active ingredients (AIs) has prompted a costly trial-and-error development of new and effective microparticle systems. In order to facilitate a more rational design and optimization of AI loadings in microparticles, we have developed a molecular-thermodynamic theory to predict the loading of liquid AIs in polymeric microparticles that are manufactured by a solvent evaporation process. This process involves the emulsification of a liquid polymer solution (consisting of polymer and AI dissolved in a volatile solvent) in an aqueous surfactant solution. The theory describes the equilibrium distribution of the AI between the aqueous phase and the dispersed polymeric droplets. The universal functional activity coefficient (UNIFAC) and UNIFAC-Free Volume (FV) group-contribution methods are utilized to model the nonidealities in the water and polymeric droplet phases, respectively. The inputs to the theory are: (i) the chemical structures, densities and total masses of the manufacturing ingredients, (ii) the manufacturing temperature and (iii) the glass transition temperature of the polymer. Since surfactant concentrations exceeding the critical micellar concentration (CMC) are often required in order to stabilize the dispersed polymeric droplets during the emulsion manufacturing process, the theory also accounts for AI solubilization in surfactant micelles present in the manufacturing solution. To test the AI loading predictions, we compare theoretical predictions of AI loadings in poly(lactic acid), poly(methyl methacrylate) and polystyrene microparticles to experimentally measured ones for five model AIs with varying degrees of hydrophobicity (benzyl alcohol, n-octanol, geraniol, farnesol and galaxolide). We also demonstrate how the developed theory can be utilized to screen polymers with respect to their abilities to load a given AI, as well as to provide

  3. Predicting the responses of soil nitrite-oxidizers to multi-factorial global change: a trait-based approach

    Directory of Open Access Journals (Sweden)

    Xavier eLE ROUX

    2016-05-01

    Full Text Available Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global change scenarios for central California on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB. Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic Nitrobacter, rare under most treatments, became dominant under the ‘High CO2+Nitrogen+Precipitation’ treatment. The mechanistic trait-based model, which simulated ecological niches of NOB types consistent with previous ecophysiological reports, helped predicting the observed effects of global change on NOB and elucidating the underlying biotic and abiotic controls. Our results are a starting point for representing the overwhelming diversity of soil bacteria by a few functional types that can be incorporated into models of terrestrial ecosystems and biogeochemical processes.

  4. Predicting the Responses of Soil Nitrite-Oxidizers to Multi-Factorial Global Change: A Trait-Based Approach.

    Science.gov (United States)

    Le Roux, Xavier; Bouskill, Nicholas J; Niboyet, Audrey; Barthes, Laure; Dijkstra, Paul; Field, Chris B; Hungate, Bruce A; Lerondelle, Catherine; Pommier, Thomas; Tang, Jinyun; Terada, Akihiko; Tourna, Maria; Poly, Franck

    2016-01-01

    Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global change scenarios for central California) on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB). Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic Nitrobacter, rare under most treatments, became dominant under the 'High CO2+Nitrogen+Precipitation' treatment. The mechanistic trait-based model, which simulated ecological niches of NOB types consistent with previous ecophysiological reports, helped predicting the observed effects of global change on NOB and elucidating the underlying biotic and abiotic controls. Our results are a starting point for representing the overwhelming diversity of soil bacteria by a few functional types that can be incorporated into models of terrestrial ecosystems and biogeochemical processes.

  5. 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.

  6. 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.

  7. Western Mountain Initiative: predicting ecosystem responses to climate change

    Science.gov (United States)

    Baron, Jill S.; Peterson, David L.; Wilson, J.T.

    2008-01-01

    Mountain ecosystems of the western United States provide irreplaceable goods and services such as water, timber, biodiversity, and recreational opportunities, but their responses to climatic changes are complex and not well understood. The Western Mountain Initiative (WMI), a collaboration between USGS and U.S. Forest Service scientists, catalyzes assessment and synthesis of the effects of disturbance and climate change across western mountain areas, focusing on national parks and surrounding national forests. The WMI takes an ecosystem approach to science, integrating research across science disciplines at scales ranging from field studies to global trends.

  8. Cortical alpha activity predicts the confidence in an impending action

    Science.gov (United States)

    Kubanek, Jan; Hill, N. Jeremy; Snyder, Lawrence H.; Schalk, Gerwin

    2015-01-01

    When we make a decision, we experience a degree of confidence that our choice may lead to a desirable outcome. Recent studies in animals have probed the subjective aspects of the choice confidence using confidence-reporting tasks. These studies showed that estimates of the choice confidence substantially modulate neural activity in multiple regions of the brain. Building on these findings, we investigated the neural representation of the confidence in a choice in humans who explicitly reported the confidence in their choice. Subjects performed a perceptual decision task in which they decided between choosing a button press or a saccade while we recorded EEG activity. Following each choice, subjects indicated whether they were sure or unsure about the choice. We found that alpha activity strongly encodes a subject's confidence level in a forthcoming button press choice. The neural effect of the subjects' confidence was independent of the reaction time and independent of the sensory input modeled as a decision variable. Furthermore, the effect is not due to a general cognitive state, such as reward expectation, because the effect was specifically observed during button press choices and not during saccade choices. The neural effect of the confidence in the ensuing button press choice was strong enough that we could predict, from independent single trial neural signals, whether a subject was going to be sure or unsure of an ensuing button press choice. In sum, alpha activity in human cortex provides a window into the commitment to make a hand movement. PMID:26283892

  9. [Model for predicting childhood obesity from diet and physical activity].

    Science.gov (United States)

    Larrosa-Haro, Alfredo; González-Pérez, Guillermo Julián; Vásquez-Garibay, Edgar Manuel; Romero-Velarde, Enrique; Chávez-Palencia, Clío; Salazar-Preciado, Laura Leticia; Lizárraga-Corona, Elizabeth

    2014-01-01

    If obesity results from the interaction of variables that involve the subject and his environment, the alternatives to face the problem could be very diverse. The objective of this study was to seek for the best predictive model of childhood obesity from energy ingestion, dietary habits and physical activity. Case control study of 99 obese and 100 healthy weight children (Center for Diseases Control criteria). Energy ingestion was estimated by means of a 24-hour recall, dietary and physical activity habits by validated questionnaires. A logistic regression analysis was made. Variables independently associated to obesity were higher energy ingestion; lower frequency in mealtimes; having the afternoon lunch outside home; higher frequency of consumption of fat, junk food and sweetened beverages; lower time of moderate physical activity at school and at home; and increased time for homework and watching TV. The variables included in the regression model were energy intake; frequency of ingestion of fat, junk foods and sweetened beverages; and physical activity at home and at school. The diversity of associated variables underlines the complexity and multi-causal condition of obesity.

  10. 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.

  11. Metabolic activity measured by FDG PET predicts pathological response in locally advanced superior sulcus NSCLC.

    Science.gov (United States)

    Bahce, I; Vos, C G; Dickhoff, C; Hartemink, K J; Dahele, M; Smit, E F; Boellaard, R; Hoekstra, O S; Thunnissen, E

    2014-08-01

    Pathological complete response and tumor regression to less than 10% vital tumor cells after induction chemoradiotherapy have been shown to be prognostically important in non-small cell lung cancer (NSCLC). Predictive imaging biomarkers could help treatment decision-making. The purpose of this study was to assess whether postinduction changes in tumor FDG uptake could predict pathological response and to evaluate the correlation between residual vital tumor cells and post-induction FDG uptake. NSCLC patients with sulcus superior tumor (SST), planned for trimodality therapy, routinely undergo FDG PET/CT scans before and after induction chemoradiotherapy in our institute. Metabolic end-points based on standardized uptake values (SUV) were calculated, including SUV(max) (maximum SUV), SUV(TTL) (tumor-to-liver ratio), SUV(peak) (SUV within 1 cc sphere with highest activity), and SUV(PTL) (peak-to-liver ratio). Pathology specimens were assessed for residual vital tumor cell percentages and scored as no (grade 3), 10% vital tumor cells (grade 2a/1). 19 and 23 patients were evaluated for (1) metabolic change and (2) postinduction PET-pathology correlation, respectively. Changes in all parameters were predictive for grade 2b/3 response. ΔSUV(TTL) and ΔSUV(PTL) were also predictive for grade 3 response. Remaining vital tumor cells correlated with post-induction SUV(peak) (R=0.55; P=0.007) and postinduction SUV(PTL) (R=0.59; P=0.004). Postinduction SUV(PTL) could predict both grades 3 and 2b/3 response. In NSCLC patients treated with chemoradiotherapy, changes in SUV(max), SUV(TTL), SUV(peak), and SUV(PTL) were predictive for pathological response (grade 2b/3 and for SUV(TTL) and SUV(PTL) grade 3 as well). Postinduction SUV(PTL) correlated with residual tumor cells. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  12. Predicting when climate-driven phenotypic change affects population dynamics

    NARCIS (Netherlands)

    McLean, Nina; Lawson, C.R.; Leech, David; Van de Pol, M.

    Species' responses to climate change are variable and diverse, yet our understanding of how different responses (e.g. physiological, behavioural, demographic) relate and how they affect the parameters most relevant for conservation (e.g. population persistence) is lacking. Despite this, studies that

  13. Predictors and Predictive Effects of Attitudinal Inconsistency Towards Organizational Change

    Science.gov (United States)

    2012-03-01

    inconsistency of cognition and affect to reconfigure job satisfaction. Oreg and Sverdlik (2011) recently applied ambivalence between evaluations of the manager...Consistency, intensity, salience, accessibility, knowledge, centrality, embeddedness , complexity, importance, and vested interest have served as...occur because conditions for motivation are improved. Cole et al. (2006) found that the quality of the change procedure increased job satisfaction and

  14. 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.

  15. Can We Predict Types of Code Changes? An Empirical Analysis

    NARCIS (Netherlands)

    Giger, E.; Pinzger, M.; Gall, H.C.

    2012-01-01

    Preprint of paper published in: 9th IEEE Working Conference on Mining Software Repositories (MSR), 2-3 June 2012; doi:10.1109/MSR.2012.6224284 There exist many approaches that help in pointing developers to the change-prone parts of a software system. Although beneficial, they mostly fall short in

  16. Relationship satisfaction predicts sexual activity following risk-reducing salpingo-oophorectomy

    Science.gov (United States)

    Lorenz, Tierney; McGregor, Bonnie; Swisher, Elizabeth

    2014-01-01

    Changes in sexual function are a common outcome following risk-reducing salpingo-oophorectomy (RRSO), a prophylactic surgery for women at high risk of ovarian and other gynecologic cancers. Despite the known importance of sexuality in patients’ quality of life and satisfaction with surgery, little is known about what predicts sexual activity following RRSO. The present study examined how mental and physical health variables predicted sexual activity before and after RRSO. We conducted a secondary analysis of quality of life measures collected in 85 women at high risk for ovarian cancer. Participants completed validated measures of mental, physical, and relationship health 1–2 weeks before surgery, and 2, 6 and 12 months following surgery. Across analyses, relationship satisfaction emerged as the most significant predictor of change in sexual activity: women with high relationship satisfaction were more likely to continue to have regular sexual activity following RRSO, even in the presence of vaginal menopausal symptoms. The effect of depression, anxiety and overall physical health on sexual activity was non-significant when controlling for relationship satisfaction. When counseling women about RRSO and its impact on sexual activity, clinicians should discuss the effect of the patient’s relationship health on this outcome. PMID:24693956

  17. 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

  18. 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

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

    Directory of Open Access Journals (Sweden)

    Murtagh Shemane

    2012-05-01

    Full Text Available Abstract 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

  20. Predicting active school travel: the role of planned behavior and habit strength.

    Science.gov (United States)

    Murtagh, Shemane; Rowe, David A; Elliott, Mark A; McMinn, David; Nelson, Norah M

    2012-05-30

    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. 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. 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. 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 antecedents of children's active school travel.

  1. 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

  2. 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...

  3. 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.

  4. Larvicidal activity prediction againstAedes aegyptimosquito using computational tools.

    Science.gov (United States)

    Cañizares-Carmenate, Yudith; Hernandez-Morfa, Mirelys; Torrens, Francisco; Castellano, Gloria; Castillo-Garit, Juan A

    2017-01-01

    Aedes aegypti is an important vector for transmission of dengue, yellow fever, chikun- gunya, arthritis, and Zika fever. According to the World Health Organization, it is estimated that Ae. aegypti causes 50 million infections and 25,000 deaths per year. Use of larvicidal agents is one of the recommendations of health organizations to control mosquito populations and limit their distribution. The aim of present study was to deduce a mathematical model to predict the larvicidal action of chemical compounds, based on their structure. A series of different compounds with experimental evidence of larvicidal activity were selected to develop a predictive model, using multiple linear regression and a genetic algorithm for the selection of variables, implemented in the QSARINS software. The model was assessed and validated using the OECDs principles. The best model showed good value for the determination coefficient (R2 = 0.752), and others parameters were appropriate for fitting (s = 0.278 and RMSEtr = 0.261). The validation results confirmed that the model hasgood robustness (Q2LOO = 0.682) and stability (R2-Q2LOO = 0.070) with low correlation between the descriptors (KXX = 0.241), an excellent predictive power (R2 ext = 0.834) and was product of a non-random correlation R2 Y-scr = 0.100). The present model shows better parameters than the models reported earlier in the literature, using the same dataset, indicating that the proposed computational tools are more efficient in identifying novel larvicidal compounds against Ae. aegypti.

  5. Solubility Prediction of Active Pharmaceutical Compounds with the UNIFAC Model

    Science.gov (United States)

    Nouar, Abderrahim; Benmessaoud, Ibtissem; Koutchoukali, Ouahiba; Koutchoukali, Mohamed Salah

    2016-03-01

    The crystallization from solution of an active pharmaceutical ingredient requires the knowledge of the solubility in the entire temperature range investigated during the process. However, during the development of a new active ingredient, these data are missing. Its experimental determination is possible, but tedious. UNIFAC Group contribution method Fredenslund et al. (Vapor-liquid equilibria using UNIFAC: a group contribution method, 1977; AIChE J 21:1086, 1975) can be used to predict this physical property. Several modifications on this model have been proposed since its development in 1977, modified UNIFAC of Dortmund Weidlich et al. (Ind Eng Chem Res 26:1372, 1987), Gmehling et al. (Ind Eng Chem Res 32:178, 1993), Pharma-modified UNIFAC Diedrichs et al. (Evaluation und Erweiterung thermodynamischer Modelle zur Vorhersage von Wirkstofflöslichkeiten, PhD Thesis, 2010), KT-UNIFAC Kang et al. (Ind Eng Chem Res 41:3260, 2002), ldots In this study, we used UNIFAC model by considering the linear temperature dependence of interaction parameters as in Pharma-modified UNIFAC and structural groups as defined by KT-UNIFAC first-order model. More than 100 binary datasets were involved in the estimation of interaction parameters. These new parameters were then used to calculate activity coefficient and solubility of some molecules in various solvents at different temperatures. The model gives better results than those from the original UNIFAC and shows good agreement between the experimental solubility and the calculated one.

  6. Predict Changes in Groundwater Systems Due to Construction of KURT

    International Nuclear Information System (INIS)

    Kim, Kyung Su; Koh, Young Kwon; Bae, Dae Seok; Kim, Geon Young; Park, Kyung Woo; Ji, Sung Hoon; Ryu, Ji Hoon

    2009-08-01

    Step 1 construction KURT facilities in connection with the entry of a 230m length of tunnel excavated by a tunnel and the research examined changes in groundwater systems. The continuum porous medium was assumed to be bedrock, Modflow model is used in the calculation. Input data from the KURT design phase consists of site surveys and existing YS series was based on data obtained from boreholes. This report has following contents: -Conceptual model and analysis presented area and the boundary conditions, Model calibration and calculation. This study evaluates the flow of groundwater and groundwater flow, impact, scope, and the underground water level derived drops

  7. 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.

  8. The meaning of life (events) predicts changes in attachment security.

    Science.gov (United States)

    Davila, Joanna; Sargent, Erica

    2003-11-01

    Building on prior research, which has failed to find consistent effects of life events on change in self-reported adult attachment security over time, the present study tested the hypothesis that it is the meaning people attach to events, rather than the objective features of events, that is associated with changing levels of security. Participants engaged in an 8-week daily diary study, during which they completed daily self-report measures of attachment security, negative life events, perceptions of loss associated with events, and mood. Hierarchical linear modeling revealed that perceptions of greater interpersonal (but not achievement) loss associated with life events were significantly associated with greater insecurity on a day-to-day basis, even controlling for objective features of events and for mood. Trait levels of security did not moderate this association. Results are discussed with regard to social-cognitive models of attachment security and the utility of understanding the meaning of life events to understand how attachment models may be confirmed or disconfirmed.

  9. Design Property Network-Based Change Propagation Prediction Approach for Mechanical Product Development

    Science.gov (United States)

    Ma, Songhua; Jiang, Zhaoliang; Liu, Wenping; Huang, Chuanzhen

    2017-05-01

    Design changes are unavoidable during mechanical product development; whereas the avalanche propagation of design change imposes severely negative impacts on the design cycle. To improve the validity of the change propagation prediction, a mathematical programming model is presented to predict the change propagation impact quantitatively. As the foundation of change propagation prediction, a design change analysis model(DCAM) is built in the form of design property network. In DCAM, the connections of the design properties are identified as the design specification, which conform to the small-world network theory. To quantify the change propagation impact, change propagation intensity(CPI) is defined as a quantitative and much more objective assessment metric. According to the characteristics of DCAM, CPI is defined and indicated by four assessment factors: propagation likelihood, node degree, long-chain linkage, and design margin. Furthermore, the optimal change propagation path is searched with the evolutionary ant colony optimization(ACO) algorithm, which corresponds to the minimized maximum of accumulated CPI. In practice, the change impact of a gear box is successfully analyzed. The proposed change propagation prediction method is verified to be efficient and effective, which could provide different results according to various the initial changes.

  10. Brain activation during fear extinction predicts exposure success.

    Science.gov (United States)

    Ball, Tali Manber; Knapp, Sarah E; Paulus, Martin P; Stein, Murray B

    2017-03-01

    Exposure therapy, a gold-standard treatment for anxiety disorders, is assumed to work via extinction learning, but this has never been tested. Anxious individuals demonstrate extinction learning deficits, likely related to less ventromedial prefrontal cortex (vmPFC) and more amygdala activation, but the relationship between these deficits and exposure outcome is unknown. We tested whether anxious individuals who demonstrate better extinction learning report greater anxiety reduction following brief exposure. Twenty-four adults with public speaking anxiety completed (1) functional magnetic resonance imaging during a conditioning paradigm, (2) a speech exposure session, and (3) anxiety questionnaires before and two weeks postexposure. Extinction learning was assessed by comparing ratings to a conditioned stimulus (neutral image) that was previously paired with an aversive noise against a stimulus that had never been paired. Robust regression analyses examined whether brain activation during extinction learning predicted anxiety reduction two weeks postexposure. On average, the conditioning paradigm resulted in acquisition and extinction effects on stimulus ratings, and the exposure session resulted in reduced anxiety two weeks post-exposure. Consistent with our hypothesis, individuals with better extinction learning (less negative stimulus ratings), greater activation in vmPFC, and less activation in amygdala, insula, and periaqueductal gray reported greater anxiety reduction two weeks postexposure. To our knowledge, this is the first time that the theoretical link between extinction learning and exposure outcome has been demonstrated. Future work should examine whether extinction learning can be used as a prognostic test to determine who is most likely to benefit from exposure therapy. © 2016 Wiley Periodicals, Inc.

  11. Geomagnetism, volcanoes, global climate change, and predictability. A progress report

    Directory of Open Access Journals (Sweden)

    G. P. Gregori

    1994-06-01

    Full Text Available A model is investigated, by which the encounters of the solar system with dense interstellar clouds ought to trigger either geomagnetic field reversals or excursions, that produce extra electric currents within the Earth dynamo, that cause extra Joule's heating, that supplies volcanoes and endogenous processes. Volcanoes increase the Earth degassing into the atmosphere, hence the concentration of the minor atmospheric constituents, including the greenhouse gases, hence they affect climate temperature, glacier melting, sea level and global change. This investigation implies both theoretical studies and observational data handling on different time scales, including present day phenomena, instrumental data series, historical records, proxy data, and geological and palaeontological evidences. The state of the art is briefly outlined, mentioning some already completed achievements, investigations in progress, and future perspectives.

  12. Phenotypic plasticity as an adaptive response to predictable and unpredictable environmental changes

    DEFF Research Database (Denmark)

    Manenti, Tommaso

    such as anti-predator behaviours or the activation of mechanisms to prevent thermal stress injuries suggest that plasticity is an adaptive response, favoured by natural selection. At the same time, organisms do show limited plastic responses, indicating that this ability is not for free. Costs and benefits...... to be an adaptive response. Despite almost a century of studies on phenotypic plasticity, the relation between plasticity and evolution is still not clear and theoretical prediction are often not met by empirical data. In my PhD I have investigated if and when plasticity can evolve. I selected Drosophila simulans......Phenotypic plasticity is the ability of a genotype to modify its phenotype in response to environmental changes as a consequence of an interaction between genes and environment (Bradshaw, 1965). Plasticity contributes to the vast phenotypic variation observed in natural populations. Many examples...

  13. 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.

  14. 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.

  15. Evidence of moderation effects in predicting active transport to school.

    Science.gov (United States)

    Garnham-Lee, Katy P; Falconer, Catherine L; Sherar, Lauren B; Taylor, Ian M

    2017-03-01

    Distance from home to school is an important influence on the decision to use active transport (AT); however, ecological perspectives would suggest this relationship may be moderated by individual, interpersonal and environmental factors. This study investigates whether (i) gender, (ii) biological maturation, (iii) perceived family support for physical activity (PA) and (iv) multiple deprivation moderate the relationship between distance to school and AT. A total of 611 children (11-12 years old, 334 females) were recruited from schools in Leicestershire, UK. Gender, family support for PA, and AT were self-reported. Home and school postcodes were used to determine multiple deprivation and distance to school (km). Predicted age at peak height velocity was used to indicate biological maturation. Logistic regressions revealed the main effects explained 40.2% of the variance in AT; however; distance to school was the only significant predictor. Further analyses revealed that distance to school had a greater negative impact on the use of AT in late-maturing (OR: 3.60, CI: 1.45-8.96), less deprived (OR: 3.54, CI: 1.17-10.72) and children with low family support of PA (OR: 0.26, CI: 0.11-0.61). This study provides evidence that, although distance to school might be the strongest predictor of AT, this relationship is complex. © The Author 2016. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  16. 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

  17. 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.

  18. 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.

  19. Prediction of a global climate change on Jupiter.

    Science.gov (United States)

    Marcus, Philip S

    2004-04-22

    Jupiter's atmosphere, as observed in the 1979 Voyager space craft images, is characterized by 12 zonal jet streams and about 80 vortices, the largest of which are the Great Red Spot and three White Ovals that had formed in the 1930s. The Great Red Spot has been observed continuously since 1665 and, given the dynamical similarities between the Great Red Spot and the White Ovals, the disappearance of two White Ovals in 1997-2000 was unexpected. Their longevity and sudden demise has been explained however, by the trapping of anticyclonic vortices in the troughs of Rossby waves, forcing them to merge. Here I propose that the disappearance of the White Ovals was not an isolated event, but part of a recurring climate cycle which will cause most of Jupiter's vortices to disappear within the next decade. In my numerical simulations, the loss of the vortices results in a global temperature change of about 10 K, which destabilizes the atmosphere and thereby leads to the formation of new vortices. After formation, the large vortices are eroded by turbulence over a time of approximately 60 years--consistent with observations of the White Ovals-until they disappear and the cycle begins again.

  20. An Innovative Network to Improve Sea Ice Prediction in a Changing Arctic

    Science.gov (United States)

    2014-09-30

    B) sea ice volume. The EXP ensemble is initialized with 1/5 of CNTL snow depths, thus resulting in a reduced snow cover and lower summer albedo ...thicker is thought to be predictable for a longer time period than thinner sea ice. In our experiments, we investigated how changes in snow cover affect...predictability in the CESM1. Snow cover may be particularly relevant to summer sea ice predictability, as it affects surface radiative fluxes and

  1. Recognition and prediction of individual and combined muscular activation modes via surface EMG analysis

    Directory of Open Access Journals (Sweden)

    Daniel Graupe

    2010-09-01

    Full Text Available The paper discusses how recognition of individual and combined muscular activation modes (functions and the prediction of intended such modes can be accomplished by identifying parameters of noninvasive surface EMG signals. It outlines the mathematical analysis of surface EMG signal to facilitate such recognition and related prediction, including recognition of intention (in terms of attempts to activate motor functions from the EMG, without accessing the CNS itself, in cases where a patient, say, a high-level amputee does not have the final-activation muscles and joints. The EMG activity thus allows to interpret and recognize CNS commands from minute variations in the parameters of surface EMG signals that record changes in the firing of motor neurons triggering contractions in related muscle fibers. We note that although in popular media this is sometimes referred to as detection of “thoughts”, no thoughts are detected, but only motor-outcomes of thoughts as found in the EMG signal. Examples of concrete cases where such recognition or prediction were accomplished in the author’s lab and in devices that came out of that lab, are given as are references to these in the literature over the last 35 years.

  2. Biocatalytic Synthesis of Acrylates in Supercritical Fluids: Tuning Enzyme Activity by Changing Pressure

    Science.gov (United States)

    Kamat, Sanjay V.; Iwaskewycz, Brian; Beckman, Eric J.; Russell, Alan J.

    1993-04-01

    Supercritical fluids are a unique class of non-aqueous media in which biocatalytic reactions can occur. The physical properties of supercritical fluids, which include gas-like diffusivities and liquid-like densities, can be predictably controlled with changing pressure. This paper describes how adjustment of pressure, with the subsequent predictable changes of the dielectric constant and Hildebrand solubility parameter for fluoroform, ethane, sulfur hexafluoride, and propane, can be used to manipulate the activity of lipase in the transesterification of methylmethacrylate with 2-ethyl-1-hexanol. Of particular interest is that the dielectric constant of supercritical fluoroform can be tuned from approximately 1 to 8, merely by increasing pressure from 850 to 4000 psi (from 5.9 to 28 MPa). The possibility now exists to predictably alter both the selectivity and the activity of a biocatalyst merely by changing pressure.

  3. 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...

  4. 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 ...

  5. 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

  6. How much will the sea level rise? Outcome selection and subjective probability in climate change predictions.

    Science.gov (United States)

    Juanchich, Marie; Sirota, Miroslav

    2017-12-01

    We tested whether people focus on extreme outcomes to predict climate change and assessed the gap between the frequency of the predicted outcome and its perceived probability while controlling for climate change beliefs. We also tested 2 cost-effective interventions to reduce the preference for extreme outcomes and the frequency-probability gap by manipulating the probabilistic format: numerical or dual-verbal-numerical. In 4 experiments, participants read a scenario featuring a distribution of sea level rises, selected a sea rise to complete a prediction (e.g., "It is 'unlikely' that the sea level will rise . . . inches") and judged the likelihood of this sea rise occurring. Results showed that people have a preference for predicting extreme climate change outcomes in verbal predictions (59% in Experiments 1-4) and that this preference was not predicted by climate change beliefs. Results also showed an important gap between the predicted outcome frequency and participants' perception of the probability that it would occur. The dual-format reduced the preference for extreme outcomes for low and medium probability predictions but not for high ones, and none of the formats consistently reduced the frequency-probability gap. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  7. 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...

  8. Modelling land Use Change : Improving the prediction of future land use patterns

    NARCIS (Netherlands)

    de Nijs, A.C.M.

    2009-01-01

    Modelling land Use Change: Improving the prediction of future land use patterns. Man has been altering his living environment since prehistoric times and will continue to do so. It is predicted that by 2030 about 90,000 ha will be needed for residential developments in the Netherlands and 55,000 ha

  9. Climate-Induced Change in South Central Siberia: Predictions Versus Current Observations

    Science.gov (United States)

    Soja, A. J.; Tchebakova, N. M.; Parfenova, E. I.; Shishikin, A.; Kanzai, V.; Westberg, D. J.; Sukhinin, A. I.; Ivanova, G. A.; Stackhouse, P. W.

    2007-12-01

    Atmosphere Ocean General Circulations Models (AOGCM) are in agreement that Siberia is expected to experience warming in excess of 40% above global mean temperature increases by 2100. Moreover, it is predicted temperature increases will be evident in both the summer and winter. In association with changes in climate, the extent of the fire season, the amount of area burned and fire severity are predicted to increase. Fire regime increases are predicted to be the catalyst for ecosystem change, which will force ecosystems to move more rapidly towards equilibrium with the climate. Bioclimatic model results predict expansive changes in ecosystems, from a landscape dominated by taiga to a landscape dominated by steppe and forest-steppe. The focus of this investigation is on south, central Siberia in the Sayan Mountains and the Tyvan Republic, where one would expect to find the initial signs of climate change. The Sayan mountain range offers relatively abrupt change in ecosystems that are often defined by altitude, temperature and precipitation. Tyva is located at a vulnerable southern border, south of the Sayan, and contains 9 Biospheric Reserves, each representing distinct ecosystems. Additionally, Tyva is the home of several relic Pinus sylvestris forests. In these regions, January temperature increases have exceeded those predicted by the Hadley Centre scenario for 2090, and July temperatures are well below predictions. Predicted increases in rainfall are not apparent, and generally, precipitation change has been negative. The growing season length has already increased by about 6 to 12 days. Consequently, several of the relic pine forests have burned (some repeatedly), and natural regeneration is not visible at several sites, even one that had been re-planted on several occasions. In the last decades, these regions have experienced changes in climate and, potentially, initial signs of ecosystem change. In this report, we present a concentrated view of one region that

  10. Global cortical activity predicts shape of hand during grasping

    Science.gov (United States)

    Agashe, Harshavardhan A.; Paek, Andrew Y.; Zhang, Yuhang; Contreras-Vidal, José L.

    2015-01-01

    Recent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via electroencephalography (EEG). Further, it is unclear as to whether joint angle velocities or movement synergies are the optimal kinematics spaces to decode. In this offline decoding study, we infer from human EEG, hand joint angular velocities as well as synergistic trajectories as subjects perform natural reach-to-grasp movements. Decoding accuracy, measured as the correlation coefficient (r) between the predicted and actual movement kinematics, was r = 0.49 ± 0.02 across 15 hand joints. Across the first three kinematic synergies, decoding accuracies were r = 0.59 ± 0.04, 0.47 ± 0.06, and 0.32 ± 0.05. The spatial-temporal pattern of EEG channel recruitment showed early involvement of contralateral frontal-central scalp areas followed by later activation of central electrodes over primary sensorimotor cortical areas. Information content in EEG about the grasp type peaked at 250 ms after movement onset. The high decoding accuracies in this study are significant not only as evidence for time-domain modulation in macro-scale brain activity, but for the field of brain-machine interfaces as well. Our decoding strategy, which harnesses the neural “symphony” as opposed to local members of the neural ensemble (as in intracranial approaches), may provide a means of extracting information about motor intent for grasping without the need for penetrating electrodes and suggests that it may be soon possible to develop non-invasive neural interfaces for the control of prosthetic limbs. PMID:25914616

  11. Determining the Importance of Calibration for Predicting Relative Changes in Streamflow from Land Use/Cover Changes

    Science.gov (United States)

    Niraula, R.; Meixner, T.; Norman, L. M.

    2012-12-01

    Human-induced land use/cover (LULC) change and climate change can have significant impacts on water quantity and quality. Prediction of impacts due to anticipated LULC and climate change on water in arid and semi-arid regions are crucial to understand due to scarce water resources. Watershed models are often used to analyze the effects of land use/cover and climate change on water resources, commonly in terms of relative changes; and provide important information for decision making. These models are often calibrated and validated with available data which can be time consuming and sometimes even very difficult. The objective of this study is to quantify the variation of estimated relative changes in streamflow associated with LULC with uncalibrated, single outlet calibrated and spatially-calibrated watershed model. Soil and Water Assessment Tool (SWAT) was applied in an uncalibrated, single outlet calibrated, and spatially-calibrated (at 7 USGS stream-gaging stations) mode to compare and quantify the relative change in terms of magnitude and direction of flow in a 9000 km2 semi-arid Santa Cruz watershed on the border of southern Arizona, United States, and northern Sonora, Mexico. While the average annual precipitation over the whole watershed is approximately 430 mm, the average annual discharge ranges between 0.17 and 2.64 m3/s. The effect due to three LULC scenarios, where urbanization is expected to increase from ~12% in 1999 to range of 35-40% in 2050 was analyzed. For the 7 USGS stations, all 3 calibration scenarios demonstrated an increase in predicted flow but magnitude of predicted change varied. The uncalibrated model predicted the increase from 4% to 15%, the single-outlet calibrated model predicted between 5% and 105%, and the spatially-calibrated model predicted the increase to be between 4% and 170%. While the results were similar between uncalibrated and single outlet calibration at some stations, the results were more similar to single outlet and

  12. 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.

  13. 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.

  14. Changes in Albuminuria Predict Mortality and Morbidity in Patients with Vascular Disease

    OpenAIRE

    Schmieder, Roland E.; Mann, Johannes F. E.; Schumacher, Helmut; Gao, Peggy; Mancia, Giuseppe; Weber, Michael A.; McQueen, Matthew; Koon, Teo; Yusuf, Salim

    2011-01-01

    The degree of albuminuria predicts cardiovascular and renal outcomes, but it is not known whether changes in albuminuria also predict similar outcomes. In two multicenter, multinational, prospective observational studies, a central laboratory measured albuminuria in 23,480 patients with vascular disease or high-risk diabetes. We quantified the association between a greater than or equal to twofold change in albuminuria in spot urine from baseline to 2 years and the incidence of cardiovascular...

  15. 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.

  16. 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…

  17. 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.

  18. PREDICTING CHANGE IN MANAGEMENT ACCOUNTING SYSTEMS: THE EFFECTS OF COMPETITIVE STRATEGY

    OpenAIRE

    Nelson Waweru

    2008-01-01

    This study reports on a survey that investigated changes in management accounting and control systems in 31 Canadian manufacturing companies. Six variables that may influence changes in management accounting and control systems are identified from contingency theory literature. The findings indicate considerable changes in the organizations’ management accounting systems during the three year period. Changes in management accounting were best predicted by organizational capacity to learn. S...

  19. 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.

  20. 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.

  1. Change You Can Believe In: Changes in Goal Setting During Emerging and Young Adulthood Predict Later Adult Well-Being.

    Science.gov (United States)

    Hill, Patrick L; Jackson, Joshua J; Roberts, Brent W; Lapsley, Daniel K; Brandenberger, Jay W

    2011-03-01

    A widely held assumption is that changes in one's goals and motives for life during emerging and young adulthood have lasting influences on well-being into adulthood. However, this claim has yet to receive rigorous empirical testing. The current study examined the effects of prosocial and occupational goal change during college on adult well-being in a 17-year study of goal setting ( N = 416). Using a latent growth model across three time points, both level and growth in goal setting predicted later well-being. Moreover, goal changes both during college and in young adulthood uniquely predicted adult well-being, controlling for goal levels entering college. These findings suggest that what matters for attaining adult well-being is both how you enter adulthood and how you change in response to it.

  2. Climate change and plant distribution: local models predict high-elevation persistence

    DEFF Research Database (Denmark)

    Randin, Christophe F.; Engler, Robin; Normand, Signe

    2009-01-01

    Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range, and spatial resolution of data used in making these models, different rates...... of habitat loss have been predicted, with associated risk of species extinction. Few coordinated across-scale comparisons have been made using data of different resolutions and geographic extents. Here, we assess whether climate change-induced habitat losses predicted at the European scale (10 × 10' grid...... in the area. Proportion of habitat loss depends on climate change scenario and study area. We find good agreement between the mismatch in predictions between scales and the fine-grain elevation range within 10 × 10' cells. The greatest prediction discrepancy for alpine species occurs in the area...

  3. Body size and activity times mediate mammalian responses to climate change.

    Science.gov (United States)

    McCain, Christy M; King, Sarah R B

    2014-06-01

    Model predictions of extinction risks from anthropogenic climate change are dire, but still overly simplistic. To reliably predict at-risk species we need to know which species are currently responding, which are not, and what traits are mediating the responses. For mammals, we have yet to identify overarching physiological, behavioral, or biogeographic traits determining species' responses to climate change, but they must exist. To date, 73 mammal species in North America and eight additional species worldwide have been assessed for responses to climate change, including local extirpations, range contractions and shifts, decreased abundance, phenological shifts, morphological or genetic changes. Only 52% of those species have responded as expected, 7% responded opposite to expectations, and the remaining 41% have not responded. Which mammals are and are not responding to climate change is mediated predominantly by body size and activity times (phylogenetic multivariate logistic regressions, P mammals respond more, for example, an elk is 27 times more likely to respond to climate change than a shrew. Obligate diurnal and nocturnal mammals are more than twice as likely to respond as mammals with flexible activity times (P mammal species can behaviorally escape climate change whereas others cannot, analogous to paleontology's climate sheltering hypothesis. Including body size and activity flexibility traits into future extinction risk forecasts should substantially improve their predictive utility for conservation and management. © 2014 John Wiley & Sons Ltd.

  4. 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.

  5. Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity

    Directory of Open Access Journals (Sweden)

    Ye Han

    2017-01-01

    Full Text Available Small interfering RNAs (siRNAs induce posttranscriptional gene silencing in various organisms. siRNAs targeted to different positions of the same gene show different effectiveness; hence, predicting siRNA activity is a crucial step. In this paper, we developed and evaluated a powerful tool named “siRNApred” with a new mixed feature set to predict siRNA activity. To improve the prediction accuracy, we proposed 2-3NTs as our new features. A Random Forest siRNA activity prediction model was constructed using the feature set selected by our proposed Binary Search Feature Selection (BSFS algorithm. Experimental data demonstrated that the binding site of the Argonaute protein correlates with siRNA activity. “siRNApred” is effective for selecting active siRNAs, and the prediction results demonstrate that our method can outperform other current siRNA activity prediction methods in terms of prediction accuracy.

  6. 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…

  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. Predicting global change effects on forest biomass and composition in south-central Siberia

    Science.gov (United States)

    Eric Gustafson; Anatoly D. Shvidenko; Brian R. Sturtevant; Robert M. Scheller

    2010-01-01

    Multiple global changes such as timber harvesting in areas not previously disturbed by cutting and climate change will undoubtedly affect the composition and spatial distribution of boreal forests, which will, in turn, affect the ability of these forests to retain carbon and maintain biodiversity. To predict future states of the boreal forest reliably, it is necessary...

  10. Caregivers' Readiness for Change: Predictive Validity in a Child Welfare Sample

    Science.gov (United States)

    Littell, J.H.; Girvin, H.

    2005-01-01

    Objective:: To assess the predictive validity of continuous measures of problem recognition (PR), intentions to change (ITC), and overall readiness for change (RFC) among primary caregivers who received in-home services following substantiated reports of child abuse or neglect. Method:: A modified version of the University of Rhode Island Change…

  11. A new statistical tool to predict phenology under climate change scenarios

    NARCIS (Netherlands)

    Gienapp, P.; Hemerik, L.; Visser, M.E.

    2005-01-01

    Climate change will likely affect the phenology of trophic levels differently and thereby disrupt the phenological synchrony between predators and prey. To predict this disruption of the synchrony under different climate change scenarios, good descriptive models for the phenology of the different

  12. 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...

  13. Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction.

    Science.gov (United States)

    Frimayanti, Neni; Yam, Mun Li; Lee, Hong Boon; Othman, Rozana; Zain, Sharifuddin M; Rahman, Noorsaadah Abd

    2011-01-01

    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, r(2) value, r(2) (CV) value and r(2) 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 IC(50) values ranging from 0.39 μM to 7.04 μM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r(2) 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.

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

    Science.gov (United States)

    Frimayanti, Neni; Yam, Mun Li; Lee, Hong Boon; Othman, Rozana; Zain, Sharifuddin M.; Rahman, Noorsaadah Abd.

    2011-01-01

    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. PMID:22272096

  15. Predicting outcome after stroke: the role of basic activities of daily living predicting outcome after stroke.

    Science.gov (United States)

    Gialanella, B; Santoro, R; Ferlucci, C

    2013-10-01

    Very few studies have investigated the influence of single activities of daily living (ADL) at admission as possible predictors of functional outcome after rehabilitation. The aim of the current study was to investigate admission functional status and performance of basic ADLs as assessed by Functional Independence Measure (FIM) scale as possible predictors of motor and functional outcome after stroke during inpatient rehabilitation. This is a prospective and observational study. Inpatients of our Department of Physical Medicine and Rehabilitation. Two hundred sixty consecutive patients with primary diagnosis of stroke were enrolled and 241 patients were used in the final analyses. Two backward stepwise regression analyses were applied to predict outcome. The first backward stepwise regression had age, gender, stroke type, stroke-lesion size, aphasia, neglect, onset to admission interval, Cumulative Illness Rating Scale, National Institute of Health Stroke Scale (NIHSS), Fugl-Meyer Scale, Trunk Control Test, and FIM (total, motor and cognitive scores) as independent variables. The second analyses included the above variables plus FIM items as an independent variable. The dependent variables were the discharge scores and effectiveness in total and motor-FIM, and discharge destination. The first multivariate analysis showed that admission Fugl-Meyer, neglect, total, motor and cognitive FIM scores were the most important predictors of FIM outcomes, while admission NIHSS score was the only predictor of discharge destination. Conversely, when admission single FIM items were included in the statistical model, admission Fugl-Meyer, neglect, grooming, dressing upper body, and social interaction scores were the most important predictors of FIM outcomes, while admission memory and bowel control scores were the only predictors of discharge destination. Our study indicates that performances of basic ADLs are important stroke outcome predictors and among which social

  16. "Monkey see, monkey do": Peers' behaviors predict preschoolers' physical activity and dietary intake in childcare centers.

    Science.gov (United States)

    Ward, Stéphanie; Bélanger, Mathieu; Donovan, Denise; Boudreau, Jonathan; Vatanparast, Hassan; Muhajarine, Nazeem; Leis, Anne; Humbert, M Louise; Carrier, Natalie

    2017-04-01

    Preschoolers observe and imitate the behaviors of those who are similar to them. Therefore, peers may be role models for preschoolers' dietary intake and physical activity in childcare centers. This study examined whether peers' behaviors predict change in preschoolers' dietary intake and physical activity in childcare centers over 9months. A total of 238 preschoolers (3 to 5years old) from 23 childcare centers in two Canadian provinces provided data at the beginning (October 2013 and 2014) and the end (June 2014 and 2015) of a 9-month period for this longitudinal study. Dietary intake was collected at lunch using weighed plate waste and digital photography on two consecutive weekdays. Physical activity was assessed using accelerometers over five days. Multilevel linear regressions were used to estimate the influence of peers' behaviors on preschoolers' change in dietary intake and physical activity over 9months. Results showed that preschoolers whose dietary intake or physical activity level deviated the most from those of their peers at the beginning of the year demonstrated greater change in their intakes and activity levels over 9months, which enabled them to become more similar to their peers (all β 95% CI ranged from -0.835 to -0.074). This study suggests that preschoolers' dietary intake and physical activity may be influenced by the behaviors of their peers in childcare centers. Since peers could play an important role in promoting healthy eating behaviors and physical activity in childcare centers, future studies should test interventions based on positive role modeling by children. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Emotionally biased cognitive processes: the weakest link predicts prospective changes in depressive symptom severity.

    Science.gov (United States)

    Everaert, Jonas; Duyck, Wouter; Koster, Ernst H W

    2015-01-01

    Emotional biases in attention, interpretation, and memory are predictive of future depressive symptoms. It remains unknown, however, how these biased cognitive processes interact to predict depressive symptom levels in the long-term. In the present study, we tested the predictive value of two integrative approaches to model relations between multiple biased cognitive processes, namely the additive (i.e., cognitive processes have a cumulative effect) vs. the weakest link (i.e., the dominant pathogenic process is important) model. We also tested whether these integrative models interacted with perceived stress to predict prospective changes in depressive symptom severity. At Time 1, participants completed measures of depressive symptom severity and emotional biases in attention, interpretation, and memory. At Time 2, one year later, participants were reassessed to determine depressive symptom levels and perceived stress. Results revealed that the weakest link model had incremental validity over the additive model in predicting prospective changes in depressive symptoms, though both models explained a significant proportion of variance in the change in depressive symptoms from Time 1 to Time 2. None of the integrative models interacted with perceived stress to predict changes in depressive symptomatology. These findings suggest that the best cognitive marker of the evolution in depressive symptoms is the cognitive process that is dominantly biased toward negative material, which operates independent from experienced stress. This highlights the importance of considering idiographic cognitive profiles with multiple cognitive processes for understanding and modifying effects of cognitive biases in depression.

  18. A more accurate method of predicting soft tissue changes after mandibular setback surgery.

    Science.gov (United States)

    Suh, Hee-Yeon; Lee, Shin-Jae; Lee, Yun-Sik; Donatelli, Richard E; Wheeler, Timothy T; Kim, Soo-Hwan; Eo, Soo-Heang; Seo, Byoung-Moo

    2012-10-01

    To propose a more accurate method to predict the soft tissue changes after orthognathic surgery. The subjects included 69 patients who had undergone surgical correction of Class III mandibular prognathism by mandibular setback. Two multivariate methods of forming prediction equations were examined using 134 predictor and 36 soft tissue response variables: the ordinary least-squares (OLS) and the partial least-squares (PLS) methods. After fitting the equation, the bias and a mean absolute prediction error were calculated. To evaluate the predictive performance of the prediction equations, a 10-fold cross-validation method was used. The multivariate PLS method showed significantly better predictive performance than the conventional OLS method. The bias pattern was more favorable and the absolute prediction accuracy was significantly better with the PLS method than with the OLS method. The multivariate PLS method was more satisfactory than the conventional OLS method in accurately predicting the soft tissue profile change after Class III mandibular setback surgery. Copyright © 2012 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. 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

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

    Directory of Open Access Journals (Sweden)

    L. Andrew Coward

    2016-01-01

    Full Text Available 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.

  7. 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.

  8. 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...

  9. Which Moral Foundations Predict Willingness to Make Lifestyle Changes to Avert Climate Change in the USA?

    Science.gov (United States)

    Dickinson, Janis L; McLeod, Poppy; Bloomfield, Robert; Allred, Shorna

    2016-01-01

    Jonathan Haidt's Moral Foundations Theory identifies five moral axes that can influence human motivation to take action on vital problems like climate change. The theory focuses on five moral foundations, including compassion, fairness, purity, authority, and ingroup loyalty; these have been found to differ between liberals and conservatives as well as Democrats and Republicans. Here we show, based on the Cornell National Social Survey (USA), that valuations of compassion and fairness were strong, positive predictors of willingness to act on climate change, whereas purity had a non-significant tendency in the positive direction (p = 0.07). Ingroup loyalty and authority were not supported as important predictor variables using model selection ([Formula: see text]). Compassion and fairness were more highly valued by liberals, whereas purity, authority, and in-group loyalty were more highly valued by conservatives. As in previous studies, participants who were younger, more liberal, and reported greater belief in climate change, also showed increased willingness to act on climate change. Our research supports the potential importance of moral foundations as drivers of intentions with respect to climate change action, and suggests that compassion, fairness, and to a lesser extent, purity, are potential moral pathways for personal action on climate change in the USA.

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

    Science.gov (United States)

    Van Dijk, Martin L; Savelberg, Hans H C M; Verboon, Peter; Kirschner, Paul A; De Groot, Renate H M

    2016-04-07

    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. 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. Physical activity levels decreased 15.3% over a 1-year period (p physical activity did not appear to predict any change in depressive symptoms and self-esteem. 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 activity is associated with a change in mental health should control for baseline levels of mental health and academic year differences.

  11. Calibration of Numerical Model for Shoreline Change Prediction Using Satellite Imagery Data

    Directory of Open Access Journals (Sweden)

    Sigit Sutikno

    2015-12-01

    Full Text Available This paper presents a method for calibration of numerical model for shoreline change prediction using satellite imagery data in muddy beach. Tanjung Motong beach, a muddy beach that is suffered high abrasion in Rangsang Island, Riau province, Indonesia was picked as study area. The primary numerical modeling tool used in this research was GENESIS (GENEralized Model for Simulating Shoreline change, which has been successfully applied in many case studies of shoreline change phenomena on a sandy beach.The model was calibrated using two extracted coastlines satellite imagery data, such as Landsat-5 TM and Landsat-8 OLI/TIRS. The extracted coastline data were analyzed by using DSAS (Digital Shoreline Analysis System tool to get the rate of shoreline change from 1990 to 2014. The main purpose of the calibration process was to find out the appropriate value for K 1 and K coefficients so that the predicted shoreline change had an acceptable correlation with the output of the satellite data processing. The result of this research showed that the shoreline change prediction had a good correlation with the historical evidence data in Tanjung Motong coast. It means that the GENESIS tool is not only applicable for shoreline prediction in sandy beach but also in muddy beach.

  12. Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits.

    Science.gov (United States)

    Moor, Helen; Hylander, Kristoffer; Norberg, Jon

    2015-01-01

    Wetlands provide multiple ecosystem services, the sustainable use of which requires knowledge of the underlying ecological mechanisms. Functional traits, particularly the community-weighted mean trait (CWMT), provide a strong link between species communities and ecosystem functioning. We here combine species distribution modeling and plant functional traits to estimate the direction of change of ecosystem processes under climate change. We model changes in CWMT values for traits relevant to three key services, focusing on the regional species pool in the Norrström area (central Sweden) and three main wetland types. Our method predicts proportional shifts toward faster growing, more productive and taller species, which tend to increase CWMT values of specific leaf area and canopy height, whereas changes in root depth vary. The predicted changes in CWMT values suggest a potential increase in flood attenuation services, a potential increase in short (but not long)-term nutrient retention, and ambiguous outcomes for carbon sequestration.

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

    Science.gov (United States)

    Ashraf, M Irfan; Meng, Fan-Rui; Bourque, Charles P-A; MacLean, David A

    2015-01-01

    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 technology

  14. 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

  15. 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.

  16. Activity changes of the cat paraventricular hypothalamus during stressor exposure

    DEFF Research Database (Denmark)

    Kristensen, Morten Pilgaard; Rector, David M; Poe, Gina R

    2004-01-01

    Dorso-medial paraventricular hypothalamus (PVH) activity was assessed by light scattering procedures in freely behaving cats during auditory stressor exposure. Acoustic noise (> 95dB) raised plasma ACTH concentrations, somatic muscle tonus, respiratory frequency and cardiac rates; PVH activity...... and nadir. Isolated pixels appeared opposite in activity pattern to overall changes. We suggest that transient activity increases represent initial PVH neural stress responses, and that subsequent profound declines result from neural inhibitory feedback....

  17. Assessing conservation relevance of organism-environment relations using predicted changes in response variables

    Science.gov (United States)

    Gutzwiller, Kevin J.; Barrow, Wylie C.; White, Joseph D.; Johnson-Randall, Lori; Cade, Brian S.; Zygo, Lisa M.

    2010-01-01

    1. Organism–environment models are used widely in conservation. The degree to which they are useful for informing conservation decisions – the conservation relevance of these relations – is important because lack of relevance may lead to misapplication of scarce conservation resources or failure to resolve important conservation dilemmas. Even when models perform well based on model fit and predictive ability, conservation relevance of associations may not be clear without also knowing the magnitude and variability of predicted changes in response variables. 2. We introduce a method for evaluating the conservation relevance of organism–environment relations that employs confidence intervals for predicted changes in response variables. The confidence intervals are compared to a preselected magnitude of change that marks a threshold (trigger) for conservation action. To demonstrate the approach, we used a case study from the Chihuahuan Desert involving relations between avian richness and broad-scale patterns of shrubland. We considered relations for three winters and two spatial extents (1- and 2-km-radius areas) and compared predicted changes in richness to three thresholds (10%, 20% and 30% change). For each threshold, we examined 48 relations. 3. The method identified seven, four and zero conservation-relevant changes in mean richness for the 10%, 20% and 30% thresholds respectively. These changes were associated with major (20%) changes in shrubland cover, mean patch size, the coefficient of variation for patch size, or edge density but not with major changes in shrubland patch density. The relative rarity of conservation-relevant changes indicated that, overall, the relations had little practical value for informing conservation decisions about avian richness. 4. The approach we illustrate is appropriate for various response and predictor variables measured at any temporal or spatial scale. The method is broadly applicable across ecological

  18. The Changing Cold Regions Network: Improving the Understanding and Prediction of Changing Land, Water, and Climate in the Mackenzie and Saskatchewan River Basins, Canada

    Science.gov (United States)

    DeBeer, C. M.; Wheater, H. S.; Chun, K. P.; Shook, K.; Whitfield, P. H.

    2014-12-01

    Within the cold interior of western and northern Canada, rapid and widespread environmental changes are taking place, which are of serious concern for society and have a range of implications from local to regional and global scales. From a scientific standpoint there is an urgent need to understand the changes and develop improved diagnostic and predictive modelling tools to deal with the uncertainty faced in the future. The Changing Cold Regions Network (CCRN) is a research consortium of over 50 Canadian university and government scientists and international researchers aimed at addressing these issues within the geographic domain of the Mackenzie and Saskatchewan River Basins. CCRN's primary focus is to integrate existing and new experimental data with modelling and remote sensing products to understand, diagnose and predict changing land, water and climate, and their interactions and feedbacks. To support these activities, the network utilizes a suite of 14 world-class water, ecosystem, cryosphere and climate (WECC) observatories across this region that provide exceptional opportunities to observe change, investigate processes and their dynamics, and develop and test environmental models. This talk will briefly describe the CCRN thematic components and WECC observatories, and will then describe some of the observed environmental changes and their linkages across the northern and mountainous parts of the network study domain. In particular, this will include changes in permafrost, terrestrial vegetation, snowcover, glaciers, and river discharge in relation to observed climatic changes across the region. The observations draw on a wide range of literature sources and statistical analyses of federal and provincial regional monitoring network data, while more detailed observations at some of the WECC observatories help to show how these regional changes are manifested at local scales and vice versa. A coordinated special observation and analysis period across all

  19. Changes in salivary estradiol predict changes in women's preferences for vocal masculinity.

    Science.gov (United States)

    Pisanski, Katarzyna; Hahn, Amanda C; Fisher, Claire I; DeBruine, Lisa M; Feinberg, David R; Jones, Benedict C

    2014-08-01

    Although many studies have reported that women's preferences for masculine physical characteristics in men change systematically during the menstrual cycle, the hormonal mechanisms underpinning these changes are currently poorly understood. Previous studies investigating the relationships between measured hormone levels and women's masculinity preferences tested only judgments of men's facial attractiveness. Results of these studies suggested that preferences for masculine characteristics in men's faces were related to either women's estradiol or testosterone levels. To investigate the hormonal correlates of within-woman variation in masculinity preferences further, here we measured 62 women's salivary estradiol, progesterone, and testosterone levels and their preferences for masculine characteristics in men's voices in five weekly test sessions. Multilevel modeling of these data showed that changes in salivary estradiol were the best predictor of changes in women's preferences for vocal masculinity. These results complement other recent research implicating estradiol in women's mate preferences, attention to courtship signals, sexual motivation, and sexual strategies, and are the first to link women's voice preferences directly to measured hormone levels. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. 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.

  1. 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

  2. A trait-based framework for predicting when and where microbial adaptation to climate change will affect ecosystem functioning

    Science.gov (United States)

    Wallenstein, Matthew D.; Hall, Edward K.

    2012-01-01

    As the earth system changes in response to human activities, a critical objective is to predict how biogeochemical process rates (e.g. nitrification, decomposition) and ecosystem function (e.g. net ecosystem productivity) will change under future conditions. A particular challenge is that the microbial communities that drive many of these processes are capable of adapting to environmental change in ways that alter ecosystem functioning. Despite evidence that microbes can adapt to temperature, precipitation regimes, and redox fluctuations, microbial communities are typically not optimally adapted to their local environment. For example, temperature optima for growth and enzyme activity are often greater than in situ temperatures in their environment. Here we discuss fundamental constraints on microbial adaptation and suggest specific environments where microbial adaptation to climate change (or lack thereof) is most likely to alter ecosystem functioning. Our framework is based on two principal assumptions. First, there are fundamental ecological trade-offs in microbial community traits that occur across environmental gradients (in time and space). These trade-offs result in shifting of microbial function (e.g. ability to take up resources at low temperature) in response to adaptation of another trait (e.g. limiting maintenance respiration at high temperature). Second, the mechanism and level of microbial community adaptation to changing environmental parameters is a function of the potential rate of change in community composition relative to the rate of environmental change. Together, this framework provides a basis for developing testable predictions about how the rate and degree of microbial adaptation to climate change will alter biogeochemical processes in aquatic and terrestrial ecosystems across the planet.

  3. Predicting habitat suitability and geographic distribution of anchovy (Engraulis ringens) due to climate change in the coastal areas off Chile

    Science.gov (United States)

    Silva, Claudio; Andrade, Isabel; Yáñez, Eleuterio; Hormazabal, Samuel; Barbieri, María Ángela; Aranis, Antonio; Böhm, Gabriela

    2016-08-01

    The effects of climate change on ocean conditions will have impacts on fish stocks, primarily through physiological and behavioural effects, such as changes in growth, reproduction, mortality and distribution. Habitat and distribution predictions for marine fishery species under climate change scenarios are important for understanding the overall impacts of such global changes on the human society and on the ecosystem. In this study, we examine the impacts of climate change on anchovy fisheries off Chile using predicted changes in global models according to the National Centre for Atmospheric Research (NCAR) Community Climate System Model 3.0 (CCSM3) and IPCC high future CO2 emission scenario A2, habitat suitability index (HSI) models and satellite-based sea surface temperature (SST) and chlorophyll-a (Chl-a) estimates from high-resolution regional models for the simulation period 2015-2065. Predictions of SST from global climate models were regionalised using the Delta statistical downscaling technique. Predictions of chlorophyll-a were developed using historical Chl-a and SST (2003-2013) satellite data and applying a harmonic model. The results show an increase in SST of up to 2.5 °C by 2055 in the north and central-south area for an A2 scenario. The habitat suitability index model was developed using historical (2001-2011) monthly fisheries and environmental data. The catch per unit effort (CPUE) was used as an abundance index in developing the HSI models and was calculated as the total catch (ton) by hold capacity (m3) in a 10‧ × 10‧ fishing grid square of anchovy, integrated over one month of fishing activity. The environmental data included the distance to coast (DC), thermal (SST) and food availability (Chl-a) conditions. The HSI modelling consists of estimating SI curves based on available evidence regarding the optimum range of environmental conditions for anchovy and estimating an integrated HSI using the Arithmetic Mean Model (AMM) method. The

  4. When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world

    Science.gov (United States)

    Eric J. Gustafson

    2013-01-01

    Researchers and natural resource managers need predictions of how multiple global changes (e.g., climate change, rising levels of air pollutants, exotic invasions) will affect landscape composition and ecosystem function. Ecological predictive models used for this purpose are constructed using either a mechanistic (process-based) or a phenomenological (empirical)...

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Shelly Levy-Tzedek

    2017-11-01

    Full Text Available 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.

  7. 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.

  8. Measurement and prediction of solubilities of active pharmaceutical ingredients.

    Science.gov (United States)

    Hahnenkamp, Inga; Graubner, Gitte; Gmehling, Jürgen

    2010-03-30

    Solubilities of 2-acetoxy benzoic acid (aspirin), N-acetyl-p-aminophenol (paracetamol) and 2-(p-isobutylphenyl)propionic acid (ibuprofen) have been measured in various solvents and compared with published and predicted data. For the prediction besides the two group contribution models UNIFAC and modified UNIFAC (Dortmund) the quantum chemical approach COSMO-RS (Ol) was used. Additionally melting temperatures and heats of fusion for 2-acetoxy benzoic acid, N-acetyl-p-aminophenol and 2-(p-isobutylphenyl)propionic acid required for the calculations have been determined by differential scanning calorimetry. Copyright (c) 2009 Elsevier B.V. All rights reserved.

  9. 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 error...

  10. 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 ...

  11. 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.

  12. Great Basin Forb Restoration: Lupine Response to Altered Precipitation Predicted by Climate Change

    OpenAIRE

    Johnson, Andrea Jo; Hulvey, Kristin; Jensen, Scott; Monaco, Tom

    2018-01-01

    Abundance of native forb species is declining, leading to degraded ecosystems within the Great Basin. Forbs provide many ecosystem functions, including wildlife habitat for species such as Sage Grouse, increased biodiversity, resistance to erosion, and protection from invasive plant species. Climate change is predicted to affect timing, frequency, and intensity of precipitation within the Great Basin. During the fall season, precipitation is expected to increase by 30%. Changes in pr...

  13. A new statistical tool to predict phenology under climate change scenarios

    OpenAIRE

    Gienapp, P.; Hemerik, L.; Visser, M.E.

    2005-01-01

    Climate change will likely affect the phenology of trophic levels differently and thereby disrupt the phenological synchrony between predators and prey. To predict this disruption of the synchrony under different climate change scenarios, good descriptive models for the phenology of the different species are necessary. Many phenological models are based on regressing the observed phenological event against temperatures measured over a fixed period. This is problematic, especially when used fo...

  14. 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.

  15. 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.

  16. Predictions of future ephemeral springtime waterbird stopover habitat availability under global change

    Science.gov (United States)

    Uden, Daniel R.; Allen, Craig R.; Bishop, Andrew A.; Grosse, Roger; Jorgensen, Christopher F.; LaGrange, Theodore G.; Stutheit, Randy G.; Vrtiska, Mark P.

    2015-01-01

    In the present period of rapid, worldwide change in climate and landuse (i.e., global change), successful biodiversity conservation warrants proactive management responses, especially for long-distance migratory species. However, the development and implementation of management strategies can be impeded by high levels of uncertainty and low levels of control over potentially impactful future events and their effects. Scenario planning and modeling are useful tools for expanding perspectives and informing decisions under these conditions. We coupled scenario planning and statistical modeling to explain and predict playa wetland inundation (i.e., presence/absence of water) and ponded area (i.e., extent of water) in the Rainwater Basin, an anthropogenically altered landscape that provides critical stopover habitat for migratory waterbirds. Inundation and ponded area models for total wetlands, those embedded in rowcrop fields, and those not embedded in rowcrop fields were trained and tested with wetland ponding data from 2004 and 2006–2009, and then used to make additional predictions under two alternative climate change scenarios for the year 2050, yielding a total of six predictive models and 18 prediction sets. Model performance ranged from moderate to good, with inundation models outperforming ponded area models, and models for non-rowcrop-embedded wetlands outperforming models for total wetlands and rowcrop-embedded wetlands. Model predictions indicate that if the temperature and precipitation changes assumed under our climate change scenarios occur, wetland stopover habitat availability in the Rainwater Basin could decrease in the future. The results of this and similar studies could be aggregated to increase knowledge about the potential spatial and temporal distributions of future stopover habitat along migration corridors, and to develop and prioritize multi-scale management actions aimed at mitigating the detrimental effects of global change on migratory

  17. 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...

  18. 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

    outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeated until the fault is detected by a passive diagnoser. It is demonstrated how the generated excitation signal...

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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...

  5. 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…

  6. 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 ...

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

    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, 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 ...

  8. 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.

  9. 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...

  10. Predicted soil management and climate change effects on SOC in South Carolina

    Science.gov (United States)

    Extensive use of inversion tillage has contributed to the loss of soil organic carbon (SOC) and degraded soil health in the southeast U.S.A. Our objective was to predict changes in SOC in a Norfolk loamy sand in Florence, SC under several crop rotations (corn (Zea mays L.)-cotton (Gossypium ssp.), C...

  11. 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.

  12. 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.

  13. 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

  14. Prediction of muscle activity during loaded movements of the upper limb

    OpenAIRE

    Tibold, Robert; Fuglevand, Andrew J

    2015-01-01

    Background Accurate prediction of electromyographic (EMG) signals associated with a variety of motor behaviors could, in theory, serve as activity templates needed to evoke movements in paralyzed individuals using functional electrical stimulation. Such predictions should encompass complex multi-joint movements and include interactions with objects in the environment. Methods Here we tested the ability of different artificial neural networks (ANNs) to predict EMG activities of 12 arm muscles ...

  15. 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.

  16. 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

  17. 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.

  18. The change of the brain activation patterns as children learn algebra equation solving

    Science.gov (United States)

    Qin, Yulin; Carter, Cameron S.; Silk, Eli M.; Stenger, V. Andrew; Fissell, Kate; Goode, Adam; Anderson, John R.

    2004-04-01

    In a brain imaging study of children learning algebra, it is shown that the same regions are active in children solving equations as are active in experienced adults solving equations. As with adults, practice in symbol manipulation produces a reduced activation in prefrontal cortex area. However, unlike adults, practice seems also to produce a decrease in a parietal area that is holding an image of the equation. This finding suggests that adolescents' brain responses are more plastic and change more with practice. These results are integrated in a cognitive model that predicts both the behavioral and brain imaging results.

  19. Larvicidal activity prediction against Aedes aegypti mosquito using computational tools

    OpenAIRE

    Yudith Cañizares-Carmenate; Mirelys Hernandez-Morfa; Francisco Torrens; Gloria Castellano; Juan A Castillo-Garit

    2017-01-01

    Background & objectives: Aedes aegypti is an important vector for transmission of dengue, yellow fever, chikun- gunya, arthritis, and Zika fever. According to the World Health Organization, it is estimated that Ae. aegypti causes 50 million infections and 25,000 deaths per year. Use of larvicidal agents is one of the recommendations of health organizations to control mosquito populations and limit their distribution. The aim of present study was to deduce a mathematical model to predict the l...

  20. 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...

  1. Plasma total and unacylated ghrelin predict 5-year changes in insulin resistance.

    Science.gov (United States)

    Barazzoni, R; Gortan Cappellari, G; Semolic, A; Ius, M; Mamolo, L; Dore, F; Giacca, M; Zanetti, M; Vinci, P; Guarnieri, G

    2016-10-01

    Ghrelin is a gastric hormone circulating in acylated (AG) and unacylated (UG) forms, and higher plasma total ghrelin (TG) and UG may be cross-sectionally associated with lower insulin resistance in metabolic syndrome patients. The potential value of ghrelin forms in predicting insulin resistance and its time-related changes in community-based population cohorts remains unknown. We measured TG, AG and calculated UG (TG-AG) in 716 individuals from the North-East-Italy MoMa study (age: 55 ± 9 years, BMI: 29 ± 5 kg/m(2), M/F:349/367) to test the hypothesis that circulating TG and UG, but not AG are negatively associated with insulin resistance (HOMA). We further hypothesized that baseline TG and UG negatively predict 5-year HOMA changes in a 350-individual subgroup. Baseline TG and UG were associated negatively with HOMA after adjusting for gender and body mass index (BMI). Baseline gender- and BMI-adjusted TG and UG were also negatively associated with HOMA at 5-year follow-up (n = 350), and changes in TG and UG were negatively associated with changes in HOMA (P insulin resistance and may contribute to predict its time-related changes in humans. Copyright © 2015 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  2. 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 l...

  3. 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) ...

  4. Estimated venous return surface and cardiac output curve precisely predicts new hemodynamics after volume change.

    Science.gov (United States)

    Sugimachi, Masaru; Sunagawa, Kenji; Uemura, Kazunori; Kamiya, Atsunori; Shimizu, Shuji; Inagaki, Masashi; Shishido, Toshiaki

    2010-01-01

    In our extended Guyton's model, the ability of heart to pump blood is characterized by a cardiac output curve and the ability of vasculature to pool blood by a venous return surface. These intersect in a three-dimensional coordinate system at the operating right atrial pressure, left atrial pressure, and cardiac output. The baseline cardiac output curve and venous return surface and their changes after volume change would predict new hemodynamics. The invasive methods needed to precisely characterize cardiac output curve and venous return surface led us to aim at estimating cardiac output curve and venous return surface from a single hemodynamic measurement. Using the average values for two logarithmic function parameters, and for two slopes of a surface, we were able to estimate cardiac output curve and venous return surface. The estimated curve and surface predicted new hemodynamics after volume change precisely.

  5. 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)

  6. Performance Prediction of Active Piezo Fiber Rackets in Terms of Tennis Power

    Science.gov (United States)

    Kawazoe, Yoshihiko; Takeda, Yukihiro; Nakagawa, Masamichi

    Several former top players sent a letter to the International Tennis Federation (ITF) encouraging the governing body to revisit the question of rackets. In the letter, the players wrote that racket technology has led to major changes in how the game is played at the top level. This paper investigated the physical properties of a new type of racket with active piezoelectric fibers appeared recently in the market, and predicted the various factors associated with the frontal impact, such as impact force, contact time, deformation of ball and strings, and also estimated the racket performance such as the coefficient of restitution, the rebound power coefficient, the post-impact ball velocity and the sweet areas relevant to the power in tennis. It is based on the experimental identification of the dynamics of the ball-racket-arm system and the approximate nonlinear impact analysis with a simple swing model. The predicted results with forehand stroke model can explain the difference in mechanism of performance between the new type racket with active piezoelectric fibers and the conventional passive representative rackets. It showed that this new type racket provides higher coefficient of restitution on the whole area of string face and also gives larger rebound power coefficients particularly at the topside and bigger powers on the whole area of string face but the difference was not so large. It seems that the racket-related improvements in play are relatively small and the players themselves continue to improve, accordingly there is a gap between a perception and reality.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. Changes in vitamin D supplement use and baseline plasma 25-hydroxyvitamin D concentration predict 5-y change in concentration in postmenopausal women.

    Science.gov (United States)

    Kluczynski, Melissa A; Wactawski-Wende, Jean; Platek, Mary E; DeNysschen, Carol A; Hovey, Kathleen M; Millen, Amy E

    2012-09-01

    Few studies have prospectively examined predictors of change in plasma concentrations of 25-hydroxyvitamin D [25(OH)D]. We sought to determine the predictors of 5-y change in 25(OH)D. Plasma 25(OH)D concentrations were assessed at baseline (1997-2000) and 5 y later (2002-2005) in 668 postmenopausal women enrolled in the Osteoporosis and Periodontal Disease Study. Baseline and changes in demographic, dietary, lifestyle, and health-related factors were tested as predictors of change in 25(OH)D concentrations by using multivariable linear regression. The mean 5-y change in 25(OH)D (mean ± SD) was 7.7 ± 0.7 nmol/L (P < 0.001). In our predictive model (n = 643), predictors explained 31% of the variance in change in 25(OH)D concentrations and included baseline 25(OH)D, baseline and change in vitamin D supplementation and physical activity, change in season of blood draw, BMI, whole-body T score, and baseline hormone therapy use. Baseline 25(OH)D and change in vitamin D supplementation explained the most variation (25%) in 25(OH)D. Exploratory analyses showed a borderline significant interaction between tertiles of baseline 25(OH)D and change in vitamin D supplementation over time (P = 0.06). The greatest mean increase in 25(OH)D (22.9 ± 16.8 nmol/L), with adjustment for other statistically significant predictors, occurred in women whose baseline 25(OH)D concentration was ≤51.0 nmol/L (tertile 1) and who increased supplementation use over time. These results confirm the importance of supplementation in increasing 25(OH)D concentrations in aging women, even after other statistically significant predictors are controlled for. These data also suggest that this is especially true among aging women with inadequate 25(OH)D (e.g., <50 nmol/L).

  12. 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.

  13. 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

  14. 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...... for solving the nonconvex optimization problem is proposed in this paper. A simulation using the nonlinear model-based controller to control the temperature levels of an intelligent office building (PowerFlexHouse) is addressed. Its performance is compared with a linear model-based controller. The nonlinear...

  15. 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.

  16. 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.

  17. Can we predict the direction of marine primary production change under global warming?

    Science.gov (United States)

    Taucher, J.; Oschlies, A.

    2011-01-01

    A global Earth System model is employed to investigate the role of direct temperature effects in the response of marine ecosystems to climate change. While model configurations with and without consideration of explicit temperature effects can reproduce observed current biogeochemical tracer distributions and estimated carbon export about equally well, carbon flow through the model ecosystem reveals strong temperature sensitivities. Depending on whether biological processes are assumed temperature sensitive or not, simulated marine net primary production (NPP) increases or decreases under projected climate change driven by a business-as-usual CO2 emission scenario for the 21st century. This suggests that indirect temperature effects such as changes in the supply of nutrients and light are not the only relevant factors to be considered when modeling the response of marine ecosystems to climate change. A better understanding of direct temperature effects on marine ecosystems is required before even the direction of change in NPP can be reliably predicted.

  18. 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.

  19. Cyclone-track based seasonal prediction for South Pacific tropical cyclone activity using APCC multi-model ensemble prediction

    Science.gov (United States)

    Kim, Ok-Yeon; Chan, Johnny C. L.

    2018-01-01

    This study aims to predict the seasonal TC track density over the South Pacific by combining the Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC) multi-model ensemble (MME) dynamical prediction system with a statistical model. The hybrid dynamical-statistical model is developed for each of the three clusters that represent major groups of TC best tracks in the South Pacific. The cross validation result from the MME hybrid model demonstrates moderate but statistically significant skills to predict TC numbers across all TC clusters, with correlation coefficients of 0.4 to 0.6 between the hindcasts and observations for 1982/1983 to 2008/2009. The prediction skill in the area east of about 170°E is significantly influenced by strong El Niño, whereas the skill in the southwest Pacific region mainly comes from the linear trend of TC number. The prediction skill of TC track density is particularly high in the region where there is climatological high TC track density around the area 160°E-180° and 20°S. Since this area has a mixed response with respect to ENSO, the prediction skill of TC track density is higher in non-ENSO years compared to that in ENSO years. Even though the cross-validation prediction skill is higher in the area east of about 170°E compared to other areas, this region shows less skill for track density based on the categorical verification due to huge influences by strong El Niño years. While prediction skill of the developed methodology varies across the region, it is important that the model demonstrates skill in the area where TC activity is high. Such a result has an important practical implication—improving the accuracy of seasonal forecast and providing communities at risk with advanced information which could assist with preparedness and disaster risk reduction.

  20. 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).

  1. Quantitative metrics for assessing predicted climate change pressure on North American tree species

    Science.gov (United States)

    Kevin M. Potter; William W. Hargrove

    2013-01-01

    Changing climate may pose a threat to forest tree species, forcing three potential population-level responses: toleration/adaptation, movement to suitable environmental conditions, or local extirpation. Assessments that prioritize and classify tree species for management and conservation activities in the face of climate change will need to incorporate estimates of the...

  2. Determinants of Change in Physical Activity in Children and Adolescents

    Science.gov (United States)

    Craggs, Christopher; Corder, Kirsten; van Sluijs, Esther M.F.; Griffin, Simon J.

    2011-01-01

    Context Data are available on correlates of physical activity in children and adolescents, less is known about the determinants of change. This review aims to systematically review the published evidence regarding determinants of change in physical activity in children and adolescents. Evidence acquisition Prospective quantitative studies investigating change in physical activity in children and adolescents aged 4–18 years were identified from seven databases (to November 2010): PubMed, SCOPUS, PsycINFO, Ovid MEDLINE, SPORTDdiscus, Embase, and Web of Knowledge. Study inclusion, quality assessment, and data extraction were independently validated by two researchers. Semi-quantitative results were stratified by age (4–9 years, 10–13 years, and 14–18 years). Evidence synthesis Of the 46 studies that were included, 31 used self-reported physical activity; average methodologic quality was 3.2 (SD=1.2), scored 0–5. Of 62 potential determinants identified, 30 were studied more than three times and 14 reported consistent findings (66% of the reported associations were in the same direction). For children aged 4–9 years, girls reported larger declines than boys. Among those aged 10–13 years, higher levels of previous physical activity and self-efficacy resulted in smaller declines. Among adolescents (aged 14–18 years), higher perceived behavioral control, support for physical activity, and self-efficacy were associated with smaller declines in physical activity. Conclusions Few of the variables studied were consistently associated with changes in physical activity, although some were similar to those identified in cross-sectional studies. The heterogeneity in study samples, exposure and outcome variables, and the reliance on self-reported physical activity limit conclusions and highlight the need for further research to inform development and targeting of interventions. PMID:21565658

  3. 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.

  4. Changes in Frailty Predict Changes in Cognition in Older Men: The Honolulu-Asia Aging Study.

    Science.gov (United States)

    Armstrong, Joshua J; Godin, Judith; Launer, Lenore J; White, Lon R; Mitnitski, Arnold; Rockwood, Kenneth; Andrew, Melissa K

    2016-06-15

    As cognitive decline mostly occurs in late life, where typically it co-exists with many other ailments, it is important to consider frailty in understanding cognitive change. Here, we examined the association of change in frailty status with cognitive trajectories in a well-studied cohort of older Japanese-American men. Using the prospective Honolulu-Asia Aging Study (HAAS), 2,817 men of Japanese descent were followed (aged 71-93 at baseline). Starting in 1991 with follow-up health assessments every two to three years, cognition was measured using the Cognitive Abilities Screening Instrument (CASI). For this study, health data was used to construct an accumulation of deficits frailty index (FI). Using six waves of data, multilevel growth curve analyses were constructed to examine simultaneous changes in cognition in relation to changes in FI, controlling for baseline frailty, age, education, and APOE-ɛ4 status. On average, CASI scores declined by 2.0 points per year (95% confidence interval 1.9-2.1). Across six waves, each 10% within-person increase in frailty from baseline was associated with a 5.0 point reduction in CASI scores (95% confidence interval 4.7-5.2). Baseline frailty and age were associated both with lower initial CASI scores and with greater decline across the five follow-up assessments (p age. Using a multidimensional measure of frailty, both baseline status and within-person changes in frailty were predictive of cognitive trajectories.

  5. Towards a Unified Framework in Hydroclimate Extremes Prediction in Changing Climate

    Science.gov (United States)

    Moradkhani, H.; Yan, H.; Zarekarizi, M.; Bracken, C.

    2016-12-01

    Spatio-temporal analysis and prediction of hydroclimate extremes are of paramount importance in disaster mitigation and emergency management. The IPCC special report on managing the risks of extreme events and disasters emphasizes that the global warming would change the frequency, severity, and spatial pattern of extremes. In addition to climate change, land use and land cover changes also influence the extreme characteristics at regional scale. Therefore, natural variability and anthropogenic changes to the hydroclimate system result in nonstationarity in hydroclimate variables. In this presentation recent advancements in developing and using Bayesian approaches to account for non-stationarity in hydroclimate extremes are discussed. Also, implications of these approaches in flood frequency analysis, treatment of spatial dependence, the impact of large-scale climate variability, the selection of cause-effect covariates, with quantification of model errors in extreme prediction is explained. Within this framework, the applicability and usefulness of the ensemble data assimilation for extreme flood predictions is also introduced. Finally, a practical and easy to use approach for better communication with decision-makers and emergency managers is presented.

  6. Serial Change in Cervical Length for the Prediction of Emergency Cesarean Section in Placenta Previa.

    Directory of Open Access Journals (Sweden)

    Jae Eun Shin

    Full Text Available To evaluate whether serial change in cervical length (CL over time can be a predictor for emergency cesarean section (CS in patients with placenta previa.This was a retrospective cohort study of patients with placenta previa between January 2010 and November 2014. All women were offered serial measurement of CL by transvaginal ultrasound at 19 to 23 weeks (CL1, 24 to 28 weeks (CL2, 29 to 31 weeks (CL3, and 32 to 34 weeks (CL4. We compared clinical characteristics, serial change in CL, and outcomes between the emergency CS group (case group and elective CS group (control group. The predictive value of change in CL for emergency CS was evaluated.A total of 93 women were evaluated; 31 had emergency CS due to massive vaginal bleeding. CL tended to decrease with advancing gestational age in each group. Until 29-31 weeks, CL showed no significant differences between the two groups, but after that, CL in the emergency CS group decreased abruptly, even though CL in the elective CS group continued to gradually decrease. On multivariate analysis to determine risk factors, only admissions for bleeding (odds ratio, 34.710; 95% CI, 5.239-229.973 and change in CL (odds ratio, 3.522; 95% CI, 1.210-10.253 were significantly associated with emergency CS. Analysis of the receiver operating characteristic curve showed that change in CL could be the predictor of emergency CS (area under the curve 0.734, p < 0.001, with optimal cutoff for predicting emergency cesarean delivery of 6.0 mm.Previous admission for vaginal bleeding and change in CL are independent predictors of emergency CS in placenta previa. Women with change in CL more than 6 mm between the second and third trimester are at high risk of emergency CS in placenta previa. Single measurements of short CL at the second or third trimester do not seem to predict emergency CS.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. Social participation predicts cognitive functioning in aging adults over time: comparisons with physical health, depression, and physical activity.

    Science.gov (United States)

    Bourassa, Kyle J; Memel, Molly; Woolverton, Cindy; Sbarra, David A

    2017-02-01

    Several risk and protective factors are associated with changes in cognitive functioning in aging adults - including physical health, depression, physical activity, and social activities - though the findings for participation in social activities are mixed. This study investigated the longitudinal association between social participation and two domains of cognitive functioning, memory and executive function. A primary goal of our analyses was to determine whether social participation predicted cognitive functioning over-and-above physical health, depression, and physical activity in a sample with adequate power to detect unique effects. The sample included aging adults (N = 19,832) who participated in a large, multi-national study and provided data across six years; split into two random subsamples. Unique associations between the predictors of interest and cognitive functioning over time and within occasion were assessed in a latent curve growth model. Social participation predicted both domains of cognitive functioning at each occasion, and the relative magnitude of this effect was comparable to physical health, depression, and physical activity level. In addition, social participation at the first time point predicted change in cognitive functioning over time. The substantive results in the initial sample were replicated in the second independent subsample. Overall, the magnitude of the association of social participation is comparable to other well-established predictors of cognitive functioning, providing evidence that social participation plays an important role in cognitive functioning and successful aging.

  12. Phonological awareness predicts activation patterns for print and speech

    Science.gov (United States)

    Frost, Stephen J.; Landi, Nicole; Mencl, W. Einar; Sandak, Rebecca; Fulbright, Robert K.; Tejada, Eleanor T.; Jacobsen, Leslie; Grigorenko, Elena L.; Constable, R. Todd; Pugh, Kenneth R.

    2009-01-01

    Using fMRI, we explored the relationship between phonological awareness (PA), a measure of metaphonological knowledge of the segmental structure of speech, and brain activation patterns during processing of print and speech in young readers from six to ten years of age. Behavioral measures of PA were positively correlated with activation levels for print relative to speech tokens in superior temporal and occipito-temporal regions. Differences between print-elicited activation levels in superior temporal and inferior frontal sites were also correlated with PA measures with the direction of the correlation depending on stimulus type: positive for pronounceable pseudowords and negative for consonant strings. These results support and extend the many indications in the behavioral and neurocognitive literature that PA is a major component of skill in beginning readers and point to a developmental trajectory by which written language engages areas originally shaped by speech for learners on the path toward successful literacy acquisition. PMID:19306061

  13. 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

  14. 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.

  15. 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

  16. Modelling and Bayesian adaptive prediction of individual patients’ tumour volume change during radiotherapy

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  17. 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...... for solving the nonconvex optimization problem is proposed in this paper. A simulation using the nonlinear model-based controller to control the temperature levels of an intelligent office building (PowerFlexHouse) is addressed. Its performance is compared with a linear model-based controller. The nonlinear...... 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....

  18. Polluted Morality: Air Pollution Predicts Criminal Activity and Unethical Behavior.

    Science.gov (United States)

    Lu, Jackson G; Lee, Julia J; Gino, Francesca; Galinsky, Adam D

    2018-02-01

    Air pollution is a serious problem that affects billions of people globally. Although the environmental and health costs of air pollution are well known, the present research investigates its ethical costs. We propose that air pollution can increase criminal and unethical behavior by increasing anxiety. Analyses of a 9-year panel of 9,360 U.S. cities found that air pollution predicted six major categories of crime; these analyses accounted for a comprehensive set of control variables (e.g., city and year fixed effects, population, law enforcement) and survived various robustness checks (e.g., balanced panel, nonparametric bootstrapped standard errors). Three subsequent experiments involving American and Indian participants established the causal effect of psychologically experiencing a polluted (vs. clean) environment on unethical behavior. Consistent with our theoretical perspective, results revealed that anxiety mediated this effect. Air pollution not only corrupts people's health, but also can contaminate their morality.

  19. The contribution of human activities to climate changes

    OpenAIRE

    Slave, Camelia; Man, Carmen

    2012-01-01

    Some of the components of the climate system, the oceans and biosphere primarily affects the concentration of greenhouse gases in the atmosphere. Plants take CO2 from the atmosphere and convert it in the process of photosynthesis, carbohydrate. In the industrial era, human activities have contributed to increased concentrations of greenhouse gases in the atmosphere. In addition, human activities contribute to climate change by altering the concentration of aerosols and clouds cover. Greatest ...

  20. 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.

  1. 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.

  2. Management of academic staff activity: modeling and prediction of rating system indicators

    Directory of Open Access Journals (Sweden)

    O. S. Logunova

    2016-01-01

    Full Text Available This paper deals with the problem of constructing a system of rating indicators for stimulating the work of the academic staff in higher educational institution. Many areas of teacher activity (for example, educational, scientific, international, etc. laid the basis of selection the groups of indicators in the system. Social challenge in improving the quality of educational services determines the relevance of research in the field of modeling and prediction of indicators which characterize the work of high school teacher. To predict the dynamics of the structure of the rating indicators in the system, the authors introduced the concept of drift and variability of each group. Using informational hypercube for the structure of input data allowed authors to take into account the individual characteristics of each parameter included in a mathematical model to describe the rating indicators. To make the prediction of the structure and values of rating system indicators the authors introduced the concept of drift. Drift of indicators takes into account the introduction of new indicators, the removal of existing indicators, and movement of indicators between the groups. In the article, authors introduced a novel quantitative indicator of group variability. The value of this indicator determines the prediction strategy of the teacher work in higher school in the future period. To predict the total amount of stimulating, the complex technique offered and it includes four modules: modeling values within the existing range in the previous period; modeling new index value based on the assumptions introduced using a random number generator; exclusion a range of values of deleted indicators; modeling new values based on the study of the modern trend of indicators. The presence of flexible information structure in the form of a hypercube and complex mathematical model allowed authors to carry out numerical simulation for predicting the values of individual

  3. Linking perceived control, physical activity, and biological health to memory change.

    Science.gov (United States)

    Infurna, Frank J; Gerstorf, Denis

    2013-12-01

    Perceived control plays an important role for remaining cognitively fit across adulthood and old age. However, much less is known about the role of perceived control over and above common correlates of cognition, and possible factors that underlie such control-cognition associations. Our study examined whether perceived control was predictive of individual differences in subsequent 4-year changes in episodic memory, and explored the mediating role of physical activity and indicators of physical fitness, cardiovascular, and metabolic health for control-memory associations. To do so, we used longitudinal data from the nationwide Health and Retirement Study (HRS; N = 4,177; ages 30 to 97 years; 59% women). Our results show that perceiving more control over one's life predicted less memory declines, and this protective effect was similar in midlife and old age. We additionally observed that higher levels and maintenance of physical activity over 2 years, better pulmonary function, lower systolic blood pressure (SPB), lower hemoglobin A1c, and higher high-density lipoprotein cholesterol (HDL-C) also predicted less memory declines. Mediation analyses revealed that levels of, and 2-year changes in, physical activity, as well as levels of pulmonary function and hemoglobin A1c and HDL-C, each uniquely mediated control-memory change associations. Our findings illustrate that perceived control, physical activity, and indicators of physical fitness and cardiovascular and metabolic health moderate changes in memory, and add to the literature on antecedents of cognitive aging by conjointly targeting perceived control and some of its mediating factors. We discuss possible pathways underlying the role of control for memory change and consider future routes of inquiry to further our understanding of control-cognition associations in adulthood and old age. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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

    African Journals Online (AJOL)

    GREGORY

    2011-12-16

    Dec 16, 2011 ... molecular topology and electrostatic interactions on the anti-cancer activity of nitorosoureas. In this equation, fractional negatively charged surface area of type 3. N. O. N. O. N. R2. R3. R1. Figure 1. Molecular structure of nitrosoureas, where R1, R2 and R3 are different substituent groups including hydrogen ...

  5. 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.

  6. Do labour market status transitions predict changes in psychological well-being?

    Science.gov (United States)

    Flint, Ellen; Bartley, Mel; Shelton, Nicola; Sacker, Amanda

    2013-09-01

    The objective of this study was to establish the direction of causality in the relationship between labour market status and psychological well-being by investigating how transitions between secure employment, insecure employment, unemployment, permanent sickness and other economic inactivity predict changes in psychological well-being over a 16-year period. This study used data from the British Household Panel Survey (1991-2007). Psychological well-being was measured using the 12-item General Health Questionnaire (GHQ-12). Fixed effects models were utilised to investigate how transitions between labour market statuses predicted GHQ-12 score, adjusting for current labour market status and a range of covariates. After taking account of the contemporaneous effects of joblessness on psychological well-being, and the impact of a range of confounding factors, experiencing a transition from employment to joblessness was significantly predictive of poorer psychological well-being. Transitions into employment were not found to have equal and opposite effects: the positive effects of moving into work from unemployment were not as large as the negative effects of job loss. Transitions between secure and insecure employment did not independently predict changes in psychological well-being. A causal relationship between labour market status and psychological well-being is indicated.

  7. The challenge of predicting karst water resources in a changing world (Invited)

    Science.gov (United States)

    Hartmann, A.

    2013-12-01

    Karst regions represent a large part of global continental area providing drinking water to almost a quarter of the world population. Climate simulations predict a strong increase in temperature and a decrease of precipitation in many karst regions in the world (see figure below). Despite of this knowledge, there are only few studies that address the impact of climate or change on karst water resources. This presentation will provide an overview about different approaches for the simulation of karst water resources, comparing their data requirements and process representation, and elaborating reasons for their limited applicability. A set of case studies will be used to show the benefits of new modeling approaches that include hydrochemical observations, and sensitivity and uncertainty analysis to evaluate and improve the prediction of karst water resources. Furthermore, the impact of uncertain temperature and precipitation predictions of climate simulation models on the prediction of karst water resources will be elaborated by another example and alternative approaches will be discussed. The presentation will end with an outlook about the application of karst simulation models on larger scales where no discharge and groundwater measurements will be presented. Location of carbonate rock outcrops in Europe [Williams and Ford, Zeitschrift für Geomorphologie, 2006, modified] compared to expected mean change of temperature and precipitation in North America (a,b) and Europe (c,d) from 1961-1990 to 2081-2090, derived from 20 general circulation models [IPCC, 2007].

  8. Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels

    NARCIS (Netherlands)

    Van der Putten, W.H.; Macel, M.; Visser, M.E.

    2010-01-01

    Current predictions on species responses to climate change strongly rely on projecting altered environmental conditions on species distributions. However, it is increasingly acknowledged that climate change also influences species interactions. We review and synthesize literature information on

  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. Changes in Albuminuria Predict Mortality and Morbidity in Patients with Vascular Disease

    Science.gov (United States)

    Mann, Johannes F. E.; Schumacher, Helmut; Gao, Peggy; Mancia, Giuseppe; Weber, Michael A.; McQueen, Matthew; Koon, Teo; Yusuf, Salim

    2011-01-01

    The degree of albuminuria predicts cardiovascular and renal outcomes, but it is not known whether changes in albuminuria also predict similar outcomes. In two multicenter, multinational, prospective observational studies, a central laboratory measured albuminuria in 23,480 patients with vascular disease or high-risk diabetes. We quantified the association between a greater than or equal to twofold change in albuminuria in spot urine from baseline to 2 years and the incidence of cardiovascular and renal outcomes and all-cause mortality during the subsequent 32 months. A greater than or equal to twofold increase in albuminuria from baseline to 2 years, observed in 28%, associated with nearly 50% higher mortality (HR 1.48; 95% CI 1.32 to 1.66), and a greater than or equal to twofold decrease in albuminuria, observed in 21%, associated with 15% lower mortality (HR 0.85; 95% CI 0.74 to 0.98) compared with those with lesser changes in albuminuria, after adjustment for baseline albuminuria, BP, and other potential confounders. Increases in albuminuria also significantly associated with cardiovascular death, composite cardiovascular outcomes (cardiovascular death, myocardial infarction, stroke, and hospitalization for heart failure), and renal outcomes including dialysis or doubling of serum creatinine (adjusted HR 1.40; 95% CI 1.11 to 1.78). In conclusion, in patients with vascular disease, changes in albuminuria predict mortality and cardiovascular and renal outcomes, independent of baseline albuminuria. This suggests that monitoring albuminuria is a useful strategy to help predict cardiovascular risk. PMID:21719791

  12. Implementing algorithms for modelling and prediction of sea level change using threshold models

    Science.gov (United States)

    Hewelt, M.; Miziński, B.; Niedzielski, T.

    2012-04-01

    The aim of this work is to present how threshold time series models can be used to model sea level change recorded in gridded time series data and to predict such time-varying maps. This task is carried out mostly in R, the Language and Environment, using satellite altimetric gridded time series from the Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO). During El Niño/Southern Oscillation (ENSO) warm and cold episodes sea level anomalies exceed certain thresholds, principally in the equatorial Pacific and in the tropical Indian Ocean. This encourages to use threshold autoregressive models to predict sea level change, particularly in the aforementioned locations. It is likely, however, that during the ENSO mode one should use the models which differ from those suitable for normal environmental conditions. Associated with this is a notion of threshold that allows one to determine various models if a certain limit value is attained or exceeded. Firstly, having the global mean sea level anomaly data spanning the time interval from 1992 onwards, available courtesy of AVISO, the autoregressive threshold model is fitted in R. Subsequently, the global mean sea level change univariate time series is forecasted, and various lead times are adopted. Secondly, based on the gridded delayed-time data as well as their near-real time equivalents provided by AVISO, predictions of sea level change determined as a function of latitude and longitude, and with various lead times, are produced. Due to the fact, that the near-real time data are being automatically updated at the local server in Wroclaw, Poland, it is possible to generate new predictions every day automatically. Such a forecasting process, which intrinsically involves the automated verification and quality control modules, is based on the above-mentioned threshold models as well as polynomial-harmonic deterministic empirical functions.

  13. Stoichiometric homeostasis predicts plant species dominance, temporal stability, and responses to global change.

    Science.gov (United States)

    Yu, Qiang; Wilcox, Kevin; La Pierre, Kimberly; Knapp, Alan K; Han, Xingguo; Smith, Melinda D

    2015-09-01

    Why some species are consistently more abundant than others, and predicting how species will respond to global change, are fundamental questions in ecology. Long-term observations indicate that plant species with high stoichiometric homeostasis for nitrogen (HN), i.e., the ability to decouple foliar N levels from variation in soil N availability, were more common and stable through time than low-HN species in a central U.S. grassland. However, with nine years of nitrogen addition, species with high H(N) decreased in abundance, while those with low H(N) increased in abundance. In contrast, in climate change experiments simulating a range of forecast hydrologic changes, e.g., extreme drought (two years), increased rainfall variability (14 years), and chronic increases in rainfall (21 years), plant species with the highest H(N) were least responsive to changes in soil water availability. These results suggest that H(N) may be predictive of plant species success and stability, and how plant species and ecosystems will respond to global-change-driven alterations in resource availability.

  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

    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...... 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...

  15. 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

  16. 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.

  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. 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.

  19. 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.

  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. 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.

  2. 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

  3. 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…

  4. 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.

  5. Larvicidal activity of Illicium difengpi BN Chang (Schisandraceae ...

    African Journals Online (AJOL)

    Purpose: To determine the larvicidal activity of the essential oil derived from Illicium difengpi B.N. Chang stem bark (Schisandraceae) and its major constituents against the larvae of Aedes aegypti L. Methods: Essential oil of I. difengpi stem bark was obtained by hydrodistillation and analyzed by gas chromatography (GC) ...

  6. 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 ...

  7. Changes in photosynthesis and activities of enzymes involved in ...

    African Journals Online (AJOL)

    AJL

    2012-04-26

    Apr 26, 2012 ... Changes in photosynthesis and activities of enzymes involved in carbon metabolism during exposure ... pigment-protein (cab gene encoding) complexes of PSII. (LHCII), which occupies approximately ... filtered through two layers of Miracloth and the dark green filtrate was centrifuged at 3000 rpm for 5 min ...

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

    African Journals Online (AJOL)

    2011-06-06

    Jun 6, 2011 ... Abstract. 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. ... college life exposes first-year students to weight gain which they ... Results. The social and demographic characteristics of the study participants.

  9. 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.

  10. Working memory training: improving intelligence--changing brain activity.

    Science.gov (United States)

    Jaušovec, Norbert; Jaušovec, Ksenija

    2012-07-01

    The main objectives of the study were: to investigate whether training on working memory (WM) could improve fluid intelligence, and to investigate the effects WM training had on neuroelectric (electroencephalography - EEG) and hemodynamic (near-infrared spectroscopy - NIRS) patterns of brain activity. In a parallel group experimental design, respondents of the working memory group after 30 h of training significantly increased performance on all tests of fluid intelligence. By contrast, respondents of the active control group (participating in a 30-h communication training course) showed no improvements in performance. The influence of WM training on patterns of neuroelectric brain activity was most pronounced in the theta and alpha bands. Theta and lower-1 alpha band synchronization was accompanied by increased lower-2 and upper alpha desynchronization. The hemodynamic patterns of brain activity after the training changed from higher right hemispheric activation to a balanced activity of both frontal areas. The neuroelectric as well as hemodynamic patterns of brain activity suggest that the training influenced WM maintenance functions as well as processes directed by the central executive. The changes in upper alpha band desynchronization could further indicate that processes related to long term memory were also influenced. Copyright © 2012 Elsevier Inc. All rights reserved.

  11. Prediction of Gene Activity in Early B Cell Development Based on an Integrative Multi-Omics Analysis.

    Science.gov (United States)

    Heydarian, Mohammad; Luperchio, Teresa Romeo; Cutler, Jevon; Mitchell, Christopher J; Kim, Min-Sik; Pandey, Akhilesh; Sollner-Webb, Barbara; Reddy, Karen

    2014-02-17

    An increasingly common method for predicting gene activity is genome-wide chromatin immuno-precipitation of 'active' chromatin modifications followed by massively parallel sequencing (ChIP-seq). In order to understand better the relationship between developmentally regulated chromatin landscapes and regulation of early B cell development, we determined how differentially active promoter regions were able to predict relative RNA and protein levels at the pre-pro-B and pro-B stages. Herein, we describe a novel ChIP-seq quantification method (cRPKM) to identify active promoters and a multi-omics approach that compares promoter chromatin status with ongoing active transcription (GRO-seq), steady state mRNA (RNA-seq), inferred mRNA stability, and relative proteome abundance measurements (iTRAQ). We demonstrate that active chromatin modifications at promoters are good indicators of transcription and steady state mRNA levels. Moreover, we found that promoters with active chromatin modifications exclusively in one of these cell states frequently predicted the differential abundance of proteins. However, we found that many genes whose promoters have non-differential but active chromatin modifications also displayed changes in abundance of their cognate proteins. As expected, this large class of developmentally and differentially regulated proteins that was uncoupled from chromatin status used mostly post-transcriptional mechanisms. Strikingly, the most differentially abundant protein in our B-cell development system, 2410004B18Rik, was regulated by a post-transcriptional mechanism, which further analyses indicated was mediated by a micro-RNA. These data highlight how this integrated multi-omics data set can be a useful resource in uncovering regulatory mechanisms. This data can be accessed at: https://usegalaxy.org/u/thereddylab/p/prediction-of-gene-activity-based-on-an-integrative-multi-omics-analysis.

  12. 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.

  13. Role of Climate Change in Global Predictions of Future Tropospheric Ozone and Aerosols

    Science.gov (United States)

    Liao, Hong; Chen, Wei-Ting; Seinfeld, John H.

    2006-01-01

    A unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies general circulation model II is applied to simulate an equilibrium CO2-forced climate in the year 2100 to examine the effects of climate change on global distributions of tropospheric ozone and sulfate, nitrate, ammonium, black carbon, primary organic carbon, secondary organic carbon, sea salt, and mineral dust aerosols. The year 2100 CO2 concentration as well as the anthropogenic emissions of ozone precursors and aerosols/aerosol precursors are based on the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) A2. Year 2100 global O3 and aerosol burdens predicted with changes in both climate and emissions are generally 5-20% lower than those simulated with changes in emissions alone; as exceptions, the nitrate burden is 38% lower, and the secondary organic aerosol burden is 17% higher. Although the CO2-driven climate change alone is predicted to reduce the global O3 concentrations over or near populated and biomass burning areas because of slower transport, enhanced biogenic hydrocarbon emissions, decomposition of peroxyacetyl nitrate at higher temperatures, and the increase of O3 production by increased water vapor at high NOx levels. The warmer climate influences aerosol burdens by increasing aerosol wet deposition, altering climate-sensitive emissions, and shifting aerosol thermodynamic equilibrium. Climate change affects the estimates of the year 2100 direct radiative forcing as a result of the climate-induced changes in burdens and different climatological conditions; with full gas-aerosol coupling and accounting for ozone and direct radiative forcings by the O2, sulfate, nitrate, black carbon, and organic carbon are predicted to be +0.93, -0.72, -1.0, +1.26, and -0.56 W m(exp -2), respectively, using present-day climate and year 2100 emissions, while they are predicted to be +0.76, -0.72, 0.74, +0.97, and -0.58 W m(exp -2

  14. 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

  15. 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…

  16. Can Muscle Soreness After Intensive Work-related Activities Be Predicted?

    NARCIS (Netherlands)

    Soer, Remko; Geertzen, Jan H. B.; van der Schans, Cees P.; Groothoff, Johan W.; Reneman, Michiel F.

    2009-01-01

    Objectives: It is currently unknown whether specific determinants are predictive for developing delayed onset muscle soreness (DOMS) after heavy work-related activities. The aim of this study was to analyze whether personal characteristics and performance measures are predictive for onset,

  17. On the prediction of solar activity using different neural network models

    Directory of Open Access Journals (Sweden)

    F. Fessant

    1996-01-01

    Full Text Available Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These parameters rely strongly on solar activity. In this paper, we analyze the use of neural networks for sunspot time series prediction. Three types of models are tested and experimental results are reported for a particular sunspot time series: the IR5 index.

  18. On the prediction of solar activity using different neural network models

    Directory of Open Access Journals (Sweden)

    F. Fessant

    Full Text Available Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These parameters rely strongly on solar activity. In this paper, we analyze the use of neural networks for sunspot time series prediction. Three types of models are tested and experimental results are reported for a particular sunspot time series: the IR5 index.

  19. 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.

  20. 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.

  1. 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

  2. Airport Gate Activity Monitoring Tool Suite for Improved Turnaround Prediction, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — The goal of this research is to create a suite of tools for monitoring airport gate activities with the objective of improving aircraft turnaround prediction....

  3. Interdecadal change of interannual variability and predictability of two types of ENSO using a MME method

    Science.gov (United States)

    Jeong, H. I.; Ahn, J. B.; Lee, J. Y.; Alessandri, A.; Hendon, H.

    2014-12-01

    A significant interdecadal climate shift of interannual variability and predictability of two types of the El Nino-Southern Oscillation (ENSO), namely the canonical or eastern Pacific (EP)-type and Modoki or central Pacific (CP) type, are investigated. Using the retrospective forecasts of six-state-of-the-art coupled models and their multi-model ensemble (MME) for December-January-February during the period of 1972-2005 along with corresponding observed and reanalyzed data, we examine the climate regime shift that occurred in the winter of 1988/1989 and how the shift affected interannual variability and predictability of two types of ENSO for the two periods of 1972-1988 (hereafter PRE) and 1989-2005 (hereafter POST). The result first shows substantial interdecadal changes of observed sea surface temperature (SST) in mean state and variability over the western and central Pacific attributable to the significant warming trend in the POST period. In the POST period, the SST variability increased (decreased) significantly over the western (eastern) Pacific. The MME realistically reproduces the observed interdecadal changes with 1- and 4-month forecast lead time. It is found that the CP-type ENSO was more prominent and predictable during the POST than the PRE period while there was no apparent difference in the variability and predictability of the EP-type ENSO between two periods. Note that the second empirical orthogonal function mode of the Pacific SST during the POST period represents the CP-type ENSO but that during the PRE period captures the ENSO transition phase. The MME better predicts the former than the latter. We also investigate distinctive regional impacts associated with the two types of ENSO during the two periods.

  4. Interdecadal change of interannual variability and predictability of two types of ENSO

    Science.gov (United States)

    Jeong, Hye-In; Ahn, Joong-Bae; Lee, June-Yi; Alessandri, Andrea; Hendon, Harry H.

    2015-02-01

    A significant interdecadal climate shift of interannual variability and predictability of two types of the El Niño-Southern Oscillation (ENSO), namely the canonical or eastern Pacific (EP)-type and Modoki or central Pacific (CP) type, are investigated. Using the retrospective forecasts of six-state-of-the-art coupled models and their multi-model ensemble (MME) for December-January-February during the period of 1972-2005 along with corresponding observed and reanalyzed data, we examine the climate regime shift that occurred in the winter of 1988/1989 and how the shift affected interannual variability and predictability of two types of ENSO for the two periods of 1972-1988 (hereafter PRE) and 1989-2005 (hereafter POST). The result first shows substantial interdecadal changes of observed sea surface temperature (SST) in mean state and variability over the western and central Pacific attributable to the significant warming trend in the POST period. In the POST period, the SST variability increased (decreased) significantly over the western (eastern) Pacific. The MME realistically reproduces the observed interdecadal changes with 1- and 4-month forecast lead time. It is found that the CP-type ENSO was more prominent and predictable during the POST than the PRE period while there was no apparent difference in the variability and predictability of the EP-type ENSO between two periods. Note that the second empirical orthogonal function mode of the Pacific SST during the POST period represents the CP-type ENSO but that during the PRE period captures the ENSO transition phase. The MME better predicts the former than the latter. We also investigate distinctive regional impacts associated with the two types of ENSO during the two periods.

  5. 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

  6. Does Perceived Racial Discrimination Predict Changes in Psychological Distress and Substance Use over Time? An Examination among Black Emerging Adults

    Science.gov (United States)

    Hurd, Noelle M.; Varner, Fatima A.; Caldwell, Cleopatra H.; Zimmerman, Marc A.

    2014-01-01

    We assessed whether perceived discrimination predicted changes in psychological distress and substance use over time and whether psychological distress and substance use predicted change in perceived discrimination over time. We also assessed whether associations between these constructs varied by gender. Our sample included 607 Black emerging…

  7. Developing and Testing a Model to Predict Outcomes of Organizational Change

    Science.gov (United States)

    Gustafson, David H; Sainfort, François; Eichler, Mary; Adams, Laura; Bisognano, Maureen; Steudel, Harold

    2003-01-01

    Objective To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. PMID:12785571

  8. Predicting River Macroinvertebrate Communities Distributional Shifts under Future Global Change Scenarios in the Spanish Mediterranean Area.

    Directory of Open Access Journals (Sweden)

    Javier Alba-Tercedor

    Full Text Available Several studies on global change over the next century predict increases in mean air temperatures of between 1°C to 5°C that would affect not only water temperature but also river flow. Climate is the predominant environmental driver of thermal and flow regimes of freshwater ecosystems, determining survival, growth, metabolism, phenology and behaviour as well as biotic interactions of aquatic fauna. Thus, these changes would also have consequences for species phenology, their distribution range, and the composition and dynamics of communities. These effects are expected to be especially severe in the Mediterranean basin due its particular climate conditions, seriously threatening Southern European ecosystems. In addition, species with restricted distributions and narrow ecological requirements, such as those living in the headwaters of rivers, will be severely affected. The study area corresponds to the Spanish Mediterranean and Balearic Islands, delimited by the Köppen climate boundary. With the application of the MEDPACS (MEDiterranean Prediction And Classification System predictive approach, the macroinvertebrate community was predicted for current conditions and compared with three posible scenarios of watertemperature increase and its associated water flow reductions. The results indicate that the aquatic macroinvertebrate communities will undergo a drastic impact, with reductions in taxa richness for each scenario in relation to simulated current conditions, accompanied by changes in the taxa distribution pattern. Accordingly, the distribution area of most of the taxa (65.96% inhabiting the mid-high elevations would contract and rise in altitude. Thus, families containing a great number of generalist species will move upstream to colonize new zones with lower water temperatures. By contrast, more vulnerable taxa will undergo reductions in their distribution area.

  9. The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems

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    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

  10. 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.

  11. Effects of predicted climatic changes on distribution of organic contaminants in brackish water mesocosms.

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    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.

  12. Changing patterns of microcalcification on screening mammography for prediction of breast cancer.

    Science.gov (United States)

    Kim, Kwan Il; Lee, Kyung Hee; Kim, Tae Ryung; Chun, Yong Soon; Lee, Tae Hoon; Choi, Hye Young; Park, Heung Kyu

    2016-05-01

    The presence of microcalcification on mammography is one of the earliest signs in breast cancer detection. However, it is difficult to distinguish malignant calcifications from benign calcifications. The aim of this study is to evaluate correlation between changing patterns of microcalcification on screening mammography and malignant breast lesions. Medical records and diagnostic images of 67 women who had previously undergone at least two digital mammograms at least 6 months apart and underwent mammography-guided needle localization and surgical excision between 2011 and 2013 were retrospectively reviewed and analyzed. Breast cancer was detected in the surgical specimens of 20 patients (29.9 %). Annual change of extent of microcalcification on mammography showed statistically significant correlation with pathologic outcome (P = 0.023). The changing pattern of new appearance or increased extent of microcalcification on mammography had positive predictive value of 54.8 % for breast cancer, and it was a statistically significant predictor for breast cancer (P = 0.012). Shape or number change of microcalcification without increased extent had less accurate predictive value for breast cancer, particularly in women younger than 50 years (P microcalcification on screening mammography was a significant predictor for breast cancer. We suggest that mammography-guided needle localization and surgical excision should be considered when increased extent of microcalcification is observed on screening mammography and closed follow-up without pathologic confirmation can be permitted if absence of extension of microcalcification was confirmed in women younger than 50 years.

  13. Prediction of Climate Change Induced Temperature & Precipitation: The Case of Iran

    Directory of Open Access Journals (Sweden)

    Samireh Saymohammadi

    2017-01-01

    Full Text Available Concern about the effects of climatic change on numerous aspects of human life in general and on agricultural production in particular is growing. The utility of HadCM3 as a tool in climate change predictions in cross cultural studies is scarce. Therefore, this study sought to investigate and predict climate change induced temperature and precipitation in Iran. The calibration and validation using the HadCM3 was performed during 1961–2001, using daily temperatures and precipitation. The data on temperature and precipitation from 1961 to 1990 were used for calibration, and, for model validation, data from 1991 to 2001 were used. Moreover, in order to downscale general circulation models to station scales, SDSM version 4.2 was utilized. The least difference between observed data and simulation data during calibration and validation showed that the parameter was precisely modeled for most of the year. Simulation under the A2 scenario was performed for three time periods (2020, 2050, and 2080. According to our simulated model, precipitation showed a decreasing trend whereas temperature showed an increasing trend. The result of this research paper makes a significant contribution to climate smart agriculture in Iran. For example, rural development practitioners can devise effective policies and programs in order to reduce the vulnerability of local communities to climate change impacts. Moreover, the result of this study can be used as an optimal model for land allocation in agriculture. Moreover, a shortage of rainfall and decreased temperatures also have implications for agricultural land allocation.

  14. 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

  15. 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...

  16. Predicting the Impact of Climate Change on Threatened Species in UK Waters

    Science.gov (United States)

    Jones, Miranda C.; Dye, Stephen R.; Fernandes, Jose A.; Frölicher, Thomas L.; Pinnegar, John K.; Warren, Rachel; Cheung, William W. L.

    2013-01-01

    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). PMID:23349829

  17. 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.

  18. 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.

  19. CHANGES IN QUADRICEPS MUSCLE ACTIVITY DURING SUSTAINED RECREATIONAL ALPINE SKIING

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    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

  20. Resting state amygdala-prefrontal connectivity predicts symptom change after cognitive behavioral therapy in generalized social anxiety disorder.

    Science.gov (United States)

    Klumpp, Heide; Keutmann, Michael K; Fitzgerald, Daniel A; Shankman, Stewart A; Phan, K Luan

    2014-01-01

    Aberrant amygdala-prefrontal interactions at rest and during emotion processing are implicated in the pathophysiology of generalized social anxiety disorder (gSAD), a common disorder characterized by fears of potential scrutiny. Cognitive behavioral therapy (CBT) is first-line psychotherapy for gSAD and other anxiety disorders. While CBT is generally effective, there is a great deal of heterogeneity in treatment response. To date, predictors of success in CBT for gSAD include reduced amygdala reactivity and increased activity in prefrontal regulatory regions (e.g., anterior cingulate cortex, "ACC") during emotion processing. However, studies have not examined whether tonic (i.e., at rest) coupling of amygdala and these prefrontal regions also predict response to CBT. Twenty-one patients with gSAD participated in resting-state functional magnetic resonance imaging (fMRI) before 12 weeks of CBT. Overall, symptom severity was significantly reduced after completing CBT; however, the patients varied considerably in degree of symptom change. Whole-brain voxel-wise findings showed symptom improvement after CBT was predicted by greater right amygdala-pregenual ACC ("pgACC") connectivity and greater left amygdala-pgACC coupling encompassing medial prefrontal cortex. In support of their predictive value, area under receiver operating characteristic curve was significant for the left and right amygdala-pgACC in relation to treatment responders. Improvement after CBT was predicted by enhanced resting-state bilateral amygdala-prefrontal coupling in gSAD. Preliminary results suggest baseline individual differences in a fundamental circuitry that may underlie emotion regulation contributed to variation in symptom change after CBT. Findings offer a new approach towards using a biological measure to foretell who will most likely benefit from CBT. In particular, the departure from neural predictors based on illness-relevant stimuli (e.g., socio-emotional stimuli in gSAD) permits

  1. 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.

  2. 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.

  3. Prediction of climate change in Brunei Darussalam using statistical downscaling model

    Science.gov (United States)

    Hasan, Dk. Siti Nurul Ain binti Pg. Ali; Ratnayake, Uditha; Shams, Shahriar; Nayan, Zuliana Binti Hj; Rahman, Ena Kartina Abdul

    2017-06-01

    Climate is changing and evidence suggests that the impact of climate change would influence our everyday lives, including agriculture, built environment, energy management, food security and water resources. Brunei Darussalam located within the heart of Borneo will be affected both in terms of precipitation and temperature. Therefore, it is crucial to comprehend and assess how important climate indicators like temperature and precipitation are expected to vary in the future in order to minimise its impact. This study assesses the application of a statistical downscaling model (SDSM) for downscaling General Circulation Model (GCM) results for maximum and minimum temperatures along with precipitation in Brunei Darussalam. It investigates future climate changes based on numerous scenarios using Hadley Centre Coupled Model, version 3 (HadCM3), Canadian Earth System Model (CanESM2) and third-generation Coupled Global Climate Model (CGCM3) outputs. The SDSM outputs were improved with the implementation of bias correction and also using a monthly sub-model instead of an annual sub-model. The outcomes of this assessment show that monthly sub-model performed better than the annual sub-model. This study indicates a satisfactory applicability for generation of maximum temperatures, minimum temperatures and precipitation for future periods of 2017-2046 and 2047-2076. All considered models and the scenarios were consistent in predicting increasing trend of maximum temperature, increasing trend of minimum temperature and decreasing trend of precipitations. Maximum overall trend of Tmax was also observed for CanESM2 with Representative Concentration Pathways (RCP) 8.5 scenario. The increasing trend is 0.014 °C per year. Accordingly, by 2076, the highest prediction of average maximum temperatures is that it will increase by 1.4 °C. The same model predicts an increasing trend of Tmin of 0.004 °C per year, while the highest trend is seen under CGCM3-A2 scenario which is 0.009

  4. 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.

  5. 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.

  6. Climate change and peripheral populations: predictions for a relict Mediterranean viper

    Directory of Open Access Journals (Sweden)

    José C. Brito

    2011-06-01

    Full Text Available Ecological niche-based models were developed in peripheral populations of Vipera latastei North Africa to: 1 identify environmental factors related to species occurrence; 2 identify present suitable areas; 3 estimate future areas according to forecasted scenarios of climate change; and 4 quantify habitat suitability changes between present and future climatic scenarios. Field observations were combined with environmental factors to derive an ensemble of predictions of species occurrence. The resulting models were projected to the future North African environmental scenarios. Species occurrence was most related to precipitation variation. Present suitable habitats were fragmented and ranged from coastal to mountain habitats, and the overall fragmented range suggests a relict distribution from wider past ranges. Future projections suggest a progressive decrease in suitable areas. The relationship with precipitation supports the current unsuitability of most North Africa for the species and predicts future increased extinction risk. Monitoring of population trends and full protection of mountain forests are key-targets for long-term conservation of African populations of this viper. Predicted trends may give indications about other peripheral populations of Palearctic vertebrates in North Africa which should be assessed in detail.

  7. Aggression Predicts Changes in Peer Victimization that Vary by Form and Function.

    Science.gov (United States)

    Frey, Karin S; Higheagle Strong, Zoe

    2018-02-01

    Peer victimization is predictive of serious problems in adjustment, especially among children who are both victimized and aggressive. This study investigated how different types of aggression contribute to later victimization. Specifically, we examined prospective relationships between the types of aggression that children perpetrated and the types that they experienced at the hands of others. Trained observers coded schoolyard behavior of 553 children in grades 3-6 during the initial year of a bullying intervention program. Both observed aggression and victimization were specified by form (direct, indirect) and function (proactive, reactive). Total hourly rates of victimization were highest in the upper grades. Direct-reactive aggression uniquely predicted increases in victimization, while direct-proactive aggression predicted decreases, particularly in direct-proactive victimization. Indirect-proactive aggression (e.g., derogatory gossip) predicted increases in indirect-proactive victimization only in the control group. Indirect-reactive aggression and victimization occurred too rarely to detect change. Aggression-victimization relationships did not differ for boys and girls. Discussion considers why children might risk direct reactive aggression in the face of increased victimization. Different sequelae for different forms and functions of aggression highlight the need to resolve theoretical ambiguities in defining proactive and reactive aggression.

  8. 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.

  9. Serial Change in Cervical Length for the Prediction of Emergency Cesarean Section in Placenta Previa.

    Science.gov (United States)

    Shin, Jae Eun; Shin, Jong Chul; Lee, Young; Kim, Sa Jin

    2016-01-01

    To evaluate whether serial change in cervical length (CL) over time can be a predictor for emergency cesarean section (CS) in patients with placenta previa. This was a retrospective cohort study of patients with placenta previa between January 2010 and November 2014. All women were offered serial measurement of CL by transvaginal ultrasound at 19 to 23 weeks (CL1), 24 to 28 weeks (CL2), 29 to 31 weeks (CL3), and 32 to 34 weeks (CL4). We compared clinical characteristics, serial change in CL, and outcomes between the emergency CS group (case group) and elective CS group (control group). The predictive value of change in CL for emergency CS was evaluated. A total of 93 women were evaluated; 31 had emergency CS due to massive vaginal bleeding. CL tended to decrease with advancing gestational age in each group. Until 29-31 weeks, CL showed no significant differences between the two groups, but after that, CL in the emergency CS group decreased abruptly, even though CL in the elective CS group continued to gradually decrease. On multivariate analysis to determine risk factors, only admissions for bleeding (odds ratio, 34.710; 95% CI, 5.239-229.973) and change in CL (odds ratio, 3.522; 95% CI, 1.210-10.253) were significantly associated with emergency CS. Analysis of the receiver operating characteristic curve showed that change in CL could be the predictor of emergency CS (area under the curve 0.734, p placenta previa. Women with change in CL more than 6 mm between the second and third trimester are at high risk of emergency CS in placenta previa. Single measurements of short CL at the second or third trimester do not seem to predict emergency CS.

  10. 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 6 years later. Hierarchical generalized linear mixed models examined the prospective association between optimism, cynical hostility, and vigorous PA over 6 years. 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.

  11. 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 s...... even stronger effects for more specialized plant-animal associations. Given the slow response time of woody plant distributions to climate change, current estimates of future biodiversity of many animal taxa may be both biased and too optimistic.......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...

  12. EFFICACY OF ACTIVATION PROCEDURES TO ILLUSTRATE EEG CHANGES IN EPILEPSY

    Directory of Open Access Journals (Sweden)

    Rimpy Bhuyan

    2017-04-01

    Full Text Available BACKGROUND EEG or Electroencephalogram, which is the most important diagnostic procedure to evaluate Epilepsy patients, may sometimes fall short of accurate sensitivity and may require few Activation Procedures such as ‘Hyperventilation’ and ‘Sleep’ to bring out the active changes of an Epileptic brain. The present study was done with the aim of knowing the efficacy of such Activation Procedures like ‘Hyperventilation’ and ‘Sleep’ in illustrating the EEG wave pattern changes of an Epileptic brain during the interictal period. MATERIALS AND METHODS The present study was done in the Department of Physiology in association with the Department of Neurology, Assam Medical College & Hospital, Dibrugarh, Assam from June 2014 to May 2015. ‘113’ clinically diagnosed cases of Epilepsy were studied and analysed through Electroencephalogram using the internationally accepted 10-20 electrode placement method. Hyperventilation was used in 28 Epilepsy cases and Sleep was used in 14 Epilepsy cases. History & Physical examination findings were recorded in a Proforma. Chi-square analysis was done through GraphPad Prism 6 software to assess the significance of the activation procedures used. RESULTS Our study found that EEG of 42 cases out of the total 113 cases required Activation Procedures to elicit the wave pattern changes of the Epileptic brain. Hyperventilation was helpful in adult age group and sleep was useful in children age group. Hyperventilation had overall 53.57% sensitivity in detecting Epilepsy, and Sleep had 64.29% sensitivity in detecting Epilepsy. Hyperventilation was specifically helpful to elicit absence seizures where it had 75% sensitivity. CONCLUSION The sensitivity of EEG in detecting Epilepsy can thus be increased by using activation procedures like sleep & Hyperventilation to ensure that no epilepsy cases are missed out in diagnosis & treatment.

  13. 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

  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. 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.

  16. Anti-glycated activity prediction of polysaccharides from two guava fruits using artificial neural networks.

    Science.gov (United States)

    Yan, Chunyan; Lee, Jinsheng; Kong, Fansheng; Zhang, Dezhi

    2013-10-15

    High-efficiency ultrasonic treatment was used to extract the polysaccharides of Psidium guajava (PPG) and Psidium littorale (PPL). The aims of this study were to compare polysaccharide activities from these two guavas, as well as to investigate the relationship between ultrasonic conditions and anti-glycated activity. A mathematical model of anti-glycated activity was constructed with the artificial neural network (ANN) toolbox of MATLAB software. Response surface plots showed the correlation between ultrasonic conditions and bioactivity. The optimal ultrasonic conditions of PPL for the highest anti-glycated activity were predicted to be 256 W, 60 °C, and 12 min, and the predicted activity was 42.2%. The predicted highest anti-glycated activity of PPG was 27.2% under its optimal predicted ultrasonic condition. The experimental result showed that PPG and PPL possessed anti-glycated and antioxidant activities, and those of PPL were greater. The experimental data also indicated that ANN had good prediction and optimization capability. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Family characteristics predicting favourable changes in 10 and 11-year-old children's lifestyle-related health behaviours during an 18-month follow-up.

    Science.gov (United States)

    Ray, Carola; Roos, Eva

    2012-02-01

    Lifestyle-related health behaviours such as screen time, physical activity, sleep duration, and food intake tend to change into non-favourable directions when children become young adolescents. Cross-sectional studies show that family characteristics are important determinants for children's health behaviours. This study examined whether family characteristics such as parenting practices at meals and family involvement predict a more favourable change in children's lifestyle-related health behaviours during an 18-month follow-up. 745 children in school grades 4 and 5 (response rate 65%) filled in a baseline questionnaire in the autumn of 2006. A follow-up was conducted in the spring of 2008 (91%). Several health behaviours had changed in a non-favourable direction. Baseline parenting practices at meals and family involvement predicted some of the changes in the lifestyle-related health behaviours in 2008. Parenting practices at meals predicted a smaller increase in TV, DVD viewing time, and a smaller decrease in fruit intake. Amongst family involvement determinants, less time alone at home after school predicted a smaller increase in screen time, a smaller decrease in sleep duration, and a smaller increase in soft drink intake. For conclusion several family characteristics predicted favourable changes in children's lifestyle-related health behaviours. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. 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.

  19. 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)

  20. 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)

  1. Strain Concentration at Structural Discontinuities and Its Prediction Based on Characteristics of Compliance Change in Structures

    Science.gov (United States)

    Kasahara, Naoto

    Elevated temperature structural design codes pay attention to strain concentration at structural discontinuities due to creep and plasticity, since it causes an increase in creep-fatigue damage of materials. One of the difficulties in predicting strain concentration is its dependence on the magnitude of loading, the constitutive equations, and the duration of loading. In this study, the author investigated the fundamental mechanism of strain concentration and its main factors. The results revealed that strain concentration is caused by strain redistribution between elastic and inelastic regions, which can be quantified by the characteristics of structural compliance. The characteristics of structural compliance are controlled by elastic region in structures and are insensitive to constitutive equations. It means that inelastic analysis can be easily applied to obtain compliance characteristics. By utilizing this fact, a simplified inelastic analysis method was proposed based on the characteristics of compliance change for the prediction of strain concentration.

  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. Eating disorders, menstrual dysfunction, weight change and DMPA use predict bone density change in college-aged women.

    Science.gov (United States)

    Nieves, Jeri W; Ruffing, Jamie A; Zion, Marsha; Tendy, Susan; Yavorek, Trudy; Lindsay, Robert; Cosman, Felicia

    2016-03-01

    There are limited longitudinal studies that have evaluated bone mineral density (BMD) changes in college-aged women. Our objective was to simultaneously evaluate factors influencing 4-year BMD change. This was a longitudinal cohort study of healthy, physically active women in the US Military Academy (n=91; average age=18.4years). Assessments over four years included: height, weight, calcium intake, physical fitness, menstrual function (annual number cycles), oral contraceptives (OCs) or depot-medroxyprogesterone acetate (DMPA) use, and eating disorder behavior (Eating Disorder Inventory; (EDI)). BMD was measured annually at the lumbar spine and total hip by dual X-ray absorptiometry and calcaneal BMD by PIXI. Slope of 4year BMD change at each skeletal site (spine total hip and calcaneus) was calculated for each woman. BMD gains occurred at the spine in 50% and the hip in 36% of women. In unadjusted analyses, spine bone gain was positively related to menstrual cycle frequency (p=0.04). Spine and hip BMD loss occurred in those using DMPA (peating disorders, weight loss, menstrual dysfunction and DMPA use can have significant detrimental effects on BMD in young healthy physically active women. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Plant physiological models of heat, water and photoinhibition stress for climate change modelling and agricultural prediction

    Science.gov (United States)

    Nicolas, B.; Gilbert, M. E.; Paw U, K. T.

    2015-12-01

    Soil-Vegetation-Atmosphere Transfer (SVAT) models are based upon well understood steady state photosynthetic physiology - the Farquhar-von Caemmerer-Berry model (FvCB). However, representations of physiological stress and damage have not been successfully integrated into SVAT models. Generally, it has been assumed that plants will strive to conserve water at higher temperatures by reducing stomatal conductance or adjusting osmotic balance, until potentially damaging temperatures and the need for evaporative cooling become more important than water conservation. A key point is that damage is the result of combined stresses: drought leads to stomatal closure, less evaporative cooling, high leaf temperature, less photosynthetic dissipation of absorbed energy, all coupled with high light (photosynthetic photon flux density; PPFD). This leads to excess absorbed energy by Photosystem II (PSII) and results in photoinhibition and damage, neither are included in SVAT models. Current representations of photoinhibition are treated as a function of PPFD, not as a function of constrained photosynthesis under heat or water. Thus, it seems unlikely that current models can predict responses of vegetation to climate variability and change. We propose a dynamic model of damage to Rubisco and RuBP-regeneration that accounts, mechanistically, for the interactions between high temperature, light, and constrained photosynthesis under drought. Further, these predictions are illustrated by key experiments allowing model validation. We also integrated this new framework within the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). Preliminary results show that our approach can be used to predict reasonable photosynthetic dynamics. For instances, a leaf undergoing one day of drought stress will quickly decrease its maximum quantum yield of PSII (Fv/Fm), but it won't recover to unstressed levels for several days. Consequently, cumulative effect of photoinhibition on photosynthesis can cause

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. New Approaches for Crop Genetic Adaptation to the Abiotic Stresses Predicted with Climate Change

    Directory of Open Access Journals (Sweden)

    Robert Redden

    2013-05-01

    Full Text Available Extreme climatic variation is predicted with climate change this century. In many cropping regions, the crop environment will tend to be warmer with more irregular rainfall and spikes in stress levels will be more severe. The challenge is not only to raise agricultural production for an expanding population, but to achieve this under more adverse environmental conditions. It is now possible to systematically explore the genetic variation in historic local landraces by using GPS locators and world climate maps to describe the natural selection for local adaptation, and to identify candidate germplasm for tolerances to extreme stresses. The physiological and biochemical components of these expressions can be genomically investigated with candidate gene approaches and next generation sequencing. Wild relatives of crops have largely untapped genetic variation for abiotic and biotic stress tolerances, and could greatly expand the available domesticated gene pools to assist crops to survive in the predicted extremes of climate change, a survivalomics strategy. Genomic strategies can assist in the introgression of these valuable traits into the domesticated crop gene pools, where they can be better evaluated for crop improvement. The challenge is to increase agricultural productivity despite climate change. This calls for the integration of many disciplines from eco-geographical analyses of genetic resources to new advances in genomics, agronomy and farm management, underpinned by an understanding of how crop adaptation to climate is affected by genotype × environment interaction.

  11. 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.

  12. 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.

  13. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism.

    Science.gov (United States)

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L; Kenworthy, Lauren; Martin, Alex

    2015-12-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome--adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement.

  14. Promoting physical activity and reducing climate change: opportunities to replace short car trips with active transportation.

    Science.gov (United States)

    Maibach, Edward; Steg, Linda; Anable, Jillian

    2009-10-01

    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 cycling--or with public transportation. In this commentary, we review a number of immediate, practical opportunities to implement policies and programs that reduce short car trips and increase active transportation.

  15. 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.

  16. 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

  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. 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.

  19. 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

  20. The ability of early changes in motivation to predict later antidepressant treatment response

    Directory of Open Access Journals (Sweden)

    Gorwood P

    2015-11-01

    Full Text Available Philip Gorwood,1,2 Guillaume Vaiva,3 Emmanuelle Corruble,4 Pierre-Michel Llorca,5 Franck J Baylé,1,2 Philippe Courtet61Centre Hospitalier Sainte-Anne (CMME, Paris, France; 2Centre of Psychiatry and Neuroscience, INSERM U894, University Paris-Descartes, Paris, France; 3Pôle de Psychiatrie, CHRU de Lille, Hôpital Michel-Fontan, Université Lille-Nord de France, Lille, France; 4Psychiatry Department of Bicêtre, University Hospital, INSERM U669, Paris XI University, Le Kremlin Bicêtre, France; 5CHU Clermont-Ferrand, Clermont Université, Université d’Auvergne, Clermont-Ferrand, France; 6Department of Emergency Psychiatry, CHU Montpellier, Montpellier, FranceIntroduction: Baseline values and early changes of emotional reactivity, cognitive speed, psychomotor function, motivation, and sensory perception have not been studied to any extent in unipolar depression, although they could help to characterize different dimensions of illness that are harder to capture by clinicians, give new insights on how patients improve, and offer new early clinical markers for later treatment response.Methods: About 1,565 adult outpatients with major depressive disorder receiving agomelatine completed the clinician-rated 16-item quick inventory of depressive symptoms, Clinical Global Impression, and Multidimensional Assessment of Thymic States (MAThyS rating scales at inclusion, Week 2 and Week 6. The MAThyS includes a 20-item self-rated visual analog scale (from inhibition [0] to activation [10], with [5] representing the usual state leading to five a priori dimensions (emotional reactivity, cognitive speed, psychomotor function, motivation, and sensory perception.Results: All MAThyS dimension scores increased from inclusion to Week 2 and from inclusion to Week 6 (P<0.001. Improvement was around 2 points (out of 10 for motivation, 1.5 points for psychomotor function, and 0.5 points for other dimensions. Motivation showed a trend to being more severely impaired

  1. 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

  2. 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

  3. Climate change, phenological shifts, eco-evolutionary responses and population viability: toward a unifying predictive approach.

    Science.gov (United States)

    Jenouvrier, Stéphanie; Visser, Marcel E

    2011-11-01

    The debate on emission targets of greenhouse gasses designed to limit global climate change has to take into account the ecological consequences. One of the clearest ecological consequences is shifts in phenology. Linking these shifts to changes in population viability under various greenhouse gasses emission scenarios requires a unifying framework. We propose a box-in-a-box modeling approach that couples population models to phenological change. This approach unifies population modeling with both ecological responses to climate change as well as evolutionary processes. We advocate a mechanistic embedded correlative approach, where the link from genes to population is established using a periodic matrix population model. This periodic model has several major advantages: (1) it can include complex seasonal behaviors allowing an easy link with phenological shifts; (2) it provides the structure of the population at each phase, including the distribution of genotypes and phenotypes, allowing a link with evolutionary processes; and (3) it can incorporate the effect of climate at different time periods. We believe that the way climatologists have approached the problem, using atmosphere-ocean coupled circulation models in which components are gradually included and linked to each other, can provide a valuable example to ecologists. We hope that ecologists will take up this challenge and that our preliminary modeling framework will stimulate research toward a unifying predictive model of the ecological consequences of climate change.

  4. 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).

  5. 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.

  6. 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

  7. 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...

  8. 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

  9. 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

  10. 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.

  11. 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...

  12. Health Impacts of Increased Physical Activity from Changes in Transportation Infrastructure: Quantitative Estimates for Three Communities.

    Science.gov (United States)

    Mansfield, Theodore J; MacDonald Gibson, Jacqueline

    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