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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. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    National Research Council Canada - National Science Library

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    .... The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer...

  5. Repetition related changes in activation and functional connectivity in hippocampus predict subsequent memory.

    Science.gov (United States)

    Manelis, Anna; Paynter, Christopher A; Wheeler, Mark E; Reder, Lynne M

    2013-01-01

    Using fMRI, this study examined the relationship between repetition-related changes in the medial temporal lobe (MTL) activation during encoding and subsequent memory for similarity of repetitions. During scanning, subjects classified pictures of objects as natural or man-made. Each object-type was judged twice with presentations of either identical pictures or pictures of different exemplars of the same object. After scanning, a surprise recognition test required subjects to decide whether a probe word corresponded to pictures judged previously. When a subject judged the word as "old," a second judgment was made concerning the physical similarity of the two pictures. Repetition related changes in MTL activation varied depending on whether or not subjects could correctly state that pictures were different. Moreover, psychophysiological interactions analyses showed that accuracy in recalling whether the two pictures were different was predicted by repetition-related changes in the functional connectivity of MTL with frontal regions. Specifically, correct recollection was predicted by increased connectivity between the left posterior hippocampus and the right inferior frontal gyrus, and also by decreased connectivity between the left posterior hippocampus and the left precentral gyrus on the second stimulus presentation. The opposite pattern was found for trials that were incorrectly judged on the nature of the repetition. These results suggest that successful encoding is predicted by a combination of increases and decreases in both the MTL activation and functional connectivity, and not merely by increases in activation and connectivity as suggested previously. Copyright © 2012 Wiley Periodicals, Inc.

  6. 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.

  7. Identifying combinations of risk and protective factors predicting physical activity change in high school students.

    Science.gov (United States)

    Dunton, Genevieve Fridlund; Atienza, Audie A; Tscherne, James; Rodriguez, Daniel

    2011-02-01

    Research sought to identify combinations of risk and protective factors predicting change in physical activity (PA) over one year in high school students. Adolescents (N = 344; M = 15.7 years) participated in a longitudinal study with assessment of demographics, substance use/smoking exposure, height and weight, psychological factors, and PA in 10th and 11th grade. PA participation in 11th grade was greatest for adolescents who engaged in PA and had high sports competence (78%), and least for adolescents who did not engage in or enjoy PA (13%) in 10th grade. Identifying adolescent subgroups at risk for decreasing PA can inform the development of tailored interventions.

  8. Organized Physical Activity in Young School Children Predicts Subsequent 4-Year Change in Body Mass Index

    Science.gov (United States)

    Dunton, Genevieve; McConnell, Rob; Jerrett, Michael; Wolch, Jennifer; Lam, Claudia; Gilliland, Frank; Berhane, Kiros

    2012-01-01

    Objective To determine whether participation in organized outdoor team sports and structured indoor non-school activity programs in kindergarten and first grade predicted subsequent 4-year change in Body Mass Index (BMI) across the adiposity rebound period of childhood. Design Longitudinal cohort study. Setting Forty-five schools in 13 communities across Southern California. Participants Largely Hispanic and non-Hispanic white children (N = 4,550; average age at study entry 6.60 years, standard deviation 0.65). Main Exposures Parents completed questionnaires assessing physical activity, demographic characteristics and other relevant covariates at baseline. Data on built and social environmental variables were linked to the neighborhood around children’s homes using geographical information systems (GIS). Main Outcome Measures Each child’s height and weight were measured annually during 4-years of follow-up. Results After adjusting for several confounders, BMI increased at a 0.05 unit per year slower rate for children who participated in outdoor organized team sports at least twice per week as compared to children who did not. For participation in each additional indoor non-school structured activity classes, lessons, and program, BMI increased at a 0.05 unit per year slower rate, and the attained BMI level at age 10 was 0.48 units lower. Conclusions Engagement in organized sports and activity programs as early as kindergarten and the first grade may result in smaller increases in BMI during the adiposity rebound period of childhood. PMID:22869403

  9. Does physical activity change predict functional recovery in low back pain? Protocol for a prospective cohort study

    Directory of Open Access Journals (Sweden)

    McDonough Suzanne M

    2009-11-01

    Full Text Available Abstract Background Activity advice and prescription are commonly used in the management of low back pain (LBP. Although there is evidence for advising patients with LBP to remain active, facilitating both recovery and return to work, to date no research has assessed whether objective measurements of free living physical activity (PA can predict outcome, recovery and course of LBP. Methods An observational longitudinal study will investigate PA levels in a cohort of community-dwelling working age adults with acute and sub-acute LBP. Each participant's PA level, functional status, mood, fear avoidance behaviours, and levels of pain, psychological distress and occupational activity will be measured on three occasions during for 1 week periods at baseline, 3 months, and 1 year. Physical activity levels will be measured by self report, RT3 triaxial accelerometer, and activity recall questionnaires. The primary outcome measure of functional recovery will be the Roland Morris Disability Questionnaire (RMDQ. Free living PA levels and changes in functional status will be quantified in order to look at predictive relationships between levels and changes in free living PA and functional recovery in a LBP population. Discussion This research will investigate levels and changes in activity levels of an acute LBP cohort and the predictive relationship to LBP recovery. The results will assess whether occupational, psychological and behavioural factors affect the relationship between free living PA and LBP recovery. Results from this research will help to determine the strength of evidence supporting international guidelines that recommend restoration of normal activity in managing LBP. Trial registration [Clinical Trial Registration Number, ACTRN12609000282280

  10. Physical activity predicts changes in body image during obesity treatment in women.

    Science.gov (United States)

    Carraça, Eliana V; Markland, David; Silva, Marlene N; Coutinho, Sílvia R; Vieira, Paulo N; Minderico, Cláudia S; Sardinha, Luís B; Teixeira, Pedro J

    2012-08-01

    This study examined effects of a behavioral weight management intervention on body image (evaluative and investment dimensions) and explored the potential mediating role of structured and lifestyle physical activity (PA). The study was a longitudinal randomized controlled trial, including a 1-yr behavior change intervention and a 2-yr follow-up (225 women, 37.6 ± 7 yr, body mass index = 31.5 ± 4.1 kg·m). Statistical analyses comprised mixed-design ANOVAs with repeated measures, bivariate/partial correlations, and mediation analyses. Body image improved considerably in both groups, favoring the intervention group (small to moderate effect sizes: 0.03-0.05), but began to deteriorate from 12 to 24 months, especially in the intervention group. Consequently, at 24 months, between-group differences were small and did not reach significance. Yet, levels of body dissatisfaction and dysfunctional investment remained below initial values (for both groups). Results were similar for both body image dimensions. Structured PA (at 12 and 24 months) and lifestyle PA (at 24 months) were positively associated with (r > -0.25, P body image improvements, especially in the investment component (95% confidence interval of -1.88 to -0.27 for structured PA at 12 months, 95% confidence interval of -1.94 to -0.21 for lifestyle PA at 24 months). In general, change in evaluative body image was not mediated by exercise participation, seeming more dependent on weight change. These findings highlight the importance of PA as a contributing factor in the improvement of body image in overweight/obese women, mainly by reducing excessive salience of appearance to one's life and self. Lifestyle PA may also be a valid option, particularly in the long term. Exercise might provide a buffer against body image deterioration overtime, favoring lasting weight loss maintenance.

  11. Physical Activity Related to Depression and Predicted Mortality Risk: Results from the Americans' Changing Lives Study

    Science.gov (United States)

    Lee, Pai-Lin; Lan, William; Lee, Charles C.-L.

    2012-01-01

    This study examined the association between three types of physical activities (PA) and depression, and the relationship between PA and later mortality. Previous studies rarely assessed these associations in one single study in randomly selected population samples. Few studies have assessed these relations by adjusting the covariate of…

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

    Science.gov (United States)

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

    2009-01-01

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

  13. 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...

  14. Volcanic activity and climatic changes.

    Science.gov (United States)

    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.

  15. Predicting change in physical activity, dietary restraint, and physique anxiety in adolescent girls: examining covariance in physical self-perceptions.

    Science.gov (United States)

    Crocker, Peter; Sabiston, Catherine; Forrestor, Shannon; Kowalski, Nanette; Kowalski, Kent; McDonough, Meghan

    2003-01-01

    To examine: i) the mean changes in adolescent females' body mass index (BMI), global self-esteem, physical self-perceptions, social physique anxiety, physical activity, and dietary restraint; ii) the stability of measuring self-perceptions, BMI, self-esteem, physique anxiety, activity, and dietary restraint; and iii) the relationships among changes in these variables over 12 months. 631 female adolescents (15-16 years old) involved in a two-year study of self-report measures completed validated questionnaires in high school classroom settings. There were small but significant group increases in BMI and social physique anxiety and significant decreases in sport, conditioning, and strength physical self-perceptions and physical activity. Stability analysis indicates moderate to strong stability for all variables. Change analyses indicated that BMI, due to its high stability, is a poor predictor of change in all variables. Stronger significant correlations were noted between change in body appearance self-perceptions and change in social physique anxiety (r=-0.54) and dietary restraint (r=-0.27). There was also a significant relationship between change in physical activity and the physical self-perceptions, although conditioning was the only significant (pphysique anxiety compared to BMI. This demonstrates the importance of physical self-perceptions when investigating health-related behaviours associated with dieting and physical activity. The decline in physical activity and increase in BMI is an ongoing concern, as is the link between body appearance self-perceptions and dietary restraint and social physique anxiety.

  16. 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

  17. 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.

  18. Adding items that assess changes in activities of daily living does not improve the predictive accuracy of the Palliative Prognostic Index.

    Science.gov (United States)

    Hamano, Jun; Tokuda, Yasuharu; Kawagoe, Shohei; Shinjo, Takuya; Shirayama, Hiroto; Ozawa, Taketoshi; Shishido, Hideki; Otomo, Sen; Nagayama, Jun; Baba, Mika; Tei, Yo; Hiramoto, Shuji; Suga, Akihiko; Hisanaga, Takayuki; Ishihara, Tatsuhiko; Iwashita, Tomoyuki; Kaneishi, Keisuke; Kuriyama, Toshiyuki; Maeda, Takashi; Morita, Tatsuya

    2017-03-01

    Changes in activities of daily living in cancer patients may predict their survival. The Palliative Prognostic Index is a useful tool to evaluate cancer patients, and adding an item about activities of daily living changes might improve its predictive value. To clarify whether adding an item about activities of daily living changes improves the accuracy of Palliative Prognostic Index. Multicenter prospective cohort study. A total of 58 palliative care services in Japan. Patients aged >20 years diagnosed with locally extensive or metastatic cancer (including hematological neoplasms) who had been admitted to palliative care units, were receiving care by hospital-based palliative care teams, or were receiving home-based palliative care. Palliative care physicians recorded clinical variables at the first assessment and followed up patients 6 months later. A total of 2425 subjects were recruited and 2343 of these had analyzable data. The C-statistic of the original Palliative Prognostic Index was 0.801, and those of modified Palliative Prognostic Indices ranged from 0.793 to 0.805 at 3 weeks. For 6-week survival predictions, the C-statistic of the original Palliative Prognostic Index was 0.802, and those of modified Palliative Prognostic Indices ranged from 0.791 to 0.799. The weighted kappa of the original Palliative Prognostic Index was 0.510, and those of modified Palliative Prognostic Indices ranged from 0.484 to 0.508. Adding items about activities of daily living changes to the Palliative Prognostic Index did not improve prognostic value in advanced cancer patients.

  19. 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.

  20. Predicting Change in Physical Activity, Dietary Restraint, and Physique Anxiety in Adolescent Girls: Examining Covariance in Physical Self-perceptions

    National Research Council Canada - National Science Library

    Peter Crocker; Catherine Sabiston; Shannon Forrestor; Nanette Kowalski; Kent Kowalski; Meghan McDonough

    2003-01-01

    ...: There were small but significant group increases in BMI and social physique anxiety and significant decreases in sport, conditioning, and strength physical self-perceptions and physical activity...

  1. Prediction of clinical change by ethological methods.

    Science.gov (United States)

    Bouhuys, A L; Beersma, D G; Van den Hoofdakker, R H

    1988-01-01

    The aim of this paper is to show that ethology may contribute to the search for early indicators of clinical changes in depression. Three studies are presented. One study deals with the prediction of treatment outcome over 10 weeks and the other two with the prediction of the acute clinical response to total sleep deprivation (TSD). In each study a number of behaviours were observed, as displayed during a baseline psychiatric interview by the patients as well as the psychiatrist. In this report, the predictive potency of directly observed behaviours is compared to the predictive value of global clinical measures of psychomotor activation. The behaviours of the patients were interpreted as "relational" and "nonrelational" behaviours. The relational behaviours (i.e., variation in looking, yes-nodding, gesturing) occurred less, the nonrelational behaviours (i.e., intensive body touching, head movements) occurred more in responders than in nonresponders to 10 weeks of treatment. Also in the TSD studies body touching was positively related to improvement. Global clinical assessment of psychomotor activation could not be related to outcome. The advantages of the observational methods are discussed.

  2. 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

  3. 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...

  4. Towards Prediction of Environmental Arctic Change

    National Research Council Canada - National Science Library

    Maslowski, Wieslaw

    2004-01-01

    Our main objective is to use models of the coupled ice-ocean Arctic environment to understand the past and present sea ice and ocean states and to predict future scenarios of environmental change in the Arctic Ocean...

  5. 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...

  6. 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 ...

  7. 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.

  8. Social support and physical activity as moderators of life stress in predicting baseline depression and change in depression over time in the Women's Health Initiative.

    Science.gov (United States)

    Uebelacker, Lisa A; Eaton, Charles B; Weisberg, Risa; Sands, Megan; Williams, Carla; Calhoun, Darren; Manson, Joann E; Denburg, Natalie L; Taylor, Teletia

    2013-12-01

    To determine whether social support and/or physical activity buffer the association between stressors and increasing risk of depression symptoms at baseline and at 3-year follow-up. This is a secondary analysis of data from the Women's Health Initiative Observational Study. 91,912 community-dwelling post-menopausal women participated in this prospective cohort study. Depression symptoms were measured at baseline and 3 years later; social support, physical activity, and stressors were measured at baseline. Stressors at baseline, including verbal abuse, physical abuse, caregiving, social strain, negative life events, financial stress, low income, acute pain, and a greater number of chronic medical conditions, were all associated with higher levels of depression symptoms at baseline and new onset elevated symptoms at 3-year follow-up. Social support and physical activity were associated with lower levels of depressive symptoms. Contrary to expectation, more social support at baseline strengthened the association between concurrent depression and physical abuse, social strain, caregiving, and low income. Similarly, more social support at baseline increased the association between financial stress, income, and pain on new onset depression 3 years later. Physical activity similarly moderated the effect of caregiving, income, and pain on depression symptoms at baseline. Stressors, social support, and physical activity showed predicted main effect associations with depression. Multiplicative interactions were small in magnitude and in the opposite direction of what was expected.

  9. Predicting Physical Activity Promotion in Health Care Settings.

    Science.gov (United States)

    Faulkner, Guy; Biddle, Stuart

    2001-01-01

    Tested the theory of planned behavior's (TPB) ability to predict stage of change for physical activity promotion among health professionals. Researchers measured attitudes, subjective norms, intentions, perceived behavioral control, and stage of change, then later reassessed stage of change. TPB variables of attitude, subjective norms, perceived…

  10. 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. .

  11. 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

  12. Predicted Biological Activity of Purchasable Chemical Space.

    Science.gov (United States)

    Irwin, John J; Gaskins, Garrett; Sterling, Teague; Mysinger, Michael M; Keiser, Michael J

    2017-12-29

    Whereas 400 million distinct compounds are now purchasable within the span of a few weeks, the biological activities of most are unknown. To facilitate access to new chemistry for biology, we have combined the Similarity Ensemble Approach (SEA) with the maximum Tanimoto similarity to the nearest bioactive to predict activity for every commercially available molecule in ZINC. This method, which we label SEA+TC, outperforms both SEA and a naïve-Bayesian classifier via predictive performance on a 5-fold cross-validation of ChEMBL's bioactivity data set (version 21). Using this method, predictions for over 40% of compounds (>160 million) have either high significance (pSEA ≥ 40), high similarity (ECFP4MaxTc ≥ 0.4), or both, for one or more of 1382 targets well described by ligands in the literature. Using a further 1347 less-well-described targets, we predict activities for an additional 11 million compounds. To gauge whether these predictions are sensible, we investigate 75 predictions for 50 drugs lacking a binding affinity annotation in ChEMBL. The 535 million predictions for over 171 million compounds at 2629 targets are linked to purchasing information and evidence to support each prediction and are freely available via https://zinc15.docking.org and https://files.docking.org .

  13. 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,

  14. 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

  15. Active machine learning for transmembrane helix prediction

    Science.gov (United States)

    2010-01-01

    Background About 30% of genes code for membrane proteins, which are involved in a wide variety of crucial biological functions. Despite their importance, experimentally determined structures correspond to only about 1.7% of protein structures deposited in the Protein Data Bank due to the difficulty in crystallizing membrane proteins. Algorithms that can identify proteins whose high-resolution structure can aid in predicting the structure of many previously unresolved proteins are therefore of potentially high value. Active machine learning is a supervised machine learning approach which is suitable for this domain where there are a large number of sequences but only very few have known corresponding structures. In essence, active learning seeks to identify proteins whose structure, if revealed experimentally, is maximally predictive of others. Results An active learning approach is presented for selection of a minimal set of proteins whose structures can aid in the determination of transmembrane helices for the remaining proteins. TMpro, an algorithm for high accuracy TM helix prediction we previously developed, is coupled with active learning. We show that with a well-designed selection procedure, high accuracy can be achieved with only few proteins. TMpro, trained with a single protein achieved an F-score of 94% on benchmark evaluation and 91% on MPtopo dataset, which correspond to the state-of-the-art accuracies on TM helix prediction that are achieved usually by training with over 100 training proteins. Conclusion Active learning is suitable for bioinformatics applications, where manually characterized data are not a comprehensive representation of all possible data, and in fact can be a very sparse subset thereof. It aids in selection of data instances which when characterized experimentally can improve the accuracy of computational characterization of remaining raw data. The results presented here also demonstrate that the feature extraction method of TMpro

  16. 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 ...

  17. Prediction technologies for assessment of climate change impacts

    Science.gov (United States)

    Temperatures, precipitation, and weather patterns are changing, in response to increasing carbon dioxide in the atmosphere. With these relatively rapid changes, existing soil erosion prediction technologies that rely upon climate stationarity are potentially becoming less reliable. This is especiall...

  18. 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 ...

  19. 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.

  20. Relationship between efficiency and predictability in stock price change

    Science.gov (United States)

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

    2008-09-01

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

  1. Predicting postoperative haemoglobin changes after burn surgery

    African Journals Online (AJOL)

    Burn surgery is associated with significant peri-operative haemoglobin. (Hb) changes. During surgery, blood loss mainly occurs owing to wound debridement and skin harvesting. However, administration of clear fluid, required to maintain intravascular volume status during anaesthesia and surgery, leads to haemodilution ...

  2. Predicting Stages of Change in Battered Women

    Science.gov (United States)

    Alexander, Pamela C.; Tracy, Allison; Radek, Megan; Koverola, Catherine

    2009-01-01

    Battered women's stages of change (SOCs) are examined in this study. First, confirmatory factor analysis and latent profile analysis were conducted on 754 battered women's responses on the Problems in Relationship Scale (Brown, 1998). Factor loadings were strong, and latent variable mixture modeling produces a two-class solution. Second,…

  3. Resting alpha activity predicts learning ability in alpha neurofeedback

    Science.gov (United States)

    Wan, Feng; Nan, Wenya; Vai, Mang I.; Rosa, Agostinho

    2014-01-01

    Individuals differ in their ability to learn how to regulate the brain activity by neurofeedback. This study aimed to investigate whether the resting alpha activity can predict the learning ability in alpha neurofeedback. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback and the learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback. PMID:25071528

  4. CERAPP: Collaborative estrogen receptor activity prediction project

    DEFF Research Database (Denmark)

    Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra

    2016-01-01

    Background: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER......). 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...

  5. Resting alpha activity predicts learning ability in alpha neurofeedback

    Directory of Open Access Journals (Sweden)

    Wenya eNan

    2014-07-01

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

  6. 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…

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

    Directory of Open Access Journals (Sweden)

    Naomi J Fox

    2011-01-01

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

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

    Science.gov (United States)

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

    2011-01-10

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

  9. 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.

  10. Learning-based approach for online lane change intention prediction

    OpenAIRE

    Kumar, P.; Perrollaz, Mathias; Lefèvre, Stéphanie; Laugier, Christian

    2013-01-01

    International audience; Predicting driver behavior is a key component for Advanced Driver Assistance Systems (ADAS). In this paper, a novel approach based on Support Vector Machine and Bayesian filtering is proposed for online lane change intention prediction. The approach uses the multiclass probabilistic outputs of the Support Vector Machine as an input to the Bayesian filter, and the output of the Bayesian filter is used for the final prediction of lane changes. A lane tracker integrated in a ...

  11. Predicting extinctions as a result of climate change

    Science.gov (United States)

    Mark W. Schwartz; Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Raymond J. O' Connor; Raymond J. O' Connor

    2006-01-01

    Widespread extinction is a predicted ecological consequence of global warming. Extinction risk under climate change scenarios is a function of distribution breadth. Focusing on trees and birds of the eastern United States, we used joint climate and environment models to examine fit and climate change vulnerability as a function of distribution breadth. We found that...

  12. Platelet serotonin transporter function predicts default-mode network activity.

    Directory of Open Access Journals (Sweden)

    Christian Scharinger

    Full Text Available The serotonin transporter (5-HTT is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence.A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (Vmax was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD activity and platelet Vmax.The present study demonstrates that increases in platelet Vmax significantly predict default-mode network (DMN suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet Vmax is related to global DMN activation and not intrinsic DMN connectivity.This study provides evidence that platelet Vmax predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal Vmax coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation.

  13. Anthropocene changes in desert area: Sensitivity to climate model predictions

    Science.gov (United States)

    Mahowald, N.

    2007-12-01

    Changes in desert area due to humans have important implications from a local, regional to global level. Here we focus on the latter in order to better understand estimated changes in desert dust aerosols and the associated iron deposition into oceans. Using 17 model simulations from the World Climate Research Programme's Coupled Model Intercomparison Project phase 3 multi-model dataset and the BIOME4 equilibrium vegetation model we estimate changes in desert dust source areas due to climate change and carbon dioxide fertilization. If we assume no carbon dioxide fertilization, the mean of the model predictions is that desert areas expand from the 1880s to the 2080s, due to increased aridity. If we allow for carbon dioxide fertilization, the desert areas become smaller. Thus better understanding carbon dioxide fertilization is important for predicting desert response to climate. There is substantial spread in the model simulation predictions for regional and global averages.

  14. 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

  15. Estuarine shoreline and sandline change model skill and predicted probabilities

    Science.gov (United States)

    Smith, Kathryn E. L.; Passeri, Davina; Plant, Nathaniel G.

    2016-01-01

    The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline and sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and event-driven (Hurricane Sandy) estuarine back-barrier shoreline and overwash (sandline) change. Input variables were constructed into a Bayesian Network (BN) using Netica. To evaluate the ability of the BN to reproduce the observations used to train the model, the skill, log likelihood ratio and probability predictions were utilized. These data are the probability and skill metrics for all four models: the long-term (LT) back-barrier shoreline change, event-driven (HS) back-barrier shoreline change, long-term (LT) sandline change, and event-driven (HS) sandline change.

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

    Directory of Open Access Journals (Sweden)

    Hector Galbraith

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

  17. Genetically informed ecological niche models improve climate change predictions.

    Science.gov (United States)

    Ikeda, Dana H; Max, Tamara L; Allan, Gerard J; Lau, Matthew K; Shuster, Stephen M; Whitham, Thomas G

    2017-01-01

    We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change. © 2016 John Wiley & Sons Ltd.

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

    Science.gov (United States)

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

    2007-01-01

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

  19. Fragmentation and stability of circadian activity rhythms predict mortality : the rotterdam study

    NARCIS (Netherlands)

    Zuurbier, Lisette A; Luik, Annemarie I; Hofman, Albert; Franco, Oscar H; Van Someren, Eus J W; Tiemeier, Henning

    2015-01-01

    Circadian rhythms and sleep patterns change as people age. Little is known about the associations between circadian rhythms and mortality rates. We investigated whether 24-hour activity rhythms and sleep characteristics independently predicted mortality. Actigraphy was used to determine the

  20. 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

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

    African Journals Online (AJOL)

    2012-04-13

    Apr 13, 2012 ... 4School of the Environment, Flinders University, GPO Box 2100, Adelaide SA 5001, Australia. ABSTRACT. Land use ... images from 1984, 1992, 2002, and 2008, and to predict the impact of these land use changes on groundwater recharge. For .... Depending on climate, vegetation is a strong determining ...

  2. 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 ...

  3. 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).

  4. Decision support system for predicting color change after tooth whitening.

    Science.gov (United States)

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  5. 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

  6. 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.

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

    Science.gov (United States)

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

    2013-05-29

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  9. 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

  10. 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.

  11. "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

    2017-11-01

    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.

  12. 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

  13. Wanting to Be Different Predicts Nonmotivated Change: Actual-Desired Self-Discrepancies and Susceptibility to Subtle Change Inductions.

    Science.gov (United States)

    DeMarree, Kenneth G; Rios, Kimberly; Randell, J Adam; Wheeler, S Christian; Reich, Darcy A; Petty, Richard E

    2016-12-01

    Actual-desired discrepancies in people's self-concepts represent structural incongruities in their self-representations that can lead people to experience subjective conflict. Theory and research suggest that structural incongruities predict susceptibility to subtle influences like priming and conditioning. Although typically examined for their motivational properties, we hypothesized that because self-discrepancies represent structural incongruities in people's self-concepts, they should also predict susceptibility to subtle influences on people's active self-views. Across three studies, we found that subtle change inductions (self-evaluative conditioning and priming) exerted greater impact on active self-perceptions and behavior as actual-desired self-discrepancies increased in magnitude. Exploratory analyses suggested that these changes occurred regardless of the compatibility of the change induction with individuals' desired self-views. © 2016 by the Society for Personality and Social Psychology, Inc.

  14. Mass Change Prediction Model of Concrete Subjected to Sulfate Attack

    Directory of Open Access Journals (Sweden)

    Kwang-Myong Lee

    2015-01-01

    Full Text Available The present study suggested a mass change prediction model for sulfate attack of concrete containing mineral admixtures through an immersion test in sulfate solutions. For this, 100% OPC as well as binary and ternary blended cement concrete specimens were manufactured by changing the types and amount of mineral admixture. The concrete specimens were immersed in fresh water, 10% sodium sulfate solution, and 10% magnesium sulfate solution, respectively, and mass change of the specimens was measured at 28, 56, 91, 182, and 365 days. The experimental results indicated that resistance of concrete containing mineral admixture against sodium sulfate attack was far greater than that of 100% OPC concrete. However, in terms of resistance against magnesium sulfate attack, concrete containing mineral admixture was lower than 100% OPC concrete due to the formation of magnesium silicate hydrate (M-S-H, the noncementitious material. Ultimately, based on the experimental results, a mass change prediction model was suggested and it was found that the prediction values using the model corresponded relatively well with the experimental results.

  15. 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.

  16. 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…

  17. 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.

  18. 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

    2017-01-01

    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…

  19. 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 .co.za ] Path dependent models to predict property changes in graphite irradiated at changing irradiation temperatures S KOK CSIR Advanced Mathematical Modelling, Modelling and Digital Science, PO Box 395, Pretoria, 0001, South Africa E-mail: skok...

  20. 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...

  1. 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.

  2. Prediction limits of mobile phone activity modelling

    Science.gov (United States)

    Kondor, Dániel; Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo

    2017-02-01

    Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.

  3. Daily update of motor predictions by physical activity.

    Science.gov (United States)

    Gueugneau, Nicolas; Schweighofer, Nicolas; Papaxanthis, Charalambos

    2015-12-03

    Motor prediction, i.e., the ability to predict the sensory consequences of motor commands, is critical for adapted motor behavior. Like speed or force, the accuracy of motor prediction varies in a 24-hour basis. Although the prevailing view is that basic biological markers regulate this circadian modulation, behavioral factors such as physical activity, itself modulated by the alternation of night and day, can also regulate motor prediction. Here, we propose that physical activity updates motor prediction on a daily basis. We tested our hypothesis by up- and down-regulating physical activity via arm-immobilization and high-intensity training, respectively. Motor prediction was assessed by measuring the timing differences between actual and mental arm movements. Results show that although mental movement time was modulated during the day when the arm was unconstrained, it remained constant when the arm was immobilized. Additionally, increase of physical activity, via release from immobilization or intense bout of training, significantly reduced mental movement time. Finally, mental and actual times were similar in the afternoon in the unconstrained condition, indicating that predicted and actual movements match after sufficient amount of physical activity. Our study supports the view that physical activity calibrates motor predictions on a daily basis.

  4. Tajikistan : Overview of Climate Change Activities

    OpenAIRE

    World Bank

    2013-01-01

    This overview of climate change activities in Tajikistan is part of a series of country notes for five Central Asian countries that summarize climate portfolio of the major development partners in a number of climate-sensitive sectors, namely energy, agriculture, forestry and natural resources, water, health, and transport. Recognizing the nature and significance of climate change contribu...

  5. Implicit self-evaluations predict changes in implicit partner evaluations.

    Science.gov (United States)

    McNulty, James K; Baker, Levi R; Olson, Michael A

    2014-08-01

    Do people who feel good about themselves have better relations with others? Although the notion that they do is central to both classic and modern theories, there is little strong evidence to support it. We argue that one reason for the lack of evidence is that prior research has relied exclusively on explicit measures of self- and relationship evaluation. The current longitudinal study of newlywed couples used implicit measures of self- and partner evaluation, as well as explicit measures of self-, relationship, and partner evaluation, to examine the link between self-evaluations and changes in relationship evaluations over the first 3 years of marriage. Whereas explicit self-evaluations were unrelated to changes in all interpersonal measures, implicit self-evaluations positively predicted changes in implicit partner evaluations. This finding adds to previous research by highlighting the importance of automatic processes and implicit measures in the study of close interpersonal relationships. © The Author(s) 2014.

  6. Wavelet change-point prediction of transmembrane proteins.

    Science.gov (United States)

    Lio, P; Vannucci, M

    2000-04-01

    A non-parametric method, based on a wavelet data-dependent threshold technique for change-point analysis, is applied to predict location and topology of helices in transmembrane proteins. A new propensity scale generated from a transmembrane helix database is proposed. We show that wavelet change-point performs well for smoothing hydropathy and transmembrane profiles generated using different scales. We investigate which wavelet bases and threshold functions are overall most appropriate to detect transmembrane segments. Prediction accuracy is based on the analysis of two data sets used as standard benchmarks for transmembrane prediction algorithms. The analysis of a test set of 83 proteins results in accuracy per segment equal to 98.2%; the analysis of a 48 proteins blind-test set, i.e. containing proteins not used to generate the propensity scales, results in accuracy per segment equal to 97.4%. We believe that this method can also be applied to the detection of boundaries of other patterns such as G + Cisochores and dot-plots. The transmembrane database, TMALN and source code are available upon request from the authors.

  7. Predicting changes in adjustment using repeated measures of sociometric status.

    Science.gov (United States)

    Mayeux, Lara; Bellmore, Amy D; Cillessen, Antonius H N

    2007-12-01

    The authors' goals in the study were to investigate the possible gains made by including multiple assessments of status in the prediction of change in psychosocial adjustment and to compare the effectiveness of continuous and categorical measures of peer status in predicting adjustment. The authors obtained continuous and categorical measures of status (social preference and rejected status) for 644 Grade 4 students at 3 points within 1 school year (fall, winter, and spring). The authors measured peer, teacher, and self-report indexes of social adjustment (including aggression, anxiety, and sociability) in Grades 4 and 5. Both measures of peer status at all 3 time points in Grade 4 were significant predictors of adjustment in Grade 5, controlling for Grade 4 levels, with the midyear (i.e., winter) assessment showing a slight predictive advantage over the fall and spring assessments. Children who were classified as peer rejected over multiple assessments had more social adjustment problems in the next school year than did children who were classified as peer rejected at 1 time point only. The authors discuss these findings in terms of the utility of multiple assessments of both continuous and categorical measures of peer status for predicting later outcomes.

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Julia eMossbridge

    2014-03-01

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

  10. White matter morphometric changes uniquely predict children's reading acquisition.

    Science.gov (United States)

    Myers, Chelsea A; Vandermosten, Maaike; Farris, Emily A; Hancock, Roeland; Gimenez, Paul; Black, Jessica M; Casto, Brandi; Drahos, Miroslav; Tumber, Mandeep; Hendren, Robert L; Hulme, Charles; Hoeft, Fumiko

    2014-10-01

    This study examined whether variations in brain development between kindergarten and Grade 3 predicted individual differences in reading ability at Grade 3. Structural MRI measurements indicated that increases in the volume of two left temporo-parietal white matter clusters are unique predictors of reading outcomes above and beyond family history, socioeconomic status, and cognitive and preliteracy measures at baseline. Using diffusion MRI, we identified the left arcuate fasciculus and superior corona radiata as key fibers within the two clusters. Bias-free regression analyses using regions of interest from prior literature revealed that volume changes in temporo-parietal white matter, together with preliteracy measures, predicted 56% of the variance in reading outcomes. Our findings demonstrate the important contribution of developmental differences in areas of left dorsal white matter, often implicated in phonological processing, as a sensitive early biomarker for later reading abilities, and by extension, reading difficulties. © The Author(s) 2014.

  11. 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....

  12. Special Analysis For Predicting Changes In Mangrove Forest

    Directory of Open Access Journals (Sweden)

    Yumna

    2015-01-01

    Full Text Available Abstract This study aims to determine the mangrove forest land cover change and farms based on the interpretation of satellite imagery and predict the extent and determine the area of mangrove rehabilitation based on the rate of change in land cover and land suitability analysis is based on the physical parameters of mangrove forests in the district Ponrang Luwu. Land suitability classification refers to the Land Suitability Classification Framework Method According to FAO 1976 are divided into three classes namely suitability Great Fit Highly Suitable Self-keeping Moderately Suitable and Not Available Not Suitable. The parameters used in the texture of the soil slope salinity temperature flow velocity wave and tidal. Making the land suitability analysis model for the growth and development of mangrove ponds Silvofishery system using weighted overlay overlaying weighted. The study concluded that the analysis of the changes by using the image data in 1994 and 2002 image shows a reduction in mangrove area of 269.16 ha whereas farms have additional land area of 587.65 ha. The pace of change by using the image data in 2002 and 2013 image shows an area of 36.28 ha of mangrove reduction and addition of 85.5 ha of pond area. Analysis of the trend of changes in the area of mangroves generate predictions of mangrove area in 2023 or 10 years down the road is 88.1 ha. Based on the analysis of land suitability the area that includes the appropriate category for the development of Silvofishery pond has an area of 557.86 ha and the area is very appropriate criteria included its range of 1071.98 ha. As for the category Mismatch has an area of 301.67 ha.

  13. Predicting the persistence of coastal wetlands to global change stressors

    Science.gov (United States)

    Guntenspergen, G.; McKee, K.; Cahoon, D.; Grace, J.; Megonigal, P.

    2006-01-01

    Despite progress toward understanding the response of coastal wetlands to increases in relative sea-level rise and an improved understanding of the effect of elevated CO2 on plant species allocation patterns, we are limited in our ability to predict the response of coastal wetlands to the effects associated with global change. Static simulations of the response of coastal wetlands to sea-level rise using LIDAR and GIS lack the biological and physical feedback mechanisms present in such systems. Evidence from current research suggests that biotic processes are likely to have a major influence on marsh vulnerability to future accelerated rates of sea-level rise and the influence of biotic processes likely varies depending on hydrogeomorphic setting and external stressors. We have initiated a new research approach using a series of controlled mesocosm and field experiments, landscape scale studies, a comparative network of brackish coastal wetland monitoring sites and a suite of predictive models that address critical questions regarding the vulnerability of coastal brackish wetland systems to global change. Specifically, this research project evaluates the interaction of sea level rise and elevated CO2 concentrations with flooding, nutrient enrichment and disturbance effects. The study is organized in a hierarchical structure that links mesocosm, field, landscape and biogeographic levels so as to provide important new information that recognizes that coastal wetland systems respond to multiple interacting drivers and feedback effects controlling wetland surface elevation, habitat stability and ecosystem function. We also present a new statistical modelling technique (Structural Equation Modelling) that synthesizes and integrates our environmental and biotic measures in a predictive framework that forecasts ecosystem change and informs managers to consider adaptive shifts in strategies for the sustainable management of coastal wetlands.

  14. 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...

  15. 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...

  16. 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.

  17. 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

    2011-03-01

    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. 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. 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 (R²self-report = .15, R²self-report + neural activity = .35, R²change = .20). 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. (c) 2011 APA, all rights reserved

  18. 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

  19. Changes in truncal obesity and fat distribution predict arterial health.

    Science.gov (United States)

    Corrigan, Frank E; Kelli, Heval Mohamed; Dhindsa, Devinder S; Heinl, Robert E; Al Mheid, Ibhar; Hammadah, Muhammad; Hayek, Salim S; Sher, Salman; Eapen, Danny J; Martin, Greg S; Quyyumi, Arshed A

    Truncal obesity is associated with metabolic syndrome and cardiovascular risk. Although vascular health is influenced by weight, it is not known whether changes in fat distribution modulate arterial function. We assessed how changes in truncal (android) fat at 1 year affect arterial stiffness and endothelial function. We recruited 711 healthy volunteers (235 males, age 48 ± 11 years) into the Emory Predictive Health Study; 498 returned at 1 year. Measurements included anthropometric and chemistry panels, fat mass using dual-energy X-ray absorptiometry, arterial stiffness indices (pulse wave velocity [PWV], augmentation index [AIx], and subendocardial viability ratio [SEVR]; Sphygmocor), flow-mediated dilation (FMD), and reactive hyperemia index (Endo-PAT). At baseline, measures of body mass correlated with PWV, AIx, SEVR, and FMD. In a multivariable analysis including body mass index (BMI) and traditional risk factors, BMI remained an independent predictor of PWV, AIx, SEVR, and FMD. In a model including BMI and measures of fat distribution, android fat remained an independent predictor of PWV (β = 0.31, P = .004), AIx (β = 0.24, P = .008), and SEVR (β = -0.41, P < .001). The 1-year change in android fat correlated negatively with change in SEVR (β = -0.13, P = .005) and FMD (β = -0.13, P = .006) after adjustment for change in gynoid fat. In addition to BMI, android fat is a determinant of arterial stiffness, independent of traditional risk factors. Changes in android fat over time are associated with simultaneous changes in vascular function, indicating fat distribution's effect on vascular health. Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.

  20. Predicting Individual Differences in Placebo Analgesia: Contributions of Brain Activity during Anticipation and Pain Experience

    Science.gov (United States)

    Wager, Tor D.; Atlas, Lauren Y.; Leotti, Lauren A.; Rilling, James K.

    2012-01-01

    Recent studies have identified brain correlates of placebo analgesia, but none have assessed how accurately patterns of brain activity can predict individual differences in placebo responses. We reanalyzed data from two fMRI studies of placebo analgesia (N = 47), using patterns of fMRI activity during the anticipation and experience of pain to predict new subjects’ scores on placebo analgesia and placebo-induced changes in pain processing. We used a cross-validated regression procedure, LASSO-PCR, which provided both unbiased estimates of predictive accuracy and interpretable maps of which regions are most important for prediction. Increased anticipatory activity in a frontoparietal network and decreases in a posterior insular/temporal network predicted placebo analgesia. Patterns of anticipatory activity across the cortex predicted a moderate amount of variance in the placebo response (~12% overall, ~40% for study 2 alone), which is substantial considering the multiple likely contributing factors. The most predictive regions were those associated with emotional appraisal, rather than cognitive control or pain processing. During pain, decreases in limbic and paralimbic regions most strongly predicted placebo analgesia. Responses within canonical pain-processing regions explained significant variance in placebo analgesia, but the pattern of effects was inconsistent with widespread decreases in nociceptive processing. Together, the findings suggest that engagement of emotional appraisal circuits drives individual variation in placebo analgesia, rather than early suppression of nociceptive processing. This approach provides a framework that will allow prediction accuracy to increase as new studies provide more precise information for future predictive models. PMID:21228154

  1. 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

  2. Personality change predicts self-reported mental and physical health.

    Science.gov (United States)

    Magee, Christopher A; Heaven, Patrick C L; Miller, Leonie M

    2013-06-01

    Personality dimensions are known to predict mortality and other health outcomes, but almost no research has assessed the effects of changes in personality traits on physical and mental health outcomes. In this article, we examined the effects of changes in the Big Five personality dimensions on health as assessed by the Short Form Health Survey (SF-36). Respondents were 11,105 Australian adults aged 20-79 years (52.7% female). Latent difference score modeling was used to examine whether personality change over a 4-year period was associated with mental and physical health, and whether these effects were moderated by birth cohort. Increases in Conscientiousness and Extraversion were found to be associated with improved mental and physical health, whereas increased Neuroticism was linked with poorer health. The nature of these associations varied significantly by birth cohort. The findings have implications for understanding how changes in personality traits over time are related to health, and could be used to aid the development of effective health promotion strategies targeted to specific personality traits and birth cohorts. © 2012 Wiley Periodicals, Inc.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2010-12-01

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

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

    Science.gov (United States)

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

    2012-03-06

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

  6. Prediction of color changes in acetaminophen solution using the time-temperature superposition principle.

    Science.gov (United States)

    Mochizuki, Koji; Takayama, Kozo

    2016-01-01

    A prediction method for color changes based on the time-temperature superposition principle (TTSP) was developed for acetaminophen solution. Color changes of acetaminophen solution are caused by the degradation of acetaminophen, such as hydrolysis and oxidation. In principle, the TTSP can be applied to only thermal aging. Therefore, the impact of oxidation on the color changes of acetaminophen solution was verified. The results of our experiment suggested that the oxidation products enhanced the color changes in acetaminophen solution. Next, the color changes of acetaminophen solution samples of the same head space volume after accelerated aging at various temperatures were investigated using the Commission Internationale de l'Eclairage (CIE) LAB color space (a*, b*, L* and ΔE*ab), following which the TTSP was adopted to kinetic analysis of the color changes. The apparent activation energies using the time-temperature shift factor of a*, b*, L* and ΔE*ab were calculated as 72.4, 69.2, 72.3 and 70.9 (kJ/mol), respectively, which are similar to the values for acetaminophen hydrolysis reported in the literature. The predicted values of a*, b*, L* and ΔE*ab at 40 °C were obtained by calculation using Arrhenius plots. A comparison between the experimental and predicted values for each color parameter revealed sufficiently high R(2) values (>0.98), suggesting the high reliability of the prediction. The kinetic analysis using TTSP was successfully applied to predicting the color changes under the controlled oxygen amount at any temperature and for any length of time.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    OpenAIRE

    Calitri, R; Pothos, E. M.; Tapper, K.; Brunstrom, J. M.; Rogers, P J

    2010-01-01

    The current study explored the predictive value of cognitive biases to food cues (assessed by emotional Stroop and dot probe tasks) on weight change over a 1-year period. This was a longitudinal study with undergraduate students (N = 102) living in shared student accommodation. After controlling for the effects of variables associated with weight (e.g., physical activity, stress, restrained eating, external eating, and emotional eating), no effects of cognitive bias were found with the dot pr...

  9. Predicting the ancestral character changes in a tree is typically easier than predicting the root state.

    Science.gov (United States)

    Gascuel, Olivier; Steel, Mike

    2014-05-01

    Predicting the ancestral sequences of a group of homologous sequences related by a phylogenetic tree has been the subject of many studies, and numerous methods have been proposed for this purpose. Theoretical results are available that show that when the substitution rates become too large, reconstructing the ancestral state at the tree root is no longer feasible. Here, we also study the reconstruction of the ancestral changes that occurred along the tree edges. We show that, that, depending on the tree and branch length distribution, reconstructing these changes (i.e., reconstructing the ancestral state of all internal nodes in the tree) may be easier or harder than reconstructing the ancestral root state. However, results from information theory indicate that for the standard Yule tree, the task of reconstructing internal node states remains feasible, even for very high substitution rates. Moreover, computer simulations demonstrate that for more complex trees and scenarios, this result still holds. For a large variety of counting, parsimony- and likelihood-based methods, the predictive accuracy of a randomly selected internal node in the tree is indeed much higher than the accuracy of the same method when applied to the tree root. Moreover, parsimony- and likelihood-based methods appear to be remarkably robust to sampling bias and model mis-specification.

  10. Deep Active Object Recognition by Joint Label and Action Prediction

    OpenAIRE

    Malmir, Mohsen; Sikka, Karan; Forster, Deborah; Fasel, Ian; Movellan, Javier R.; Cottrell, Garrison W.

    2015-01-01

    An active object recognition system has the advantage of being able to act in the environment to capture images that are more suited for training and that lead to better performance at test time. In this paper, we propose a deep convolutional neural network for active object recognition that simultaneously predicts the object label, and selects the next action to perform on the object with the aim of improving recognition performance. We treat active object recognition as a reinforcement lear...

  11. 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.

  12. 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.

  13. Physical fitness predicts adiposity longitudinal changes over childhood and adolescence.

    Science.gov (United States)

    Rodrigues, Luís Paulo; Leitão, Raquel; Lopes, Vítor P

    2013-03-01

    The purpose of this study was to examine the influence of physical fitness (PF) on the development of subcutaneous adipose tissue in children followed longitudinally over a 9 year period ranging from childhood to adolescence. This longitudinal study followed 518 healthy participants (262 boys, 256 girls) over a 9-year period ranging from childhood (age 6) to adolescence (age 15). Adiposity (triceps and subscapular skinfolds), and fitness (60s sit-ups, flexed arm hang, standing long jump, 50m dash, 10m shuttle run, sit-and-reach, and 20m pacer run) were assessed at four annual time points during primary school, and on a follow up, 6 years later, during secondary school. Growth in subcutaneous fat was modeled within a HLM statistical framework, using fitness components as time changing predictors. Flexed arm hang (β=-0.059; p=0.000), standing long jump (β=-0.072; p=0.000), 60s sit-ups (β=-0.041; p=0.040), 50m dash (β=0.956; p=0.000), and 20m PACER (β=-0.077; p=0.000) tests, were found to predict changes on body fat growth over the years, independently of sex. Improving PF individual levels can positively influence adiposity deposition over the time period covering childhood and adolescence. That occurs independently of the typical sex differentiated adiposity growth. Copyright © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

  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. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

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

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and faulty...... 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...

  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. 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.

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

    Science.gov (United States)

    Pawson, Stephen M; Marcot, Bruce G; Woodberry, Owen G

    2017-01-01

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

  20. 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.

  1. Prediction of Land use changes using CA in GIS Environment

    Science.gov (United States)

    Kiavarz Moghaddam, H.; Samadzadegan, F.

    2009-04-01

    GIS extention. A set of crisp rules are defined and calibrated based on real urban growth pattern. Uncertainty analysis is performed to evaluate the accuracy of the simulated results as compared to the historical real data. Evaluation shows promising results represented by the high average accuracies achieved. The average accuracy for the predicted growth images 1964 and 2002 is over 80 %. Modifying CA growth rules over time to match the growth pattern changes is important to obtain accurate simulation. This modification is based on the urban growth relationship for Tehran over time as can be seen in the historical raster data. The feedback obtained from comparing the simulated and real data is crucial in identifying the optimal set of CA rules for reliable simulation and calibrating growth steps.

  2. Climate Change Policies for the XXIst Century: Mechanisms, Predictions and Recommendations

    CERN Document Server

    Khmelinskii, Igor

    2011-01-01

    Recent experimental works demonstrated that the Anthropogenic Global Warming (AGW) hypothesis, embodied in a series of Intergovernmental Panel on Climate Change (IPCC) global climate models, is erroneous. These works prove that atmospheric carbon dioxide contributes only very moderately to the observed warming, and that there is no climatic catastrophe in the making, independent on whether or not carbon dioxide emissions will be reduced. In view of these developments, we discuss climate predictions for the XXIst century. Based on the solar activity tendencies, a new Little Ice Age is predicted by the middle of this century, with significantly lower global temperatures. We also show that IPCC climate models can't produce any information regarding future climate, due to essential physical phenomena lacking in those, and that the current budget deficit in many EU countries is mainly caused by the policies promoting renewable energies and other AGW-motivated measures. In absence of any predictable adverse climate...

  3. 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...... 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...... response of the activated sludge most likely results from the sequence of intracellular reactions involved in substrate degradation by the activated sludge. Results from studies performed elsewhere with pure cultures (S. cerevisae and E. coli) support the hypothesis. The transient phenomenon can...

  4. Predicting the Effect of Changing Precipitation Extremes and Land Cover Change on Urban Water Quality

    Science.gov (United States)

    SUN, N.; Yearsley, J. R.; Lettenmaier, D. P.

    2013-12-01

    Recent research shows that precipitation extremes in many of the largest U.S. urban areas have increased over the last 60 years. These changes have important implications for stormwater runoff and water quality, which in urban areas are dominated by the most extreme precipitation events. We assess the potential implications of changes in extreme precipitation and changing land cover in urban and urbanizing watersheds at the regional scale using a combination of hydrology and water quality models. Specifically, we describe the integration of a spatially distributed hydrological model - the Distributed Hydrology Soil Vegetation Model (DHSVM), the urban water quality model in EPA's Storm Water Management Model (SWMM), the semi-Lagrangian stream temperature model RBM10, and dynamical and statistical downscaling methods applied to global climate predictions. Key output water quality parameters include total suspended solids (TSS), toal nitrogen, total phosphorous, fecal coliform bacteria and stream temperature. We have evaluated the performance of the modeling system in the highly urbanized Mercer Creek watershed in the rapidly growing Bellevue urban area in WA, USA. The results suggest that the model is able to (1) produce reasonable streamflow predictions at fine temporal and spatial scales; (2) provide spatially distributed water temperature predictions that mostly agree with observations throughout a complex stream network, and characterize impacts of climate, landscape, near-stream vegetation change on stream temperature at local and regional scales; and (3) capture plausibly the response of water quality constituents to varying magnitude of precipitation events in urban environments. Next we will extend the scope of the study from the Mercer Creek watershed to include the entire Puget Sound Basin, WA, USA.

  5. 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...

  6. Predictive Active Set Selection Methods for Gaussian Processes

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2012-01-01

    likelihood maximization. The active set update rules rely on the ability of the predictive distributions of a Gaussian process classifier to estimate the relative contribution of a datapoint when being either included or removed from the model. This means that we can use it to include points with potentially...

  7. In Vivo Feedback Predicts Parent Behavior Change in the Attachment and Biobehavioral Catch-up Intervention.

    Science.gov (United States)

    Caron, E B; Bernard, Kristin; Dozier, Mary

    2016-04-04

    Understanding mechanisms and active ingredients of intervention is critical to training clinicians, particularly when interventions are transported from laboratories to communities. One promising active ingredient of parenting programs is clinicians' in vivo feedback regarding parent-child interactions. The present study examined whether a form of in vivo feedback, in the moment commenting, predicted treatment retention and parent behavior change when the Attachment and Biobehavioral Catch-up (ABC) intervention was implemented in a community setting. Observational data were collected from 78 parent-child dyads (96% mothers; M age = 29 years; 81% minority; infants' M age = 12 months; 90% minority) across 640 sessions conducted by 9 clinicians (100% female, M age = 39; 67% minority) in Hawaii. Parental behavior was assessed with a semistructured play task before and after intervention. Clinicians' in-the-moment feedback to parents was assessed from intervention session videos. Clinicians' frequency and quality of in-the-moment feedback predicted change in parental intrusiveness and sensitivity at posttreatment. Frequency of in-the-moment feedback also predicted likelihood of retention. Hierarchical linear modeling demonstrated strong support for these associations at the between-clinician level, and limited additional support at the within-clinician (i.e., between-case) level. Thus, a hypothesized active ingredient of treatment, in-the-moment feedback, predicted community-based ABC outcomes. The results complement lab-based evidence to suggest that in vivo feedback may be a mechanism of change in parenting interventions. Helping clinicians to provide frequent, high-quality in vivo feedback may improve parenting program outcomes in community settings.

  8. One model to predict them all : Predicting energy behaviours with the norm activation model

    NARCIS (Netherlands)

    van der Werff, Ellen; Steg, Linda

    2015-01-01

    One of the most influential models explaining how and which (normative) factors influence environmental behaviour is the norm activation model (NAM). In support of the compatibility principle, research revealed that the NAM predicts behaviour best when all variables are measured on the same level of

  9. 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.

  10. Predicting climate change impacts on polar bear litter size

    OpenAIRE

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

    2011-01-01

    Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size de...

  11. 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.)

  12. 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.

  13. 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.

  14. High solar activity predictions through an artificial neural network

    Science.gov (United States)

    Orozco-Del-Castillo, M. G.; Ortiz-Alemán, J. C.; Couder-Castañeda, C.; Hernández-Gómez, J. J.; Solís-Santomé, A.

    The effects of high-energy particles coming from the Sun on human health as well as in the integrity of outer space electronics make the prediction of periods of high solar activity (HSA) a task of significant importance. Since periodicities in solar indexes have been identified, long-term predictions can be achieved. In this paper, we present a method based on an artificial neural network to find a pattern in some harmonics which represent such periodicities. We used data from 1973 to 2010 to train the neural network, and different historical data for its validation. We also used the neural network along with a statistical analysis of its performance with known data to predict periods of HSA with different confidence intervals according to the three-sigma rule associated with solar cycles 24-26, which we found to occur before 2040.

  15. 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.

  16. 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.

  17. 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

  18. 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…

  19. 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.

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

    KAUST Repository

    Lawton, Rebecca J.

    2011-07-14

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

  1. 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.

  2. Cortical activity predicts good variation in human motor output.

    Science.gov (United States)

    Babikian, Sarine; Kanso, Eva; Kutch, Jason J

    2017-04-01

    Human movement patterns have been shown to be particularly variable if many combinations of activity in different muscles all achieve the same task goal (i.e., are goal-equivalent). The nervous system appears to automatically vary its output among goal-equivalent combinations of muscle activity to minimize muscle fatigue or distribute tissue loading, but the neural mechanism of this "good" variation is unknown. Here we use a bimanual finger task, electroencephalography (EEG), and machine learning to determine if cortical signals can predict goal-equivalent variation in finger force output. 18 healthy participants applied left and right index finger forces to repeatedly perform a task that involved matching a total (sum of right and left) finger force. As in previous studies, we observed significantly more variability in goal-equivalent muscle activity across task repetitions compared to variability in muscle activity that would not achieve the goal: participants achieved the task in some repetitions with more right finger force and less left finger force (right > left) and in other repetitions with less right finger force and more left finger force (left > right). We found that EEG signals from the 500 milliseconds (ms) prior to each task repetition could make a significant prediction of which repetitions would have right > left and which would have left > right. We also found that cortical maps of sites contributing to the prediction contain both motor and pre-motor representation in the appropriate hemisphere. Thus, goal-equivalent variation in motor output may be implemented at a cortical level.

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

    Science.gov (United States)

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

    2011-02-08

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

  4. What measure of interpersonal dependency predicts changes in social support?

    Science.gov (United States)

    Shahar, Golan

    2008-01-01

    One of the most intriguing characteristics of interpersonal dependency is its ability to predict elevated levels of social support. Yet studies of interpersonal dependency use various measures to assess this effect. In this study, I compared 3 commonly used measures of interpersonal dependency in terms of their prediction of social support: Hirschfield's Interpersonal Dependency Inventory (IDI; Hirschfeld et al., 1977), the dependency factor of the Depressive Experiences Questionnaire (DEQ; Blatt, D'Afflitti, & Quinlan, 1976), and the Dependency subscale of the Personal Style Inventory (PSI; Robins et al., 1994). A total of 152 undergraduates were administered these measures as well as measures of depressive symptoms and social support a week prior to their first exam period and a week after this period (interval time = 8 weeks). DEQ-dependency predicted an increase in social support, whereas PSI-Dependency and IDI predicted a decrease in social support over time. DEQ-dependency appears to capture better than the other 2 measures the dialectic tension between risk and resilience in interpersonal dependency.

  5. 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 ...

  6. 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…

  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. 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

  9. Regularities of solar wind parameter changes based on spaced measurements at near-Earth orbit during cycles 20-24 as a basis for prediction of solar activity and space weather

    Science.gov (United States)

    Kuznetsova, Tamara

    Here we discuss parameters of the solar wind streams as consequences of activity of solar cycles 20-24. We use in the report results of our study of connection between solar wind parameters (IMF B, solar wind velocity V, concentration N, electric field Е = [V,B]) and IMF longitude angle U during period of SC20-24. We have used for the study data base of B, V, N, measured at 1 a.u. near ecliptic plane for period of 1963 - 2013.The azimuth component of IMF spiral corresponds to east-west component By (GSE) which plays important role in reconnection on magnetopause and in progress of geomagnetic activity. Resulting from the conducted study, main regularities determining relationship between solar wind parameters in each from SC20-24 have been derived. In particular, it was shown that E for By>0 has its maxima in each solar cycle at average U=80 deg, herewith the maxima for odd cycles (21, 23) are considerably larger than ones for even cycles (20, 22). Besides, the value of E for 23 cycle has the absolute maximum for By>0 among SC20-24! So, relative low value of maximum of sunspot number Wm=121 of SC23 is a parameter, which does not determine strength of solar wind electric field E and consequently geomagnetic activity. Geomagnetic index Dst(U) shows also absolute maximum of depression for cycle 23 at near the same U=80 deg. (By>0). B(U) is larger, Wm is larger for all U except interval for By>0, where B for odd cycles 21, 23 is higher than B for even ones 20,22. It should be noted that V (U) for SC with minimal Wm (20,23) has the highest maximum for By>0; maximum of V for Byminimum (near 2020) similar to Dalton minimum (near 1820).

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

    Indian Academy of Sciences (India)

    Although, in general, it is difficult to relate land- slide occurrences to land-use changes (Glade 2003), case studies in New Zealand could establish explicit relationship between landslide events and anthro- pogenic land-use changes, particularly deforesta- tion (O'Loughlin and Pearce 1976; Crozier et al. 1978; Page et al.

  11. model prediction of maize yield responses to climate change

    African Journals Online (AJOL)

    Prof. Adipala Ekwamu

    decision makers to address the challenges of climate change. Recent IPCC and global environmental change .... The functional components of the model are: soil and its balance with water, the plant and its processes, the ... optimal balance between accuracy, robustness, simplicity and it requires a relatively small number.

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

    African Journals Online (AJOL)

    Land use change is a major factor influencing catchment hydrology and groundwater resources. In South ... To reduce water loss due to evapotranspiration, non-native hill slope vegetation upstream of the Berg River Dam was cut down. It was hypothesised that recharge has been increased due to this change in vegetation.

  15. Predictability and irreversibility of genetic changes associated with flower color evolution in Penstemon barbatus.

    Science.gov (United States)

    Wessinger, Carolyn A; Rausher, Mark D

    2014-04-01

    Two outstanding questions in evolutionary biology are whether, and how often, the genetic basis of phenotypic evolution is predictable; and whether genetic change constrains evolutionary reversibility. We address these questions by studying the genetic basis of red flower color in Penstemon barbatus. The production of red flowers often involves the inactivation of one or both of two anthocyanin pathway genes, Flavonoid 3',5'-hydroxylase (F3'5'h) and Flavonoid 3'-hydroxylase (F3'h). We used gene expression and enzyme function assays to determine that redundant inactivating mutations to F3'5'h underlie the evolution of red flowers in P. barbatus. Comparison of our results to previously characterized shifts from blue to red flowers suggests that the genetic change associated with the evolution of red flowers is predictable: when it involves elimination of F3'5'H activity, functional inactivation or deletion of this gene tends to occur; however, when it involves elimination of F3'H activity, tissue-specific regulatory substitutions occur and the gene is not functionally inactivated. This pattern is consistent with emerging data from physiological experiments indicating that F3'h may have pleiotropic effects and is thus subject to purifying selection. The multiple, redundant inactivating mutations to F3'5'h suggest that reversal to blue-purple flowers in this group would be unlikely. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

  16. Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

    Science.gov (United States)

    Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

  17. 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.

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

    Science.gov (United States)

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

    2012-08-01

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

  19. A model for prediction of color change after tooth bleaching based on CIELAB color space

    Science.gov (United States)

    Herrera, Luis J.; Santana, Janiley; Yebra, Ana; Rivas, María. José; Pulgar, Rosa; Pérez, María. M.

    2017-08-01

    An experimental study aiming to develop a model based on CIELAB color space for prediction of color change after a tooth bleaching procedure is presented. Multivariate linear regression models were obtained to predict the L*, a*, b* and W* post-bleaching values using the pre-bleaching L*, a*and b*values. Moreover, univariate linear regression models were obtained to predict the variation in chroma (C*), hue angle (h°) and W*. The results demonstrated that is possible to estimate color change when using a carbamide peroxide tooth-bleaching system. The models obtained can be applied in clinic to predict the colour change after bleaching.

  20. Identification and prediction of physical activity trajectories in women treated for breast cancer.

    Science.gov (United States)

    Brunet, Jennifer; Amireault, Steve; Chaiton, Michael; Sabiston, Catherine M

    2014-11-01

    In this study, we aimed to identify trajectories of physical activity in a cohort of women over a 1-year period after treatment for breast cancer. We also examined factors that could predict trajectory group membership. We collected data from 199 women using questionnaires at baseline (mean = 3.46 months after treatment), and 3, 6, 9, and 12 months thereafter. Based on semiparametric group-based modeling, there were five trajectories: consistently inactive, decreasing levels, inactive with increasing levels, somewhat active, and consistently sufficiently active. Based on logistic regression analysis, women who reported higher levels of depressive symptoms and fatigue were less likely to remain consistently sufficiently active, and women who reported higher levels of cancer worry were more likely to remain consistently sufficiently active. Age, stage of cancer, time since treatment, number of treatment types received, and number of physical symptoms did not predict trajectory group membership. Women do not have uniform physical activity trajectories after treatment for breast cancer. Identification subgroups of women who do not remain consistently sufficiently active, and factors that predict these trajectories, can aid in the development of targeted behavior change interventions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  1. 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

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

    National Research Council Canada - National Science Library

    Helfrich, Christian D; Blevins, Dean; Smith, Jeffrey L; Kelly, P Adam; Hogan, Timothy P; Hagedorn, Hildi; Dubbert, Patricia M; Sales, Anne E

    2011-01-01

    ...-documented by organizational scholars, are often ignored in health services research. We describe a protocol to comprehensively assess the psychometric properties of a previously developed survey, the Organizational Readiness to Change Assessment...

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

    Science.gov (United States)

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

    2010-01-01

    Global climate change has the potential to substantially alter the production and community structure of marine fisheries and modify the ongoing impacts of fishing. Fish community composition is already changing in some tropical, temperate and polar ecosystems, where local combinations of warming trends and higher environmental variation anticipate the changes likely to occur more widely over coming decades. Using case studies from the Western Indian Ocean, the North Sea and the Bering Sea, we contextualize the direct and indirect effects of climate change on production and biodiversity and, in turn, on the social and economic aspects of marine fisheries. Climate warming is expected to lead to (i) yield and species losses in tropical reef fisheries, driven primarily by habitat loss; (ii) community turnover in temperate fisheries, owing to the arrival and increasing dominance of warm-water species as well as the reduced dominance and departure of cold-water species; and (iii) increased diversity and yield in Arctic fisheries, arising from invasions of southern species and increased primary production resulting from ice-free summer conditions. How societies deal with such changes will depend largely on their capacity to adapt—to plan and implement effective responses to change—a process heavily influenced by social, economic, political and cultural conditions. PMID:20980322

  4. 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......-term equilibria. As a result, land systems can shift to new regimes with markedly different economic and ecological characteristics. Anticipating the timing and nature of regime shifts of land systems is extremely challenging, as we demonstrate through empirical case studies in four countries in Southeast Asia...

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

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

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

    IDRC

    maternal deaths and spontaneous abortions, premature deliveries, and neonatal deaths. With climate change and other factors such as deforestation, conditions considered unusual in the late 1990s may become the norm. Temperatures in the East African highlands have risen by half a degree. Celsius in the last 50 years, ...

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

    African Journals Online (AJOL)

    2012-04-13

    Apr 13, 2012 ... Land use change is a major factor influencing catchment hydrology and groundwater resources. In South Africa, the man- agement of scarce water resources is a big concern. The study area, the upper Berg catchment, Western Cape, South Africa, contains strategic water resources. The catchment has ...

  14. 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

  15. [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.

  16. 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.

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

    Science.gov (United States)

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

    2004-01-01

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

  18. 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.

  19. Predicting success: factors associated with weight change in obese youth undertaking a weight management program.

    Science.gov (United States)

    Baxter, Kimberley A; Ware, Robert S; Batch, Jennifer A; Truby, Helen

    2013-01-01

    To explore which baseline physiological and psychosocial variables predict change in body mass index (BMI) z-score in obese youth after 12 weeks of a dietary weight management study. Participants were obese young people participating in a dietary intervention trial in Brisbane Australia. The outcome variable was change in BMI z-score. Potential predictors considered included demographic, physiological and psychosocial parameters of the young person, and demographic characteristics of their parents. A multivariable regression model was constructed to examine the effect of potential predictive variables. Participants (n = 88) were predominantly female (69.3%), and had a mean(standard deviation) age of 13.1(1.9) years and BMI z-score of 2.2(0.4) on presentation. Lower BMI z-score (p resistance (p = 0.04) at baseline, referral from a paediatrician (p = 0.02) and being more socially advantaged (p = 0.046) were significantly associated with weight loss. Macronutrient distribution of diet and physical activity level did not contribute. Early intervention in obesity treatment in young people improves likelihood of success. Other factors such as degree of insulin resistance, social advantage and referral source also appear to play a role. Assessing presenting characteristics and factors associated with treatment outcome may allow practicing clinicians to individualise a weight management program or determine the 'best-fit' treatment for an obese adolescent. © 2013 Asian Oceanian Association for the Study of Obesity . Published by Elsevier Ltd. All rights reserved.

  20. 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.

  1. Changes in positive affect and mindfulness predict changes in cortisol response and psychiatric symptoms: a latent change score modelling approach.

    Science.gov (United States)

    Hou, Wai Kai; Ng, Sin Man; Wan, Jacky Ho Yin

    2015-01-01

    This study examined whether and how changes in positive affect and mindfulness predicted changes in cortisol secretion and psychological distress in adaptation to examination stress. A sample of 105 college students completed a questionnaire set and provided salivary samples before (T1), during (T2) and after (T3) an examination period. Latent change score modelling revealed that T1-T2 and T2-T3 increases in mindfulness were associated with larger T2-T3 decrease in area-under-the-curve ground of cortisol awakening response (CARg), whereas T2-T3 increases in both positive affect and mindfulness were associated with larger T2-T3 decrease in anxiety symptoms (comparative fit index = .96; Tucker-Lewis index = .93-.95; root-mean-square error of approximation = .04-.08; standardised root-mean-square residual = .08-.10). T1-T2 and T2-T3 increases in positive affect were not associated T2-T3 decrease in CARg, whereas T1-T2 increases in positive affect and mindfulness were not associated with T2-T3 decrease in anxiety symptoms. The levels of post-stress recovery from anxiety symptoms could depend on concurrent increases in positive affect and mindfulness, whereas the levels of post-stress decline in cortisol secretion could depend on increases in mindfulness both during and after stress. Directions for translating the present findings into stress management programmes in college settings are discussed.

  2. Improving the reliability of fishery predictions under climate change

    DEFF Research Database (Denmark)

    Brander, Keith

    2015-01-01

    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...... will decline. These levels of confidence seem unwarranted, since many processes are either absent from or poorly represented in the models used, data are sparse and, unlike terrestrial crop projections, there are no controlled experiments.This review discusses methodological issues that affect our...

  3. 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.

  4. Improving synthetic efficiency using the computational prediction of biological activity.

    Science.gov (United States)

    Broglé, K C; Gund, T; Kyle, D J

    2006-02-01

    A process has been developed whereby libraries of compounds for lead optimization can be synthesized and screened with greater efficiency using computational tools. In this method, analogues of a lead chemical structure are considered in the form of a virtual library. Less than 1/3 of the library is selected as a training set by clustering the compounds and choosing the centroid of each cluster. This training set is then used to generate a model using PLS regression upon the experimental values from that assay using 1D/2D descriptors. The model is applied to the remaining compounds (the test set) for which assay values are predicted and a rank ordering established. An example of this was a set of 169 PDE4 inhibitors. A predictive model was achieved using a training set of 52 compounds. When applied to the remaining 117 compounds this model allowed a rank ordering of these compounds for synthesis and testing. Selecting the top 33 compounds of the test set gives 78% of the compounds with the desired activity (hits) by synthesizing only 50% of the library, including the training set. Selecting the top 59 of the test set gives 97% of the hits from only 67% of the library. This process succeeds by avoiding two principal weaknesses of 2D descriptors: lack of interpretation and lack of extrapolation. Two principal assumptions of QSAR are shown to be unnecessary; removing descriptor redundancy does not improve fit and a predictive r2 greater than 0.5 is not necessary if rank-ordering is desired.

  5. 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.

  6. 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.

  7. Insider Activism: Faculty as Institutional Change Agents

    Science.gov (United States)

    Guckenheimer, Debra

    2009-01-01

    Social movements not only target organizations from outside locations; activism also takes place from insider locations. Insider activism often only goes unrecognized and unrewarded, and activists must also overcome institutional constraints. In this dissertation, I that faculty efforts at institutional diversity deserve attention from the social…

  8. Using Data Assimilation Methods of Prediction of Solar Activity

    Science.gov (United States)

    Kitiashvili, Irina N.; Collins, Nancy S.

    2017-01-01

    The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

  9. Target of rapamycin activation predicts lifespan in fruit flies.

    Science.gov (United States)

    Scialò, Filippo; Sriram, Ashwin; Naudí, Alba; Ayala, Victoria; Jové, Mariona; Pamplona, Reinald; Sanz, Alberto

    2015-01-01

    Aging and age-related diseases are one of the most important health issues that the world will confront during the 21(st) century. Only by understanding the proximal causes will we be able to find treatments to reduce or delay the onset of degenerative diseases associated with aging. Currently, the prevalent paradigm in the field is the accumulation of damage. However, a new theory that proposes an alternative explanation is gaining momentum. The hyperfunction theory proposes that aging is not a consequence of a wear and tear process, but a result of the continuation of developmental programs during adulthood. Here we use Drosophila melanogaster, where evidence supporting both paradigms has been reported, to identify which parameters that have been previously related with lifespan best predict the rate of aging in wild type flies cultured at different temperatures. We find that mitochondrial function and mitochondrial reactive oxygen species (mtROS) generation correlates with metabolic rate, but not with the rate of aging. Importantly, we find that activation of nutrient sensing pathways (i.e. insulin-PI3K/Target of rapamycin (Tor) pathway) correlates with lifespan, but not with metabolic rate. Our results, dissociate metabolic rate and lifespan in wild type flies and instead link nutrient sensing signaling with longevity as predicted by the hyperfunction theory.

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

    Science.gov (United States)

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

    2003-04-01

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

  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. Can physicians accurately predict which patients will lose weight, improve nutrition and increase physical activity?

    Science.gov (United States)

    Pollak, Kathryn I; Coffman, Cynthia J; Alexander, Stewart C; Tulsky, James A; Lyna, Pauline; Dolor, Rowena J; Cox, Mary E; Brouwer, Rebecca J Namenek; Bodner, Michael E; Østbye, Truls

    2012-10-01

    Physician counselling may help patients increase physical activity, improve nutrition and lose weight. However, physicians have low outcome expectations that patients will change. The aims are to describe the accuracy of physicians' outcome expectations about whether patients will follow weight loss, nutrition and physical activity recommendations. The relationships between physician outcome expectations and patient motivation and confidence also are assessed. This was an observational study that audio recorded encounters between 40 primary care physicians and 461 of their overweight or obese patients. We surveyed physicians to assess outcome expectations that patients will lose weight, improve nutrition and increase physical activity after counselling. We assessed actual patient change in behaviours from baseline to 3 months after the encounter and changes in motivation and confidence from baseline to immediately post-encounter. Right after the visit, ~55% of the time physicians were optimistic that their individual patients would improve. Physicians were not very accurate about which patients actually would improve weight, nutrition and physical activity. More patients had higher confidence to lose weight when physicians thought that patients would be likely to follow their weight loss recommendations. Physicians are moderately optimistic that patients will follow their weight loss, nutrition and physical activity recommendations. Patients might perceive physicians' confidence in them and thus feel more confident themselves. Physicians, however, are not very accurate in predicting which patients will or will not change behaviours. Their optimism, although helpful for patient confidence, might make physicians less receptive to learning effective counselling techniques.

  13. Temporo-parietal connectivity uniquely predicts reading change from childhood to adolescence.

    Science.gov (United States)

    Lee, Shu-Hui; Booth, James R; Chou, Tai-Li

    2016-11-15

    Previous research has shown that left posterior middle temporal gyrus (pMTG) is a core node in the semantic network, and cross-sectional studies have shown that activation in this region changes developmentally and is related to skill measured concurrently. However, it is not known how functional connectivity with this region changes developmentally, and whether functional connectivity is related to future gains in reading. We conducted a longitudinal functional magnetic resonance imaging (fMRI) study in 30 typically developing children (aged 8-15) to examine whether initial brain measures, including activation and connectivity, can predict future behavioral improvement in a semantic judgment task. Participants were scanned on entering the study (time 1, T1) and a follow-up period of 2years (time 2, T2). Character pairs were arranged in a continuous variable according to association strength (i.e. strong versus weak), and participants were asked to determine if these visually presented pairs were related in meaning. Our results demonstrated greater developmental changes from time 1 to time 2 for weaker association pairs in the left pMTG for the children (aged 8-11) as compared to the adolescents (aged 12-15). Moreover, the results showed greater developmental changes from time 1 to time 2 for weaker association pairs in connectivity between the pMTG and inferior parietal lobule (IPL) for the children as compared to the adolescents. Furthermore, a hierarchical stepwise regression model revealed that connectivity between the pMTG and IPL in weak association pairs was uniquely predictive of behavioral improvement from time 1 to time 2 for the children, but not the adolescents. Taken together, the activation results suggest relatively rapid development before adolescence of semantic representations in the pMTG. Moreover, the connectivity results of pMTG with IPL tentatively suggest that early development of semantic representations may be facilitated by enhanced

  14. 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.

  15. Prediction of energy expenditure and physical activity in preschoolers.

    Science.gov (United States)

    Butte, Nancy F; Wong, William W; Lee, Jong Soo; Adolph, Anne L; Puyau, Maurice R; Zakeri, Issa F

    2014-06-01

    Accurate, nonintrusive, and feasible methods are needed to predict energy expenditure (EE) and physical activity (PA) levels in preschoolers. Herein, we validated cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on accelerometry and heart rate (HR) for the prediction of EE using room calorimetry and doubly labeled water (DLW) and established accelerometry cut points for PA levels. Fifty preschoolers, mean ± SD age of 4.5 ± 0.8 yr, participated in room calorimetry for minute-by-minute measurements of EE, accelerometer counts (AC) (Actiheart and ActiGraph GT3X+), and HR (Actiheart). Free-living 105 children, ages 4.6 ± 0.9 yr, completed the 7-d DLW procedure while wearing the devices. AC cut points for PA levels were established using smoothing splines and receiver operating characteristic curves. On the basis of calorimetry, mean percent errors for EE were -2.9% ± 10.8% and -1.1% ± 7.4% for CSTS models and -1.9% ± 9.6% and 1.3% ± 8.1% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. On the basis of DLW, mean percent errors were -0.5% ± 9.7% and 4.1% ± 8.5% for CSTS models and 3.2% ± 10.1% and 7.5% ± 10.0% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. Applying activity EE thresholds, final accelerometer cut points were determined: 41, 449, and 1297 cpm for Actiheart x-axis; 820, 3908, and 6112 cpm for ActiGraph vector magnitude; and 240, 2120, and 4450 cpm for ActiGraph x-axis for sedentary/light, light/moderate, and moderate/vigorous PA (MVPA), respectively. On the basis of confusion matrices, correctly classified rates were 81%-83% for sedentary PA, 58%-64% for light PA, and 62%-73% for MVPA. The lack of bias and acceptable limits of agreement affirms the validity of the CSTS and MARS models for the prediction of EE in preschool-aged children. Accelerometer cut points are satisfactory for the classification of sedentary, light, and moderate

  16. 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.

  17. 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.

  18. Baseline activity predicts working memory load of preceding task condition.

    Science.gov (United States)

    Pyka, Martin; Hahn, Tim; Heider, Dominik; Krug, Axel; Sommer, Jens; Kircher, Tilo; Jansen, Andreas

    2013-11-01

    The conceptual notion of the so-called resting state of the brain has been recently challenged by studies indicating a continuing effect of cognitive processes on subsequent rest. In particular, activity in posterior parietal and medial prefrontal areas has been found to be modulated by preceding experimental conditions. In this study, we investigated which brain areas show working memory dependent patterns in subsequent baseline periods and how specific they are for the preceding experimental condition. During functional magnetic resonance imaging, 94 subjects performed a letter-version of the n-back task with the conditions 0-back and 2-back followed by a low-level baseline in which subjects had to passively observe the letters appearing. In a univariate analysis, 2-back served as control condition while 0-back, baseline after 0-back and baseline after 2-back were modeled as regressors to test for activity changes between both baseline conditions. Additionally, we tested, using Gaussian process classifiers, the recognition of task condition from functional images acquired during baseline. Besides the expected activity changes in the precuneus and medial prefrontal cortex, we found differential activity in the thalamus, putamen, and postcentral gyrus that were affected by the preceding task. The multivariate analysis revealed that images of the subsequent baseline block contain task related patterns that yield a recognition rate of 70%. The results suggest that the influence of a cognitive task on subsequent baseline is strong and specific for some areas but not restricted to areas of the so-called default mode network. Copyright © 2012 Wiley Periodicals, Inc.

  19. 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

  20. 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.

  1. Fibromyalgia and the Prediction of Two-Year Changes in Functional Status in Rheumatoid Arthritis Patients.

    Science.gov (United States)

    Kim, Hyein; Cui, Jing; Frits, Michelle; Iannaccone, Christine; Coblyn, Jonathan; Shadick, Nancy A; Weinblatt, Michael E; Lee, Yvonne C

    2017-12-01

    Previous cross-sectional studies have shown that rheumatoid arthritis (RA) patients with fibromyalgia (FM) have higher disease activity, greater medical costs, and worse quality of life compared to RA patients without FM. We determined the impact of FM on 2-year changes in the functional status of RA patients in a prospective study. Subjects included participants in the Brigham Rheumatoid Arthritis Sequential Study who were enrolled in a substudy of the effects of pain in RA. Subjects completed questionnaires, including the Multi-Dimensional Health Assessment Questionnaire (MDHAQ) and Polysymptomatic Distress (PSD) scale, semiannually, and underwent physical examination and laboratory tests yearly. Of the 156 included RA subjects, 16.7% had FM, while 83.3% did not. In a multivariable linear regression model adjusted for age, sex, race, baseline MDHAQ score, disease duration, rheumatoid factor/cyclic citrullinated peptide antibody seropositivity, disease activity, and psychological distress, RA patients with FM had a 0.14 greater 2-year increase in MDHAQ score than RA patients without FM (P = 0.021). In secondary analyses examining the association between continuous PSD scale score and change in MDHAQ, higher PSD scale scores were significantly associated with greater 2-year increases in MDHAQ score (β coefficient 0.013, P = 0.011). Both the presence of FM and increasing number of FM symptoms predicted worsening of functional status among individuals with RA. Among individuals with RA and FM, the magnitude of the difference in changes in MDHAQ was 4- to 7-fold higher than typical changes in MDHAQ score among individuals with established RA. © 2017, American College of Rheumatology.

  2. 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...

  3. 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.

  4. 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.

  5. 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

  6. 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 ...

  7. How Much Will the Sea Level Rise? Outcome Selection and Subjective Probability in Climate Change Predictions.

    Science.gov (United States)

    Juanchich, Marie; Sirota, Miroslav

    2017-08-17

    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).

  8. Using Source Code Metrics to Predict Change-Prone Java Interfaces

    NARCIS (Netherlands)

    Romano, D.; Pinzger, M.

    2011-01-01

    Recent empirical studies have investigated the use of source code metrics to predict the change- and defect-proneness of source code files and classes. While results showed strong correlations and good predictive power of these metrics, they do not distinguish between interface, abstract or concrete

  9. 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

  10. 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...

  11. Cultural Change, Human Activity, and Cognitive Development

    Science.gov (United States)

    Gauvain, Mary; Munroe, Robert L.

    2012-01-01

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

  12. 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.

  13. European Union Financing of the Climate Change Mitigation Activity

    OpenAIRE

    Paul Calanter

    2014-01-01

    The following paper aims at analyzing the financing by the European Union of the climate change limitation and mitigation activities. The general objectives of the activities directed towards reducing and combating climate change, analyzed on the two directions of action, namely the mitigation of the phenomenon, and the adaptation to climate change, are exposed. The financing action by the EU in order to combat climate change at the international level, both the fast start financing, and medi...

  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. Global cortical activity predicts shape of hand during grasping

    Directory of Open Access Journals (Sweden)

    Harshavardhan Ashok Agashe

    2015-04-01

    Full Text Available 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 fifteen 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.

  17. 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

  18. Predicting changes of body weight, body fat, energy expenditure and metabolic fuel selection in C57BL/6 mice.

    Directory of Open Access Journals (Sweden)

    Juen Guo

    Full Text Available The mouse is an important model organism for investigating the molecular mechanisms of body weight regulation, but a quantitative understanding of mouse energy metabolism remains lacking. Therefore, we created a mathematical model of mouse energy metabolism to predict dynamic changes of body weight, body fat, energy expenditure, and metabolic fuel selection. Based on the principle of energy balance, we constructed ordinary differential equations representing the dynamics of body fat mass (FM and fat-free mass (FFM as a function of dietary intake and energy expenditure (EE. The EE model included the cost of tissue deposition, physical activity, diet-induced thermogenesis, and the influence of FM and FFM on metabolic rate. The model was calibrated using previously published data and validated by comparing its predictions to measurements in five groups of male C57/BL6 mice (N = 30 provided ad libitum access to either chow or high fat diets for varying time periods. The mathematical model accurately predicted the observed body weight and FM changes. Physical activity was predicted to decrease immediately upon switching from the chow to the high fat diet and the model coefficients relating EE to FM and FFM agreed with previous independent estimates. Metabolic fuel selection was predicted to depend on a complex interplay between diet composition, the degree of energy imbalance, and body composition. This is the first validated mathematical model of mouse energy metabolism and it provides a quantitative framework for investigating energy balance relationships in mouse models of obesity and diabetes.

  19. 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.

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

    Science.gov (United States)

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

    2017-09-01

    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.

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

    Science.gov (United States)

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

    2016-01-01

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

  2. 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

    2018-01-17

    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 105 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.

  3. 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.

  4. Predicting change over time in career planning and career exploration for high school students.

    Science.gov (United States)

    Creed, Peter A; Patton, Wendy; Prideaux, Lee-Ann

    2007-06-01

    This study assessed 166 high school students in Grade 8 and again in Grade 10. Four models were tested: (a) whether the T1 predictor variables (career knowledge, indecision, decision-making self efficacy, self-esteem, demographics) predicted the outcome variable (career planning/exploration) at T1; (b) whether the T1 predictor variables predicted the outcome variable at T2; (c) whether the T1 predictor variables predicted change in the outcome variable from T1-T2; and (d) whether changes in the predictor variables from T1-T2 predicted change in the outcome variable from T1-T2. Strong associations (R(2)=34%) were identified for the T1 analysis (confidence, ability and paid work experience were positively associated with career planning/exploration). T1 variables were less useful predictors of career planning/exploration at T2 (R(2)=9%; having more confidence at T1 was associated with more career planning/exploration at T2) and change in career planning/exploration from T1-T2 (R(2)=11%; less confidence and no work experience were associated with change in career planning/exploration from T1-T2). When testing effect of changes in predictor variables predicting changes in outcome variable (R(2)=22%), three important predictors, indecision, work experience and confidence, were identified. Overall, results indicated important roles for self-efficacy and early work experiences in current and future career planning/exploration of high school students.

  5. 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 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 levels of self-esteem at baseline predicted a smaller increase in self-esteem (β = -.48, 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.

  6. Towards actionable climate change science for S2S climate monitoring and prediction

    Science.gov (United States)

    Collins, D. C.

    2016-12-01

    A great need and challenge in the prediction and attribution of climate variability on subseasonal-to-seasonal (S2S) timescales is to identify and express the nonstationarity of S2S variability, originating from anthropogenic climate change, in a usable form. Much of actionable climate science is produced for much shorter timescales than climate change, such as subseasonal and seasonal monitoring and prediction of anomalous or extreme climate events; while much of the information from climate change science is imparted in forms that are not directly usable for S2S prediction or monitoring. Traditional analyses of both observations of S2S variability and S2S model predictions ignore the nonstationarity of the data over multiple decades, when expressing statistics of S2S events. The extensive body of knowledge on climate change impacts and the attribution of shorter timescale climate events, including extremes, should provide a pathway towards actionable climate change science for S2S climate variability. Methods of attribution of S2S climate events to climate change are advancing (National Academies of Sciences, Engineering and Medicine, 2016. Attribution of Extreme Weather Events in the Context of Climate Change. Washington, DC: The National Academies Press. doi: 10.17226/21852), but when does such information change the actions of those addressing the impacts of S2S climate variability? Robust scientific attribution of S2S climate variability to climate change should not only provide information for adaptation to there occurrence in future decades, but should help improve the interpretation and response to current subseasonal and seasonal climate events and their prediction. We describe the potential form of actionable climate information on S2S timescales and what is needed to connect recent work on climate change attribution to S2S prediction and monitoring.

  7. 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...

  8. Predicting Impacts of Lightning Strikes on Aviation under a Changing Climate Using Regression Kriging

    Science.gov (United States)

    Rakas, J.; Ding, C.; Murthi, A.; Lukovic, J.; Bajat, B.

    2016-12-01

    Lightning is a serious hazard that can cause significant impacts on human infrastructure. In the aviation industry, lightning strikes cause damage and outages to air traffic control equipment and facilities at airports that result in major disruptions in commercial air travel, compounding delays during storm events that lead to losses in the millions of dollars. To date poor attention has been given to how lightning might change with the increase of greenhouse gases and temperature. Under some climate change scenarios, the increase in the occurrence and severity of storms in the future with potential for increases in lightning activity has been studied. Recent findings suggest that lighting rates will increase 12 percent per every degree Celsius rise in global temperatures. That will results to a 50 percent increase by the end of the century. Accurate prediction of the intensity and frequency of lightning strikes is therefore required by the air traffic management and control sector in order to develop more robust adaptation and mitigation strategies under the threat of global climate change and increasing lightning rates. In this work, we use the regression kriging method to predict lightning strikes over several regions over the contiguous United Sates using two meteorological variables- namely convective available potential energy (CAPE) and total precipitation rate. These two variables are used as a measure of storm convection, since strong convections are related to more lightning. Specifically, CAPE multiplied by precipitation is used as a proxy for lightning strikes owing to a strong linear relationship between the two. These two meteorological variables are obtained from a subset of models used in phase 5 of the coupled model inter-comparison experiment pertaining to the "high emissions" climate change scenario corresponding to the representative concentration pathway (RCP) 8.5. Precipitation observations from the National Weather Cooperative Network (COOP

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

    Science.gov (United States)

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

    2004-08-15

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

  10. Possible Influence of Volcanic Activity on the Decadal Potential Predictability of the Natural Variability in Near-Term Climate Predictions

    Directory of Open Access Journals (Sweden)

    Hideo Shiogama

    2010-01-01

    Full Text Available Initialization based on data assimilations using historical observations possibly improves near-term climate predictions. Significant volcanic activity in the future is unpredictable and not assumed in future climate predictions. To examine the possible influence of unpredictable future volcanic activity on the decadal potential predictability of the natural variability, we performed a 2006–2035 climate prediction experiment with the assumption that the 1991  Mt. Pinatubo eruption would take place again in 2010. The Pinatubo forcing induced not only significant cooling responses but also considerable noises in the natural variability. The errors due to the Pinatubo forcing grew faster than that arising from imperfect knowledge of the observed state, leading to a rapid reduction of the decadal potential predictability of the natural variability.

  11. Predictive active disturbance rejection control for processes with time delay.

    Science.gov (United States)

    Zheng, Qinling; Gao, Zhiqiang

    2014-07-01

    Active disturbance rejection control (ADRC) has been shown to be an effective tool in dealing with real world problems of dynamic uncertainties, disturbances, nonlinearities, etc. This paper addresses its existing limitations with plants that have a large transport delay. In particular, to overcome the delay, the extended state observer (ESO) in ADRC is modified to form a predictive ADRC, leading to significant improvements in the transient response and stability characteristics, as shown in extensive simulation studies and hardware-in-the-loop tests, as well as in the frequency response analysis. In this research, it is assumed that the amount of delay is approximately known, as is the approximated model of the plant. Even with such uncharacteristic assumptions for ADRC, the proposed method still exhibits significant improvements in both performance and robustness over the existing methods such as the dead-time compensator based on disturbance observer and the Filtered Smith Predictor, in the context of some well-known problems of chemical reactor and boiler control problems. © 2013 Published by ISA on behalf of ISA.

  12. Extremely Randomized Machine Learning Methods for Compound Activity Prediction.

    Science.gov (United States)

    Czarnecki, Wojciech M; Podlewska, Sabina; Bojarski, Andrzej J

    2015-11-09

    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.

  13. 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.

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

    NARCIS (Netherlands)

    Bakker, M.M.; Veldkamp, A.

    2012-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  16. 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…

  17. Strong artificial selection in the wild results in predicted small evolutionary change

    NARCIS (Netherlands)

    Postma, E.; Visser, J.; Van Noordwijk, A.J.

    2007-01-01

    Estimates of genetic variation and selection allow for quantitative predictions of evolutionary change, at least in controlled laboratory experiments. Natural populations are, however, different in many ways, and natural selection on heritable traits does not always result in phenotypic change. To

  18. 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...

  19. 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...

  20. Reversed optimality and predictive ecology : burrowing depth forecasts population change in a bivalve

    NARCIS (Netherlands)

    van Gils, Jan A.; Kraan, Casper; Dekinga, Anne; Koolhaas, Anita; Drent, Jan; de Goeij, Petra; Piersma, Theunis

    2009-01-01

    Optimality reasoning from behavioural ecology can be used as a tool to infer how animals perceive their environment. Using optimality principles in a 'reversed manner' may enable ecologists to predict changes in population size before such changes actually happen. Here we show that a behavioural

  1. 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

  2. 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.

  3. Do early therapeutic alliance, motivation, and stages of change predict therapy change for high-risk, psychopathic violent prisoners?

    Science.gov (United States)

    Polaschek, Devon L L; Ross, Elizabeth C

    2010-04-01

    Examination of the extent of offenders' engagement in change, and in rehabilitation programmes, is important to understanding success or failure following rehabilitation. In treatment programmes, the alliance between therapist and offender, and the therapy process itself appear central to progress offenders make that may reduce their criminal risk. But research with offenders seldom has measured therapeutic alliance and clinical writing suggests that it is difficult to form an alliance with those not ready to change their behaviour; especially with higher risk and psychopathic offenders. This study outlines the course of the therapeutic alliance in an 8-month treatment programme for high-risk, PCL-psychopathic violent prisoners. It examines relationships between early-treatment therapeutic alliance, therapists' global ratings of motivation to change, and initial stage of change on dynamic risk factors. In addition, it investigates which factors best predict who will complete treatment and change behaviourally during treatment. In this challenging, high-needs client group, early-programme stage of change, therapists' perceptions of motivation, therapeutic alliance and psychopathy did not predict how much change prisoners made. Regardless of initial levels, prisoners whose alliance increased the most over the course of treatment made the most change.

  4. 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...

  5. Prediction of enzyme mutant activity using computational mutagenesis and incremental transduction.

    Science.gov (United States)

    Basit, Nada; Wechsler, Harry

    2011-01-01

    Wet laboratory mutagenesis to determine enzyme activity changes is expensive and time consuming. This paper expands on standard one-shot learning by proposing an incremental transductive method (T2bRF) for the prediction of enzyme mutant activity during mutagenesis using Delaunay tessellation and 4-body statistical potentials for representation. Incremental learning is in tune with both eScience and actual experimentation, as it accounts for cumulative annotation effects of enzyme mutant activity over time. The experimental results reported, using cross-validation, show that overall the incremental transductive method proposed, using random forest as base classifier, yields better results compared to one-shot learning methods. T2bRF is shown to yield 90% on T4 and LAC (and 86% on HIV-1). This is significantly better than state-of-the-art competing methods, whose performance yield is at 80% or less using the same datasets.

  6. Prediction of Enzyme Mutant Activity Using Computational Mutagenesis and Incremental Transduction

    Directory of Open Access Journals (Sweden)

    Nada Basit

    2011-01-01

    Full Text Available Wet laboratory mutagenesis to determine enzyme activity changes is expensive and time consuming. This paper expands on standard one-shot learning by proposing an incremental transductive method (T2bRF for the prediction of enzyme mutant activity during mutagenesis using Delaunay tessellation and 4-body statistical potentials for representation. Incremental learning is in tune with both eScience and actual experimentation, as it accounts for cumulative annotation effects of enzyme mutant activity over time. The experimental results reported, using cross-validation, show that overall the incremental transductive method proposed, using random forest as base classifier, yields better results compared to one-shot learning methods. T2bRF is shown to yield 90% on T4 and LAC (and 86% on HIV-1. This is significantly better than state-of-the-art competing methods, whose performance yield is at 80% or less using the same datasets.

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

    Directory of Open Access Journals (Sweden)

    Sharifuddin M. Zain

    2011-11-01

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

  8. Seasonal changes in the learning and activity patterns of goldfish.

    Science.gov (United States)

    Shashoua, V E

    1973-08-10

    Goldfish exhibit cyclic changes with an annual rhythm in their learning and activity patterns. Maximum learning ability and active behavior occurred during the months of January, February, and March. Poor learning was obtained in the summer months, after the onset of the spawning season. The results indicate that the annual periodic changes of the hormonal levels which govern spawning may also influence learning and activity patterns.

  9. 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...

  10. 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.

  11. A Longitudinal Evaluation of Physical Activity in Brazilian Adolescents: Tracking, Change and Predictors

    Science.gov (United States)

    Dumith, Samuel C.; Gigante, Denise P.; Domingues, Marlos R.; Hallal, Pedro C.; Menezes, Ana M.B.; Kohl, Harold W.

    2013-01-01

    This study aimed to: 1) describe the change in leisure-time physical activity (LTPA) during early-to-mid adolescence; 2) analyze the tracking of LTPA; 3) identify the predictors of LTPA change. 4,120 adolescents were from 11 to 15 years old. Outcome was self-reported LTPA (min/wk). Boys increased their LTPA level over the four years (mean: 75 min/wk; 95%CI: 49,100), whereas a decrease was observed among girls (mean: −42 min/wk; 95%CI: −57,−28). Likelihood to be active at 15 years of age was 50% higher (95%CI: 39–62) among those who were active at 11 years. The main predictor of LTPA change was the number of physical activities performed at baseline. Regular physical activity early in life can predict this behavior afterward. PMID:22433265

  12. 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.

  13. Predicting anti-androgenic activity of bisphenols using molecular docking and quantitative structure-activity relationships.

    Science.gov (United States)

    Yang, Xianhai; Liu, Huihui; Yang, Qian; Liu, Jining; Chen, Jingwen; Shi, Lili

    2016-11-01

    Both in vivo and in vitro assay indicated that bisphenols can inhibit the androgen receptor. However, the underlying antagonistic mechanism is unclear. In this study, molecular docking was employed to probe the interaction mechanism between bisphenols and human androgen receptor (hAR). The binding pattern of ligands in hAR crystal structures was also analyzed. Results show that hydrogen bonding and hydrophobic interactions are the dominant interactions between the ligands and hAR. The critical amino acid residues involved in forming hydrogen bonding between bisphenols and hAR is Asn 705 and Gln 711. Furthermore, appropriate molecular structural descriptors were selected to characterize the non-bonded interactions. Stepwise multiple linear regressions (MLR) analysis was employed to develop quantitative structure-activity relationship (QSAR) models for predicting the anti-androgenic activity of bisphenols. Based on the QSAR development and validation guideline issued by OECD, the goodness-of-fit, robustness and predictive ability of constructed QSAR model were assessed. The model application domain was characterized by the Euclidean distance and Williams plot. The mechanisms of the constructed model were also interpreted based on the selected molecular descriptors i.e. the number of hydroxyl groups (nROH), the most positive values of the molecular surface potential (Vs,max) and the lowest unoccupied molecular orbital energy (ELUMO). Finally, based on the model developed, the data gap for other twenty-six bisphenols on their anti-androgenic activity was filled. The predicted results indicated that the anti-androgenic activity of seven bisphenols was higher than that of bisphenol A. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Performance prediction of circular dielectric electro-active polymers membrane actuators with various geometries

    Science.gov (United States)

    Hau, Steffen; York, Alexander; Seelecke, Stefan

    2015-04-01

    Circular dielectric electro-active polymer (DEAP) membrane actuators are easy to manufacture and therefore can be uniquely designed to perform optimally for specific applications. The performance of these actuators is naturally dependent on the materials used, and also dictated by the specific geometry of the circular design. For a given overall actuator size, changing their internal geometry will directly change the force and stroke output. In addition the DEAP technology itself is a promising technology for constructing lightweight, cost and energy efficient sensor and actuator systems. Thus, several potential applications like pressure sensors, pumps, valves, micro-positioners and loudspeakers were already proposed. The circular DEAP membrane actuators used in this study consist of a silicone based elastomer, carbon ink based electrodes, and are held together with a stiff frame. Experimentally collected force-displacement curves for these actuators can be used to determine force and stroke output of the actuators as described by Hodgins et al. in. This work presents an efficient method to predict these force-displacement plots and thus stroke and force output for different actuator geometries. These results than can be used to adapt the actuator geometry to the needs of a specific application with its particular force and stroke requirements. The prediction method is based on an average stress-stretch calculation for training samples. The calculated stress-stretch data is then geometry independent and can be used to predict desired geometry dependent force-displacement data for stroke and force output analysis.

  15. Predicting Classroom Achievement from Active Responding on a Computer-Based Groupware System.

    Science.gov (United States)

    Shin, Jongho; Deno, Stanley L.; Robinson, Steven L.; Marston, Douglas

    2000-01-01

    The predictive validity of active responding on a computer-based groupware system was examined with 48 second graders. Results showed that active responding correlated highly with initial and final performance measures and that active responding contributed significantly to predicting final performance when initial performance was controlled.…

  16. Sensitivity to Physical Activity Predicts Daily Activity Among Pain-Free Older Adults.

    Science.gov (United States)

    Miller, Leah; Ohlman, Thomas; Naugle, Kelly Marie

    2017-10-04

    Prior research indicates that older adults with knee osteoarthritis have increased sensitivity to physical activity (SPA) and respond to physical activities of stable intensity with increases in pain. Whether SPA is present in healthy older adults without chronic pain and predicts functional outcomes remains relatively unexplored. The purpose of this study was to determine the degree of SPA in healthy older adults in response to a standardized walking task, and whether SPA was associated with temporal summation of pain, pain-related fear of movement, and functional outcomes. Fifty-two older adults without chronic pain completed self-reported measures of activity-related pain and physical function, completed the Six-Minute Walk Test (6MWT), underwent quantitative sensory testing to measure temporal summation of heat pain, and wore an accelerometer for one week to measure physical activity behavior. Subjects rated overall bodily discomfort (0-100 scale) prior to and during each minute of the 6MWT. An SPA index was created by subtracting the initial bodily discomfort ratings from the peak ratings. Repeated-measures analysis of variance indicated that bodily discomfort significantly increased across the walking task, with approximately 60% of the sample experiencing SPA. Hierarchical regressions indicated that greater SPA was associated with fewer average steps per day and greater activity-related pain. Additionally, analyses revealed that temporal summation of pain and pain-related fear of movement significantly predicted the degree of SPA on the walking task. These findings shed light on potential mechanisms underlying SPA in older adults and suggest that SPA might be a risk factor for reduced physical activity.

  17. 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.

  18. 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.

  19. 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

  20. Interactive Land Use-Climate Change Predictions in West Africa: Preliminary Results

    Science.gov (United States)

    Wang, G.; Ahmed, K. F.; You, L.; Koo, J.

    2013-12-01

    Land use changes constitute an important regional climate change forcing that modifies the greenhouse gas induced future climate changes. At the same time, climate change is an important driver for land use changes, although it is unclear how important this impact might be relative to the impact of socio-economic factors on future land use. Using West Africa as an example, this study examines the importance of considering land use-climate change interactions in decadal predictions for future land use and climate changes, and thus assess whether there is a strong need to incorporate land use modeling into earth system models. Specifically, we evaluate the impact of projected climate changes from a regional climate model (RegCM4-CLM4) on crop yields using the crop model DSSAT, and assess the need for future land use changes by combining crop yield changes with demand for local productions predicted based on socio-economic drivers using an economic model (IFPRI's IMPACT model). For this preliminary assessment, a simple land use allocation approach is used, which favors agricultural expansion over intensification in order to provide an upper limit for land use changes. As a first test, the RCP8.5 mid-century climate projected by the NCAR CESM model is used as the future climate boundary conditions to drive the regional climate model. The impact of considering the land use-climate change interactions will be evaluated based on the differences in projected climate changes between two types of simulations: one that considers land use changes driven by both climate-induced crop yield changes and socioeconomic factors, and one that considers land use changes driven solely by socioeconomic factors.

  1. 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

  2. Urbanization Impact on Temperature Change in China with Emphasis on Land Cover Change and Human Activity

    National Research Council Canada - National Science Library

    Li, Yan; Zhu, Lijuan; Zhao, Xinyi; Li, Shuangcheng; Yan, Yan

    2013-01-01

    ... in the study area have been converted from nonurban to urban stations as a result of land cover change associated with urban expansion. It was determined that both land cover change and human activity play important roles in temperature change and contribute to the observed warming, particularly in urbanized stations, where the highest amount of war...

  3. 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.

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

    Science.gov (United States)

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

    2017-07-01

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

  5. Body Image and Body Change: Predictive Factors in an Iranian Population

    OpenAIRE

    Behshid Garrusi; Saeide Garousi; 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-cultura...

  6. Life history trade-off moderates model predictions of diversity loss from climate change.

    Directory of Open Access Journals (Sweden)

    Helen Moor

    Full Text Available Climate change can trigger species range shifts, local extinctions and changes in diversity. Species interactions and dispersal capacity are important mediators of community responses to climate change. The interaction between multispecies competition and variation in dispersal capacity has recently been shown to exacerbate the effects of climate change on diversity and to increase predictions of extinction risk dramatically. Dispersal capacity, however, is part of a species' overall ecological strategy and are likely to trade off with other aspects of its life history that influence population growth and persistence. In plants, a well-known example is the trade-off between seed mass and seed number. The presence of such a trade-off might buffer the diversity loss predicted by models with random but neutral (i.e. not impacting fitness otherwise differences in dispersal capacity. Using a trait-based metacommunity model along a warming climatic gradient the effect of three different dispersal scenarios on model predictions of diversity change were compared. Adding random variation in species dispersal capacity caused extinctions by the introduction of strong fitness differences due an inherent property of the dispersal kernel. Simulations including a fitness-equalising trade-off based on empirical relationships between seed mass (here affecting dispersal distance, establishment probability, and seedling biomass and seed number (fecundity maintained higher initial species diversity and predicted lower extinction risk and diversity loss during climate change than simulations with variable dispersal capacity. Large seeded species persisted during climate change, but developed lags behind their climate niche that may cause extinction debts. Small seeded species were more extinction-prone during climate change but tracked their niches through dispersal and colonisation, despite competitive resistance from residents. Life history trade-offs involved in

  7. Predicting the effect of climate change on African trypanosomiasis: integrating epidemiology with parasite and vector biology.

    Science.gov (United States)

    Moore, Sean; Shrestha, Sourya; Tomlinson, Kyle W; Vuong, Holly

    2012-05-07

    Climate warming over the next century is expected to have a large impact on the interactions between pathogens and their animal and human hosts. Vector-borne diseases are particularly sensitive to warming because temperature changes can alter vector development rates, shift their geographical distribution and alter transmission dynamics. For this reason, African trypanosomiasis (sleeping sickness), a vector-borne disease of humans and animals, was recently identified as one of the 12 infectious diseases likely to spread owing to climate change. We combine a variety of direct effects of temperature on vector ecology, vector biology and vector-parasite interactions via a disease transmission model and extrapolate the potential compounding effects of projected warming on the epidemiology of African trypanosomiasis. The model predicts that epidemics can occur when mean temperatures are between 20.7°C and 26.1°C. Our model does not predict a large-range expansion, but rather a large shift of up to 60 per cent in the geographical extent of the range. The model also predicts that 46-77 million additional people may be at risk of exposure by 2090. Future research could expand our analysis to include other environmental factors that influence tsetse populations and disease transmission such as humidity, as well as changes to human, livestock and wildlife distributions. The modelling approach presented here provides a framework for using the climate-sensitive aspects of vector and pathogen biology to predict changes in disease prevalence and risk owing to climate change.

  8. 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.

  9. Parabolic dunes and their transformations under environmental and climatic changes: Towards a conceptual framework for understanding and prediction

    Science.gov (United States)

    Yan, Na; Baas, Andreas C. W.

    2015-01-01

    The formation and evolution of parabolic aeolian dunes depend on vegetation, and as such are particularly sensitive to changes in environmental controls (e.g., temperature, precipitation, and wind regime) as well as to human disturbances (e.g., grazing, agriculture, and recreation). Parabolic dunes can develop from the stabilisation of highly mobile barchan dunes and transverse dunes as well as from blowouts, as a consequence of colonisation and establishment of vegetation when aeolian sand transport is reduced and/or when water stress is relieved (by increasing precipitation, for instance). Conversely, existing parabolic dunes can be activated and may be transformed into barchan dunes and/or transverse dunes when vegetation suffers environmental or anthropogenic stresses. Predicted increases in temperature and drought severity in various regions raise concerns that dune activation and transformations may intensify, and this intensification would have far-reaching implications for environmental, social, and economic sustainability. To date, a broad examination of the development of parabolic dunes and their related transformations across a variety of climate gradients has been absent. This paper reviews existing literature, compares data on the morphology and development of parabolic dunes in a comprehensive global inventory, and scrutinises the mechanisms of different dune transformations and the eco-geomorphic interactions involved. This knowledge is then integrated into a conceptual framework to facilitate understanding and prediction of potential aeolian dune transformations induced by changes in environmental controls and human activities. This conceptual framework can aid judicious land management policies for better adaptations to climatic changes.

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

    OpenAIRE

    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 st...

  11. Uncertain future soil carbon dynamics under global change predicted by models constrained by total carbon measurements.

    Science.gov (United States)

    Luo, Zhongkui; Wang, Enli; Sun, Osbert J

    2017-04-01

    Pool-based carbon (C) models are widely applied to predict soil C dynamics under global change and infer underlying mechanisms. However, it is unclear about the credibility of model-predicted C pool size, decay rate (k), and/or microbial C use efficiency (e) as only data on bulked total C is usually available for model constraining. Using observing system simulation experiments (OSSE), we constrained a two-pool model using simulated data sets of total soil C dynamics under topical hypotheses on responses of soil C dynamics to warming and elevated CO2 (i.e., global change scenarios). The results indicated that the model predicted great uncertainties in C pool size, k, and e under all global change scenarios, resulting in the difficulty to correctly infer the presupposed "real" values of those parameters that are used to generate the simulated total soil C for constraining the model. Furthermore, the model using the constrained parameters generated divergent future soil C dynamics. Compared with the predictions using the presupposed real parameters (i.e., the real future C dynamics), the percentage uncertainty in 100-yr predictions using the constrained parameters was up to 45% depending on global change scenarios and data availability for model-constraining. Such great uncertainty was mainly due to the high collinearity among the model parameters. Using pool-based models, we argue that soil C pool size, k, and/or e and their responses to global change have to be estimated explicitly and empirically, rather than through model-fitting, in order to accurately predict C dynamics and infer underlying mechanisms. The OSSE approach provides a powerful way to identify data requirement for the new generation of model development and test model performance. © 2017 by the Ecological Society of America.

  12. Habits predict physical activity on days when intentions are weak.

    Science.gov (United States)

    Rebar, Amanda L; Elavsky, Steriani; Maher, Jaclyn P; Doerksen, Shawna E; Conroy, David E

    2014-04-01

    Physical activity is regulated by controlled processes, such as intentions, and automatic processes, such as habits. Intentions relate to physical activity more strongly for people with weak habits than for people with strong habits, but people's intentions vary day by day. Physical activity may be regulated by habits unless daily physical activity intentions are strong. University students (N = 128) self-reported their physical activity habit strength and subsequently self-reported daily physical activity intentions and wore an accelerometer for 14 days. On days when people had intentions that were weaker than typical for them, habit strength was positively related to physical activity, but on days when people had typical or stronger intentions than was typical for them, habit strength was unrelated to daily physical activity. Efforts to promote physical activity may need to account for habits and the dynamics of intentions.

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  14. Rapid changes in brain structure predict improvements induced by perceptual learning.

    Science.gov (United States)

    Ditye, Thomas; Kanai, Ryota; Bahrami, Bahador; Muggleton, Neil G; Rees, Geraint; Walsh, Vincent

    2013-11-01

    Practice-dependent changes in brain structure can occur in task relevant brain regions as a result of extensive training in complex motor tasks and long-term cognitive training but little is known about the impact of visual perceptual learning on brain structure. Here we studied the effect of five days of visual perceptual learning in a motion-color conjunction search task using anatomical MRI. We found rapid changes in gray matter volume in the right posterior superior temporal sulcus, an area sensitive to coherently moving stimuli, that predicted the degree to which an individual's performance improved with training. Furthermore, behavioral improvements were also predicted by volumetric changes in an extended white matter region underlying the visual cortex. These findings point towards quick and efficient plastic neural mechanisms that enable the visual brain to deal effectively with changing environmental demands. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. Predicting responses to climate change requires all life-history stages.

    Science.gov (United States)

    Zeigler, Sara

    2013-01-01

    In Focus: Radchuk, V., Turlure, C. & Schtickzelle, N. (2013) Each life stage matters: the importance of assessing response to climate change over the complete life cycle in butterflies. Journal of Animal Ecology, 82, 275-285. Population-level responses to climate change depend on many factors, including unexpected interactions among life history attributes; however, few studies examine climate change impacts over complete life cycles of focal species. Radchuk, Turlure & Schtickzelle () used experimental and modelling approaches to predict population dynamics for the bog fritillary butterfly under warming scenarios. Although they found that warming improved fertility and survival of all stages with one exception, populations were predicted to decline because overwintering larvae, whose survival declined with warming, were disproportionately important contributors to population growth. This underscores the importance of considering all life history stages in analyses of climate change's effects on population dynamics. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

  16. Spontaneous activity in the precuneus predicts individual differences in verbal fluency in cognitively normal elderly.

    Science.gov (United States)

    Yin, Shufei; Zhu, Xinyi; He, Rongqiao; Li, Rui; Li, Juan

    2015-11-01

    The precuneus is 1 of the major cortical hubs and plays an important role in normal aging and verbal fluency processing. The main aim of present study was to investigate how intrinsic brain activity in the precuneus at rest predicts individual differences in verbal fluency ability among elderly adults. Regional amplitude of low-frequency fluctuations (ALFF) analysis and a correlation-based functional connectivity (FC) approach were used to analyze data acquired from 101 cognitively normal elderly. ALFF in the precuneus declined with normal aging and was significantly correlated with individual differences in performance on the verbal fluency test (VFT). Specifically, ALFF in the precuneus was reduced in elderly with high fluency (HF) ability compared with those with low fluency (LF) ability. In addition, the HF individuals displayed increased functional connectivity of the precuneus with the lateral temporal area and prefrontal lobe, including the inferior frontal, medial frontal, superior temporal, middle temporal, and superior frontal gyri. Spontaneous activity in the precuneus could predict individual differences in verbal fluency processing. Our results suggest that spontaneous activity in the precuneus is an indicator of aging-related changes in semantic verbal fluency processing, or even a potential biomarker for the early detection of semantic verbal fluency deterioration. (c) 2015 APA, all rights reserved).

  17. Preseismic Velocity Changes Observed from Active Source Monitoringat the Parkfield SAFOD Drill Site

    Energy Technology Data Exchange (ETDEWEB)

    Daley, Thomas; Niu, Fenglin; Silver, Paul G.; Daley, Thomas M.; Cheng, Xin; Majer, Ernest L.

    2008-06-10

    Measuring stress changes within seismically active fault zones has been a long-sought goal of seismology. Here we show that such stress changes are measurable by exploiting the stress dependence of seismic wave speed from an active source cross-well experiment conducted at the SAFOD drill site. Over a two-month period we observed an excellent anti-correlation between changes in the time required for an S wave to travel through the rock along a fixed pathway--a few microseconds--and variations in barometric pressure. We also observed two large excursions in the traveltime data that are coincident with two earthquakes that are among those predicted to produce the largest coseismic stress changes at SAFOD. Interestingly, the two excursions started approximately 10 and 2 hours before the events, respectively, suggesting that they may be related to pre-rupture stress induced changes in crack properties, as observed in early laboratory studies.

  18. Repeated predictable or unpredictable stress: effects on cocaine-induced locomotion and cyclic AMP-dependent protein kinase activity.

    Science.gov (United States)

    Araujo, Ana Paula N; DeLucia, Roberto; Scavone, Cristoforo; Planeta, Cleopatra S

    2003-02-17

    Stressful experiences appear to have a strong influence on susceptibility to drug taking behavior. Cross-sensitization between stress and drug-induced locomotor response has been found. Locomotor response to novelty or cocaine (10 mg/kg, i.p.), cyclic AMP-dependent protein kinase (PKA) activity in the nucleus accumbens and basal corticosterone levels were evaluated in male adult rats exposed to acute and chronic predictable or unpredictable stress. Rats exposed to a 14-day predictable stress showed increased locomotor response to novelty and to cocaine, whereas rats exposed to chronic unpredictable stress demonstrated increased cyclic AMP-dependent PKA activity in the nucleus accumbens. Both predictable and unpredictable stress increased basal corticosterone plasma levels. These experiments demonstrated that stress-induced early cocaine sensitization depends on the stress regime and is apparently dissociated from stress-induced changes in cyclic AMP-dependent PKA activity and corticosterone levels.

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

    African Journals Online (AJOL)

    /tjpr.v14i1.15. Original Research Article. Larvicidal activity of Illicium difengpi BN Chang. (Schisandraceae) Stem Bark and its Constituent. Compounds against Aedes aegypti L. Ying Liu1,2,3, Xin Chao Liu1, Qi Yong Liu2, Chang Niu3 and Zhi ...

  20. 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 ...

  1. 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...

  2. Stage of physical activity change and correlates among ...

    African Journals Online (AJOL)

    Conclusion: Most hypertensives in the outpatient setting are in inactive stages of change (83.6%), but the unemployed are more likely to be in active stage. Physicians managing hypertensives should offer more cognitive-based change counselling, and exercise prescriptions that consider employment status. Key words: ...

  3. 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.

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

    Science.gov (United States)

    Mella, Nathalie; Grob, Emmanuelle; Döll, Salomé; Ghisletta, Paolo; de Ribaupierre, Anik

    2017-01-01

    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. PMID:28257047

  5. 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.

  6. Predicting Plasma Olanzapine Concentration Following a Change in Dosage: A Population Pharmacokinetic Study.

    Science.gov (United States)

    Tsuboi, T; Bies, R R; Suzuki, T; Takeuchi, H; Nakajima, S; Graff-Guerrero, A; Mamo, D C; Caravaggio, F; Plitman, E; Mimura, M; Pollock, B G; Uchida, H

    2015-11-01

    Due to high inter-individual variability in peripheral pharmacokinetic parameters, dosing of antipsychotics currently relies on clinical trial-and-error, and predicting antipsychotic plasma concentrations before changing a dose has been a challenge. Patients with schizophrenia receiving a stable dose of olanzapine were included. 2 plasma samples were collected at 2 given time points for the measurement of plasma olanzapine concentrations. At least 7 days after a dosage change of olanzapine, a third sample was collected. The plasma concentration of the third sample was predicted in a blinded fashion using a mixed-effects model with NONMEM(®), using the following information: the 2 baseline plasma concentrations, the interval between the last dose and blood draw, and clinical and demographic information. 31 subjects (mean±SD age=56.0±11.6; 19 men) were enrolled. The mean prediction (95% confidence interval) errors were 1.6 (-2.8 to 6.0) ng/mL. A highly significant correlation was observed between the observed and predicted concentrations of the third sample (r=0.91, p<0.001). Plasma olanzapine concentrations following an actual dosage change can be predicted in advance with a high degree of certainty. © Georg Thieme Verlag KG Stuttgart · New York.

  7. Predicting opponent team activity in a RoboCup environment

    OpenAIRE

    Baez, Selene

    2015-01-01

    The goal of this project is to predict the opponent's configuration in a RoboCup SSL environment. For simplicity, a Markov model assumption is made such that the predicted formation of the opponent team only depends on its current formation. The field is divided into a grid and a robot state per player is created with information about its position and its velocity. To gather a more general sense of what the opposing team is doing, the state also incorporates the team's average position (cent...

  8. 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...... to cope with this problem but, generally, they assume that the underlying process is stationary. However, in real cases this assumption is not always true. In this work we present new methods for predicting the remaining time of running cases. In particular we propose a method, assuming process...

  9. JAXA Activities on Prediction of Vibroacoustic Prediction for Panel Mounted Equipments

    Science.gov (United States)

    Akagi, Hiroki; Ando, Shigemasa; Yanagase, Keiichi; Shi, Qinzhong

    2012-07-01

    Spacecraft is exposed to the severe random vibration by acoustic during its launch. In the spacecraft design, random vibration of spacecraft equipments mounted on panel structure during launch environments needs to be predicted. In the present methods, SEA is the method for analyzing the high frequency band, FEA is for the low frequency band. This paper introduces major methods of recent years to predict the vibroacoustic response of spacecraft structure, including SEA, Joint Acceptance and most recent approach using Combination of FEA and SEA methods. The Combination method focuses on the vibroacoustic prediction which keeps advantages to use detail model of structure expressed by FEA and statistical energy approach expressed by SEA of reverberant acoustic excitation. These methods are applied to diffuse sound field excitation of honeycomb panel, and compared with the results in test verification.

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

    African Journals Online (AJOL)

    Conclusion: Na+- K+ATPase specific activity is a biomarker for the diagnosis of individuals with different physiological diseases. Keywords: Na+-K+ATPase ... aging and that changes in young females were more re- markable than that in young .... activity which might be due to increased / decreased con- centration of ions ...

  11. Changes in Total Protein and Transaminase Activities in Clarias ...

    African Journals Online (AJOL)

    Changes in Total Protein and Transaminase Activities in Clarias Gariepinus Exposed to Diazinon. ... Animal Production Research Advances ... The aim of the study was to assess the effects induced by diazinon on total protein and transaminase activities in Clarias gariepinus, a common Niger Delta wetland fish. Fish were ...

  12. Phosalone-Induced Changes in Regional Cholinesterase Activities ...

    African Journals Online (AJOL)

    Phosalone-Induced Changes in Regional Cholinesterase Activities in Rat Brain during Behavioral Tolerance. ... PROMOTING ACCESS TO AFRICAN RESEARCH ... The present study was undertaken to examine the activity levels of cholinesterases in different regions of rat brain during the development of behavioral ...

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

    Science.gov (United States)

    Qin, Pengmin; Duncan, Niall W.; Wiebking, Christine; Gravel, Paul; Lyttelton, Oliver; Hayes, Dave J.; Verhaeghe, Jeroen; Kostikov, Alexey; Schirrmacher, Ralf; Reader, Andrew J.; Northoff, Georg

    2012-01-01

    Recent imaging studies have demonstrated that levels of resting γ-aminobutyric acid (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 modeling 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 to 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 predicted the change in functional connectivity between the 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. PMID:23293594

  14. 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.

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

    NARCIS (Netherlands)

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

    2016-01-01

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

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

    NARCIS (Netherlands)

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

    2016-01-01

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

  17. Predicting Changes in Cultural Sensitivity among Students of Spanish during Short-Term Study Abroad

    Science.gov (United States)

    Martinsen, Rob

    2011-01-01

    Short-term study abroad programs of less than a semester are becoming increasingly popular among undergraduate students in the United States. However, little research has examined the changes in students' cultural sensitivity through their participation in such programs or what factors may predict growth and improvement in such areas. This study…

  18. 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...

  19. Emotion regulation predicts change of perceived health in patients with rheumatoid arthritis

    NARCIS (Netherlands)

    van Middendorp, H; Geenen, R; Sorbi, MJ; van Doornen, LJP; Bijlsma, JWJ

    Objectives: To examine whether emotion regulation predicts change of perceived health in patients with rheumatoid arthritis ( RA). Methods: Sixty six patients ( 44 female, 22 male; mean (SD) age 57.7 (11.6) years) participated in a prospective study. Hierarchical regression analysis was used to

  20. 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…

  1. 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...

  2. 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 ...

  3. 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.

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

    Science.gov (United States)

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

    2015-02-01

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

  5. 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...

  6. Prediction of User Context Using Smartphone Activity Data

    Science.gov (United States)

    2016-07-22

    Jie Yang. 2003. Predicting Human Interruptibility with Sensors: A Wizard of Oz Feasibility Study. In Proc. 2003 SIGCHI Conf. on Human Factors in...Assessing the Availability of Users to Engage in Just-in-Time Intervention in the Natural Environment. In Proc. 2014 ACM Int’l Joint Conf. on

  7. 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.

  8. Predicting the toxicity of substituted phenols to aquatic species and its changes in the stream and effluent waters.

    Science.gov (United States)

    Lee, Yong G; Hwang, Seok H; Kim, Sang D

    2006-02-01

    The changes in the acute toxicity of 16 phenols toward Selenastrum capricornutum and Daphnia magna were examined as a function of their physical/chemical properties. The results demonstrated that phenols with a higher octanol-water partition coefficient (K(ow)) had a higher toxicity toward aquatic organisms. The toxicity of phenols was closely related to the log K(ow) values, with correlation coefficients of 0.93 (except for the nitrophenols) and 0.89 for S. capricornutum and D. magna, respectively. The changes in the phenols toxicities in the site waters (i.e., stream and effluent waters) were investigated by calculating the water effect ratios (WER) from the results of the toxicity tests in the site waters using D. magna. The results showed that the degree of ionization for each phenolic compound was altered by the differences in the dissociation constant (pK(a)), and the change in the toxicity could be predicted. Therefore, the WER should be considered when the toxicity of phenolic compounds is estimated in site waters. The quantitative structure-activity relationships (QSAR) study showed that the toxicity of the phenols to D. magna could be predicted by the hydrophobicity (log K(ow)) alone and by combining the log K(ow) with pK(a), while the toxicity to S. capricornutum was predicted by a combination of hydrophobicity (log K(ow)) and E(LUMO) (or pK(a)).

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Blake A Grisham

    Full Text Available 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 Niña 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.

  11. Collegiate Heavy Drinking Prospectively Predicts Change in Sensation Seeking and Impulsivity

    Science.gov (United States)

    Quinn, Patrick D.; Stappenbeck, Cynthia A.; Fromme, Kim

    2011-01-01

    Recent models of alcohol use in youth and young adulthood have incorporated personality change and maturation as causal factors underlying variability in developmental changes in heavy drinking. Whereas these models assume that personality affects alcohol use, the current prospective study tested the converse relation. That is, we tested whether, after accounting for the effect of traits on drinking, collegiate heavy drinking in turn predicted individual differences in change in alcohol-related aspects of personality. We also examined whether affiliation with heavy-drinking peers better accounted for this relation. Following a cohort of recent high school graduates (N = 1,434) through the college years, we found evidence for transactional relations between heavy drinking and changes in impulsivity and sensation seeking. Both traits predicted increases in heavy drinking, but more importantly, heavy drinking predicted increases in sensation seeking and impulsivity. In final models, social influences did not underlie the effect of heavy drinking on increases in sensation seeking and impulsivity. The results of this investigation suggest that collegiate heavy drinking may negatively and pervasively impact a wide range of behaviors because of its effect on personality change. PMID:21443288

  12. 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.

  13. 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...

  14. Changes in physical activity and all-cause mortality in COPD.

    Science.gov (United States)

    Vaes, Anouk W; Garcia-Aymerich, Judith; Marott, Jacob L; Benet, Marta; Groenen, Miriam T J; Schnohr, Peter; Franssen, Frits M E; Vestbo, Jørgen; Wouters, Emiel F M; Lange, Peter; Spruit, Martijn A

    2014-11-01

    Little is known about changes in physical activity in subjects with chronic obstructive pulmonary disease (COPD) and its impact on mortality. Therefore, we aimed to study changes in physical activity in subjects with and without COPD and the impact of physical activity on mortality risk. Subjects from the Copenhagen City Heart Study with at least two consecutive examinations were selected. Each examination included a self-administered questionnaire and clinical examination. 1270 COPD subjects and 8734 subjects without COPD (forced expiratory volume in 1 s 67±18 and 91±15% predicted, respectively) were included. COPD subjects with moderate or high baseline physical activity who reported low physical activity level at follow-up had the highest hazard ratios of mortality (1.73 and 2.35, respectively; both pphysical activity, no differences were found in survival between unchanged or increased physical activity at follow-up. In addition, subjects without COPD with low physical activity at follow-up had the highest hazard ratio of mortality, irrespective of baseline physical activity level (p≤0.05). A decline to low physical activity at follow-up was associated with an increased mortality risk in subjects with and without COPD. These observational data suggest that it is important to assess and encourage physical activity in the earliest stages of COPD in order to maintain a physical activity level that is as high as possible, as this is associated with better prognosis. ©ERS 2014.

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

    Directory of Open Access Journals (Sweden)

    Guoxing Li

    2015-01-01

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

  16. 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.

  17. 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) ...

  18. A predictive control algorithm for an active three-phase power filter

    Directory of Open Access Journals (Sweden)

    R.V. Vlasenko

    2014-09-01

    Full Text Available The paper deals with grid connection circuits for active filters, structures of active power filter control systems, and methods based on full capacity components determination. The existing structures of active power filter control and control algorithm adjustment for valve commutation loss reduction are analyzed. A predictive control algorithm for an active three-phase power filter is introduced.

  19. Changes in thigh muscle volume predict bone mineral density response to lifestyle therapy in frail, obese older adults.

    Science.gov (United States)

    Armamento-Villareal, R; Aguirre, L; Napoli, N; Shah, K; Hilton, T; Sinacore, D R; Qualls, C; Villareal, D T

    2014-02-01

    We studied the relationships among strength, muscle mass, and bone mineral density (BMD) with lifestyle change. Lifestyle therapy consisted of exercise, diet, and diet plus exercise. Diet was by caloric restriction to induce and maintain a weight loss of 10 % from baseline body weight. Exercise attenuated weight loss-induced muscle and bone losses. Exercise improved strength despite muscle loss in patients on diet and exercise. Changes in strength did not correlate with changes in BMD. However, changes in thigh muscle volume correlated with, and predicted changes in hip BMD. Losses of hip BMD and lean body mass are major complications of lifestyle therapy in frail, obese older adults; however, the contribution of mechanical strain loss from muscle loss is poorly defined. We determined the effect of changes in thigh muscle volume and muscle strength on BMD in frail, obese older adults undergoing lifestyle therapy aimed at intentional weight loss with or without exercise. One hundred seven obese older adults were randomized to control, diet, exercise, and diet-exercise groups for 1 year. Thigh muscle volume was measured by magnetic resonance imaging, BMD by DXA, knee strength by dynamometry, total strength by one-repetition maximum (1-RM), and bone markers by immunoassay. Thigh muscle volume decreased in the diet group (-6.2 ± 4.8 %) and increased in the exercise group (2.7 ± 3.1 %), while it was not significantly different from the control in the diet-exercise group. Changes in hip BMD followed similar pattern as those in thigh muscle volume. Knee extension and flexion increased in the exercise group (23 ± 20 %; 25 ± 19 %) and diet-exercise group (20 ± 19 %; 20.6 ± 27 %) but were unchanged in the control and diet groups. Changes in thigh muscle volume correlated with changes in hip BMD (r = 0.55, P = BMD (β = 0.12, P = 0.03) in the multiple regression analyses after accounting for demographic factors and changes in weight and physical activity. There were no

  20. Objectively Measured Physical Activity and Changes in Life-Space Mobility Among Older People.

    Science.gov (United States)

    Tsai, Li-Tang; Rantakokko, Merja; Rantanen, Taina; Viljanen, Anne; Kauppinen, Markku; Portegijs, Erja

    2016-11-01

    Our aim was to study the relationship between objectively measured physical activity and subsequent changes in life-space mobility over 2 years among older people. Life-space mobility refers to the area a person moves through in daily life, taking into account frequency, and need of assistance. Life-space mobility and physical activity correlate, but whether different intensities of objectively assessed physical activity predicts decline in life-space mobility is not known. Prospective cohort study of the "Life-space Mobility in Old Age" (LISPE) project accelerometer substudy. Participants were community-dwelling older people aged 75-90 (n = 164). Life-space mobility was measured with the Life-Space Assessment at baseline face-to-face home interview and telephone follow-up interviews 1 and 2 years after baseline. Physical activity (step count and time spent in moderate activity, low activity, and sedentary behavior) was measured by a tri-axial accelerometer (Hookie "AM20 Activity Meter") for 7 days at baseline. Generalized estimating equations (GEE models) were used to compare changes in life-space mobility between participants categorized according to the baseline physical activity measures. Median age of the participants was 79.5 (IQR 6.7) and 64% were women. Over the 2 years, life-space mobility declined significantly among those with lower step counts and less time spent in moderate activity measured at baseline. Time spent in low activity and sedentary behavior did not predict changes in life-space mobility. In old age, more time spent walking outdoors and accumulation of moderate-intensity physical activity may help to maintain higher life-space mobility, a correlate of good quality of life. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

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

    Science.gov (United States)

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

    2017-12-01

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

  7. 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...

  8. 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.

  9. 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.

  10. Ability of physical activity to predict cardiovascular disease beyond commonly evaluated cardiometabolic risk factors.

    Science.gov (United States)

    McGuire, K Ashlee; Janssen, Ian; Ross, Robert

    2009-12-01

    It is well-established that increasing physical activity (PA) is important for the prevention and management of cardiovascular disease (CVD). Although it has been demonstrated that PA predicts CVD independent of commonly measured cardiometabolic risk factors in women, it is unclear whether this association is true in men. The study participants consisted of 5,882 adults (age >or=18 years) from the 1999 to 2004 United States National Health and Nutrition Examination Survey. Blood pressure, triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, glucose, and waist circumference were categorized using standard clinical thresholds. The participants were divided into the following groups according to the volume of their moderate-to-vigorous intensity PA: active (>or=150 min/wk), somewhat active (30 to 149 min/wk), and inactive (active participants to have CVD. Additional adjustment for cardiometabolic risk factors did not change the odds ratio for CVD in the inactive group. To further delineate the effects of PA on CVD, the participants were cross-classified according to their PA level and their number of cardiometabolic risk factors. Both PA and cardiometabolic risk factors were independent predictors of CVD (P(trend) <0.0001). The results were not modified by gender. In conclusion, PA was associated with CVD, independent of the common cardiometabolic risk factors, in men and women. The association between PA and CVD risk was not mediated by the measured cardiometabolic risk factors.

  11. 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.

  12. 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

  13. 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......, and model skill typically did not outperform a null model assuming distributions to be constant in time. The predicted prevalence increasingly differed from the observed prevalence for predictions with more distance in time from their training dataset. More detailed investigations based on four focal...... species revealed that strong spatial variations in skill exist, with the least skill at the edges of the distributions, where prevalence is lowest. Furthermore, the scores of traditional single-value model performance metrics were contrasting and some implied overoptimistic conclusions about model skill...

  14. 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

  15. 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.

  16. 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...... 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. 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...

  17. Changes in Quadriceps Muscle Activity During Sustained Recreational Alpine Skiing

    OpenAIRE

    Josef Kröll; Erich Müller; Seifert, John G.; Wakeling, James M.

    2011-01-01

    During a day of skiing thousands of repeated contractions take place. Previous research on prolonged recreational alpine skiing show that physiological changes occur and hence some level of fatigue is inevitable. In the present paper the effect of prolonged skiing on the recruitment and coordination of the muscle activity was investigated. Six subjects performed 24 standardized runs. Muscle activity during the first two (PREskiing) and the last two (POSTskiing) runs was measured from the vast...

  18. 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

  19. 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.

  20. 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.

  1. Changes in complex spike activity during classical conditioning

    Directory of Open Access Journals (Sweden)

    Anders eRasmussen

    2014-08-01

    Full Text Available The cerebellar cortex is necessary for adaptively timed conditioned responses (CRs in eyeblink conditioning. During conditioning, Purkinje cells acquire pause responses or Purkinje cell CRs to the conditioned stimuli (CS, resulting in disinhibition of the cerebellar nuclei (CN, allowing them to activate motor nuclei that control eyeblinks. This disinhibition also causes inhibition of the inferior olive (IO, via the nucleo-olivary pathway (N-O. Activation of the IO, which relays the unconditional stimulus (US to the cortex, elicits characteristic complex spikes in Purkinje cells. Although Purkinje cell activity, as well as stimulation of the CN, is known to influence IO activity, much remains to be learned about the way that learned changes in simple spike firing affects the IO. In the present study, we analyzed changes in simple and complex spike firing, in extracellular Purkinje cell records, from the C3 zone, in decerebrate ferrets undergoing training in a conditioning paradigm. In agreement with the N-O feedback hypothesis, acquisition resulted in a gradual decrease in complex spike activity during the conditioned stimulus, with a delay that is consistent with the long N-O latency. Also supporting the feedback hypothesis, training with a short interstimulus interval (ISI, which does not lead to acquisition of a Purkinje cell CR, did not cause a suppression of complex spike activity. In contrast, observations that extinction did not lead to a recovery in complex spike activity and the irregular patterns of simple and complex spike activity after the conditioned stimulus are less conclusive.

  2. 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.

  3. 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.

  4. 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].

  5. 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

  6. 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.

  7. Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

    NARCIS (Netherlands)

    de Sousa Pereira Simoes de Melo, Manuel; Ferre, Rafael; Feliu, Lidia; Bardaji, Eduard; Planas, Marta; Castanho, Miguel A. R. B.

    2011-01-01

    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

  8. Worry tendencies predict brain activation during aversive imagery.

    Science.gov (United States)

    Schienle, Anne; Schäfer, Axel; Pignanelli, Roman; Vaitl, Dieter

    2009-09-25

    Because of its abstract nature, worrying might function as an avoidance response in order to cognitively disengage from fearful imagery. The present functional magnetic resonance imaging study investigated neural correlates of aversive imagery and their association with worry tendencies, as measured by the Penn State Worry Questionnaire (PSWQ). Nineteen healthy women first viewed, and subsequently imagined pictures from two categories, 'threat' and 'happiness'. Worry tendencies were negatively correlated with brain activation in the anterior cingulate cortex, the prefrontal cortex (dorsolateral, dorsomedial, ventrolateral), the parietal cortex and the insula. These negative correlations between PSWQ scores and localized brain activation were specific for aversive imagery. Moreover, activation in the above mentioned regions was positively associated with the experienced vividness of both pleasant and unpleasant mental pictures. As the identified brain regions are involved in emotion regulation, vivid imagery and memory retrieval, a lowered activity in high PSWQ scorers might be associated with cognitive disengagement from aversive imagery as well as insufficient refresh rates of mental pictures. Our preliminary findings encourage future imagery studies on generalized anxiety disorder patients, as one of the main symptoms of this disorder is excessive worrying.

  9. 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

  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. Electrocardiographic Changes Improve Risk Prediction in Asymptomatic Persons Age 65 Years or Above Without Cardiovascular Disease

    DEFF Research Database (Denmark)

    Jørgensen, Peter Godsk; Jensen, Jan S; Marott, Jacob L

    2014-01-01

    endpoint was fatal cardiovascular disease (CVD) event and the secondary was fatal or nonfatal CVD event. In our study, 2,236 fatal CVD and 3,849 fatal or nonfatal CVD events occurred during a median of 11.9 and 9.8 years of follow-up. RESULTS: ECG changes were frequently present (30.6%) and associated......BACKGROUND: Risk prediction in elderly patients is increasingly relevant due to longer life expectancy. OBJECTIVES: This study sought to examine whether electrocardiographic (ECG) changes provide prognostic information incremental to current risk models and to the conventional risk factors. METHODS...

  12. Family History Predicts Stress Fracture in Active Female Adolescents

    Science.gov (United States)

    Loud, Keith J.; Micheli, Lyle J.; Bristol, Stephanie; Austin, S. Bryn; Gordon, Catherine M.

    2011-01-01

    OBJECTIVE Increased physical activity and menstrual irregularity have been associated with increased risk for stress fracture among adult women active in athletics. The purposes of this study were to determine whether menstrual irregularity is also a risk factor for stress fracture in active female adolescents and to estimate the quantity of exercise associated with an increased risk for this injury. PATIENTS AND METHODS A case-control study was conducted of 13- to 22-year-old females diagnosed with their first stress fracture, each matched prospectively on age and self-reported ethnicity with 2 controls. Patients with chronic illnesses or use of medications known to affect bone mineral density were excluded, including use of hormonal preparations that could alter menstrual cycles. The primary outcome, stress fracture in any extremity or the spine, was confirmed radiographically. Girls with stress fracture had bone mineral density measured at the lumbar spine by dual-energy x-ray absorptiometry. RESULTS The mean ± SD age of the 168 participants was 15.9 ± 2.1 years; 91.7% were postmenarchal, with a mean age at menarche of 13.1 ± 1.1 years. The prevalence of menstrual irregularity was similar among cases and controls. There was no significant difference in the mean hours per week of total physical activity between girls in this sample with stress fracture (8.2 hours/week) and those without (7.4 hours/week). In multivariate models, case subjects had nearly 3 times the odds of having a family member with osteoporosis or osteopenia. In secondary analyses, participants with stress fracture had a low mean spinal bone mineral density for their age. CONCLUSIONS Among highly active female adolescents, only family history was independently associated with stress fracture. The magnitude of this association suggests that further investigations of inheritable skeletal factors are warranted in this population, along with evaluation of bone mineral density in girls with stress

  13. Implicit identification with death predicts change in suicide ideation during psychiatric treatment in adolescents.

    Science.gov (United States)

    Glenn, Catherine R; Kleiman, Evan M; Coppersmith, Daniel D L; Santee, Angela C; Esposito, Erika C; Cha, Christine B; Nock, Matthew K; Auerbach, Randy P

    2017-12-01

    Suicidal thoughts and behaviors are major public health concerns in youth. Unfortunately, knowledge of reliable predictors of suicide risk in adolescents is limited. Promising research using a death stimuli version of the Implicit Association Test (Death IAT) indicates that stronger identification with death differs between adults with and without a history of suicidal thoughts and behaviors and uniquely predicts suicide ideation and behavior. However, research in adolescents is lacking and existing findings have been mixed. This study extends previous research by testing whether implicit identification with death predicts changes in suicide ideation during psychiatric treatment in adolescents. Participants included 276 adolescents, ages 13-19, admitted to a short-term residential treatment program. At hospital admission and discharge, adolescents completed the Death IAT and measures of recent suicidal thoughts. At admission, implicit identification with death was associated with recent suicide ideation, but did not differ between those who engaged in prior suicidal behavior and those who did not. Prospectively, adolescents' implicit identification with death at admission significantly predicted their suicide ideation severity at discharge, above and beyond explicit suicide ideation. However, this effect only was significant for adolescents with longer treatment stays (i.e., more than 13 days). Implicit identification with death predicts suicidal thinking among adolescents in psychiatric treatment. Findings clarify over what period of time implicit cognition about death may predict suicide risk in adolescents. © 2017 Association for Child and Adolescent Mental Health.

  14. Examining Change in Therapeutic Alliance to Predict Youth Mental Health Outcomes.

    Science.gov (United States)

    Duppong Hurley, Kristin; Van Ryzin, Mark J; Lambert, Matthew; Stevens, Amy L

    2015-06-01

    To examine the link between therapeutic alliance and youth outcomes. The study was conducted at a group-home with 112 youth with a disruptive-behavior diagnosis. Therapeutic alliance was collected routinely via youth and staff report. Outcome data were collected using youth and staff reports of externalizing behavior as well as behavioral incidents occurring during care. Outcome data were collected following intake into services and at 6 and 12 months of care. Data were analyzed to examine (1) if youth behavior problems at intake were predictive of therapeutic alliance and (2) if changes in alliance were predictive of subsequent youth outcomes. These were conducted with a 6-month service-delivery model and replicated with a 12-month model. There was some support for the first hypothesis, that initial levels of youth externalizing behavior would be related to alliance ratings; however, most of the effects were marginally significant. The second hypothesis, that changes in therapeutic alliance would be related to subsequent youth outcomes, was supported for the 6-month model, but not the 12-month model. Changes in therapeutic alliance may be predictive of youth outcomes during care. Additional research into examining therapeutic alliance trajectories is warranted to improve mental health services for youth.

  15. 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.

  16. Predicting short-term weight loss using four leading health behavior change theories

    Directory of Open Access Journals (Sweden)

    Barata José T

    2007-04-01

    Full Text Available Abstract Background This study was conceived to analyze how exercise and weight management psychosocial variables, derived from several health behavior change theories, predict weight change in a short-term intervention. The theories under analysis were the Social Cognitive Theory, the Transtheoretical Model, the Theory of Planned Behavior, and Self-Determination Theory. Methods Subjects were 142 overweight and obese women (BMI = 30.2 ± 3.7 kg/m2; age = 38.3 ± 5.8y, participating in a 16-week University-based weight control program. Body weight and a comprehensive psychometric battery were assessed at baseline and at program's end. Results Weight decreased significantly (-3.6 ± 3.4%, p Conclusion The present models were able to predict 20–30% of variance in short-term weight loss and changes in weight management self-efficacy accounted for a large share of the predictive power. As expected from previous studies, exercise variables were only moderately associated with short-term outcomes; they are expected to play a larger explanatory role in longer-term results.

  17. Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China

    Directory of Open Access Journals (Sweden)

    Huiran Han

    2015-04-01

    Full Text Available Land use and land cover (LULC models are essential for analyzing LULC change and predicting land use requirements and are valuable for guiding reasonable land use planning and management. However, each LULC model has its own advantages and constraints. In this paper, we explore the characteristics of LULC change and simulate future land use demand by combining a CLUE-S model with a Markov model to deal with some shortcomings of existing LULC models. Using Beijing as a case study, we describe the related driving factors from land-adaptive variables, regional spatial variables and socio-economic variables and then simulate future land use scenarios from 2010 to 2020, which include a development scenario (natural development and rapid development and protection scenarios (ecological and cultivated land protection. The results indicate good consistency between predicted results and actual land use situations according to a Kappa statistic. The conversion of cultivated land to urban built-up land will form the primary features of LULC change in the future. The prediction for land use demand shows the differences under different scenarios. At higher elevations, the geographical environment limits the expansion of urban built-up land, but the conversion of cultivated land to built-up land in mountainous areas will be more prevalent by 2020; Beijing, however, still faces the most pressure in terms of ecological and cultivated land protection.

  18. Change in active travel and changes in recreational and total physical activity in adults: longitudinal findings from the iConnect study

    National Research Council Canada - National Science Library

    Sahlqvist, Shannon; Goodman, Anna; Cooper, Ashley R; Ogilvie, David

    2013-01-01

    To better understand the health benefits of promoting active travel, it is important to understand the relationship between a change in active travel and changes in recreational and total physical activity...

  19. 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

  20. 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.

  1. 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.

  2. Changes in specific activity of ascorbate peroxidase during seed ...

    African Journals Online (AJOL)

    Changes in specific activity of ascorbate peroxidase during seed development of pea ( Pisum sativum L.) treated with salicylic acid. ... Four phenological growth stages were selected of seed and fruit development (BBCH 73, BBCH 77, BBCH 83 and BBCH 88) for enzyme assay. Aqueous SA was applied by three different ...

  3. 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) ...

  4. 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…

  5. 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

  6. Assessing debris flow activity in a changing climate

    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

  7. Modeling the sensitivity of outdoor recreation activities to climate change

    NARCIS (Netherlands)

    Finger, R.; Lehmann, N.

    2012-01-01

    This study develops a methodological framework to analyze the climate sensitivity as well as climate change impacts on outdoor recreation activities, applied to a case study of 2 lidos in the city of Zurich. A negative binomial regression is used to link daily data on lido entries with weather

  8. Molecular physicochemical parameters predicting antioxidant activity of Brazilian natural products

    Directory of Open Access Journals (Sweden)

    Luciana Scotti

    Full Text Available Reactive oxygen species (ROS are capable of oxidizing cellular proteins, nucleic acids and lipids, contributing to cellular aging, mutagenesis, carcinogenesis, coronary heart and neurodegenerative diseases. Free radicals-scavenging by phenolic compounds occurs by the transfer of one electron followed by the H-abstraction. In order to evaluate the antioxidant activity of a series of seventeen phenolic compounds extracted from Brazilian flora (Chimarrhis turbinata and Arrabidea samydoides, some physicochemical parameters (heat formation of the neutral, radical, and cationic compounds; orbitals' energies; ClogP; ΔH OX; and ΔHf were calculated. Considering the results from the calculated descriptors, the molecules 10a-f can be classified as having a higher antioxidant activity.

  9. Connectivity Changes Underlying Neurofeedback Training of Visual Cortex Activity

    Science.gov (United States)

    Scharnowski, Frank; Rosa, Maria Joao; Golestani, Narly; Hutton, Chloe; Josephs, Oliver

    2014-01-01

    Neurofeedback based on real-time functional magnetic resonance imaging (fMRI) is a new approach that allows training of voluntary control over regionally specific brain activity. However, the neural basis of successful neurofeedback learning remains poorly understood. Here, we assessed changes in effective brain connectivity associated with neurofeedback training of visual cortex activity. Using dynamic causal modeling (DCM), we found that training participants to increase visual cortex activity was associated with increased effective connectivity between the visual cortex and the superior parietal lobe. Specifically, participants who learned to control activity in their visual cortex showed increased top-down control of the superior parietal lobe over the visual cortex, and at the same time reduced bottom-up processing. These results are consistent with efficient employment of top-down visual attention and imagery, which were the cognitive strategies used by participants to increase their visual cortex activity. PMID:24609065

  10. Connectivity changes underlying neurofeedback training of visual cortex activity.

    Directory of Open Access Journals (Sweden)

    Frank Scharnowski

    Full Text Available Neurofeedback based on real-time functional magnetic resonance imaging (fMRI is a new approach that allows training of voluntary control over regionally specific brain activity. However, the neural basis of successful neurofeedback learning remains poorly understood. Here, we assessed changes in effective brain connectivity associated with neurofeedback training of visual cortex activity. Using dynamic causal modeling (DCM, we found that training participants to increase visual cortex activity was associated with increased effective connectivity between the visual cortex and the superior parietal lobe. Specifically, participants who learned to control activity in their visual cortex showed increased top-down control of the superior parietal lobe over the visual cortex, and at the same time reduced bottom-up processing. These results are consistent with efficient employment of top-down visual attention and imagery, which were the cognitive strategies used by participants to increase their visual cortex activity.

  11. Activity engagement is related to level, but not change in cognitive ability across adulthood.

    Science.gov (United States)

    Bielak, Allison A M; Anstey, Kaarin J; Christensen, Helen; Windsor, Tim D

    2012-03-01

    It is unclear whether the longitudinal relation between activity participation and cognitive ability is due to preserved differentiation (active individuals have higher initial levels of cognitive ability), or differential preservation (active individuals show less negative change across time). This distinction has never been evaluated after dividing time-varying activity into its two sources of variation: between-person and within-person variability. Further, few studies have investigated how the association between activity participation and cognitive ability may differ from early to older adulthood. Using the PATH Through Life Project, we evaluated whether between- and within-person variation in activity participation was associated with cognitive ability and change within cohorts aged 20-24 years, 40-44 years, and 60-64 years at baseline (n = 7,152) assessed on three occasions over an 8-year interval. Multilevel models indicated that between-person differences in activity significantly predicted baseline cognitive ability for all age cohorts and for each assessed cognitive domain (perceptual speed, short-term memory, working memory, episodic memory, and vocabulary), even after accounting for sex, education, occupational status, and physical and mental health. In each case, greater average participation was associated with higher baseline cognitive ability. However, the size of the relationship involving average activity participation and baseline cognitive ability did not differ across adulthood. Between-person activity and within-person variation in activity level were both not significantly associated with change in cognitive test performance. Results suggest that activity participation is indeed related to cognitive ability across adulthood, but only in relation to the starting value of cognitive ability, and not change over time.

  12. 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...... between ACE activity and risk of SH....

  13. Input techniques that dynamically change their cursor activation area

    DEFF Research Database (Denmark)

    Hertzum, Morten; Hornbæk, Kasper

    2007-01-01

    Efficient pointing is crucial to graphical user interfaces, and input techniques that dynamically change their activation area may yield improvements over point cursors by making objects selectable at a distance. Input techniques that dynamically change their activation area include the bubble...... for operating the input techniques, in the other a mouse. In both experiments, the bubble cursor is fastest and participants make fewer errors with it. Participants also unanimously prefer this technique. For small targets, the cell cursors are generally more accurate than the point cursor; in the second...... experiment the box cursor is also faster. The cell cursors succeed in letting participants select objects while the cursor is far away from the target, but are relatively slow in the final phase of target acquisition. We discuss limitations and possible enhancements of input techniques with activation areas...

  14. 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

  15. Predicting the effects of climate change on sea turtle nesting habitat in Florida

    OpenAIRE

    Poti, Matthew

    2010-01-01

    Rising global temperatures threaten the survival of many plant and animal species. Having already risen at an unprecedented rate in the past century, temperatures are predicted to rise between 0.3 and 7.5C in North America over the next 100 years (Hawkes et al. 2007). Studies have documented the effects of climate warming on phenology (timing of seasonal activities), with observations of early arrival at breeding grounds, earlier ends to the reproductive season, and delayed autumnal ...

  16. 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…

  17. Quantifying `missing melt' in regional climate model predictions of Greenland ice sheet change

    Science.gov (United States)

    Leeson, A.; Eastoe, E.; Fettweis, X.

    2016-12-01

    Since 2010, the rate of mass loss from Greenland has increased and the ice sheet has experienced more episodes of rare and extreme surface melt. In addition to directly removing more of the ice sheet into the sea, extreme melt events reduce the reflectivity of the ice sheet and can warm the perennial snow pack through latent heat release when the melt water refreezes, both of which act as a positive feedback to further enhance melt. As such, an understanding of the frequency, duration and magnitude of extreme melt events is necessary to constrain predictions of future ice sheet state. Melting on Greenland is typically predicted using Regional Climate Models (RCM), however, although RCMs are excellent at reproducing 'normal' conditions (low amplitude/frequency signals) and long term trends, they may not resolve unusually high/low magnitude features, particularly of either small spatial scale or short temporal duration. Extreme melt events for example, typically only last for a day or so and thus their effects are likely omitted from RCM estimates of future ice sheet change. Here, we present a new climatology of historic extreme melt events on Greenland, diagnosed using tools from Extreme Value Theory Statistics. We use these data to evaluate the ability of the MAR (Modele Atmospherique Regional) RCM to reproduce the frequency, magnitude and duration of extreme melt events in the past, with forcing by both re-analysis (ERA-Interim) and GCM (CMIP5) predictions at the model boundaries. By modelling the relationship between MAR predicted values, and observations, we are able to estimate the degree to which MAR over/under estimates melting due to the omission of extreme events for a given boundary forcing. We use this relationship together with MAR predictions of future change to quantify the likely amount of `missing melt' in MAR-based projections of global sea level rise due to these short term, high magnitude perturbations.

  18. 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

  19. 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,

  20. Tools for Consumer Rights Protection in the Prediction of Electronic Virtual Market and Technological Changes

    Directory of Open Access Journals (Sweden)

    Mikuláš Gangur

    2014-05-01

    Full Text Available Electronic virtual markets can serve as an alternative tool for collecting information that is spread among numerous experts. This is the principal market functionality from the operators’ point of view. On the other hand it is profits that are the main interest of the market participants. What they expect from the market is liquidity as high as possible and the opportunity for unrestricted trading. Both the operator and the electronic market participant can be considered consumers of this particular market with reference to the requirements for the accuracy of its outputs but also for the market liquidity. Both the above mentioned groups of consumers (the operators and the participants themselves expect protection of their specific consumer rights, i.e. securing the two above mentioned functionalities of the market. These functionalities of the electronic market are, however, influenced by many factors, among others by participants’ activity. The article deals with the motivation tools that may improve the quality of the prediction market. In the prediction electronic virtual market there may be situations in which the commonly used tools for increasing business activities described in the published literature are not significantly effective. For such situations we suggest a new type of motivation incentive consisting in penalizing the individual market participants whose funds are not placed in the market. The functionality of the proposed motivation incentive is presented on the example of the existing data gained from the electronic virtual prediction market which is actively operated.

  1. 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

  2. Predictive Modeling of Rice Yellow Stem Borer Population Dynamics under Climate Change Scenarios in Indramayu

    Science.gov (United States)

    Nurhayati, E.; Koesmaryono, Y.; Impron

    2017-03-01

    Rice Yellow Stem Borer (YSB) is one of the major insect pests in rice plants that has high attack intensity in rice production center areas, especially in West Java. This pest is consider as holometabola insects that causes rice damage in the vegetative phase (deadheart) as well as generative phase (whitehead). Climatic factor is one of the environmental factors influence the pattern of dynamics population. The purpose of this study was to develop a predictive modeling of YSB pest dynamics population under climate change scenarios (2016-2035 period) using Dymex Model in Indramayu area, West Java. YSB modeling required two main components, namely climate parameters and YSB development lower threshold of temperature (To) to describe YSB life cycle in every phase. Calibration and validation test of models showed the coefficient of determination (R2) between the predicted results and observations of the study area were 0.74 and 0.88 respectively, which was able to illustrate the development, mortality, transfer of individuals from one stage to the next life also fecundity and YSB reproduction. On baseline climate condition, there was a tendency of population abundance peak (outbreak) occured when a change of rainfall intensity in the rainy season transition to dry season or the opposite conditions was happen. In both of application of climate change scenarios, the model outputs were generated well and able to predict the pattern of YSB population dynamics with a the increasing trend of specific population numbers, generation numbers per season and also shifting pattern of populations abundance peak in the future climatic conditions. These results can be adopted as a tool to predict outbreak and to give early warning to control YSB pest more effectively.

  3. Changes in estradiol predict within-women shifts in attraction to facial cues of men's testosterone.

    Science.gov (United States)

    Roney, James R; Simmons, Zachary L; Gray, Peter B

    2011-06-01

    Many studies have demonstrated that women express stronger attraction to androgen-related traits when tested near ovulation than when tested at other times in the cycle. Much less research, however, has directly addressed which hormonal or other physiological signals may regulate these temporal shifts in women's attractiveness judgments. In the present study, we measured women's preferences for facial cues of men's testosterone concentrations on two occasions spaced two weeks apart, while also measuring women's salivary estradiol and testosterone concentrations at each testing session. Changes in women's estradiol concentrations across sessions positively predicted changes in their preferences for facial cues of high testosterone; there was no such effect for changes in women's testosterone concentrations. For the subset of women who had a testing session fall within the estimated fertile window, preferences for high testosterone faces were stronger in the fertile window session, and change in estradiol from outside to inside the fertile window positively predicted the magnitude of the ovulatory preference shift. These patterns were not replicated when testing preferences for faces that were rated as high in masculinity, suggesting that facial cues of high testosterone can be distinguished from the cues used to subjectively judge facial masculinity. Our findings suggest that women's estradiol promotes attraction to androgen-dependent cues in men (similar to its effects in females of various nonhuman species), and support a role for this hormone as a physiological regulator of cycle phase shifts in mating psychology. Copyright © 2010 Elsevier Ltd. All rights reserved.

  4. 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.

  5. 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.

  6. Analgesia Nociception Index (ANI) to predict intraoperative haemodynamic changes: results of a pilot investigation.

    Science.gov (United States)

    Ledowski, T; Averhoff, L; Tiong, W S; Lee, C

    2014-01-01

    The Analgesia Nociception Index has been described to reflect different levels of intraoperative nociceptive stimulation during total intravenous anaesthesia. The association between this index and haemodynamic changes during sevoflurane-based anaesthesia was investigated in 30 patients with the hypothesis that changes in the Analgesia Nociception Index may coincide with or even predict haemodynamic changes. The Analgesia Nociception Index as well as blood pressure and heart rate were observed during induction, at skin incision, at times of an Analgesia Noceception Index decrease > 20% ('event') and pre-/post-fentanyl administration. The Analgesia Nociception Index decreased with airway manipulation [mean: 52 (before) vs. 33 (after); P 10% was low (heart rate 0.61; blood pressure 0.59). The Analgesia Nociception Index appears to reflect different levels of stimulation during sevoflurane-based general anaesthesia. However, it was of little predictive value to pre-empt significant haemodynamic changes. © 2013 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

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

    Science.gov (United States)

    Ripszam, M; Gallampois, C M J; Berglund, Å; Larsson, H; Andersson, A; Tysklind, M; Haglund, P

    2015-06-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15°C and 4 mg DOCL(-1) and, within ranges of predicted increases, 18°C and 6 mg DOCL(-1), respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Prediction and characterization of enzymatic activities guided by sequence similarity and genome neighborhood networks.

    Science.gov (United States)

    Zhao, Suwen; Sakai, Ayano; Zhang, Xinshuai; Vetting, Matthew W; Kumar, Ritesh; Hillerich, Brandan; San Francisco, Brian; Solbiati, Jose; Steves, Adam; Brown, Shoshana; Akiva, Eyal; Barber, Alan; Seidel, Ronald D; Babbitt, Patricia C; Almo, Steven C; Gerlt, John A; Jacobson, Matthew P

    2014-06-30

    Metabolic pathways in eubacteria and archaea often are encoded by operons and/or gene clusters (genome neighborhoods) that provide important clues for assignment of both enzyme functions and metabolic pathways. We describe a bioinformatic approach (genome neighborhood network; GNN) that enables large scale prediction of the in vitro enzymatic activities and in vivo physiological functions (metabolic pathways) of uncharacterized enzymes in protein families. We demonstrate the utility of the GNN approach by predicting in vitro activities and in vivo functions in the proline racemase superfamily (PRS; InterPro IPR008794). The predictions were verified by measuring in vitro activities for 51 proteins in 12 families in the PRS that represent ∼85% of the sequences; in vitro activities of pathway enzymes, carbon/nitrogen source phenotypes, and/or transcriptomic studies confirmed the predicted pathways. The synergistic use of sequence similarity networks3 and GNNs will facilitate the discovery of the components of novel, uncharacterized metabolic pathways in sequenced genomes.

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

    Directory of Open Access Journals (Sweden)

    Wilfredo Blanco

    2017-09-01

    Full Text Available Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the “intermediate neurons.” We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes

  10. Changes in depth distribution and activity in small benthic riverine fishes under gradually changing light intensities

    OpenAIRE

    Prenda Marín, José; Rossomanno, S.; Armitage, Patrick D.

    2000-01-01

    Three experiments were performed to determine how changes in light conditions affect the activity patterns of three small benthic fishes (Barbatula barbatula, Gobio gobio and Cottus gobio) and if they had any influence on fish microhabitat selection. First, the depth used by three individuals of each species was monitored when light conditions changed at dusk in an aquarium with three depth levels. During daylight most fish stayed in the deep level, but at dusk fish began to move fro...

  11. 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...

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    Josef Kröll

    2011-03-01

    Full Text Available During a day of skiing thousands of repeated contractions take place. Previous research on prolonged recreational alpine skiing show that physiological changes occur and hence some level of fatigue is inevitable. In the present paper the effect of prolonged skiing on the recruitment and coordination of the muscle activity was investigated. Six subjects performed 24 standardized runs. Muscle activity during the first two (PREskiing and the last two (POSTskiing runs was measured from the vastus lateralis (VL and rectus femoris (RF using EMG and quantified using wavelet and principal component analysis. The frequency content of the EMG signal shifted in seven out of eight cases significantly towards lower frequencies with highest effects observed for RF on outside leg. A significant pronounced outside leg loading occurred during POSTskiing and the timing of muscle activity peaks occurred more towards turn completion. Specific EMG frequency changes were observed at certain time points throughout the time windows and not over the whole double turn. It is suggested that general muscular fatigue, where additional specific muscle fibers have to be recruited due to the reduced power output of other fibers did not occur. The EMG frequency decrease and intensity changes for RF and VL are caused by altered timing (coordination within the turn towards a most likely more uncontrolled skiing technique. Hence, these data provide evidence to suggest recreational skiers alter their skiing technique before a potential change in muscle fiber recruitment occurs

  14. Prediction of changes in groundwater dynamics caused by relocation of river embankments

    Directory of Open Access Journals (Sweden)

    U. Mohrlok

    2003-01-01

    Full Text Available Ecosystems in river valleys are affected mainly by the hydraulic conditions in wetlands including groundwater dynamics. The quantitative prediction of changes in groundwater dynamics caused by river embankment relocation requires numerical modelling using a physically-based approach. Groundwater recharge from the intermittently flooded river plains was determined by a leakage approach considering soil hydraulic properties. For the study area in the Elbe river valley north of Magdeburg, Germany, a calibrated groundwater flow model was established and the groundwater dynamics for the present situation as well as for the case of embankment relocation were simulated over a 14-year time period. Changes in groundwater depth derived from simulated groundwater levels occurred only during flood periods. By analysing the spatial distributions of changes in statistical parameters, those areas with significant impact on the ecosystems by embankment relocation can be determined. Keywords: groundwater dynamics,groundwater recharge, flood plains, soil hydraulic properties, numerical modelling, river embankment relocation

  15. 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

  16. Multivariate Prediction of Total Water Storage Changes Over West Africa from Multi-Satellite Data

    Science.gov (United States)

    Forootan, Ehsan; Kusche, Jürgen; Loth, Ina; Schuh, Wolf-Dieter; Eicker, Annette; Awange, Joseph; Longuevergne, Laurent; Diekkrüger, Bernd; Schmidt, Michael; Shum, C. K.

    2014-07-01

    West African countries have been exposed to changes in rainfall patterns over the last decades, including a significant negative trend. This causes adverse effects on water resources of the region, for instance, reduced freshwater availability. Assessing and predicting large-scale total water storage (TWS) variations are necessary for West Africa, due to its environmental, social, and economical impacts. Hydrological models, however, may perform poorly over West Africa due to data scarcity. This study describes a new statistical, data-driven approach for predicting West African TWS changes from (past) gravity data obtained from the gravity recovery and climate experiment (GRACE), and (concurrent) rainfall data from the tropical rainfall measuring mission (TRMM) and sea surface temperature (SST) data over the Atlantic, Pacific, and Indian Oceans. The proposed method, therefore, capitalizes on the availability of remotely sensed observations for predicting monthly TWS, a quantity which is hard to observe in the field but important for measuring regional energy balance, as well as for agricultural, and water resource management. Major teleconnections within these data sets were identified using independent component analysis and linked via low-degree autoregressive models to build a predictive framework. After a learning phase of 72 months, our approach predicted TWS from rainfall and SST data alone that fitted to the observed GRACE-TWS better than that from a global hydrological model. Our results indicated a fit of 79 % and 67 % for the first-year prediction of the two dominant annual and inter-annual modes of TWS variations. This fit reduces to 62 % and 57 % for the second year of projection. The proposed approach, therefore, represents strong potential to predict the TWS over West Africa up to 2 years. It also has the potential to bridge the present GRACE data gaps of 1 month about each 162 days as well as a—hopefully—limited gap between GRACE and the GRACE

  17. 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

  18. 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.

  19. 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.

  20. Prediction of volumetric change in the "triple ring" caused by glioma I-125 brachytherapy.

    Science.gov (United States)

    Julow, Jeno; Kolumbán, Zsuzsa; Viola, Arpád; Major, Tibor; Kolumbán, Géza

    2008-08-01

    The aim of this study was to reveal the volumetric changes in tumor necrosis, reactive zone, and edema referred to as the "triple ring" appearing after low-dose-rate iodine-125 (I-125) interstitial irradiation of 20 inoperable low-grade gliomas. To enable prediction of these volumetric changes, we provide mathematical expressions that describe the dynamics of the triple ring. Volumes of the three regions on image-fused control CT/MR images were measured for a 24-month period. The delivered dose on the tumor surface was 50-60 Gy. Dose planning and image fusion were performed with Brain-Lab Target 1.19 software; mathematical and statistical computations were carried out with Matlab numeric computation and visualization software. To determine the volumes, control images with the triple rings were fused with the planning images. Relative volumes normalized with respect to the volume of reference dose were calculated and plotted in the time domain. First, the mean values of volumes were determined from the patients' measured data; then, polynomials were fitted to the mean values using the polynomial curve-fitting method. The accuracy of our results was verified by correlating the predicted data with the measured ones. The polynomial prediction approach proposed here reveals the dynamics of the triple ring. These polynomials will assist with (1) designing the best treatment, (2) following the patient's condition, and (3) planning reirradiation if necessary.

  1. 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.

  2. Changes in Leisure Activities and Dimensions of Depressive Symptoms in Later Life: A 12-Year Follow-Up.

    Science.gov (United States)

    Chao, Shiau-Fang

    2016-06-01

    Although leisure activities benefit the mental health of the elderly population, the effect of changes in leisure activities on dimensions of depressive symptoms remains unclear. This investigation examined the influences of changes in intellectual, social, and physical activities between waves on four dimensions of depressive symptoms at follow-up. Random effects modeling was utilized with data from a nationwide longitudinal study conducted in Taiwan. The study data comprised 6,942 observations from 2,660 older adults over a 12-year period. The results suggested that changes in physical activities contributed to depressive symptoms which reflected positive affect in the later wave. Increased social activities between waves predicted higher positive affect and lower interpersonal difficulties scores at follow-up. Increased intellectual activities between waves did not substantially affect any domain of depressive symptoms. In contrast, declines in intellectual activities between waves predicted higher scores in three depressive symptoms domains, including depressed mood, somatic symptoms, and interpersonal difficulties. Engagement in a varied range of activities benefits mental health among elders more than participation in any single type of activity among elders. Reducing physical activities can lower positive affect, while the adverse effect may be balanced by increasing social activities. Also, the impact of decreasing intellectual activities on the interpersonal difficulties domain of depressive symptoms may be offset by increasing social activities. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. 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.

  4. Non-linear Regression and Machine Learning for Streamflow Prediction and Climate Change Impact Analysis

    Science.gov (United States)

    Shortridge, J.; Guikema, S.; Zaitchik, B. F.

    2015-12-01

    In the past decade, machine-learning methods for empirical rainfall-runoff modeling have seen extensive development. However, the majority of research has focused on a small number of methods, such as artificial neural networks, while not considering other approaches for non-parametric regression that have been developed in recent years. These methods may be able to achieve comparable predictive accuracy to ANN's and more easily provide physical insights into the system of interest through evaluation of covariate influence. Additionally, these methods could provide a straightforward, computationally efficient way of evaluating climate change impacts in basins where data to support physical hydrologic models is limited. In this paper, we use multiple regression and machine-learning approaches to predict monthly streamflow in five highly-seasonal rivers in the highlands of Ethiopia. We find that generalized additive models, random forests, and cubist models achieve better predictive accuracy than ANNs in many basins assessed and are also able to outperform physical models developed for the same region. We discuss some challenges that could hinder the use of such models for climate impact assessment, such as biases resulting from model formulation and prediction under extreme climate conditions, and suggest methods for preventing and addressing these challenges. Finally, we demonstrate how predictor variable influence can be assessed to provide insights into the physical functioning of data-sparse watersheds.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant 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...

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

    Science.gov (United States)

    Gustafson, Eric J; Shvidenko, Anatoly Z; Sturtevant, Brian R; Scheller, Robert M

    2010-04-01

    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 to understand the complex interactions among forest regenerative processes (succession), natural disturbances (e.g., fire, wind, and insects), and anthropogenic disturbances (e.g., timber harvest). We used a landscape succession and disturbance model (LANDIS-II) to study the relative effects of climate change, timber harvesting, and insect outbreaks on forest composition, biomass (carbon), and landscape pattern in south-central Siberia. We found that most response variables were more strongly influenced by timber harvest and insect outbreaks than by the direct effects of climate change. Direct climate effects generally increased tree productivity and modified probability of establishment, but indirect effects on the fire regime generally counteracted the direct effects of climate on forest composition. Harvest and insects significantly changed forest composition, reduced living aboveground biomass, and increased forest fragmentation. We concluded that: (1) Global change is likely to significantly change forest composition of south-central Siberian landscapes, with some changes taking ecosystems outside the historic range of variability. (2) The direct effects of climate change in the study area are not as significant as the exploitation of virgin forest by timber harvest and the potential increased outbreaks of the Siberian silk moth. (3) Novel disturbance by timber harvest and insect outbreaks may greatly reduce the aboveground living biomass of Siberian forests and may significantly alter ecosystem dynamics and wildlife populations by increasing forest fragmentation.

  7. Asymmetric frontal cortical activity predicts effort expenditure for reward.

    Science.gov (United States)

    Hughes, David M; Yates, Mark J; Morton, Emma E; Smillie, Luke D

    2015-07-01

    An extensive literature shows that greater left, relative to right, frontal cortical activity (LFA) is involved in approach-motivated affective states and reflects stable individual differences in approach motivation. However, relatively few studies have linked LFA to behavioral indices of approach motivation. In this study, we examine the relation between LFA and effort expenditure for reward, a behavioral index of approach motivation. LFA was calculated for 51 right-handed participants (55% female) using power spectral analysis of electroencephalogram recorded at rest. Participants also completed the effort expenditure for rewards task (EEfRT), which presents a series of trials requiring a choice between a low-reward low-effort task and a high-reward high-effort task. We found that individuals with greater resting LFA were more willing to expend greater effort in the pursuit of larger rewards, particularly when reward delivery was less likely. Our findings offer a more nuanced understanding of the motivational significance of LFA, in terms of processes that mitigate the effort- and uncertainty-related costs of pursuing rewarding goals. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  8. 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.

  9. 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.

  10. 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...... of the longest running and most extensive marine biological monitoring programs, to investigate the reliability of predicted plankton distributions. We apply three commonly used SDMs to 20 representative plankton species, including copepods, diatoms, and dinoflagellates, all found in the North Atlantic....... Plankton may be particularly challenging to model, due to its short life span and the dispersive effects of constant water movements on all spatial scales, however there are few other studies against which to compare these results. We conclude that rigorous model validation, including comparison against...

  11. 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.

  12. Can phenological models predict tree phenology accurately under climate change conditions?

    Science.gov (United States)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  13. 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.

  14. The impact of climatological model biases in the North Atlantic jet on predicted future circulation change

    Science.gov (United States)

    Simpson, I.

    2015-12-01

    A long standing bias among global climate models (GCMs) is their incorrect representation of the wintertime circulation of the North Atlantic region. Specifically models tend to exhibit a North Atlantic jet (and associated storm track) that is too zonal, extending across central Europe, when it should tilt northward toward Scandinavia. GCM's consistently predict substantial changes in the large scale circulation in this region, consisting of a localized anti-cyclonic circulation, centered over the Mediterranean and accompanied by increased aridity there and increased storminess over Northern Europe.Here, we present preliminary results from experiments that are designed to address the question of what the impact of the climatological circulation biases might be on this predicted future response. Climate change experiments will be compared in two versions of the Community Earth System Model: the first is a free running version of the model, as typically used in climate prediction; the second is a bias corrected version of the model in which a seasonally varying cycle of bias correction tendencies are applied to the wind and temperature fields. These bias correction tendencies are designed to account for deficiencies in the fast parameterized processes, with an aim to push the model toward a more realistic climatology.While these experiments come with the caveat that they assume the bias correction tendencies will remain constant with time, they allow for an initial assessment, through controlled experiments, of the impact that biases in the climatological circulation can have on future predictions in this region. They will also motivate future work that can make use of the bias correction tendencies to understand the underlying physical processes responsible for the incorrect tilt of the jet.

  15. 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

  16. Predicting habits of vegetable parenting practices to facilitate the design of change programmes.

    Science.gov (United States)

    Baranowski, Tom; Chen, Tzu-An; O'Connor, Teresia M; Hughes, Sheryl O; Diep, Cassandra S; Beltran, Alicia; Brand, Leah; Nicklas, Theresa; Baranowski, Janice

    2016-08-01

    Habit has been defined as the automatic performance of a usual behaviour. The present paper reports the relationships of variables from a Model of Goal Directed Behavior to four scales in regard to parents' habits when feeding their children: habit of (i) actively involving child in selection of vegetables; (ii) maintaining a positive vegetable environment; (iii) positive communications about vegetables; and (iv) controlling vegetable practices. We tested the hypothesis that the primary predictor of each habit variable would be the measure of the corresponding parenting practice. Internet survey data from a mostly female sample. Primary analyses employed regression modelling with backward deletion, controlling for demographics and parenting practices behaviour. Houston, Texas, USA. Parents of 307 pre-school (3-5-year-old) children. Three of the four models accounted for about 50 % of the variance in the parenting practices habit scales. Each habit scale was primarily predicted by the corresponding parenting practices scale (suggesting validity). The habit of active child involvement in vegetable selection was also most strongly predicted by two barriers and rudimentary self-efficacy; the habit of maintaining a positive vegetable environment by one barrier; the habit of maintaining positive communications about vegetables by an emotional scale; and the habit of controlling vegetable practices by a perceived behavioural control scale. The predictiveness of the psychosocial variables beyond parenting practices behaviour was modest. Discontinuing the habit of ineffective controlling parenting practices may require increasing the parent's perceived control of parenting practices, perhaps through simulated parent-child interactions.

  17. 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.

  18. 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.

  19. Meditation-induced changes in high-frequency heart rate variability predict smoking outcomes

    Directory of Open Access Journals (Sweden)

    Daniel J. Libby

    2012-03-01

    Full Text Available Background: High-frequency heart rate variability (HF-HRV is a measure of parasympathetic nervous system output that has been associated with enhanced self-regulation. Low resting levels of HF-HRV are associated with nicotine dependence and blunted stress-related changes in HF-HRV are associated with decreased ability to resist smoking. Meditation has been shown to increase HF-HRV. However, it is unknown whether tonic levels of HF-HRV or acute changes in HF-HRV during meditation predict treatment responses in addictive behaviors such as smoking cessation. Purpose: To investigate the relationship between HF-HRV and subsequent smoking outcomes. Methods: HF-HRV during resting baseline and during mindfulness meditation was measured within two weeks of completing a 4-week smoking cessation intervention in a sample of 31 community participants. Self-report measures of smoking were obtained at a follow up 17-weeks after the initiation of treatment. Results: Regression analyses indicated that individuals exhibiting acute increases in HF-HRV from resting baseline to meditation smoked fewer cigarettes at follow-up than those who exhibited acute decreases in HF-HRV (b=-4.94, p=.009. Conclusion: Acute changes in HF-HRV in response to meditation may be a useful tool to predict smoking cessation treatment response.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. A Unified Framework for Activity Recognition-Based Behavior Analysis and Action Prediction in Smart Homes

    Directory of Open Access Journals (Sweden)

    Sungyoung Lee

    2013-02-01

    Full Text Available In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users” actions to gain knowledge about their habits and preferences.

  7. The use of early summer mosquito surveillance to predict late summer West Nile virus activity

    Science.gov (United States)

    Ginsberg, Howard S.; Rochlin, Ilia; Campbell, Scott R.

    2010-01-01

    Utility of early-season mosquito surveillance to predict West Nile virus activity in late summer was assessed in Suffolk County, NY. Dry ice-baited CDC miniature light traps paired with gravid traps were set weekly. Maximum-likelihood estimates of WNV positivity, minimum infection rates, and % positive pools were generally well correlated. However, positivity in gravid traps was not correlated with positivity in CDC light traps. The best early-season predictors of WNV activity in late summer (estimated using maximum-likelihood estimates of Culex positivity in August and September) were early date of first positive pool, low numbers of mosquitoes in July, and low numbers of mosquito species in July. These results suggest that early-season entomological samples can be used to predict WNV activity later in the summer, when most human cases are acquired. Additional research is needed to establish which surveillance variables are most predictive and to characterize the reliability of the predictions.

  8. Predictive performance for human skin sensitizing potential of the human cell line activation test (h-CLAT).

    Science.gov (United States)

    Nukada, Yuko; Ashikaga, Takao; Sakaguchi, Hitoshi; Sono, Sakiko; Mugita, Nanae; Hirota, Morihiko; Miyazawa, Masaaki; Ito, Yuichi; Sasa, Hitoshi; Nishiyama, Naohiro

    2011-12-01

    Recent changes in regulatory restrictions and social opposition to animal toxicology experiments have driven the need for reliable in vitro tests for predicting the skin sensitizing potentials of a wide variety of industrial chemicals. Previously, we developed the human cell line activation test (h-CLAT) as a cell-based assay to predict the skin sensitizing potential of chemicals, and showed the correspondence between the h-CLAT and the murine local lymph node assay results. This study was conducted to investigate the predictive performance of the h-CLAT for human skin sensitizing potential. We selected a total of 66 test chemicals with known human sensitizing potential, and tested all chemicals with the h-CLAT. We then evaluated the performance of the h-CLAT in predicting human sensitizing potential. Forty-five of 51 tested sensitizers were positive in the h-CLAT, indicating relatively high sensitivity. Also, 10 of 15 non-sensitizers were correctly detected as negative. The overall agreement between human data and h-CLAT outcome was 83%. Furthermore, the h-CLAT could accurately predict the human sensitizing potential of 23 tested chemicals that were amines, heterocyclic compounds, or sulfur compounds. Our data indicate the utility of the h-CLAT for predicting the human skin sensitizing potential of a variety of chemicals. © 2011 John Wiley & Sons A/S.

  9. Improving predictions of carbon fluxes in the tropics undre climatic changes using ED2

    Science.gov (United States)

    Feng, X.; Uriarte, M.

    2016-12-01

    Tropical forests play a critical role in the exchange of carbon between land and atmosphere, highlighting the urgency of understanding the effects of climate change on these ecosystems. The most optimistic predictions of climate models indicate that global mean temperatures will increase by up to 2 0C with some tropical regions experiencing extreme heat. Drought and heat-induced tree mortality will accelerate the release of carbon to the atmosphere creating a positive feedback that greatly exacerbates global warming. Thus, under a warmer and drier climate, tropical forests may become net sources, rather than sinks, of carbon. Earth system models have not reached a consensus on the magnitude and direction of climate change impacts on tropical forests, calling into question the reliability of their predictions. Thus, there is an immediate need to improve the representation of tropical forests in earth system models to make robust predictions. The goal of our study is to quantify the responses of tropical forests to climate variability and improve the predictive capacity of terrestrial ecosystem models. We have collected species-specific physiological and functional trait data from 144 tree species in a Puerto Rican rainforest to parameterize the Ecosystem Demography model (ED2). The large amount of data generated by this research will lead to better validation and lowering the uncertainty in future model predictions. To best represent the forest landscape in ED2, all the trees have been assigned to three plant functional types (PFTs): early, mid, and late successional species. Trait data for each PFT were synthesized in a Bayesian meta-analytical model and posterior distributions of traits were used to parameterize the ED2 model. Model predictions show that biomass production of late successional PFT (118.89 ton/ha) was consistently higher than mid (71.33 ton/ha) and early (13.21 ton/ha) PFTs. However, mid successional PFT had the highest contributions to NPP for the

  10. 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.

  11. Perceptual distortions in pitch and time reveal active prediction and support for an auditory pitch-motion hypothesis.

    Directory of Open Access Journals (Sweden)

    Molly J Henry

    Full Text Available A number of accounts of human auditory perception assume that listeners use prior stimulus context to generate predictions about future stimulation. Here, we tested an auditory pitch-motion hypothesis that was developed from this perspective. Listeners judged either the time change (i.e., duration or pitch change of a comparison frequency glide relative to a standard (referent glide. Under a constant-velocity assumption, listeners were hypothesized to use the pitch velocity (Δf/Δt of the standard glide to generate predictions about the pitch velocity of the comparison glide, leading to perceptual distortions along the to-be-judged dimension when the velocities of the two glides differed. These predictions were borne out in the pattern of relative points of subjective equality by a significant three-way interaction between the velocities of the two glides and task. In general, listeners' judgments along the task-relevant dimension (pitch or time were affected by expectations generated by the constant-velocity standard, but in an opposite manner for the two stimulus dimensions. When the comparison glide velocity was faster than the standard, listeners overestimated time change, but underestimated pitch change, whereas when the comparison glide velocity was slower than the standard, listeners underestimated time change, but overestimated pitch change. Perceptual distortions were least evident when the velocities of the standard and comparison glides were matched. Fits of an imputed velocity model further revealed increasingly larger distortions at faster velocities. The present findings provide support for the auditory pitch-motion hypothesis and add to a larger body of work revealing a role for active prediction in human auditory perception.

  12. 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

  13. 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.

  14. 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.

  15. Does diffusion restriction changes in magnetic resonance imaging predict neurological outcome in neonatal seizures?

    Science.gov (United States)

    Ravindran, Manipriya; Amborium, Prakash; Umamaheswari, B; Ramani, Gokul; Ninan, Binu

    2015-01-01

    Neonatal seizures are a common manifestation of brain dysfunction. Neonatal magnetic resonance imaging (MRI) has rapidly become the study of choice for the evaluation of central nervous systems disorders in newborns. According to a study conducted in Wilhelmina Children's Hospital, University Medical Center Utrecht, diffusion Restriction (DR) changes in the MRI is a good indicator of cell dysfunction (reversible or irreversible) within one week of insult. The main aim of this study was to find the association of DR changes in MRI of brain for neonatal seizures with long term neurodevelopment outcome. This is a retrospective observational study conducted in Sri Ramachandra University. Retrospective data was collected for the time period of January 2010 to December 2011 from medical records department (MRD) for patient data, neonatal intensive care unit and reports from PACS for MRI images and the Karthikeyan child development unit for their developmental follow up reports. Comparison of composite score for various domains with DR changes was done with a t-test and comparison of babies with developmental delay and DR changes with Chi-square test. MRI DR changes with developmental outcome in different domains namely cognition, language-receptive/expressive, fine and gross motor was studied. There is no statistical significance among those who have DR changes and with those who do not have DR changes. Though diffusion restriction changes in MRI may not predict adverse long term neuro developmental outcome, they can be of use with regards to individual etiological profile as in stroke. Larger group study and long term follow up is required to substantiate these findings.

  16. Oscillatory brain activity in the time frequency domain associated to change blindness and change detection awareness.

    Science.gov (United States)

    Darriba, Alvaro; Pazo-Álvarez, Paula; Capilla, Almudena; Amenedo, Elena

    2012-02-01

    Despite the importance of change detection (CD) for visual perception and for performance in our environment, observers often miss changes that should be easily noticed. In the present study, we employed time-frequency analysis to investigate the neural activity associated with CD and change blindness (CB). Observers were presented with two successive visual displays and had to look for a change in orientation in any one of four sinusoid gratings between both displays. Theta power increased widely over the scalp after the second display when a change was consciously detected. Relative to no-change and CD, CB was associated with a pronounced theta power enhancement at parietal-occipital and occipital sites and broadly distributed alpha power suppression during the processing of the prechange display. Finally, power suppressions in the beta band following the second display show that, even when a change is not consciously detected, it might be represented to a certain degree. These results show the potential of time-frequency analysis to deepen our knowledge of the temporal curse of the neural events underlying CD. The results further reveal that the process resulting in CB begins even before the occurrence of the change itself.

  17. Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules.

    Science.gov (United States)

    Ranganathan, Rajiv; Krishnan, Chandramouli; Dhaher, Yasin Y; Rymer, William Z

    2016-03-21

    The motor module hypothesis in motor control proposes that the nervous system can simplify the problem of controlling a large number of muscles in human movement by grouping muscles into a smaller number of modules. Here, we tested one prediction of the modular organization hypothesis by examining whether there is preferential exploration along these motor modules during the learning of a new gait pattern. Healthy college-aged participants learned a new gait pattern which required increased hip and knee flexion during the swing phase while walking in a lower-extremity robot (Lokomat). The new gait pattern was displayed as a foot trajectory in the sagittal plane and participants attempted to match their foot trajectory to this template. We recorded EMG from 8 lower-extremity muscles and we extracted motor modules during both baseline walking and target-tracking using non-negative matrix factorization (NMF). Results showed increased trajectory variability in the first block of learning, indicating that participants were engaged in exploratory behavior. Critically, when we examined the muscle activity during this exploratory phase, we found that the composition of motor modules changed significantly within the first few strides of attempting the new gait pattern. The lack of persistence of the motor modules under even short time scales suggests that motor modules extracted during locomotion may be more indicative of correlated muscle activity induced by the task constraints of walking, rather than reflecting a modular control strategy. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. High-frequency neural activity predicts word parsing in ambiguous speech streams.

    Science.gov (United States)

    Kösem, Anne; Basirat, Anahita; Azizi, Leila; van Wassenhove, Virginie

    2016-12-01

    During speech listening, the brain parses a continuous acoustic stream of information into computational units (e.g., syllables or words) necessary for speech comprehension. Recent neuroscientific hypotheses have proposed that neural oscillations contribute to speech parsing, but whether they do so on the basis of acoustic cues (bottom-up acoustic parsing) or as a function of available linguistic representations (top-down linguistic parsing) is unknown. In this magnetoencephalography study, we contrasted acoustic and linguistic parsing using bistable speech sequences. While listening to the speech sequences, participants were asked to maintain one of the two possible speech percepts through volitional control. We predicted that the tracking of speech dynamics by neural oscillations would not only follow the acoustic properties but also shift in time according to the participant's conscious speech percept. Our results show that the latency of high-frequency activity (specifically, beta and gamma bands) varied as a function of the perceptual report. In contrast, the phase of low-frequency oscillations was not strongly affected by top-down control. Whereas changes in low-frequency neural oscillations were compatible with the encoding of prelexical segmentation cues, high-frequency activity specifically informed on an individual's conscious speech percept. Copyright © 2016 the American Physiological Society.

  19. A first look at global flash drought: long term change and short term predictability

    Science.gov (United States)

    Yuan, Xing; Wang, Linying; Ji, Peng

    2017-04-01

    "Flash drought" became popular after the unexpected 2012 central USA drought, mainly due to its rapid development, low predictability and devastating impacts on water resources and crop yields. A pilot study by Mo and Lettenmaier (2015) found that flash drought, based on a definition of concurrent heat extreme, soil moisture deficit and evapotranspiration (ET) enhancement at pentad scale, were in decline over USA during recent 100 years. Meanwhile, a recent work indicated that the occurrence of flash drought in China was doubled during the past 30 years, where a severe flash drought in the summer of 2013 ravaged 13 provinces in southern China. As global warming increases the frequency of heat waves and accelerates the hydrological cycle, the flash drought is expected to increase in general, but its trend might also be affected by interannual to decadal climate oscillations. To consolidate the hotspots of flash drought and the effects of climate change on flash drought, a global inventory is being conducted by using multi-source observations (in-situ, satellite and reanalysis), CMIP5 historical simulations and future projections under different forcing scenarios, as well as global land surface hydrological modeling for key variables including surface air temperature, soil moisture and ET. In particular, a global picture of the flash drought distribution, the contribution of naturalized and anthropogenic forcings to global flash drought change, and the risk of global flash drought in the future, will be presented. Besides investigating the long-term change of flash drought, providing reliable early warning is also essential to developing adaptation strategies. While regional drought early warning systems have been emerging in recent decade, forecasting of flash drought is still at an exploratory stage due to limited understanding of flash drought predictability. Here, a set of sub-seasonal to seasonal (S2S) hindcast datasets are being used to assess the short term

  20. 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, W Maartin; Fuller, Andrea

    2018-02-26

    1.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. 2.We have revisited the relevant principles of thermal physiology and analyzed 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. 3.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. 4.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. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  1. Predicting Nitrogen Loading in Streams Under Climate Change Scenarios in the Continental United States.

    Science.gov (United States)

    Sinha, E.; Michalak, A. M.

    2014-12-01

    Human actions have doubled the amount of nitrogen in the terrestrial biosphere. Although nitrogen application in the form of fertilizers increases food production, excess nitrogen can be harmful to the environment and to human well-being. Excess nitrogen in streams is transported into downstream water bodies, which leads to increased eutrophication and associated problems such as harmful algal blooms and/or hypoxic conditions. The amount of nitrogen exported to streams depends on several factors, including nitrogen input to the watershed, land use, and precipitation. Previous studies have developed models for predicting nitrate load using stream discharge, in order to estimate the contribution of various factors to total nitrogen load, to identify strategies for reducing nitrogen load, and to assess future changes in nitrogen load resulting from anticipated changes in precipitation patterns. Applying these models to estimate future nitrogen loads thus requires running a rainfall-runoff model driven by climate model predictions before nitrogen loading can, in turn, be estimated, thereby compounding uncertainties. In this study, we present a statistical modeling approach that circumvents this two-step process by estimating nitrogen loading directly from precipitation predictions that can be obtained from climate model outputs. The proposed model uses net anthropogenic nitrogen input (NANI), land use type, and precipitation as input parameters. Preliminary results show that the model explains greater than 65% of the variance in the observed annual log transformed nitrogen loads across various catchments throughout the United States. The model is applied to the watersheds comprising the Mississippi river basin to identify the spatial distribution of the sources of nitrogen loading and the inter-annual variation in nitrogen loads under current conditions. Additionally, the model is used to examine changes in magnitude and spatial patterns of nitrogen loading for

  2. 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 management (especially tillage operations and soil cover) played a primary role to affect SOC stock change, while climate conditions were only slightly involved in C

  3. Activation of vegetated parabolic dunes into mobile barchans under potential environmental change scenarios

    Science.gov (United States)

    Yan, Na; Baas, Andreas C. W.

    2016-04-01

    Parabolic dunes are a quintessential example of the co-evolution of soil, landform, and vegetation, and they are found around the world, on coasts, river valleys, lake shores, and margins of deserts and steppes. These areas are often sensitive to changes in natural and anthropogenic forcings and socio-economic activities. Some studies have indicated parabolic dunes can lose vegetation and transform into barchan and transverse dunes by environmental change such as decreased precipitation or lowered water table, as well as anthropogenic stress such as increased burning and grazing. These transformations and shifts between states of eco-geomorphic systems may have significant implications on land management and social-economic development. This study utilises the Extended-DECAL - parameterised by field measurements of dune topography and vegetation characteristics combined with remote sensing - to explore how increases in drought stress, wind strength, and grazing stress may lead to the activation of stabilised parabolic dunes into highly mobile barchans. The modelling results show that the mobility of an initial parabolic dune at the outset of perturbations determines to a large extent the capacity of a system to absorb the environmental change, and a slight increase in vegetation cover of an initial parabolic dune can increase the activation threshold significantly. Plants with a higher deposition tolerance increase the activation threshold for the climatic impact and sand transport rate, whereas the erosion tolerance of plants influences the patterns of resulting barchans. The change in the characteristics of eco-geomorphic interaction zones may indirectly reflect the dune stability and predict an ongoing transformation, whilst the activation angle may be potentially used as a proxy of environmental stresses. In contrast to the natural environmental changes which tend to affect relatively weak and young plants, grazing stress can exert a broader impact on all

  4. 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

  5. Changes in the colour of light cue circadian activity

    Science.gov (United States)

    Kuchenbecker, James A.; Neitz, Maureen

    2012-01-01

    The discovery of melanopsin, the non-visual opsin present in intrinsically photosensitive retinal ganglion cells (ipRGCs), has created great excitement in the field of circadian biology. Now, researchers have emphasized melanopsin as the main photopigment governing circadian activity in vertebrates. Circadian biologists have tested this idea under standard laboratory, 12h Light: 12h Dark, lighting conditions that lack the dramatic daily colour changes of natural skylight. Here we used a stimulus paradigm in which the colour of the illumination changed throughout the day, thus mimicking natural skylight, but luminance, sensed intrinsically by melanopsin containing ganglion cells, was kept constant. We show in two species of cichlid, Aequidens pulcher and Labeotropheus fuelleborni, that changes in light colour, not intensity, are the primary determinants of natural circadian activity. Moreover, opponent-cone photoreceptor inputs to ipRGCs mediate the sensation of wavelength change, and not the intrinsic photopigment, melanopsin. These results have implications for understanding the evolutionary biology of non-visual photosensory pathways and answer long-standing questions about the nature and distribution of photopigments in organisms, including providing a solution to the mystery of why nocturnal animals routinely have mutations that interrupt the function of their short wavelength sensitive photopigment gene. PMID:22639465

  6. Changes in the colour of light cue circadian activity.

    Science.gov (United States)

    Pauers, Michael J; Kuchenbecker, James A; Neitz, Maureen; Neitz, Jay

    2012-05-01

    The discovery of melanopsin, the non-visual opsin present in intrinsically photosensitive retinal ganglion cells (ipRGCs), has created great excitement in the field of circadian biology. Now, researchers have emphasized melanopsin as the main photopigment governing circadian activity in vertebrates. Circadian biologists have tested this idea under standard laboratory, 12h Light: 12h Dark, lighting conditions that lack the dramatic daily colour changes of natural skylight. Here we used a stimulus paradigm in which the colour of the illumination changed throughout the day, thus mimicking natural skylight, but luminance, sensed intrinsically by melanopsin containing ganglion cells, was kept constant. We show in two species of cichlid, Aequidens pulcher and Labeotropheus fuelleborni, that changes in light colour, not intensity, are the primary determinants of natural circadian activity. Moreover, opponent-cone photoreceptor inputs to ipRGCs mediate the sensation of wavelength change, and not the intrinsic photopigment, melanopsin. These results have implications for understanding the evolutionary biology of non-visual photosensory pathways and answer long-standing questions about the nature and distribution of photopigments in organisms, including providing a solution to the mystery of why nocturnal animals routinely have mutations that interrupt the function of their short wavelength sensitive photopigment gene.

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. Microarray data can predict diurnal changes of starch content in the picoalga Ostreococcus

    Directory of Open Access Journals (Sweden)

    Goryanin Igor

    2011-02-01

    Full Text Available Abstract Background The storage of photosynthetic carbohydrate products such as starch is subject to complex regulation, effected at both transcriptional and post-translational levels. The relevant genes in plants show pronounced daily regulation. Their temporal RNA expression profiles, however, do not predict the dynamics of metabolite levels, due to the divergence of enzyme activity from the RNA profiles. Unicellular phytoplankton retains the complexity of plant carbohydrate metabolism, and recent transcriptomic profiling suggests a major input of transcriptional regulation. Results We used a quasi-steady-state, constraint-based modelling approach to infer the dynamics of starch content during the 12 h light/12 h dark cycle in the model alga Ostreococcus tauri. Measured RNA expression datasets from microarray analysis were integrated with a detailed stoichiometric reconstruction of starch metabolism in O. tauri in order to predict the optimal flux distribution and the dynamics of the starch content in the light/dark cycle. The predicted starch profile was validated by experimental data over the 24 h cycle. The main genetic regulatory targets within the pathway were predicted by in silico analysis. Conclusions A single-reaction description of starch production is not able to account for the observed variability of diurnal activity profiles of starch-related enzymes. We developed a detailed reaction model of starch metabolism, which, to our knowledge, is the first attempt to describe this polysaccharide polymerization while preserving the mass balance relationships. Our model and method demonstrate the utility of a quasi-steady-state approach for inferring dynamic metabolic information in O. tauri directly from time-series gene expression data.

  12. Betting and Belief: Modeling the Impact of Prediction Markets on Public Attribution of Climate Change

    Science.gov (United States)

    Gilligan, J. M.; Nay, J. J.; van der Linden, M.

    2016-12-01

    Despite overwhelming scientific evidence and an almost complete consensus among scientists, a large fraction of the American public is not convinced that global warming is anthropogenic. This doubt correlates strongly with political, ideological, and cultural orientation. [1] It has been proposed that people who do not trust climate scientists tend to trust markets, so prediction markets might be able to influence their beliefs about the causes of climate change. [2] We present results from an agent-based simulation of a prediction market in which traders invest based on their beliefs about what drives global temperature change (here, either CO2 concentration or total solar irradiance (TSI), which is a popular hypothesis among many who doubt the dominant role of CO2). At each time step, traders use historical and observed temperatures and projected future forcings (CO2 or TSI) to update Bayesian posterior probability distributions for future temperatures, conditional on their belief about what drives climate change. Traders then bet on future temperatures by trading in climate futures. Trading proceeds by a continuous double auction. Traders are randomly assigned initial beliefs about climate change, and they have some probability of changing their beliefs to match those of the most successful traders in their social network. We simulate two alternate realities in which the global temperature is controlled either by CO2 or by TSI, with stochastic noise. In both cases traders' beliefs converge, with a large majority reaching agreement on the actual cause of climate change. This convergence is robust, but the speed with which consensus emerges depends on characteristics of the traders' psychology and the structure of the market. Our model can serve as a test-bed for studying how beliefs might evolve under different market structures and different modes of decision-making and belief-change. We will report progress on studying alternate models of belief-change. This

  13. 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...

  14. 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...

  15. Can Gymnastic Teacher Predict Leisure Activity Preference among Children with Developmental Coordination Disorders (DCD)?

    Science.gov (United States)

    Engel-Yeger, Batya; Hanna-Kassis, Amany; Rosenblum, Sara

    2012-01-01

    The aims of the study were to analyze: (1) whether significant differences exist between children with typical development and children with developmental coordination disorders (DCD) in their preference to participate in leisure activities (2) whether the teacher estimation of activity form (TEAF) evaluation predicts participation preference.…

  16. 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

  17. 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.

  18. A conceptual framework for effectively anticipating water-quality changes resulting from changes in agricultural activities

    Science.gov (United States)

    Capel, Paul D.; Wolock, David M.; Coupe, Richard H.; Roth, Jason L.

    2018-01-10

    Agricultural activities can affect water quality and the health of aquatic ecosystems; many water-quality issues originate with the movement of water, agricultural chemicals, and eroded soil from agricultural areas to streams and groundwater. Most agricultural activities are designed to sustain or increase crop production, while some are designed to protect soil and water resources. Numerous soil- and water-protection practices are designed to reduce the volume and velocity of runoff and increase infiltration. This report presents a conceptual framework that combines generalized concepts on the movement of water, the environmental behavior of chemicals and eroded soil, and the designed functions of various agricultural activities, as they relate to hydrology, to create attainable expectations for the protection of—with the goal of improving—water quality through changes in an agricultural activity.The framework presented uses two types of decision trees to guide decision making toward attainable expectations regarding the effectiveness of changing agricultural activities to protect and improve water quality in streams. One decision tree organizes decision making by considering the hydrologic setting and chemical behaviors, largely at the field scale. This decision tree can help determine which agricultural activities could effectively protect and improve water quality in a stream from the movement of chemicals, or sediment, from a field. The second decision tree is a chemical fate accounting tree. This decision tree helps set attainable expectations for the permanent removal of sediment, elements, and organic chemicals—such as herbicides and insecticides—through trapping or conservation tillage practices. Collectively, this conceptual framework consolidates diverse hydrologic settings, chemicals, and agricultural activities into a single, broad context that can be used to set attainable expectations for agricultural activities. This framework also enables

  19. Food-web models predict species abundances in response to habitat change.

    Directory of Open Access Journals (Sweden)

    Nicholas J Gotelli

    2006-10-01

    Full Text Available Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss.

  20. Salivary testosterone change following monetary wins and losses predicts future financial risk-taking.

    Science.gov (United States)

    Apicella, Coren L; Dreber, Anna; Mollerstrom, Johanna

    2014-01-01

    While baseline testosterone has recently been implicated in risk-taking in men, less is known about the effects of changing levels of testosterone on financial risk. Here we attempt to influence testosterone in men by having them win or lose money in a chance-based competition against another male opponent. We employ two treatments where we vary the amount of money at stake so that we can directly compare winners to losers who earn the same amount, thereby abstracting from income effects. We find that men who experience a greater increase in bioactive testosterone take on more risk, an association that remains when controlling for whether the participant won the competition. In fact, whether subjects won the competition did not predict future risk. These results suggest that testosterone change, and thus individual differences in testosterone reactivity, rather than the act of winning or losing, influence financial risk-taking. Copyright © 2013. Published by Elsevier Ltd.

  1. Predictability problems of global change as seen through natural systems complexity description. 1. General Statements

    Directory of Open Access Journals (Sweden)

    Vladimir V. Kozoderov

    1998-01-01

    Full Text Available The overall problem of global change is considered as the mathematical discrete dynamics discipline that deals with the sets, measures and metrics (SMM categories in information sub-spaces. The SMM conception enables to unify techniques of data interpretation and analysis and to explain how effectively the giant amounts of information from multispectral satellite radiometers and ground-based instruments are to be processed. It is shown that Prigogine's chaos/order theory and Kolmogorov's probability space are two milestones in understanding the predictability problems of global change. The essence of the problems is maintained to be in filtering out a “useful signal” that would spread from key regions of the globe as compared to their background. Global analysis, interpretation and modelling issues are outlined in the framework of incorrect mathematical problems and of the SMM categories, which contribute to solving the comparability problem for different sets of observations.

  2. Personality and attention: Levels of neuroticism and extraversion can predict attentional performance during a change detection task.

    Science.gov (United States)

    Hahn, Sowon; Buttaccio, Daniel R; Hahn, Jungwon; Lee, Taehun

    2015-01-01

    The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the Revised Eysenck Personality Questionnaire (EPQ-R). Multiple regression analyses revealed that higher levels of extraversion predict increased change detection accuracies, while higher levels of neuroticism predict decreased change detection accuracies. In addition, neurotic individuals exhibited decreased sensitivity A' and increased fixation dwell times. Hierarchical regression analyses further revealed that eye movement measures mediate the relationship between neuroticism and change detection accuracies. Based on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the relationship between neuroticism and attention.

  3. Prediction of activity type in preschool children using machine learning techniques.

    Science.gov (United States)

    Hagenbuchner, Markus; Cliff, Dylan P; Trost, Stewart G; Van Tuc, Nguyen; Peoples, Gregory E

    2015-07-01

    Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Eleven children aged 3-6 years (mean age=4.8±0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  4. Predicted disappearance of Cephalantheropsis obcordata in Luofu Mountain due to changes in rainfall patterns.

    Directory of Open Access Journals (Sweden)

    Xin-Ju Xiao

    Full Text Available BACKGROUND: In the past century, the global average temperature has increased by approximately 0.74°C and extreme weather events have become prevalent. Recent studies have shown that species have shifted from high-elevation areas to low ones because the rise in temperature has increased rainfall. These outcomes challenge the existing hypothesis about the responses of species to climate change. METHODOLOGY/PRINCIPAL FINDINGS: With the use of data on the biological characteristics and reproductive behavior of Cephalantheropsis obcordata in Luofu Mountain, Guangdong, China, trends in the population size of the species were predicted based on several factors. The response of C. obcordata to climate change was verified by integrating it with analytical findings on meteorological data and an artificially simulated environment of water change. The results showed that C. obcordata can grow only in waterlogged streams. The species can produce fruit with many seeds by insect pollination; however, very few seeds can burgeon to become seedlings, with most of those seedlings not maturing into the sexually reproductive phase, and grass plants will die after reproduction. The current population's age pyramid is kettle-shaped; it has a Deevey type I survival curve; and its net reproductive rate, intrinsic rate of increase, as well as finite rate of increase are all very low. The population used in the artificial simulation perished due to seasonal drought. CONCLUSIONS: The change in rainfall patterns caused by climate warming has altered the water environment of C. obcordata in Luofu Mountain, thereby restricting seed burgeoning as well as seedling growth and shortening the life span of the plant. The growth rate of the C. obcordata population is in descending order, and models of population trend predict that the population in Luofu Mountain will disappear in 23 years.

  5. Predicted disappearance of Cephalantheropsis obcordata in Luofu Mountain due to changes in rainfall patterns.

    Science.gov (United States)

    Xiao, Xin-Ju; Liu, Ke-Wei; Zheng, Yu-Yun; Zhang, Yu-Ting; Tsai, Wen-Chieh; Hsiao, Yu-Yun; Zhang, Guo-Qiang; Chen, Li-Jun; Liu, Zhong-Jian

    2012-01-01

    In the past century, the global average temperature has increased by approximately 0.74°C and extreme weather events have become prevalent. Recent studies have shown that species have shifted from high-elevation areas to low ones because the rise in temperature has increased rainfall. These outcomes challenge the existing hypothesis about the responses of species to climate change. With the use of data on the biological characteristics and reproductive behavior of Cephalantheropsis obcordata in Luofu Mountain, Guangdong, China, trends in the population size of the species were predicted based on several factors. The response of C. obcordata to climate change was verified by integrating it with analytical findings on meteorological data and an artificially simulated environment of water change. The results showed that C. obcordata can grow only in waterlogged streams. The species can produce fruit with many seeds by insect pollination; however, very few seeds can burgeon to become seedlings, with most of those seedlings not maturing into the sexually reproductive phase, and grass plants will die after reproduction. The current population's age pyramid is kettle-shaped; it has a Deevey type I survival curve; and its net reproductive rate, intrinsic rate of increase, as well as finite rate of increase are all very low. The population used in the artificial simulation perished due to seasonal drought. The change in rainfall patterns caused by climate warming has altered the water environment of C. obcordata in Luofu Mountain, thereby restricting seed burgeoning as well as seedling growth and shortening the life span of the plant. The growth rate of the C. obcordata population is in descending order, and models of population trend predict that the population in Luofu Mountain will disappear in 23 years.

  6. MSQoL-54 predicts change in fatigue after inpatient rehabilitation for people with multiple sclerosis.

    Science.gov (United States)

    Drulovic, Jelena; Bursac, Lidija Obradovic; Milojkovic, Dragana; Tepavcevic, Darija Kisic; Gazibara, Tatjana; Pekmezovic, Tatjana

    2013-03-01

    The aim of our study was to investigate the impact of a short-term inpatient rehabilitation program on fatigue in patients with multiple sclerosis (MS) and to assess whether the scales of Multiple Sclerosis Quality of Life 54 (MSQoL-54) could predict change in fatigue after rehabilitation. Included in the study were 151 moderately disabled MS patients admitted for 3 weeks of inpatient rehabilitation. Fatigue (Fatigue Severity Scale; FSS) was assessed at baseline and after treatment, and quality of life (MSQoL-54), disability (Expanded Disability Status Scale; EDSS) and depression (Beck Depression Inventory; BDI) were estimated at baseline. Sixty-four percentage of the subjects showed fatigue. Both EDSS (r = 0.720, p = 0.001) and BDI (r = 0.655, p = 0.001) scores showed statistically significant positive correlation with FSS scores. Significant negative correlation was demonstrated between FSS and both, Physical Health Composite (PHC) and Mental Health Composite (MHC) scores of MSQoL-54 (r = -0.770, p = 0.001, and r = -0.646, p = 0.001, respectively). The mean FSS score significantly decreased by 0.19 ± 0.29 points in the fatigue group, immediately after rehabilitation. The multiple regression analyses with change of FSS as dependent variable and baseline scores of MSQoL-54 as independent variables showed statistically significant relation between change in fatigue and baseline PHC score (p = 0.034). Inpatient rehabilitation decreased MS patients' fatigue. Change in fatigue was predicted with certain domains of QoL at baseline.

  7. Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa.

    Science.gov (United States)

    Tonnang, Henri E Z; Kangalawe, Richard Y M; Yanda, Pius Z

    2010-04-23

    Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their traditional locations to invade new zones is an important concern. The vision of this study was to exploit the sets of information previously generated by entomologists, e.g. on geographical range of vectors and malaria distribution, to build models that will enable prediction and mapping the potential redistribution of Anopheles mosquitoes in Africa. The development of the modelling tool was carried out through calibration of CLIMEX parameters. The model helped estimate the potential geographical distribution and seasonal abundance of the species in relation to climatic factors. These included temperature, rainfall and relative humidity, which characterized the living environment for Anopheles mosquitoes. The same parameters were used in determining the ecoclimatic index (EI). The EI values were exported to a GIS package for special analysis and proper mapping of the potential future distribution of Anopheles gambiae and Anophles arabiensis within the African continent under three climate change scenarios. These results have shown that shifts in these species boundaries southward and eastward of Africa may occur rather than jumps into quite different climatic environments. In the absence of adequate control, these predictions are crucial in understanding the possible future geographical range of the vectors and the disease, which could facilitate planning for various adaptation options. Thus, the outputs from this study will be helpful at various levels of decision making, for example, in setting up of an early warning and sustainable strategies for climate change and climate change adaptation for malaria vectors control programmes in Africa.

  8. Predicting the effects of climate change on Schistosoma mansoni transmission in eastern Africa.

    Science.gov (United States)

    McCreesh, Nicky; Nikulin, Grigory; Booth, Mark

    2015-01-06

    Survival and fitness attributes of free-living and sporocyst schistosome life-stages and their intermediate host snails are sensitive to water temperature. Climate change may alter the geographical distribution of schistosomiasis by affecting the suitability of freshwater bodies for hosting parasite and snail populations. We have developed an agent-based model of the temperature-sensitive stages of the Schistosoma mansoni and intermediate host snail lifecycles. The model was run using low, moderate and high warming climate projections over eastern Africa. For each climate projection, eight model scenarios were used to determine the sensitivity of predictions to different relationships between air and water temperature, and different snail mortality rates. Maps were produced showing predicted changes in risk as a result of increasing temperatures over the next 20 and 50 years. Baseline model output compared to prevalence data indicates suitable temperatures are necessary but not sufficient for both S. mansoni transmission and high infection prevalences. All else being equal, infection risk may increase by up to 20% over most of eastern Africa over the next 20 and 50 years. Increases may be higher in Rwanda, Burundi, south-west Kenya and eastern Zambia, and S. mansoni may become newly endemic in some areas. Results for 20-year projections are robust to changes in simulated intermediate host snail habitat conditions. There is greater uncertainty about the effects of different habitats on changes in risk in 50 years' time. Temperatures are likely to become suitable for increased S. mansoni transmission over much of eastern Africa. This may reduce the impact of control and elimination programmes. S. mansoni may also spread to new areas outside existing control programmes. We call for increased surveillance in areas defined as potentially suitable for emergent transmission.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ripszam, M., E-mail: matyas.ripszam@chem.umu.se [Department of Chemistry, Umea University, 901 87 Umeå (Sweden); Gallampois, C.M.J. [Department of Chemistry, Umea University, 901 87 Umeå (Sweden); Berglund, Å. [Department of Ecology and Environmental Sciences, Umeå University, 901 87 Umeå (Sweden); Larsson, H. [Umeå Marine Sciences Centre, Umeå University, Norrbyn, 905 71 Hörnefors (Sweden); Andersson, A. [Department of Ecology and Environmental Sciences, Umeå University, 901 87 Umeå (Sweden); Tysklind, M.; Haglund, P. [Department of Chemistry, Umea University, 901 87 Umeå (Sweden)

    2015-06-01

    Predicted consequences of future climate change in the northern Baltic Sea include increases in sea surface temperatures and terrestrial dissolved organic carbon (DOC) runoff. These changes are expected to alter environmental distribution of anthropogenic organic contaminants (OCs). To assess likely shifts in their distributions, outdoor mesocosms were employed to mimic pelagic ecosystems at two temperatures and two DOC concentrations, current: 15 °C and 4 mg DOC L{sup −1} and, within ranges of predicted increases, 18 °C and 6 mg DOC L{sup −1}, respectively. Selected organic contaminants were added to the mesocosms to monitor changes in their distribution induced by the treatments. OC partitioning to particulate matter and sedimentation were enhanced at the higher DOC concentration, at both temperatures, while higher losses and lower partitioning of OCs to DOC were observed at the higher temperature. No combined effects of higher temperature and DOC on partitioning were observed, possibly because of the balancing nature of these processes. Therefore, changes in OCs' fates may largely depend on whether they are most sensitive to temperature or DOC concentration rises. Bromoanilines, phenanthrene, biphenyl and naphthalene were sensitive to the rise in DOC concentration, whereas organophosphates, chlorobenzenes (PCBz) and polychlorinated biphenyls (PCBs) were more sensitive to temperature. Mitotane and diflufenican were sensitive to both temperature and DOC concentration rises individually, but not in combination. - Highlights: • More contaminants remained in the ecosystem at higher organic carbon levels. • More contaminants were lost in the higher temperature treatments. • The combined effects are competitive with respect to contaminant cycling. • The individual properties of each contaminant determine their respective fate.

  10. Changes of lung tumour volume on CT - prediction of the reliability of assessments.

    Science.gov (United States)

    Beaumont, Hubert; Souchet, Simon; Labatte, Jean Marc; Iannessi, Antoine; Tolcher, Anthony William

    2015-10-31

    For oncological evaluations, quantitative radiology gives clinicians significant insight into patients' response to therapy. In regard to the Response Evaluation Criteria in Solid Tumours (RECIST), the classification of disease evolution partly consists in applying thresholds to the measurement of the relative change of tumour. In the case of tumour volumetry, response thresholds have not yet been established. This study proposes and validates a model for calculating thresholds for the detection of minimal tumour change when using the volume of pulmonary lesions on CT as imaging biomarker. Our work is based on the reliability analysis of tumour volume measurements documented by the Quantitative Imaging Biomarker Alliance. Statistics of measurements were entered into a multi-parametric mathematical model of the relative changes derived from the Geary-Hinkley transformation. The consistency of the model was tested by comparing modelled thresholds against Monte Carlo simulations of tumour volume measurements with additive random error. The model has been validated by repeating measurements on real patient follow ups. For unchanged tumour volume, relying on a normal distribution of error, the agreement between model and simulations featured a type I error of 5.25%. Thus, we established that a threshold of 35% of volume reduction corresponds to a partial response (PR) and a 55% volume increase corresponds to progressive disease (PD). Changes between -35 and +55% are categorized as stable disease (SD). Tested on real clinical data, 97.1% [95.7; 98.0] of assessments fall into the range of variability predicted by our model of confidence interval. Our study indicates that the Geary Hinkley model, using published statistics, is appropriate to predict response thresholds for the volume of pulmonary lesions on CT.

  11. Changes in quadriceps muscle activity during sustained recreational alpine skiing.

    Science.gov (United States)

    Kröll, Josef; Müller, Erich; Seifert, John G; Wakeling, James M

    2011-01-01

    During a day of skiing thousands of repeated contractions take place. Previous research on prolonged recreational alpine skiing show that physiological changes occur and hence some level of fatigue is inevitable. In the present paper the effect of prolonged skiing on the recruitment and coordination of the muscle activity was investigated. Six subjects performed 24 standardized runs. Muscle activity during the first two (PREskiing) and the last two (POSTskiing) runs was measured from the vastus lateralis (VL) and rectus femoris (RF) using EMG and quantified using wavelet and principal component analysis. The frequency content of the EMG signal shifted in seven out of eight cases significantly towards lower frequencies with highest effects observed for RF on outside leg. A significant pronounced outside leg loading occurred during POSTskiing and the timing of muscle activity peaks occurred more towards turn completion. Specific EMG frequency changes were observed at certain time points throughout the time windows and not over the whole double turn. It is suggested that general muscular fatigue, where additional specific muscle fibers have to be recruited due to the reduced power output of other fibers did not occur. The EMG frequency decrease and intensity changes for RF and VL are caused by altered timing (coordination) within the turn towards a most likely more uncontrolled skiing technique. Hence, these data provide evidence to suggest recreational skiers alter their skiing technique before a potential change in muscle fiber recruitment occurs. Key pointsThe frequency content of the EMG signal shifted in seven out of eight cases significantly towards lower frequencies with highest effects observed for RF.General muscular fatigue, where additional specific fibers have to be recruited due to the reduced power output of other fibers, did not occur.A modified skiing style towards a less functional and hence more uncontrolled skiing technique seems to be a key issue

  12. Evaluation of Climate Change Effect on Agricultural Production of Iran: I. Predicting the Future Agroclimatic Conditions

    Directory of Open Access Journals (Sweden)

    A Koocheki

    2016-02-01

    Full Text Available Introduction Future climate change may affect agricultural production through changes in both mean and variability of climatic conditions which in turn could affect crop growth and development. Results of many studies have shown that crop production systems of dry regions are more vulnerable to the predicted climate changes (5 and these impacts are mainly due to the effects of increased temperature on agro-climatic variables (4. During the last decade future changes in agro-climatic variables such as growth degree days, length of growth period and duration of dry season have been studied at regional or national scale with different results depending on studied location (1, 6. However, such information are not available for Iran. In this study different agro-climatic indices of Iran across the country are calculated for the target year 2050 based on business as usual scenario and the results are compared with the current conditions. Materials and Methods Long term climatic data (1965-2005 of 34 stations covering different climates across the country were used as the baseline for predicting future climate as well as current conditions. Two general circulation models (GISS and GFDL were used for prediction of climatic variables in the selected stations for the year 2050 based on business as usual (A1f scenario of CERES family (2 and the results were statistically downscaled for higher resolution (Koocheki et al., 2006. Daily temperatures (minimum, maximum and mean and precipitation were generated from the predicted monthly values. Several agro-climatic indices including potential evapotranspiration, length of growing season (time period between the last spring frost and the first autumn frost, length of dry season (time period where evapotranspiration exceeds precipitation which obtained from ombrothermic curve, and precipitation deficiency index (sum of differences between evapotranspiration and precipitation were calculated based on daily

  13. Location of breakfast consumption predicts body mass index change in young Hong Kong children.

    Science.gov (United States)

    Tin, S P P; Ho, S Y; Mak, K H; Wan, K L; Lam, T H

    2012-07-01

    An association between weight gain and breakfast skipping has been reported, but breakfast location was rarely considered. We investigated the prospective associations between breakfast location, breakfast skipping and body mass index (BMI) change in a large cohort of Chinese children. Our baseline cohort consisted of 113,457 primary 4 (US grade 4) participants of the Hong Kong Department of Health Student Health Service in 1998-2000. Of these, 68,606 (60.5%) had complete records and were successfully followed-up 2 years later. Data on breakfast consumption and location were collected at both time points along with other lifestyle characteristics. BMI was derived from objectively measured height and weight. Associations between breakfast habits and BMI change were assessed by multivariable linear regression, adjusting for demographic, socioeconomic and lifestyle characteristics. At baseline, 85.3, 9.4 and 5.2% of children had breakfast at home, away from home and skipped breakfast, respectively. Prospectively, having breakfast away from home (vs at home) predicted a greater BMI increase over two years (β = 0.15; 95% CI: 0.11-0.18). Breakfast skipping had a comparable, slightly smaller effect (0.13; 0.09-0.18). Both breakfast skipping and eating breakfast away from home predict greater increases in BMI during childhood, the effect being slightly stronger in the latter. Having breakfast, particularly at home, could have important implications for weight management and reducing obesity in children. Further research is required to gain insight into potential underlying mechanisms.

  14. Prediction of Land Use Change in Long Island Sound Watersheds Using Nighttime Light Data

    Directory of Open Access Journals (Sweden)

    Ruiting Zhai

    2016-12-01

    Full Text Available The Long Island Sound Watersheds (LISW are experiencing significant land use/cover change (LUCC, which affects the environment and ecosystems in the watersheds through water pollution, carbon emissions, and loss of wildlife. LUCC modeling is an important approach to understanding what has happened in the landscape and what may change in the future. Moreover, prospective modeling can provide sustainable and efficient decision support for land planning and environmental management. This paper modeled the LUCCs between 1996, 2001 and 2006 in the LISW in the New England region, which experienced an increase in developed area and a decrease of forest. The low-density development pattern played an important role in the loss of forest and the expansion of urban areas. The key driving forces were distance to developed areas, distance to roads, and social-economic drivers, such as nighttime light intensity and population density. In addition, this paper compared and evaluated two integrated LUCC models—the logistic regression–Markov chain model and the multi-layer perception–Markov chain (MLP–MC model. Both models achieved high accuracy in prediction, but the MLP–MC model performed slightly better. Finally, a land use map for 2026 was predicted by using the MLP–MC model, and it indicates the continued loss of forest and increase of developed area.

  15. Space can substitute for time in predicting climate-change effects on biodiversity

    Science.gov (United States)

    Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

    2013-01-01

    “Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  16. Space can substitute for time in predicting climate-change effects on biodiversity.

    Science.gov (United States)

    Blois, Jessica L; Williams, John W; Fitzpatrick, Matthew C; Jackson, Stephen T; Ferrier, Simon

    2013-06-04

    "Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  17. Changes of resting cerebral activities in subacute ischemic stroke patients

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    Ping Wu

    2015-01-01

    Full Text Available This study aimed to detect the difference in resting cerebral activities between ischemic stroke patients and healthy participants, define the abnormal site, and provide new evidence for pathological mechanisms, clinical diagnosis, prognosis prediction and efficacy evaluation of ischemic stroke. At present, the majority of functional magnetic resonance imaging studies focus on the motor dysfunction and the acute stage of ischemic stroke. This study recruited 15 right-handed ischemic stroke patients at subacute stage (15 days to 11.5 weeks and 15 age-matched healthy participants. A resting-state functional magnetic resonance imaging scan was performed on each subject to detect cerebral activity. Regional homogeneity analysis was used to investigate the difference in cerebral activities between ischemic stroke patients and healthy participants. The results showed that the ischemic stroke patients had lower regional homogeneity in anterior cingulate and left cerebrum and higher regional homogeneity in cerebellum, left precuneus and left frontal lobe, compared with healthy participants. The experimental findings demonstrate that the areas in which regional homogeneity was different between ischemic stroke patients and healthy participants are in the cerebellum, left precuneus, left triangle inferior frontal gyrus, left inferior temporal gyrus and anterior cingulate. These locations, related to the motor, sensory and emotion areas, are likely potential targets for the neural regeneration of subacute ischemic stroke patients.

  18. Combining public participatory surveillance and occupancy modelling to predict the distributional response of Ixodes scapularis to climate change.

    Science.gov (United States)

    Lieske, David J; Lloyd, Vett K

    2018-02-16

    Ixodes scapularis, a known vector of Borrelia burgdorferi sensu stricto (Bbss), is undergoing range expansion in many parts of Canada. The province of New Brunswick, which borders jurisdictions with established populations of I. scapularis, constitutes a range expansion zone for this species. To better understand the current and potential future distribution of this tick under climate change projections, this study applied occupancy modelling to distributional records of adult ticks that successfully overwintered, obtained through passive surveillance. This study indicates that I. scapularis occurs throughout the southern-most portion of the province, in close proximity to coastlines and major waterways. Milder winter conditions, as indicated by the number of degree days <0 °C, was determined to be a strong predictor of tick occurrence, as was, to a lesser degree, rising levels of annual precipitation, leading to a final model with a predictive accuracy of 0.845 (range: 0.828-0.893). Both RCP 4.5 and RCP 8.5 climate projections predict that a significant proportion of the province (roughly a quarter to a third) will be highly suitable for I. scapularis by the 2080s. Comparison with cases of canine infection show good spatial agreement with baseline model predictions, but the presence of canine Borrelia infections beyond the climate envelope, defined by the highest probabilities of tick occurrence, suggest the presence of Bbss-carrying ticks distributed by long-range dispersal events. This research demonstrates that predictive statistical modelling of multi-year surveillance information is an efficient way to identify areas where I. scapularis is most likely to occur, and can be used to guide subsequent active sampling efforts in order to better understand fine scale species distributional patterns. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

  19. Climatic associations of British species distributions show good transferability in time but low predictive accuracy for range change.

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    Giovanni Rapacciuolo

    Full Text Available Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time--due to their accuracy to predict large areas retained by species--but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records

  20. Predicting plant invasions under climate change: are species distribution models validated by field trials?

    Science.gov (United States)

    Sheppard, Christine S; Burns, Bruce R; Stanley, Margaret C

    2014-09-01

    Climate change may facilitate alien species invasion into new areas, particularly for species from warm native ranges introduced into areas currently marginal for temperature. Although conclusions from modelling approaches and experimental studies are generally similar, combining the two approaches has rarely occurred. The aim of this study was to validate species distribution models by conducting field trials in sites of differing suitability as predicted by the models, thus increasing confidence in their ability to assess invasion risk. Three recently naturalized alien plants in New Zealand were used as study species (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla): they originate from warm native ranges, are woody bird-dispersed species and of concern as potential weeds. Seedlings were grown in six sites across the country, differing both in climate and suitability (as predicted by the species distribution models). Seedling growth and survival were recorded over two summers and one or two winter seasons, and temperature and precipitation were monitored hourly at each site. Additionally, alien seedling performances were compared to those of closely related native species (Rhopalostylis sapida, Lophomyrtus bullata and Schefflera digitata). Furthermore, half of the seedlings were sprayed with pesticide, to investigate whether enemy release may influence performance. The results showed large differences in growth and survival of the alien species among the six sites. In the more suitable sites, performance was frequently higher compared to the native species. Leaf damage from invertebrate herbivory was low for both alien and native seedlings, with little evidence that the alien species should have an advantage over the native species because of enemy release. Correlations between performance in the field and predicted suitability of species distribution models were generally high. The projected increase in minimum temperature and reduced