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Sample records for activity change predict

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

    Shangkun Deng; Takashi Mitsubuchi; Akito Sakurai

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as pe...

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

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

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

    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. PMID:27151536

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

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

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

    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

  6. Occipital MEG Activity in the Early Time Range (<300 ms) Predicts Graded Changes in Perceptual Consciousness

    Andersen, Lau Møller; Pedersen, Michael Nygaard; Sandberg, Kristian;

    2016-01-01

    Two electrophysiological components have been extensively investigated as candidate neural correlates of perceptual consciousness: An early, occipitally realized component occurring 130-320 ms after stimulus onset and a late, frontally realized component occurring 320-510 ms after stimulus onset...... when decoding perceptual consciousness from the 2 components using sources from occipital and frontal lobes. We found that occipital sources during the early time range were significantly more accurate in decoding perceptual consciousness than frontal sources during both the early and late time ranges....... These results are the first of its kind where the predictive values of the 2 components are quantitatively compared, and they provide further evidence for the primary importance of occipital sources in realizing perceptual consciousness. The results have important consequences for current theories of...

  7. Predicting geomagnetic activity indices

    Complete text of publication follows. Magnetically active times, e.g., Kp > 5, are notoriously difficult to predict, precisely the times when such predictions are crucial to the space weather users. Taking advantage of the routinely available solar wind measurements at Lagrangian point (L1) and nowcast Kps, Kp and Dst forecast models based on neural networks were developed with the focus on improving the forecast for active times. To satisfy different needs and operational constraints, three models were developed: (1) a model that inputs nowcast Kp and solar wind parameters and predicts Kp 1 hr ahead; (2) a model with the same input as model 1 and predicts Kp 4 hr ahead; and (3) a model that inputs only solar wind parameters and predicts Kp 1 hr ahead (the exact prediction lead time depends on the solar wind speed and the location of the solar wind monitor.) Extensive evaluations of these models and other major operational Kp forecast models show that, while the new models can predict Kps more accurately for all activities, the most dramatic improvements occur for moderate and active times. Similar Dst models were developed. Information dynamics analysis of Kp, suggests that geospace is more dominated by internal dynamics near solar minimum than near solar maximum, when it is more directly driven by external inputs, namely solar wind and interplanetary magnetic field (IMF).

  8. Predicting cognitive change within domains

    Duff, Kevin; Beglinger, Leigh J.; Moser, David J.; Paulsen, Jane S.

    2010-01-01

    Standardized regression based (SRB) formulas, a method for predicting cognitive change across time, traditionally use baseline performance on a neuropsychological measure to predict future performance on that same measure. However, there are instances in which the same tests may not be given at follow-up assessments (e.g., lack of continuity of provider, avoiding practice effects). The current study sought to expand this methodology by developing SRBs to predict performance on different tests...

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

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

    2009-01-01

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

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

    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

  11. Optimization of Muscle Activity for Task-Level Goals Predicts Complex Changes in Limb Forces across Biomechanical Contexts

    McKay, J. Lucas; Ting, Lena H.

    2012-01-01

    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 i...

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

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

    2015-01-01

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

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

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

    2016-01-01

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

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

    Antonio Montresor

    2016-04-01

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

  15. Are Some Semantic Changes Predictable?

    Schousboe, Steen

    2010-01-01

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

  16. Using Constructs of the Transtheoretical Model to Predict Classes of Change in Regular Physical Activity: A Multi-Ethnic Longitudinal Cohort Study

    Vandenberg, Robert J.; Motl, Robert W.; Nigg, Claudio R.

    2011-01-01

    Explaining variation in meeting recommended levels of physical activity across time is important for the design of effective public health interventions. To model longitudinal change in constructs of the Transtheoretical Model and test their hypothesized relations with change in meeting the Healthy People 2010 guidelines for regular participation in moderate or vigorous physical activity, a cohort (N=497) from a random, multi-ethnic sample of 700 adults living in Hawaii was assessed at 6-month intervals three or more times for 2 years. Latent class growth modeling was used to classify people according to their initial levels and trajectories of change in the transtheoretical variables and separately according to whether they met the physical activity guideline each time. Relations of the variables and their change with classes of meeting the guideline were then tested using multinomial logistic regression. Despite declines or no change in mean scores for all transtheoretical variables except self-efficacy, participants who maintained or attained the physical activity guideline were more likely to retain higher scores across the 2 years of observation. The usefulness of transtheoretical constructs for predicting maintenance of, or increases in, public health levels of physical activity was generally supported. These longitudinal results support earlier cross-sectional findings which indicate that, contrary to theory, people appear to use both experiential and behavioral processes while they attempt to increase or maintain their physical activity. PMID:20552417

  17. A model for aryl hydrocarbon receptor-activated gene expression shows potency and efficacy changes and predicts squelching due to competition for transcription co-activators.

    Ted W Simon

    Full Text Available A stochastic model of nuclear receptor-mediated transcription was developed based on activation of the aryl hydrocarbon receptor (AHR by 2,3,7,8-tetrachlorodibenzodioxin (TCDD and subsequent binding the activated AHR to xenobiotic response elements (XREs on DNA. The model was based on effects observed in cells lines commonly used as in vitro experimental systems. Following ligand binding, the AHR moves into the cell nucleus and forms a heterodimer with the aryl hydrocarbon nuclear translocator (ARNT. In the model, a requirement for binding to DNA is that a generic coregulatory protein is subsequently bound to the AHR-ARNT dimer. Varying the amount of coregulator available within the nucleus altered both the potency and efficacy of TCDD for inducing for transcription of CYP1A1 mRNA, a commonly used marker for activation of the AHR. Lowering the amount of available cofactor slightly increased the EC50 for the transcriptional response without changing the efficacy or maximal response. Further reduction in the amount of cofactor reduced the efficacy and produced non-monotonic dose-response curves (NMDRCs at higher ligand concentrations. The shapes of these NMDRCs were reminiscent of the phenomenon of squelching. Resource limitations for transcriptional machinery are becoming apparent in eukaryotic cells. Within single cells, nuclear receptor-mediated gene expression appears to be a stochastic process; however, intercellular communication and other aspects of tissue coordination may represent a compensatory process to maintain an organism's ability to respond on a phenotypic level to various stimuli within an inconstant environment.

  18. Permafrost, climate, and change: predictive modelling approach.

    Anisimov, O.

    2003-04-01

    Predicted by GCMs enhanced warming of the Arctic will lead to discernible impacts on permafrost and northern environment. Mathematical models of different complexity forced by scenarios of climate change may be used to predict such changes. Permafrost models that are currently in use may be divided into four groups: index-based models (e.g. frost index model, N-factor model); models of intermediate complexity based on equilibrium simplified solution of the Stephan problem ("Koudriavtcev's" model and its modifications), and full-scale comprehensive dynamical models. New approach of stochastic modelling came into existence recently and has good prospects for the future. Important task is to compare the ability of the models that are different in complexity, concept, and input data requirements to capture the major impacts of changing climate on permafrost. A progressive increase in the depth of seasonal thawing (often referred to as the active-layer thickness, ALT) could be a relatively short-term reaction to climatic warming. At regional and local scales, it may produce substantial effects on vegetation, soil hydrology and runoff, as the water storage capacity of near-surface permafrost will be changed. Growing public concerns are associated with the impacts that warming of permafrost may have on engineered infrastructure built upon it. At the global scale, increase of ALT could facilitate further climatic change if more greenhouse gases are released when the upper layer of the permafrost thaws. Since dynamic permafrost models require complete set of forcing data that is not readily available on the circumpolar scale, they could be used most effectively in regional studies, while models of intermediate complexity are currently best tools for the circumpolar assessments. Set of five transient scenarios of climate change for the period 1980 - 2100 has been constructed using outputs from GFDL, NCAR, CCC, HadCM, and ECHAM-4 models. These GCMs were selected in the course

  19. Climate Change as a Predictable Surprise

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

  20. Using Constructs of the Transtheoretical Model to Predict Classes of Change in Regular Physical Activity: A Multi-Ethnic Longitudinal Cohort Study

    Dishman, Rod K.; Vandenberg, Robert J.; Motl, Robert W.; Nigg, Claudio R

    2010-01-01

    Explaining variation in meeting recommended levels of physical activity across time is important for the design of effective public health interventions. To model longitudinal change in constructs of the Transtheoretical Model and test their hypothesized relations with change in meeting the Healthy People 2010 guidelines for regular participation in moderate or vigorous physical activity, a cohort (N=497) from a random, multi-ethnic sample of 700 adults living in Hawaii was assessed at 6-mont...

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

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

  2. Human activity recognition and prediction

    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. .

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

    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

  4. Activity Prediction: A Twitter-based Exploration

    Weerkamp, W.; Rijke, de, 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, that is, trying to establish a set of activities that are likely to become popular at a later time. We perform a small-scale initial experiment, in which we try to predict popular activities for the ...

  5. Diffusion changes predict cognitive and functional outcome

    Jokinen, Hanna; Schmidt, Reinhold; Ropele, Stefan; Fazekas, Franz; Gouw, Alida A; Barkhof, Frederik; Scheltens, Philip; Madureira, Sofia; Verdelho, Ana; Ferro, José M; Wallin, Anders; Poggesi, Anna; Inzitari, Domenico; Pantoni, Leonardo; Erkinjuntti, Timo; Group, LADIS Study; Waldemar, Gunhild

    2013-01-01

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

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

    Dormann, Carsten F; Schweiger, Oliver; Arens, P; Augenstein, I; Aviron, St; Bailey, Debra; Baudry, J; Billeter, R; Bugter, R; Bukácek, R; Burel, F; Cerny, M; Cock, Raphaël De; De Blust, Geert; DeFilippi, R; Diekötter, Tim; Dirksen, J; Durka, W; Edwards, P J; Frenzel, M; Hamersky, R; Hendrickx, Frederik; Herzog, F; Klotz, St; Koolstra, B; Lausch, A; Le Coeur, D; Liira, J; Maelfait, J P; Opdam, P; Roubalova, M; Schermann-Legionnet, Agnes; Schermann, N; Schmidt, T; Smulders, M J M; Speelmans, M; Simova, P; Verboom, J; van Wingerden, Walter; Zobel, M

    2008-03-01

    Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental change (such as in climate or land cover) on biodiversity may differ considerably, depending on the chosen set of explanatory variables. Here we use multimodel prediction to evaluate effects of climate, land-use intensity and landscape structure on species richness in each of seven groups of organisms (plants, birds, spiders, wild bees, ground beetles, true bugs and hoverflies) in temperate Europe. We contrast this approach with traditional best-model predictions, which we show, using cross-validation, to have inferior prediction accuracy. Multimodel inference changed the importance of some environmental variables in comparison with the best model, and accordingly gave deviating predictions for environmental change effects. Overall, prediction uncertainty for the multimodel approach was only slightly higher than that of the best model, and absolute changes in predicted species richness were also comparable. Richness predictions varied generally more for the impact of climate change than for land-use change at the coarse scale of our study. Overall, our study indicates that the uncertainty introduced to environmental change predictions through uncertainty in model selection both qualitatively and quantitatively affects species richness projections. PMID:18070098

  7. Relationship between efficiency and predictability in stock price change

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

    2008-09-01

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

  8. Predictive modeling of effects under global change.

    Kickert, R N; Tonella, G; Simonov, A; Krupa, S V

    1999-01-01

    The status of computer simulation models from around the world for evaluating the possible ecological, environmental, and societal consequences of global change is presented in this paper. In addition, a brief synopsis of the state of the science of these impacts is included. Issues considered include future changes in climate and patterns of land use for societal needs. Models discussed relate to vegetation (e.g. crop), soil, bio-geochemistry, water, and wildlife responses to conventional, forecasted changes in temperature and precipitation. Also described are models of these responses, alone and interactively, to increased CO(2), other air pollutants and UV-B radiation, as the state of the science allows. Further, models of land-use change are included. Additionally, global multiple sector models of environment, natural resources, human population dynamics, economics, energy, and political relations are reviewed for integrated impact assessment. To the extent available, information on computer software and hardware requirements is presented for the various models. The paper concludes with comments about using these technologies as they relate to ecological risk assessment for policy decision analysis. Such an effort is hampered by considerable uncertainties with the output of existing models, because of the uncertainties associated with input data and the definitions of their dose-response relationships. The concluding suggestions point the direction for new developments in modeling and analyses that are needed for the 21st century. PMID:15093114

  9. Prediction control of active power filters

    王莉娜; 罗安

    2003-01-01

    A prediction method to obtain harmonic reference for active power filter is presented. It is a new use ofthe adaptive predictive filter based on FIR. The delay inherent in digital controller is successfully compensated by u-sing the proposed method, and the computing load is not very large compared with the conventional method. Moreo-ver, no additional hardware is needed. Its DSP-based realization is also presented, which is characterized by time-va-riant rate sampling, quasi synchronous sampling, and synchronous operation among the line frequency, PWM gener-ating and sampling in A/D unit. Synchronous operation releases the limitation on PWM modulation ratio and guar-antees that the electrical noises resulting from the switching operation of IGBTs do not interfere with the sampledcurrent. The simulation and experimental results verify the satisfactory performance of the proposed method.

  10. Climate change and related activities

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

  11. CERAPP: Collaborative estrogen receptor activity prediction project

    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) and...

  12. Resting alpha activity predicts learning ability in alpha neurofeedback

    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.

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

    Müller, Daniel; Sun, Zhanli; Vongvisouk, Thoumthone;

    2014-01-01

    and abrupt change that invalidate predictions calibrated on past trends. Rapid land-system change can occur when critical thresholds in broad-scale underlying drivers such as commodity prices and climate conditions are crossed or when sudden events such as political change or natural disasters punctuate long...... (China, Laos, Vietnam and Indonesia). The results show how sudden events and gradual changes in underlying drivers caused rapid, surprising and widespread land-system changes, including shifts to different regimes in China, Vietnam and Indonesia, whereas land systems in Laos remained stable in the study...... period but show recent signs of rapid change. The observed regime shifts were difficult to anticipate, which compromises the validity of predictions of future land-system changes and the assessment of their impact on greenhouse gas emissions, hydrological processes, agriculture, biodiversity...

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

    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.

  15. Predicting coastal morphological changes with empirical orthogonal functionmethod

    Fernando Alvarez

    2016-01-01

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

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

    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. Special Analysis For Predicting Changes In Mangrove Forest

    Yumna; Irman Halid

    2015-01-01

    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 in...

  18. Social change and physical activity

    Engström, Lars-Magnus

    2008-01-01

    Today’s Western society is undergoing rapid change, and the speed of this process of change seems to be increasing. One of the major social changes is the gradual changeover from daily lives that contained high levels of physical effort to lives that are increasingly sedentary. A sedentary lifestyle is not without its problems. Several common illnesses are related to physical inactivity. Athletics, exercise, outdoor life and trend sports must be regarded as expressions of lifestyle and not as...

  19. RECENT CHANGES IN THUNDERSTORM ACTIVITY IN VASLUI

    Mihai Florin Necula

    2010-10-01

    Full Text Available A thunderstorm (also called an electrical storm is a form of weather characterized by the presence of lightning and its attendant thunder, produced from a cumulonimbus cloud. Thunderstorms form when significant condensation (resulting in the production of a wide range of water droplets and ice crystals occurs in an atmosphere that is unstable and supports deep, rapid upward motion. This appears in the presence of three conditions: sufficient moisture accumulated in the lower atmosphere, reflected by high temperatures; a significant fall in air temperature with increasing height (steep adiabatic lapse rate; and a force such as mechanical convergence along a cold front to focus the lift. The process to initiate vertical lifting can be caused by: (1 unequal warming of the surface of the Earth, (2 orographic lifting due to topographic obstruction of airflow, and (3 dynamic lifting created by the presence of a frontal zone. As an intricate part of the global climatic system, thunderstorms pattern and activity are highly susceptible to anthropogenic climate change, and recent observation concerning thunderstorms in Vaslui seems to support this connection. But even if this is only a temporary period of anomaly, a cyclic variation or the beginning of a trend prone to continue in the future, the period spanning more than 22 years analyzed in this paper (1985-2006, deserve some more in depth research, because of the significant and rapid developments in thunderstorm activity, and also considering the� ackground: this interval contains the top 17 hottest years ever recorded in the instrumental meteorology era. In addition, the fact that the changes in thunderstorm activity can be clearly linked to the significant changes in the way precipitations fall in the warm season, opens a new way in which the ferocity and destructive force of recent extreme weather phenomena can be explained, and ultimately predicted .

  20. Phylogeny predicts future habitat shifts due to climate change.

    Matjaž Kuntner

    Full Text Available 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.

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

    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....

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

    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.

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

    Twedt, Daniel J.; Tirpak, John M.; Jones-Farrand, D. Todd; Thompson, Frank R., III; 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

  4. Active Learning about Climate Change

    Hwang, I.C.; Tol, R.S.J.; Hofkes, M.W.

    2013-01-01

    We develop a climate-economy model with active learning. We consider three ways of active learning: improved observations, adding observations from the past and improved theory from climate research. From the model, we find that the decision maker invests a significant amount of money in climate research. Expenditures to increase the rate of learning are far greater than the current level of expenditure on climate research, as it helps in taking improved decisions. The optimal carbon tax for ...

  5. Predicting Changes in the Radio Emission Fluxes of Extragalactic Sources

    Sukharev, A. L.; Ryabov, M. I.; Donskikh, G. I.

    2016-06-01

    Data from long-term monitoring with the 26-m University of Michigan radio telescope at a frequency of 14.5 GHz (1974-2011) is used to predict changes in the radio emission fluxes from the extragalactic sources 3C273, 3C120, 3C345, 3C446, 3C454.3, OJ287, OT081, and BLLac. The predictions are based on data on the major periods of variability and their durations obtained by wavelet analysis. The radio emission fluxes from the sources 3C345, 3C446, and 3C454.3, which have complicated variabilities, are predicted using an autoregression linear prediction method. This yields a forecast of the flux variations extending up to 5 years. Harmonic prediction is used for another group of sources, BLLac, OJ287, and OT081, with rapid variability. This approach yielded forecasts extending 4-9 years. For the sources 3C273 and 3C120, which have stable long periods, the harmonic method was also used and yielded a forecast extending up to 16 years. The reliability of the prediction was confirmed by independent observational data from the MOJAVE program for 2011-2015.

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

    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.

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

    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

  8. Predicting Climate Change Impacts to the Canadian Boreal Forest

    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.

  9. Hydrologic predictions in a changing environment: behavioral modeling

    B. Schaefli

    2010-10-01

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

  10. The Built Environment Predicts Observed Physical Activity

    Kelly, Cheryl; Wilson, Jeffrey S.; Schootman, Mario; Clennin, Morgan; Baker, Elizabeth A.; Miller, Douglas K.

    2014-01-01

    Background: In order to improve our understanding of the relationship between the built environment and physical activity, it is important to identify associations between specific geographic characteristics and physical activity behaviors. Purpose: Examine relationships between observed physical activity behavior and measures of the built environment collected on 291 street segments in Indianapolis and St. Louis. Methods: Street segments were selected using a stratified geographic samp...

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

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

  12. Active Power Filter Using Predicted Current Control

    Xiaojie, Y.; Pivoňka, P.; Valouch, Viktor

    2001-01-01

    Roč. 46, č. 1 (2001), s. 41-50. ISSN 0001-7043 Institutional research plan: CEZ:AV0Z2057903 Keywords : active power filter * control strategy Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

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

    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. PMID:25212581

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

    McLean, Nina; Lawson, Callum R; Leech, Dave I; van de Pol, Martijn

    2016-06-01

    Species' responses to climate change are variable and diverse, yet our understanding of how different responses (e.g. physiological, behavioural, demographic) relate and how they affect the parameters most relevant for conservation (e.g. population persistence) is lacking. Despite this, studies that observe changes in one type of response typically assume that effects on population dynamics will occur, perhaps fallaciously. We use a hierarchical framework to explain and test when impacts of climate on traits (e.g. phenology) affect demographic rates (e.g. reproduction) and in turn population dynamics. Using this conceptual framework, we distinguish four mechanisms that can prevent lower-level responses from impacting population dynamics. Testable hypotheses were identified from the literature that suggest life-history and ecological characteristics which could predict when these mechanisms are likely to be important. A quantitative example on birds illustrates how, even with limited data and without fully-parameterized population models, new insights can be gained; differences among species in the impacts of climate-driven phenological changes on population growth were not explained by the number of broods or density dependence. Our approach helps to predict the types of species in which climate sensitivities of phenotypic traits have strong demographic and population consequences, which is crucial for conservation prioritization of data-deficient species. PMID:27062059

  15. Decreased dopamine activity predicts relapse in methamphetamine abusers

    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 (11C)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.

  16. Decreased dopamine activity predicts relapse in methamphetamine abusers

    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.

  17. Prediction of subsurface water level change from satellite data

    Saykawlard, Suphan; Honda, Kiyoshi; Das Gupta, Ashim; Eiumnoh, Apisit; Chen, Xiaoyong

    2005-03-01

    This study explores the potential for predicting the spatial variation in subsurface water level change with crop growth stage from satellite data in Thabua Irrigation Project, situated in the northern central region of Thailand. The relationship between subsurface water level change from pumping water to irrigate rice in the dry season and the age of the rice was analysed. The spatial model of subsurface water level change was developed from the classification using greenness or (normalized difference vegetation index NDVI) derived from Landsat 5 Thematic Mapper data. The NDVI of 52 rice fields was employed to assess its relationship to the age of the rice. It was found that NDVI and rice age have a good correlation (R2 = 0.73). The low NDVI values (-0.059 to 0.082) in these fields were related to the young rice stage (0-30 days). NDVI and subsurface water level change were also correlated in this study and found to have a high correlation (Water level change (m day-1) = 0.3442 × NDVI - 0.0372; R2 = 0.96). From this model, the water level change caused by rice at different growth stages was derived. This was used to show the spatial variation of water level change in the project during the 1998-99 dry-season cropping. This simple method of using NDVI relationships with water level change and crop growth stages proves to be useful in determining the areas prone to excessive lowering of the subsurface water level during the dry season. This could assist in the appropriate planning of the use of subsurface water resources in dry-season cropping.

  18. Predicting mining activity with parallel genetic algorithms

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.

    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.

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

    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

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

    Brander, Keith

    2010-01-01

    , predators, parasites and diseases are much more difficult to estimate and predict. Climate can affect all life-history stages through direct and indirect processes and although the consequences in terms of growth, survival and reproductive output can be monitored, it is often difficult to determine...... the causes. Investigation of cod Gadus morhua populations across the whole North Atlantic Ocean has shown large-scale patterns of change in productivity due to lower individual growth and condition, caused by large-scale climate forcing. If a population is being heavily exploited then a drop in productivity...... can push it into decline unless the level of fishing is reduced: the idea of a stable carrying capacity is a dangerous myth. Overexploitation can be avoided by keeping fishing mortality low and by monitoring and responding rapidly to changes in productivity. There are signs that this lesson has been...

  1. Should we believe model predictions of future climate change? (Invited)

    Knutti, R.

    2009-12-01

    As computers get faster and our understanding of the climate system improves, climate models to predict the future are getting more complex by including more and more processes, and they are run at higher and higher resolution to resolve more of the small scale processes. As a result, some of the simulated features and structures, e.g. ocean eddies or tropical cyclones look surprisingly real. But are these deceptive? A pattern can look perfectly real but be in the wrong place. So can the current global models really provide the kind of information on local scales and on the quantities (e.g. extreme events) that the decision maker would need to know to invest for example in adaptation? A closer look indicates that evaluating skill of climate models and quantifying uncertainties in predictions is very difficult. This presentation shows that while models are improving in simulating the climate features we observe (e.g. the present day mean state, or the El Nino Southern Oscillation), the spread from multiple models in predicting future changes is often not decreasing. The main problem is that (unlike with weather forecasts for example) we cannot evaluate the model on a prediction (for example for the year 2100) and we have to use the present, or past changes as metrics of skills. But there are infinite ways of testing a model, and many metrics used to test models do not clearly relate to the prediction. Therefore there is little agreement in the community on metrics to separate ‘good’ and ‘bad’ models, and there is a concern that model development, evaluation and posterior weighting or ranking of models are all using the same datasets. While models are continuously improving in representing what we believe to be the key processes, many models also share ideas, parameterizations or even pieces of model code. The current models can therefore not be considered independent. Robustness of a model simulated result is often interpreted as increasing the confidence

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

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

    2011-12-01

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

  3. Kazakhstan : Overview of Climate Change Activities

    World Bank

    2013-01-01

    This overview of climate change activities in Kazakhstan 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 contrib...

  4. Kyrgyz Republic : Overview of Climate Change Activities

    World Bank

    2013-01-01

    This overview of climate change activities in the Kyrgyz Republic is part of a series of country notes for five Central Asian countries that summarize climate portfolio in a number of sectors, namely agriculture, forestry, water, health, energy, and transport. Recognizing the nature and significance of climate change contribution to an increase in disaster risk, the note also looks into th...

  5. Tajikistan : Overview of Climate Change Activities

    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...

  6. Using Proximity to Predict Activity in Social Networks

    Lerman, Kristina; Intagorn, Suradej; Kang, Jeon-Hyung; Ghosh, Rumi

    2011-01-01

    The structure of a social network contains information useful for predicting its evolution. Nodes that are "close" in some sense are more likely to become linked in the future than more distant nodes. We show that structural information can also help predict node activity. We use proximity to capture the degree to which two nodes are "close" to each other in the network. In addition to standard proximity metrics used in the link prediction task, such as neighborhood overlap, we introduce new ...

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

    Kelly P Adam

    2011-07-01

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

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

    Ross S. Davidson

    2012-03-01

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

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

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

    2012-01-01

    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. PMID:26486780

  10. Institutional Constraints, Legislative Activism, and Policy Change

    Citi, Manuele; Justesen, Mogens Kamp

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

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

    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. PMID:20379149

  12. Changes in active commuting and changes in physical activity in adults: a cohort study

    Foley, Louise; Panter, Jenna; Heinen, Eva; Prins, Richard; Ogilvie, David

    2015-01-01

    Background Active travel is associated with greater physical activity, but there is a dearth of research examining this relationship over time. We examined the longitudinal associations between change in time spent in active commuting and changes in recreational and total physical activity. Methods Adult commuters working in Cambridge, United Kingdom completed questionnaires in 2009 and 2012, and a sub-set completed objective physical activity monitoring in 2010 and 2012. Commuting was assess...

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

    Mochizuki, Koji; Takayama, Kozo

    2016-07-01

    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. PMID:26559666

  14. Betting and Belief: Prediction Markets and Attribution of Climate Change

    Nay, John J; Gilligan, Jonathan M

    2016-01-01

    Despite much scientific evidence, a large fraction of the American public doubts that greenhouse gases are causing global warming. We present a simulation model as a computational test-bed for climate prediction markets. Traders adapt their beliefs about future temperatures based on the profits of other traders in their social network. We simulate two alternative climate futures, in which global temperatures are primarily driven either by carbon dioxide or by solar irradiance. These represent, respectively, the scientific consensus and a hypothesis advanced by prominent skeptics. We conduct sensitivity analyses to determine how a variety of factors describing both the market and the physical climate may affect traders' beliefs about the cause of global climate change. Market participation causes most traders to converge quickly toward believing the "true" climate model, suggesting that a climate market could be useful for building public consensus.

  15. Solar activities and Climate change hazards

    Hady, A. A., II

    2014-12-01

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

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

    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...

  17. The prediction of changes of characteristics of materials and units of the drive mechanism of solar arrays of a spacecraft with the term of active existence of 10 to 15 years

    Shatikhin, V. Ye.; Pereverziev, Ye. S.; Daniiev, Yu. F.

    We consider changes of characteristics of materials and units of the drive mechanism of solar arrays of spacecraft under the influence of open space factors for the term of active existence of 10 to 15 years. The main open space factors effecting on the characteristics of materials and units of the drive mechanism are listed. The analysis of possible flaws and failures of the drive mechanism is made. We derived the probability of the penetration of meteoric bodies for a drive unit of a solar array during a 10-year and a 15-year flights. We developed some recommendations concerning the elaboration of solar array drive mechanisms for spacecraft with the long term of existence.

  18. Predicting Physical Activity in Arab American School Children

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

    2008-01-01

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

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

    Luis-Miguel Chevin

    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.

  20. Predicting eruptions from precursory activity using remote sensing data hybridization

    Reath, K. A.; Ramsey, M. S.; Dehn, J.; Webley, P. W.

    2016-07-01

    Many volcanoes produce some level of precursory activity prior to an eruption. This activity may or may not be detected depending on the available monitoring technology. In certain cases, precursors such as thermal output can be interpreted to make forecasts about the time and magnitude of the impending eruption. Kamchatka (Russia) provides an ideal natural laboratory to study a wide variety of eruption styles and precursory activity prior to an eruption. At Bezymianny volcano for example, a clear increase in thermal activity commonly occurs before an eruption, which has allowed predictions to be made months ahead of time. Conversely, the eruption of Tolbachik volcano in 2012 produced no discernable thermal precursors before the large scale effusive eruption. However, most volcanoes fall between the extremes of consistently behaved and completely undetectable, which is the case with neighboring Kliuchevskoi volcano. This study tests the effectiveness of using thermal infrared (TIR) remote sensing to track volcanic thermal precursors using data from both the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Advanced Very High Resolution Radiometer (AVHRR) sensors. It focuses on three large eruptions that produced different levels and durations of effusive and explosive behavior at Kliuchevskoi. Before each of these eruptions, TIR spaceborne sensors detected thermal anomalies (i.e., pixels with brightness temperatures > 2 °C above the background temperature). High-temporal, low-spatial resolution (i.e., ~ hours and 1 km) AVHRR data are ideal for detecting large thermal events occurring over shorter time scales, such as the hot material ejected following strombolian eruptions. In contrast, high-spatial, low-temporal resolution (i.e., days to weeks and 90 m) ASTER data enables the detection of much lower thermal activity; however, activity with a shorter duration will commonly be missed. ASTER and AVHRR data are combined to track low

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

    Henao, Ricardo; Winther, Ole

    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...... the active set selection strategy and marginal likelihood optimization on the active set. We make extensive tests on the USPS and MNIST digit classification databases with and without incorporating invariances, demonstrating that we can get state-of-the-art results (e.g.0.86% error on MNIST) with...

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

    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

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

    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.

  4. Pacific Walrus and climate change: observations and predictions.

    Maccracken, James G

    2012-08-01

    The extent and duration of sea-ice habitats used by Pacific walrus (Odobenus rosmarus divergens) are diminishing resulting in altered walrus behavior, mortality, and distribution. I document changes that have occurred over the past several decades and make predictions to the end of the 21st century. Climate models project that sea ice will monotonically decline resulting in more ice-free summers of longer duration. Several stressors that may impact walruses are directly influenced by sea ice. How these stressors materialize were modeled as most likely-case, worst-case, and best-case scenarios for the mid- and late-21st century, resulting in four comprehensive working hypotheses that can help identify and prioritize management and research projects, identify comprehensive mitigation actions, and guide monitoring programs to track future developments and adjust programs as needed. In the short term, the most plausible hypotheses predict a continuing northward shift in walrus distribution, increasing use of coastal haulouts in summer and fall, and a population reduction set by the carrying capacity of the near shore environment and subsistence hunting. Alternatively, under worst-case conditions, the population will decline to a level where the probability of extinction is high. In the long term, walrus may seasonally abandon the Bering and Chukchi Seas for sea-ice refugia to the northwest and northeast, ocean warming and pH decline alter walrus food resources, and subsistence hunting exacerbates a large population decline. However, conditions that reverse current trends in sea ice loss cannot be ruled out. Which hypothesis comes to fruition depends on how the stressors develop and the success of mitigation measures. Best-case scenarios indicate that successful mitigation of unsustainable harvests and terrestrial haulout-related mortalities can be effective. Management and research should focus on monitoring, elucidating effects, and mitigation, while ultimately

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

    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.

  6. Predicted changes in energy demands for heating and cooling due to climate change

    Dolinar, Mojca; Vidrih, Boris; Kajfež-Bogataj, Lučka; Medved, Sašo

    In the last 3 years in Slovenia we experienced extremely hot summers and demand for cooling the buildings have risen significantly. Since climate change scenarios predict higher temperatures for the whole country and for all seasons, we expect that energy demand for heating would decrease while demand for cooling would increase. An analysis for building with permitted energy demand and for low-energy demand building in two typical urban climates in Slovenia was performed. The transient systems simulation program (TRNSYS) was used for simulation of the indoor conditions and the energy use for heating and cooling. Climate change scenarios were presented in form of “future” Test Reference Years (TRY). The time series of hourly data for all meteorological variables for different scenarios were chosen from actual measurements, using the method of highest likelihood. The climate change scenarios predicted temperature rise (+1 °C and +3 °C) and solar radiation increase (+3% and +6%). With the selection of these scenarios we covered the spectra of possible predicted climate changes in Slovenia. The results show that energy use for heating would decrease from 16% to 25% (depends on the intensity of warming) in subalpine region, while in Mediterranean region the rate of change would not be significant. In summer time we would need up to six times more energy for cooling in subalpine region and approximately two times more in Mediterranean region. low-energy building proved to be very economical in wintertime while on average higher energy consumption for cooling is expected in those buildings in summertime. In case of significant warmer and more solar energy intensive climate, the good isolated buildings are more efficient than standard buildings. TRY proved not to be efficient for studying extreme conditions like installed power of the cooling system.

  7. Nonlinear Predictive Control of Semi-Active Landing Gear System

    Wu, Dongsu; Gu, Hongbin; Liu, Hui

    2010-01-01

    The application of model predictive control and constructive nonlinear control methodology to semi-active landing gear system is studied in this paper. A unified shock absorber mathematical model incorporates solenoid valve’s electromechanical and magnetic dynamics is built to facilitate simulation and controller design. Then we propose a hierarchical control structure to deal with the high nonlinearity. A dual mode model predictive controller as an outer loop controller is developed to gen...

  8. The inventory-based approach for prediction of SOC change following land use change

    van Wesemael B.

    2004-01-01

    Full Text Available This paper describes and illustrates an approach to predict soil organic carbon (SOC change in time after land use change as derived from SOC differences in space. The approach requires the availability of a SOC inventory for spatially explicit combinations of soil and land use type, further termed landscape units (LSU. SOC of LSU with equal soil type but different land use type are compared and the observed differences in SOC are interpreted as the expected SOC change after the corresponding land use change. From a confrontation with time series of agro-statistical data on crop and grassland areas and on animal manure production, we conclude that the approach is a low-cost alternative for more complex methods like multitemporal assessments and modelling, provided that (i an inventory reflecting current management and climate conditions and (ii additional information on the extent and type of recent land use changes are available. Examples of land use and land management changes are discussed, such as grassland – cropland conversions, the conversion of permanent to temporary grassland, or changes in manure application.

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

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

    2016-01-01

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

  10. Changes in proinflammatory cytokine activity after menopause.

    Pfeilschifter, Johannes; Köditz, Roland; Pfohl, Martin; Schatz, Helmut

    2002-02-01

    There is now a large body of evidence suggesting that the decline in ovarian function with menopause is associated with spontaneous increases in proinflammatory cytokines. The cytokines that have obtained the most attention are IL-1, IL-6, and TNF-alpha. The exact mechanisms by which estrogen interferes with cytokine activity are still incompletely known but may potentially include interactions of the ER with other transcription factors, modulation of nitric oxide activity, antioxidative effects, plasma membrane actions, and changes in immune cell function. Experimental and clinical studies strongly support a link between the increased state of proinflammatory cytokine activity and postmenopausal bone loss. Preliminary evidence suggests that these changes also might be relevant to vascular homeostasis and the development of atherosclerosis. Better knowledge of the mechanisms and the time course of these interactions may open new avenues for the prevention and treatment of some of the most prevalent and important disorders in postmenopausal women. PMID:11844745

  11. Structure based activity prediction of HIV-1 reverse transcriptase inhibitors.

    de Jonge, Marc R; Koymans, Lucien M H; Vinkers, H Maarten; Daeyaert, Frits F D; Heeres, Jan; Lewi, Paul J; Janssen, Paul A J

    2005-03-24

    We have developed a fast and robust computational method for prediction of antiviral activity in automated de novo design of HIV-1 reverse transcriptase inhibitors. This is a structure-based approach that uses a linear relation between activity and interaction energy with discrete orientation sampling and with localized interaction energy terms. The localization allows for the analysis of mutations of the protein target and for the separation of inhibition and a specific binding to the enzyme. We apply the method to the prediction of pIC(50) of HIV-1 reverse transcriptase inhibitors. The model predicts the activity of an arbitrary compound with a q(2) of 0.681 and an average absolute error of 0.66 log value, and it is fast enough to be used in high-throughput computational applications. PMID:15771460

  12. Turn, turn, turn: Predicting turning points in economic activity

    Marco Del Negro

    2001-01-01

    Policy and investment decisions are made with an eye toward future economic conditions, and an econometric model that can correctly forecast directional changes in the business cycle would be a boon to policymakers, the business community, and the general public. This article provides some evidence on econometric models' ability to predict these directional changes, also known as turning points, in an effort to answer the question, How good is the state of the art in turning point forecasting...

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

    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...

  14. Incorporating Student Activities into Climate Change Education

    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.

  15. Multinationals' Political Activities on Climate Change

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

  16. Predicting Active Users' Personality Based on Micro-Blogging Behaviors

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

    2014-01-01

    Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 845 micro-blogging behavioral fe...

  17. Predicting China’s Land-use Change and Soil Carbon Sequestration under Alternative Climate Change Scenarios

    Li, Man; Wu, Junjie

    2010-01-01

    This paper examines and predicts the effects of climate change and climate extremes on China’s land use conversion and soil carbon sequestration under two alternative climate change scenarios. It intends to investigate the following three questions. 1) How did climate factors affect land-use conversion in China from 1988 to 2000 and what was the relative importance of these factors? 2) How would the predicted future climate change pattern affect land-use choice under alternative climate chang...

  18. The climatic change induced by human activities

    The climate of the Earth is a changing climate. Along their history many natural climate changes have existed in all time scales. At the present time we use the term climate changes have existed in all time scales. At the present time we use the term climate change in a restricted way, understanding that we have referring to a singular change that has their origin in the modification of the natural composition of the atmosphere. The increase of greenhouse gases from the second half the XVIII century, is due to the human activities of fossil fuels burning to obtain energy and to industrial and agricultural activities needing for the development of a world which population has been duplicated between 1960 and 2000, until overcoming the 6,000 million inhabitants. In particular, the concentrations of carbon dioxide-CO2 have increased in a 34%. The more recent emission scenarios proposed by the IPCC (SRES, 2000) are based on hypothesis about the population evolution, the energy consumption and the word patterns of development, which are grouped in four families dominated as A1, A2, B1 and B2. The answer for these scenarios from a range of climate models results in an increase of the world average surface atmospheric temperature between 1,4 degree centigrade and 5,8 degree centigrade and a corresponding sea level rise understood between 9 cm and 88 cm. The changes in the precipitation patterns show us that could be above to the current one in high and media latitudes and below in subtropical latitudes, with exceptions highly depending of the model used. (Author)

  19. Optimal Coding Predicts Attentional Modulation of Activity in Neural Systems

    Jaramillo, Santiago; Pearlmutter, Barak A.

    2007-01-01

    Neuronal activity in response to a fixed stimulus has been shown to change as a function of attentional state, implying that the neural code also changes with attention. We propose an information-theoretic account of such modulation: that the nervous system adapts to optimally encode sensory stimuli while taking into account the changing relevance of different features. We show using computer simulation that such modulation emerges in a coding system informed about the uneven relevance of ...

  20. Demographic Metabolism: A Predictive Theory of Socio-economic Change

    Lutz, Wolfgang

    2013-01-01

    This essay introduces a general theory of how societies change as a consequence of the changing composition of their members with respect to certain relevant and measurable characteristics. These characteristics can either change over the life course of individuals or from one generation to the next. While the former changes can be analytically identified and described by certain age- and duration-specific transition schedules, the latter changes resulting from cohort replacement can be mode...

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

    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.

  2. Prediction of Changes in Vegetation Distribution Under Climate Change Scenarios Using Modis Dataset

    Hirayama, Hidetake; Tomita, Mizuki; Hara, Keitarou

    2016-06-01

    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.

  3. Human activities change marine ecosystems by altering predation risk.

    Madin, Elizabeth M P; Dill, Lawrence M; Ridlon, April D; Heithaus, Michael R; Warner, Robert R

    2016-01-01

    In ocean ecosystems, many of the changes in predation risk - both increases and decreases - are human-induced. These changes are occurring at scales ranging from global to local and across variable temporal scales. Indirect, risk-based effects of human activity are known to be important in structuring some terrestrial ecosystems, but these impacts have largely been neglected in oceans. Here, we synthesize existing literature and data to explore multiple lines of evidence that collectively suggest diverse human activities are changing marine ecosystems, including carbon storage capacity, in myriad ways by altering predation risk. We provide novel, compelling evidence that at least one key human activity, overfishing, can lead to distinct, cascading risk effects in natural ecosystems whose magnitude exceeds that of presumed lethal effects and may account for previously unexplained findings. We further discuss the conservation implications of human-caused indirect risk effects. Finally, we provide a predictive framework for when human alterations of risk in oceans should lead to cascading effects and outline a prospectus for future research. Given the speed and extent with which human activities are altering marine risk landscapes, it is crucial that conservation and management policy considers the indirect effects of these activities in order to increase the likelihood of success and avoid unfortunate surprises. PMID:26448058

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

    Lin Li

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

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

    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.

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

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

    2016-01-01

    Tail biting, resulting in outbreaks of tail damage in pigs, is a multifactorial welfare and economic problem which is usually partly prevented through tail docking. According to European Union legislation, tail docking is not allowed on a routine basis; thus there is a need for alternative...... preventive methods. One strategy is the surveillance of the pigs' behaviour for known preceding indicators of tail damage, which makes it possible to predict a tail damage outbreak and prevent it in proper time. This review discusses the existing literature on behavioural changes observed prior to a tail...... damage outbreak. Behaviours found to change prior to an outbreak include increased activity level, increased performance of enrichment object manipulation, and a changed proportion of tail posture with more tails between the legs. Monitoring these types of behaviours is also discussed for the purpose of...

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

    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

  8. Ways that Social Change Predicts Personal Quality of Life

    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…

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

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

    2016-03-01

    Tail biting, resulting in outbreaks of tail damage in pigs, is a multifactorial welfare and economic problem which is usually partly prevented through tail docking. According to European Union legislation, tail docking is not allowed on a routine basis; thus there is a need for alternative preventive methods. One strategy is the surveillance of the pigs' behaviour for known preceding indicators of tail damage, which makes it possible to predict a tail damage outbreak and prevent it in proper time. This review discusses the existing literature on behavioural changes observed prior to a tail damage outbreak. Behaviours found to change prior to an outbreak include increased activity level, increased performance of enrichment object manipulation, and a changed proportion of tail posture with more tails between the legs. Monitoring these types of behaviours is also discussed for the purpose of developing an automatic warning system for tail damage outbreaks, with activity level showing promising results for being monitored automatically. Encouraging results have been found so far for the development of an automatic warning system; however, there is a need for further investigation and development, starting with the description of the temporal development of the predictive behaviour in relation to tail damage outbreaks. PMID:26831153

  10. Predicting activity approach based on new atoms similarity kernel function.

    Abu El-Atta, Ahmed H; Moussa, M I; Hassanien, Aboul Ella

    2015-07-01

    Drug design is a high cost and long term process. To reduce time and costs for drugs discoveries, new techniques are needed. Chemoinformatics field implements the informational techniques and computer science like machine learning and graph theory to discover the chemical compounds properties, such as toxicity or biological activity. This is done through analyzing their molecular structure (molecular graph). To overcome this problem there is an increasing need for algorithms to analyze and classify graph data to predict the activity of molecules. Kernels methods provide a powerful framework which combines machine learning with graph theory techniques. These kernels methods have led to impressive performance results in many several chemoinformatics problems like biological activity prediction. This paper presents a new approach based on kernel functions to solve activity prediction problem for chemical compounds. First we encode all atoms depending on their neighbors then we use these codes to find a relationship between those atoms each other. Then we use relation between different atoms to find similarity between chemical compounds. The proposed approach was compared with many other classification methods and the results show competitive accuracy with these methods. PMID:26117822

  11. Predictive Active Set Selection Methods for Gaussian Processes

    Henao, Ricardo; Winther, Ole

    2012-01-01

    We propose an active set selection framework for Gaussian process classification for cases when the dataset is large enough to render its inference prohibitive. Our scheme consists of a two step alternating procedure of active set update rules and hyperparameter optimization based upon marginal...... active set parameters that directly control its complexity. We also provide both theoretical and empirical support for our active set selection strategy being a good approximation of a full Gaussian process classifier. Our extensive experiments show that our approach can compete with state...... 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...

  12. Outlook for activity and structural change

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

  13. Predicting risk selection following major changes in Medicare.

    Pizer, Steven D; Frakt, Austin B; Feldman, Roger

    2008-04-01

    The Medicare Modernization Act of 2003 created several new types of private insurance plans within Medicare, starting in 2006. Some of these plan types previously did not exist in the commercial market and there was great uncertainty about their prospects. In this paper, we show that statistical models and historical data from the Medicare Current Beneficiary Survey can be used to predict the experience of new plan types with reasonable accuracy. This lays the foundation for the analysis of program modifications currently under consideration. We predict market share, risk selection, and stability for the most prominent new plan type, the stand-alone Medicare prescription drug plan (PDP). First, we estimate a model of consumer choice across Medicare insurance plans available in the data. Next, we modify the data to include PDPs and use the model to predict the probability of enrollment for each beneficiary in each plan type. Finally, we calculate mean-adjusted actual spending by plan type. We predict that adverse selection into PDPs will be substantial, but that enrollment and premiums will be stable. Our predictions correspond well to actual experience in 2006. PMID:17557273

  14. Cue predictability changes scaling in eye-movement fluctuations.

    Wallot, Sebastian; Coey, Charles A; Richardson, Michael J

    2015-10-01

    Recent research has provided evidence for scaling-relations in eye-movement fluctuations, but not much is known about what these scaling relations imply about cognition or eye-movement control. Generally, scaling relations in behavioral and neurophysiological data have been interpreted as an indicator for the coordination of neurophysiological and cognitive processes. In this study, we investigated the effect of predictability in timing and gaze-direction on eye-movement fluctuations. Participants performed a simple eye-movement task, in which a visual cue prompted their gaze to different locations on a spatial layout, and the predictability about temporal and directional aspects of the cue were manipulated. The results showed that scaling exponents in eye-movements decreased with predictability and were related to the participants' perceived effort during the task. In relation to past research, these findings suggest that scaling exponents reflect a relative demand for voluntary control during task performance. PMID:26337612

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

    Lawton, Rebecca J.

    2011-07-14

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

  16. Mathematical models for predicting indoor air quality from smoking activity.

    Ott, W R

    1999-01-01

    Much progress has been made over four decades in developing, testing, and evaluating the performance of mathematical models for predicting pollutant concentrations from smoking in indoor settings. Although largely overlooked by the regulatory community, these models provide regulators and risk assessors with practical tools for quantitatively estimating the exposure level that people receive indoors for a given level of smoking activity. This article reviews the development of the mass balanc...

  17. Resource assurance predicts specialist and generalist bee activity in drought

    Minckley, Robert L.; Roulston, T'ai H.; Williams, Neal M.

    2013-01-01

    Many short-lived desert organisms remain in diapause during drought. Theoretically, the cues desert species use to continue diapause through drought should differ depending on the availability of critical resources, but the unpredictability and infrequent occurrence of climate extremes and reduced insect activity during such events make empirical tests of this prediction difficult. An intensive study of a diverse bee–plant community through a drought event found that bee specialists of a drou...

  18. Platelet Serotonin Transporter Function Predicts Default-Mode Network Activity

    Christian Scharinger; Ulrich Rabl; Christian H. Kasess; Meyer, Bernhard M.; Tina Hofmaier; Kersten Diers; Lucie Bartova; Gerald Pail; Wolfgang Huf; Zeljko Uzelac; Beate Hartinger; Klaudius Kalcher; Thomas Perkmann; Helmuth Haslacher; Andreas Meyer-Lindenberg

    2014-01-01

    Background 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. Methods A functional magnetic resonance study was performed in 48 healthy...

  19. Neural activity during encoding predicts false memories created by misinformation

    Okado, Yoko; Stark, Craig E.L.

    2005-01-01

    False memories are often demonstrated using the misinformation paradigm, in which a person's recollection of a witnessed event is altered after exposure to misinformation about the event. The neural basis of this phenomenon, however, remains unknown. We used fMRI to investigate encoding processes during the viewing of an event and misinformation to see whether neural activity during either encoding phase could predict what would be remembered. fMRI data were collected as participants studied ...

  20. Changing the world through shareholder activism?

    Joakim Sandberg

    2011-05-01

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

  1. Prefrontal activity predicts monkeys' decisions during an auditory category task

    Jung Hoon Lee

    2009-06-01

    Full Text Available The neural correlates that relate auditory categorization to aspects of goal-directed behavior, such as decision-making, are not well understood. Since the prefrontal cortex plays an important role in executive function and the categorization of auditory objects, we hypothesized that neural activity in the prefrontal cortex (PFC should predict an animal's behavioral reports (decisions during a category task. To test this hypothesis, we tested PFC activity that was recorded while monkeys categorized human spoken words (Russ et al., 2008b. We found that activity in the ventrolateral PFC, on average, correlated best with the monkeys' choices than with the auditory stimuli. This finding demonstrates a direct link between PFC activity and behavioral choices during a non-spatial auditory task.

  2. Predicting plant invasion in an era of global change

    Previous studies have indicated that ongoing global change will promote the spread of invasive plants. Recent research points to a more complex response. The components of global change that increase plant resources (e.g., rising CO2, N deposition) most consistently favor invasive species, but, chan...

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

    Buchanan, Trey

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

  4. Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization

    Chiu, Hung-Chih; Lin, Yen-Hung; Lo, Men-Tzung; Tang, Sung-Chun; Wang, Tzung-Dau; Lu, Hung-Chun; Ho, Yi-Lwun; Ma, Hsi-Pin; Peng, Chung-Kang

    2015-08-01

    The hierarchical interaction between electrical signals of the brain and heart is not fully understood. We hypothesized that the complexity of cardiac electrical activity can be used to predict changes in encephalic electricity after stress. Most methods for analyzing the interaction between the heart rate variability (HRV) and electroencephalography (EEG) require a computation-intensive mathematical model. To overcome these limitations and increase the predictive accuracy of human relaxing states, we developed a method to test our hypothesis. In addition to routine linear analysis, multiscale entropy and detrended fluctuation analysis of the HRV were used to quantify nonstationary and nonlinear dynamic changes in the heart rate time series. Short-time Fourier transform was applied to quantify the power of EEG. The clinical, HRV, and EEG parameters of postcatheterization EEG alpha waves were analyzed using change-score analysis and generalized additive models. In conclusion, the complexity of cardiac electrical signals can be used to predict EEG changes after stress.

  5. Emotional attentional control predicts changes in diurnal cortisol secretion following exposure to a prolonged psychosocial stressor.

    Lenaert, Bert; Barry, Tom J; Schruers, Koen; Vervliet, Bram; Hermans, Dirk

    2016-01-01

    Hypothalamic-pituitary-adrenal (HPA) axis irregularities have been associated with several psychological disorders. Hence, the identification of individual difference variables that predict variations in HPA-axis activity represents an important challenge for psychiatric research. We investigated whether self-reported attentional control in emotionally demanding situations prospectively predicted changes in diurnal salivary cortisol secretion following exposure to a prolonged psychosocial stressor. Low ability to voluntarily control attention has previously been associated with anxiety and depressive symptomatology. Attentional control was assessed using the Emotional Attentional Control Scale. In students who were preparing for academic examination, salivary cortisol was assessed before (time 1) and after (time 2) examination. Results showed that lower levels of self-reported emotional attentional control at time 1 (N=90) predicted higher absolute diurnal cortisol secretion and a slower decline in cortisol throughout the day at time 2 (N=71). Difficulty controlling attention during emotional experiences may lead to chronic HPA-axis hyperactivity after prolonged exposure to stress. These results indicate that screening for individual differences may foster prediction of HPA-axis disturbances, paving the way for targeted disorder prevention. PMID:26539967

  6. Prediction of Factors Determining Changes in Stability in Protein Mutants

    Parthiban, Vijayarangakannan

    2006-01-01

    Analysing the factors behind protein stability is a key research topic in molecular biology and has direct implications on protein structure prediction and protein-protein docking solutions. Protein stability upon point mutations were analysed using a distance dependant pair potential representing mainly through-space interactions and torsion angle potential representing neighbouring effects as a basic statistical mechanical setup for the analysis. The synergetic effect of accessible surface ...

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

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

    2016-01-01

    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...

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

    YOCCOZ, Nigel G.; Anne Delestrade; Anne Loison

    2011-01-01

    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 therefor...

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

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

    2016-01-01

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

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

    Boris Cheval

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

  11. Predicting the Response of Electricity Load to Climate Change

    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.

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

    Nielsen, Karina; Cleal, Bryan

    2010-04-01

    Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. PMID:20364915

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

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

    2008-01-01

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

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

    Guoxing Li; Tie Wang; Ruiliang Zhang; Fengshou Gu; Jinxian Shen

    2015-01-01

    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 perfor...

  15. Prediction of Antifungal Activity of Gemini Imidazolium Compounds

    Łukasz Pałkowski

    2015-01-01

    Full Text Available The progress of antimicrobial therapy contributes to the development of strains of fungi resistant to antimicrobial drugs. Since cationic surfactants have been described as good antifungals, we present a SAR study of a novel homologous series of 140 bis-quaternary imidazolium chlorides and analyze them with respect to their biological activity against Candida albicans as one of the major opportunistic pathogens causing a wide spectrum of diseases in human beings. We characterize a set of features of these compounds, concerning their structure, molecular descriptors, and surface active properties. SAR study was conducted with the help of the Dominance-Based Rough Set Approach (DRSA, which involves identification of relevant features and relevant combinations of features being in strong relationship with a high antifungal activity of the compounds. The SAR study shows, moreover, that the antifungal activity is dependent on the type of substituents and their position at the chloride moiety, as well as on the surface active properties of the compounds. We also show that molecular descriptors MlogP, HOMO-LUMO gap, total structure connectivity index, and Wiener index may be useful in prediction of antifungal activity of new chemical compounds.

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

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

    2016-02-01

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

  17. Improving models to predict phenological responses to global change

    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.

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

    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.

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

    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.

  20. Prediction of stability changes upon mutation in an icosahedral capsid.

    Hickman, Samuel J; Ross, James F; Paci, Emanuele

    2015-09-01

    Identifying the contributions to thermodynamic stability of capsids is of fundamental and practical importance. Here we use simulation to assess how mutations affect the stability of lumazine synthase from the hyperthermophile Aquifex aeolicus, a T = 1 icosahedral capsid; in the simulations the icosahedral symmetry of the capsid is preserved by simulating a single pentamer and imposing crystal symmetry, in effect simulating an infinite cubic lattice of icosahedral capsids. The stability is assessed by estimating the free energy of association using an empirical method previously proposed to identify biological units in crystal structures. We investigate the effect on capsid formation of seven mutations, for which it has been experimentally assessed whether they disrupt capsid formation or not. With one exception, our approach predicts the effect of the mutations on the capsid stability. The method allows the identification of interaction networks, which drive capsid assembly, and highlights the plasticity of the interfaces between subunits in the capsid. PMID:26178267

  1. Improving the reliability of fishery predictions under climate change

    Brander, Keith

    2015-01-01

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

  2. Early onset of hypertension and serum electrolyte changes as potential predictive factors of activity in advanced HCC patients treated with sorafenib: results from a retrospective analysis of the HCC-AVR group

    Gardini, Andrea Casadei; Scarpi, Emanuela; Marisi, Giorgia; Foschi, Francesco Giuseppe; Donati, Gabriele; Giampalma, Emanuela; Faloppi, Luca; Scartozzi, Mario; Silvestris, Nicola; Bisulli, Marcello; Corbelli, Jody; Gardini, Andrea; Barba, Giuliano La; Veneroni, Luigi; Tamberi, Stefano; Cascinu, Stefano; Frassineti, Giovanni Luca

    2016-01-01

    Hypertension (HTN) is frequently associated with the use of angiogenesis inhibitors targeting the vascular endothelial growth factor pathway and appears to be a generalized effect of this class of agent. We investigated the phenomenon in 61 patients with advanced hepatocellular carcinoma (HCC) receiving sorafenib. Blood pressure and plasma electrolytes were measured on days 1 and 15 of the treatment. Patients with sorafenib-induced HTN had a better outcome than those without HTN (disease control rate: 63.4% vs. 17.2% (p=0.001); progression-free survival 6.0 months (95% CI 3.2-10.1) vs. 2.5 months (95% CI 1.9-2.6) (p<0.001) and overall survival 14.6 months (95% CI9.7-19.0) vs. 3.9 months (95% CI 3.1-8.7) (p=0.003). Sodium levels were generally higher on day 15 than at baseline (+2.38, p<0.0001) in the group of responders (+4.95, p <0.0001) compared to patients who progressed (PD) (+0.28, p=0.607). In contrast, potassium was lower on day 14 (−0.30, p=0.0008) in the responder group (−0.58, p=0.003) than in those with progressive disease (−0.06, p=0.500). The early onset of hypertension is associated with improved clinical outcome in HCC patients treated with sorafenib. Our data are suggestive of an activation of the renin-angiotensin system in patients with advanced disease who developed HTN during sorafenib treatment. PMID:26893366

  3. Demographic change and unemployment: what do macroeconometric models predict?

    J.-F. OUVRARD; R. RATHELOT

    2006-01-01

    Declining natality and mortality are reshaping demographic patterns in most industrialized countries. We investigate the case of France where, after a few decades of sustained growth, active population is likely to stop growing and could eventually start decreasing. This will coincide with a boom for the retired population. The purpose of this paper is to examine the consequences of both phenomena for the labour market. We tackle the issue using two approaches: WS-PS models and Phillips curve...

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

    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…

  5. How the cerebral serotonin homeostasis predicts environmental changes

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

    2013-01-01

    Molecular imaging studies with positron emission tomography have revealed that the availability of serotonin transporter (5-HTT) in the human brain fluctuates over the course of the year. This effect is most pronounced in carriers of the short allele of the 5-HTT promoter region (5-HTTLPR), which...... with pronounced seasonal climatic changes, while this hypothesis does not rule out that genetic drift plays an additional or even exclusive role. We argue that s-allele manifests as an intermediate phenotype in terms of an increased responsiveness of the 5-HTT expression to number of daylight hours...

  6. The sequential structure of brain activation predicts skill.

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

    2016-01-29

    In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. PMID:26707716

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

    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.

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

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

  9. CA-Markov for Predicting Land Use Changes in Tropical Catchment Area: A Case Study in Cameron Highland, Malaysia

    Muhammad Rendana

    2015-01-01

    Full Text Available The land use/land cover pattern of a region is an outcome of natural and socio-economic factors and the utilization by humans in time and space. The land use/cover change analysis is used to evaluate and monitor land use change in the specific period of time. Nowadays, the rapid changes of land use and land cover can lead to land degradation and environmental problems by anthropogenic activities like agriculture development, deforestation, urbanization and tourism. The study is conducted in Cameron Highland which is the agriculture and recreational area situated in Pahang, Malaysia. It aims to analyze land use change and make the prediction of future land use scenario in this region. In order to detect and evaluate land use changes, supervised classification and image differencing method are applied. Then, Cellular Automata and Markov Chain analysis is employed predict of future land use in study area. The output of study reveals that land use change in study area has changed about 18.95% in 1997-2014 and estimated to change about a further 3.66% in 2014-2020. Additionally, it predicted that open water, mixed agriculture, open land and built up areas will increase by 80.37 (0.54%, 501.02 (12.24%, 499.95 (5.47% and 119.88 ha (0.85% in 2020.

  10. Prediction of Dynamical Impact of Changes in Stratospheric Ozone

    Cunnold, Derek M.

    1998-01-01

    Under this grant one paper by Lou et al and a second paper by Kindler et al is in journal. These papers both describe N2O simulations using UKMO and Goddard assimilated wind fields and comparisons of the results against CLAES N2O observations. The results of these studies indicate some of the difficulties of using the assimilated wind fields, and the vertical motions in particular, in simulating long term variations in trace gases in the stratosphere. On the other hand, qualitatively the results possess a number of features of the observations even on time scales longer than a month or two. More recently we have started to examine results obtained using NCAR models a 3D version of which also uses the UKMO assimilated wind fields. Calculations have already been made with their 2D model with emphasis on the seasonal cycle in ozone at high latitudes in the upper stratosphere. Simultaneously trends in stratospheric ozone have been studied in detail from SAGE and UARS observations. Moreover, observations of the trends since 1984 do not show a significant interhemispheric asymmetry in upper stratospheric ozone. Therefore any asymmetry in the trends must have occurred prior to the mid-eighties and would most likely have been related to interhemispheric differences in upper stratospheric temperature trends. Another activity has been to compile an ozone climatology from UARS and SAGE observations. This effort has been performed as part of a UARS team activity to assemble a climatology of all the UARS long-lived trace gases for 1992-1993.

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

    Murtagh Shemane

    2012-05-01

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

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

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

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

    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.

  14. Statistical estimations for predicting the detection limit of low activities

    When extremely low activities are measured, the statistics of the observed decay events may be insufficient for a justified application of statistical assessments based on the Gaussian distribution. Student's t-distribution and the theory of the interval estimation are used as the basis for a statistical model for predicting the detection limit and the signal-to-noise ratio which could be reached under the conditions of the measurement. The derived statistical estimations are applicable in cases when a small number of decay events is expected to be recorded. The minimum detectable activity characterizing the detection limit under the conditions of the measurement, is determined at the given confidence limits and assumed permissible relative statistical errors during the measurement of the sample and the background (within the available time limits). The derived statistical estimations can be used for comparing the possibilities offered by the different measuring methods applied for determination of extremely low activities. These evaluations can also be used as a criterion for discussing the reliability of the measurement results. (author). 6 refs

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

    Wang, Qijie

    2015-08-01

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

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

    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. PMID:25877227

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

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

    2012-12-01

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

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

    Nelson Waweru

    2008-01-01

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

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

    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.

  20. Reward prediction-related increases and decreases in tonic neuronal activity of the pedunculopontine tegmental nucleus

    Ken-Ichi Okada

    2013-05-01

    Full Text Available The neuromodulators serotonin, acetylcholine, and dopamine have been proposed to play important roles in the execution of movement, control of several forms of attentional behavior, and reinforcement learning. While the response pattern of midbrain dopaminergic neurons and its specific role in reinforcement learning have been revealed, the roles of the other neuromodulators remain elusive. Reportedly, neurons in the dorsal raphe nucleus, one major source of serotonin, continually track the state of expectation of future rewards by showing a correlated response to the start of a behavioral task, reward cue presentation, and reward delivery. Here, we show that neurons in the pedunculopontine tegmental nucleus (PPTN, one major source of acetylcholine, showed similar encoding of the expectation of future rewards by a systematic increase or decrease in tonic activity. We recorded and analyzed PPTN neuronal activity in monkeys during a reward conditioned visually guided saccade task. The firing patterns of many PPTN neurons were tonically increased or decreased throughout the task period. The tonic activity pattern of neurons was correlated with their encoding of the predicted reward value; neurons exhibiting an increase or decrease in tonic activity showed higher or lower activity in the large reward-predicted trials, respectively. Tonic activity and reward-related modulation ended around the time of reward delivery. Additionally, some tonic changes in activity started prior to the appearance of the initial stimulus, and were related to the anticipatory fixational behavior. A partially overlapping population of neurons showed both the initial anticipatory response and subsequent predicted reward value-dependent activity modulation by their systematic increase or decrease of tonic activity. These bi-directional reward- and anticipatory behavior-related modulation patterns are suitable for the presumed role of the PPTN in reward processing and

  1. Changing Physician Practice of Physical Activity Counseling

    Eckstrom, Elizabeth; Hickam, David H.; Lessler, Daniel S; Buchner, David M.

    1999-01-01

    We conducted a prospective controlled trial to determine whether an educational intervention could improve resident physician self-efficacy and counseling behaviors for physical activity and increase their patients’ reported activity levels. Forty-eight internal medicine residents who practiced at a Department of Veterans Affairs hospital received either two workshops on physical activity counseling or no intervention. All residents completed questionnaires before and 3 months after the works...

  2. Brain monoamine oxidase A activity predicts trait aggression.

    Alia-Klein, Nelly; Goldstein, Rita Z; Kriplani, Aarti; Logan, Jean; Tomasi, Dardo; Williams, Benjamin; Telang, Frank; Shumay, Elena; Biegon, Anat; Craig, Ian W; Henn, Fritz; Wang, Gene-Jack; Volkow, Nora D; Fowler, Joanna S

    2008-05-01

    The genetic deletion of monoamine oxidase A (MAO A), an enzyme that breaks down the monoamine neurotransmitters norepinephrine, serotonin, and dopamine, produces aggressive phenotypes across species. Therefore, a common polymorphism in the MAO A gene (MAOA, Mendelian Inheritance in Men database number 309850, referred to as high or low based on transcription in non-neuronal cells) has been investigated in a number of externalizing behavioral and clinical phenotypes. These studies provide evidence linking the low MAOA genotype and violent behavior but only through interaction with severe environmental stressors during childhood. Here, we hypothesized that in healthy adult males the gene product of MAO A in the brain, rather than the gene per se, would be associated with regulating the concentration of brain amines involved in trait aggression. Brain MAO A activity was measured in vivo in healthy nonsmoking men with positron emission tomography using a radioligand specific for MAO A (clorgyline labeled with carbon 11). Trait aggression was measured with the multidimensional personality questionnaire (MPQ). Here we report for the first time that brain MAO A correlates inversely with the MPQ trait measure of aggression (but not with other personality traits) such that the lower the MAO A activity in cortical and subcortical brain regions, the higher the self-reported aggression (in both MAOA genotype groups) contributing to more than one-third of the variability. Because trait aggression is a measure used to predict antisocial behavior, these results underscore the relevance of MAO A as a neurochemical substrate of aberrant aggression. PMID:18463263

  3. Predicted impacts of climate change on malaria transmission in West Africa

    Yamana, T. K.; Eltahir, E. A. B.

    2014-12-01

    Increases in temperature and changes in precipitation due to climate change are expected to alter the spatial distribution of malaria transmission. This is especially true in West Africa, where malaria prevalence follows the current north-south gradients in temperature and precipitation. We assess the skill of GCMs at simulating past and present climate in West Africa in order to select the most credible climate predictions for the periods 2030-2060 and 2070-2100. We then use the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a mechanistic model of malaria transmission, to translate the predicted changes in climate into predicted changes availability of mosquito breeding sites, mosquito populations, and malaria prevalence. We investigate the role of acquired immunity in determining a population's response to changes in exposure to the malaria parasite.

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

    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.

  5. Predicting IQ change from brain structure: A cross-validation study

    Price, C.J.; Ramsden, S.; Hope, T.M.H.; Friston, K.J.; Seghier, M.L.

    2013-01-01

    Procedures that can predict cognitive abilities from brain imaging data are potentially relevant to educational assessments and studies of functional anatomy in the developing brain. Our aim in this work was to quantify the degree to which IQ change in the teenage years could be predicted from structural brain changes. Two well-known k-fold cross-validation analyses were applied to data acquired from 33 healthy teenagers – each tested at Time 1 and Time 2 with a 3.5 year interval. One approach, a Leave-One-Out procedure, predicted IQ change for each subject on the basis of structural change in a brain region that was identified from all other subjects (i.e., independent data). This approach predicted 53% of verbal IQ change and 14% of performance IQ change. The other approach used half the sample, to identify regions for predicting IQ change in the other half (i.e., a Split half approach); however – unlike the Leave-One-Out procedure – regions identified using half the sample were not significant. We discuss how these out-of-sample estimates compare to in-sample estimates; and draw some recommendations for k-fold cross-validation procedures when dealing with small datasets that are typical in the neuroimaging literature. PMID:23567505

  6. The prediction of induced activity levels in and around NIMROD

    Hack, R C

    1973-01-01

    Comparisons are reported between measured and predicted levels of induced radioactivity for a number of irradiation conditions. Good agreement was found between experimental measurements and fairly simple methods of prediction developed at CERN.

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

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

    2009-01-01

    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...... with the largest nival zone. Our results suggest elevation range as the main driver for the observed prediction discrepancies. Local-scale projections may better reflect the possibility for species to track their climatic requirement toward higher elevations....

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

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

    2015-09-01

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

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

    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…

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

    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 sp

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

    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...... null models, is essential to assess the robustness of projections of marine planktonic species under climate change...

  12. Changes in Biston robustum and Camellia japonica distributions, according to climate change predictions in South Korea

    Tae Guen Kim; Yong-Gu Han; Jong Chul Jeong; Youngjin Kim; Ohseok Kwon; Youngho Cho

    2015-01-01

    We investigated the current and potential spatial distributions and habitable areas of Biston robustum and Camellia japonica in South Korea in order to provide useful data for the conservation of C. japonica and minimize the damage caused by B. robustum. It was predicted that, by 2070, although B. robustum would be widely distributed throughout the Korean Peninsula, except for the western and eastern coa...

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

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

    2011-01-01

    Context Data are available on correlates of physical activity in children and adolescents, less is known about the determinants of change. This review aims to systematically review the published evidence regarding determinants of change in physical activity in children and adolescents. Evidence acquisition Prospective quantitative studies investigating change in physical activity in children and adolescents aged 4–18 years were identified from seven databases (to November 2010): PubMed, SCOPU...

  14. Social Cohesion Activities and Attitude Change in Cyprus

    Direnç Kanol

    2015-01-01

    Do social cohesion activities change the attitudes of the participants? This paper uses intergroup contact theory to explore attitude change resulting from contact with out-group(s) in social cohesion activities. Results from a pre-test/post-test design with fifty-five participants in two bicommunal camps in Cyprus show how attitudes change at the immediate end of these activities; an analysis of fourteen participants’ comments after one, thirteen, and twenty-five months provides a medium- to...

  15. Numerical Model Predictions of Intrinsically Generated Fluvial Terraces and Comparison to Climate-Change Expectations

    Limaye, A. B. S.; Lamb, M. P.

    2014-12-01

    Terraces eroded into sediment (cut-fill) and bedrock (strath) preserve a geomorphic record of river activity. River terraces are often thought to form when a river switches from a period of low vertical incision rates and valley widening to high vertical incision rates and terrace abandonment. Consequently, terraces are frequently interpreted to reflect landscape response to changing external drivers, including tectonics, sea-level, and most commonly, climate. In contrast, unsteady lateral migration in meandering rivers may generate river terraces even under constant vertical incision and without changes in external forcing. To explore this latter mechanism, we use a numerical model and an automated terrace detection algorithm to simulate landscape evolution by a vertically incising, meandering river and isolate the age and geometric fingerprints of intrinsically generated river terraces. Simulations indicate that terraces form for a wide range of lateral and vertical incision rates, and the time interval between unique terrace levels is limited by a characteristic timescale for relief generation. Surprisingly, intrinsically generated terraces are commonly paired, an attribute that is thought to be diagnostic of climate change. For low ratios of vertical-to-lateral erosion rates, modeled terraces are longitudinally extensive and typically dip toward the valley center, and terrace slope is proportional to the ratio of vertical to lateral erosion. Evolving, spatial differences in bank strength between bedrock and sediment reduce terrace formation frequency and length, and can explain sub-linear terrace margins at valley boundaries. Comparison of model predictions to natural river terraces indicates that terrace length is the most reliable indicator of terrace formation by pulses of vertical incision, and may contain the imprint of past climate change on landscapes.

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

    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. PMID:24182516

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

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

    2004-01-01

    AIM: To predict wild human heme oxygenase-1 (whHO-1)and hHO-1 His25Ala mutant (△hHO-1) structures, to clone and express them and analyze their activities.METHODS: Swiss-PdbViewer and Antheprot 5.0 were used for the prediction of structure diversity and physicalchemical changes between wild and mutant hHO-1. hHO1 His25Ala mutant cDNA was constructed by site-directed mutagenesis in two plasmids of E. coli DH5α. Expression products were purified by ammonium sulphate precipitation and Q-Sepharose Fast Flow column chromatography, and their activities were measured.RESULTS: rHO-1 had the structure of a helical fold with the heme sandwiched between heme-heme oxygenase1 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 △hHO-1 was reduced 91.21% after mutation compared with whHO-1.CONCLUSION: Proximal His25 ligand is crucial for normal hHO-1 catalytic activity. △hHO-1 is deactivated by mutation but keeps the same binding site as whHO-1. △hHO-1 might be a potential inhibitor of whHO-1 for preventing neonatal hyperbilirubinemia.

  18. An activity theoretic model for information quality change

    Stvilia, Besiki; Gasser, Les

    2008-01-01

    To manage information quality (IQ) effectively, one needs to know how IQ changes over time, what causes it to change, and whether the changes can be predicted. In this paper we analyze the structure of IQ change in Wikipedia, an open, collaborative general encyclopedia. We found several patterns in Wikipedia’s IQ process trajectories and linked them to article types. Drawing on the results of our analysis, we develop a general model of IQ change that can be used for reasoning about IQ dynamic...

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

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

    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...

  20. Multinationals’ Political Activities on Climate Change

    A. Kolk; J.M. Pinkse

    2007-01-01

    This article explores the international dimensions of multinationals’ corporate political activities, focusing on an international issue—climate change—being implemented differently in a range of countries. Analyzing data from Financial Times Global 500 firms, it examines the influence on types and

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

    Sutton Stephen

    2010-04-01

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

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

    Jennings, Simon; Brander, Keith

    2010-01-01

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

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

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

    2010-01-01

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

  4. Corrosion fatigue behavior and life prediction method under changing temperature condition

    Axially strain controlled low cycle fatigue tests of a carbon steel in oxygenated high temperature water were carried out under changing temperature conditions. Two patterns of triangular wave were selected for temperature cycling. One was in-phase pattern synchronizing with strain cycling and the other was an out-of-phase pattern in which temperature was changed in anti-phase to the strain cycling. The fatigue life under changing temperature condition was in the range of the fatigue life under various constant temperature within the range of the changing temperature. The fatigue life of in-phase pattern was equivalent to that of out-of-phase pattern. The corrosion fatigue life prediction method was proposed for changing temperature condition, and was based on the assumption that the fatigue damage increased in linear proportion to increment of strain during cycling. The fatigue life predicted by this method was in good agreement with the test results

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

    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…

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

    M Irfan Ashraf

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

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

    Rios Velazquez, Emmanuel; Aerts, Hugo J.W.L.; Oberije, Cary; Ruysscher, Dirk De; Lambin, Philippe (Dept. of Radiation Oncology, School for Oncology and Developmental Biology, Maastricht Univ. Medical Center, Maastricht (Netherlands)), E-mail: emmanuel.rios@maastro.nl

    2010-10-15

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

  8. Spatial Predictive Process Models Yield Improved Forecasts of Vegetation Response to Climate Change

    Swanson, A.; Dobrowski, S. Z.; Mynsberge, A.

    2010-12-01

    Species distribution models (SDMs) relate the presence and absence of plant species to environmental covariates, and are commonly used to forecast climate change impacts on biota. Such models have predicted increased extinction risk and dramatic shifts in habitat for many species, but their validity relies on the assumption that SDM projections are transferable through space and time, an assumption that is largely untested due to the rarity of independent data for assessing transferability. In practice, there are many obstacles to the SDM approach that can limit their transferability. For example, most SDMs are non-spatial, treating observations as independent even when close in space. This can lead to biased parameter estimates, overconfidence in predictions, and invalid tests of predictor significance. SDMs also fail to account for biotic effects known to be important in shaping species distributions. Spatial ‘predictive process’ models show promise in increasing both the biological and statistical realism of species distribution models. Predictive process models introduce a spatially autocorrelated covariate into parametric statistical approaches. The spatial process covariate can serve as a proxy to unmeasured factors affecting species distribution, such as dispersal or competition, and can account for sampling bias. Implemented in a Bayesian framework, the parameters of the spatial process are estimated concurrently with the conventional model coefficients, and associated uncertainties are propagated through to spatially explicit predictions. We hypothesize that SDMs incorporating a predictive process term will produce predictions with greater transferability than conventional approaches, and will more readily capture the species-climate relationship in an unbiased fashion. To test this, we fit conventional and spatial predictive process GLMs (Generalized Linear Models) to historic (1910-1940) vegetation data from the mountain ranges of California

  9. Present and future distributions of horseshoe crabs under predicted climate changes

    Funch, Peter; Obst, Matthias; Quevedo, Francisco;

    factors for the species distribution, quantify range shifts of the species in response to predicted climatic change, and obtain spatial predictions of suitable habitats under present and future climate scenarios. Suitable habitat was projected into marine protected areas in the region to better understand...... the potential of existing horseshoe crabs’ sanctuaries to accommodate the species in a changing climate........ gigas lives in sandy and shallow near-coast habitats, while C. rotundicauda mostly inhabits estuaries and mangroves. The third species T. tridentatus is living in shallow coastal zones from Malaysia to Japan. In order to improve our knowledge on current and future distribution of horseshoe crab...

  10. Body image and body change: Predictive factors in an Iranian population

    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...

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

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

    1999-01-01

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

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

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

    2014-12-01

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

  13. Predicting changes in protein thermostability brought about by single- or multi-site mutations

    Chu Xiaoyu

    2010-07-01

    Full Text Available Abstract Background An important aspect of protein design is the ability to predict changes in protein thermostability arising from single- or multi-site mutations. Protein thermostability is reflected in the change in free energy (ΔΔG of thermal denaturation. Results We have developed predictive software, Prethermut, based on machine learning methods, to predict the effect of single- or multi-site mutations on protein thermostability. The input vector of Prethermut is based on known structural changes and empirical measurements of changes in potential energy due to protein mutations. Using a 10-fold cross validation test on the M-dataset, consisting of 3366 mutants proteins from ProTherm, the classification accuracy of random forests and the regression accuracy of random forest regression were slightly better than support vector machines and support vector regression, whereas the overall accuracy of classification and the Pearson correlation coefficient of regression were 79.2% and 0.72, respectively. Prethermut performs better on proteins containing multi-site mutations than those with single mutations. Conclusions The performance of Prethermut indicates that it is a useful tool for predicting changes in protein thermostability brought about by single- or multi-site mutations and will be valuable in the rational design of proteins.

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

    Wallenstein, Matthew D.; Hall, Edward K.

    2012-01-01

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

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

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

    2016-08-01

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

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

    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.…

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

    Kissling, W. D.; Field, R.; Korntheuer, H.; Heyder, U.; Böhning-Gaese, K.

    2010-01-01

    Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climat...

  18. Predicting Early Positive Change in Multisystemic Therapy with Youth Exhibiting Antisocial Behaviors

    Tiernan, Kristine; Foster, Sharon L.; Cunningham, Phillippe B.; Brennan, Patricia; Whitmore, Elizabeth

    2014-01-01

    This study examined individual and family characteristics that predicted early positive change in the context of Multisystemic Therapy (MST). Families (n=185; 65% male; average youth age 15 years) receiving MST in community settings completed assessments at the outset of treatment and 6-12 weeks into treatment. Early positive changes in youth antisocial behavior were assessed using the caregiver report on the CBCL Externalizing Behaviors subscale and youth report on the Self-Report Delinquenc...

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

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

    2012-01-01

    Simple Summary Parasitic helminths represent one of the most pervasive challenges to livestock, and their intensity and distribution will be influenced by climate change. There is a need for long-term predictions to identify potential risks and highlight opportunities for control. We explore the approaches to modelling future helminth risk to livestock under climate change. One of the limitations to model creation is the lack of purpose driven data collection. We also conclude that models nee...

  20. Does Change on the MOLEST and RAPE Scales Predict Sexual Recidivism?

    Nunes, Kevin L; Pettersen, Cathrine; Hermann, Chantal A; Looman, Jan; Spape, Jessica

    2016-08-01

    The purpose of the current study was to examine whether the MOLEST and RAPE scales and change on these measures predicted sexual recidivism in a sample of 146 adult male sexual offenders who participated in a high-intensity treatment program while incarcerated. The majority of subjects had functional scores on the MOLEST and RAPE scales prior to treatment. Of those who had dysfunctional pre-treatment scores, the majority made significant gains. However, the MOLEST and RAPE scales did not significantly predict sexual recidivism. This was the case for pre-treatment scores, post-treatment scores, and change scores. Our findings are generally not consistent with the view that these measures assess dynamic risk factors for sexual recidivism. However, this is the first published study to examine the predictive validity of these scales and more rigorous research is needed before firm conclusions can be drawn. PMID:24996579

  1. Predicting Climate Change using Response Theory: Global Averages and Spatial Patterns

    Lucarini, Valerio; Ragone, Francesco

    2015-01-01

    The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source general circulation model of the atmosphere featuring O($10^5$) degrees of freedom, we show how it is possible to approach such a problem using nonequilibrium statistical mechanics. Response theory allows one to practically compute the time-dependent measure supported on the pullback attractor of the climate system, whose dynamics is non-autonomous as a result of time-dependent forcings. We propose a simple yet efficient method for predicting - at any lead time and in an ensemble sense - the change in climate properties resulting from increase in the concentration of CO$_2$ using test perturbation model runs. We assess strengths and limitations of the response theory in predicting the changes in the globally averaged values of surface temperature and of the yearly total precipitation, as well as their spatial patter...

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

    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.

  3. Predicting life-cycle adaptation of migratory birds to global climate change

    Coppack, T.; Both, C.

    2002-01-01

    Analyses of long-term data indicate that human-caused climatic changes are affecting bird phenology in directions consistent with theoretical predictions. Here, we report on recent trends in the timing of spring arrival and egg laying found within a western European Pied Flycatcher Ficedula hypoleuc

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

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

    2010-01-01

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

  5. Nestling activity levels during begging behaviour predicts activity level and body mass in adulthood

    Luke S.C. McCowan

    2014-09-01

    Full Text Available Across a range of species including humans, personality traits, or differences in behaviour between individuals that are consistent over time, have been demonstrated. However, few studies have measured whether these consistent differences are evident in very young animals, and whether they persist over an individual’s entire lifespan. Here we investigated the begging behaviour of very young cross-fostered zebra finch nestlings and the relationship between that and adult activity levels. We found a link between the nestling activity behaviour head movements during begging, measured at just five and seven days after hatching, and adult activity levels, measured when individuals were between three and three and a half years old. Moreover, body mass was found to be negatively correlated with both nestling and adult activity levels, suggesting that individuals which carry less body fat as adults are less active both as adults and during begging as nestlings. Our work suggests that the personality traits identified here in both very young nestlings and adults may be linked to physiological factors such as metabolism or environmental sources of variation. Moreover, our work suggests it may be possible to predict an individual’s future adult personality at a very young age, opening up new avenues for future work to explore the relationship between personality and a number of aspects of individual life history and survival.

  6. Nestling activity levels during begging behaviour predicts activity level and body mass in adulthood.

    McCowan, Luke S C; Griffith, Simon C

    2014-01-01

    Across a range of species including humans, personality traits, or differences in behaviour between individuals that are consistent over time, have been demonstrated. However, few studies have measured whether these consistent differences are evident in very young animals, and whether they persist over an individual's entire lifespan. Here we investigated the begging behaviour of very young cross-fostered zebra finch nestlings and the relationship between that and adult activity levels. We found a link between the nestling activity behaviour head movements during begging, measured at just five and seven days after hatching, and adult activity levels, measured when individuals were between three and three and a half years old. Moreover, body mass was found to be negatively correlated with both nestling and adult activity levels, suggesting that individuals which carry less body fat as adults are less active both as adults and during begging as nestlings. Our work suggests that the personality traits identified here in both very young nestlings and adults may be linked to physiological factors such as metabolism or environmental sources of variation. Moreover, our work suggests it may be possible to predict an individual's future adult personality at a very young age, opening up new avenues for future work to explore the relationship between personality and a number of aspects of individual life history and survival. PMID:25279258

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

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

    2013-01-01

    The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La 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.

  8. Order is needed to promote linear or quantum changes in nutrition and physical activity behaviors: a reaction to 'A chaotic view of behavior change' by Resnicow and Vaughan.

    Brug Johannes

    2006-01-01

    Abstract Recently, Drs. Ken Resnicow and Roger Vaughan published a thought-provoking paper in the International Journal of Behavioral Nutrition and Physical Activity (IJBNPA). They argue that the most often used social-cognition theories in behavioral nutrition and physical activity are of limited use. These models describe behavior change as a linear event, while Resnicow and Vaughan posit that behavior change is more likely to occur in quantum leaps that are impossible to predict. They intr...

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

    Guoxing Li

    2015-01-01

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

  10. PROTS-RF: a robust model for predicting mutation-induced protein stability changes.

    Yunqi Li

    Full Text Available The ability to improve protein thermostability via protein engineering is of great scientific interest and also has significant practical value. In this report we present PROTS-RF, a robust model based on the Random Forest algorithm capable of predicting thermostability changes induced by not only single-, but also double- or multiple-point mutations. The model is built using 41 features including evolutionary information, secondary structure, solvent accessibility and a set of fragment-based features. It achieves accuracies of 0.799,0.782, 0.787, and areas under receiver operating characteristic (ROC curves of 0.873, 0.868 and 0.862 for single-, double- and multiple- point mutation datasets, respectively. Contrary to previous suggestions, our results clearly demonstrate that a robust predictive model trained for predicting single point mutation induced thermostability changes can be capable of predicting double and multiple point mutations. It also shows high levels of robustness in the tests using hypothetical reverse mutations. We demonstrate that testing datasets created based on physical principles can be highly useful for testing the robustness of predictive models.

  11. Factors Predicting Physical Activity Among Children With Special Needs

    Shahram Yazdani, MD

    2013-07-01

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

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

    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.

  13. Predicted climate change alters the indirect effect of predators on an ecosystem process.

    Lensing, Janet R; Wise, David H

    2006-10-17

    Changes in rainfall predicted to occur with global climate change will likely alter rates of leaf-litter decomposition through direct effects on primary decomposers. In a field experiment replicated at two sites, we show that altered rainfall may also change how cascading trophic interactions initiated by arthropod predators in the leaf litter indirectly influence litter decomposition. On the drier site there was no interaction between rainfall and the indirect effect of predators on decomposition. In contrast, on the moister site spiders accelerated the disappearance rate of deciduous leaf litter under low rainfall, but had no, or possibly a negative, indirect effect under high rainfall. Thus, changes resulting from the more intense hydrological cycle expected to occur with climate change will likely influence how predators indirectly affect an essential ecosystem process. PMID:17023538

  14. Predicting ecosystem shifts requires new approaches that integrate the effects of climate change across entire systems.

    Russell, Bayden D; Harley, Christopher D G; Wernberg, Thomas; Mieszkowska, Nova; Widdicombe, Stephen; Hall-Spencer, Jason M; Connell, Sean D

    2012-04-23

    Most studies that forecast the ecological consequences of climate change target a single species and a single life stage. Depending on climatic impacts on other life stages and on interacting species, however, the results from simple experiments may not translate into accurate predictions of future ecological change. Research needs to move beyond simple experimental studies and environmental envelope projections for single species towards identifying where ecosystem change is likely to occur and the drivers for this change. For this to happen, we advocate research directions that (i) identify the critical species within the target ecosystem, and the life stage(s) most susceptible to changing conditions and (ii) the key interactions between these species and components of their broader ecosystem. A combined approach using macroecology, experimentally derived data and modelling that incorporates energy budgets in life cycle models may identify critical abiotic conditions that disproportionately alter important ecological processes under forecasted climates. PMID:21900317

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

    Brun, Philipp; Kiørboe, Thomas; Licandro, Priscilla; Payne, Mark R

    2016-09-01

    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 and adjacent seas. We fit the models to decadal subsets of the full (1958-2012) dataset, and then use them to predict both forward and backward in time, comparing the model predictions against the corresponding observations. The probability of correctly predicting presence was low, peaking at 0.5 for copepods, 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. 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 null models, is essential to assess the robustness of projections of marine planktonic species under climate change. PMID:27040720

  16. Resting alpha activity predicts learning ability in alpha neurofeedback

    Wenya eNan; Feng eWan; Mang I eVai; Agostinho eRosa

    2014-01-01

    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 tr...

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

    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.

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

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

    2016-05-01

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

  19. Predicting early positive change in multisystemic therapy with youth exhibiting antisocial behaviors.

    Tiernan, Kristine; Foster, Sharon L; Cunningham, Phillippe B; Brennan, Patricia; Whitmore, Elizabeth

    2015-03-01

    This study examined individual and family characteristics that predicted early positive change in the context of Multisystemic Therapy (MST). Families (n = 185; 65% male; average youth age 15 years) receiving MST in community settings completed assessments at the outset of treatment and 6-12 weeks into treatment. Early positive changes in youth antisocial behavior were assessed using the caregiver report on the Child Behavior Checklist Externalizing Behaviors subscale and youth report on the Self-Report Delinquency Scale. Overall, families showed significant positive changes by 6-12 weeks into treatment; these early changes were maintained into midtreatment 6-12 weeks later. Families who exhibited clinically significant gains early in treatment were more likely to terminate treatment successfully compared with those who did not show these gains. Low youth internalizing behaviors and absence of youth drug use predicted early positive changes in MST. High levels of parental monitoring and low levels of affiliation with deviant peers (mechanisms known to be associated with MST success) were also associated with early positive change. PMID:24866967

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

    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.

  1. Predicting Climate Change Using Response Theory: Global Averages and Spatial Patterns

    Lucarini, Valerio; Ragone, Francesco; Lunkeit, Frank

    2016-04-01

    The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source general circulation model of the atmosphere featuring O(10^5 ) degrees of freedom, we show how it is possible to approach such a problem using nonequilibrium statistical mechanics. Response theory allows one to practically compute the time-dependent measure supported on the pullback attractor of the climate system, whose dynamics is non-autonomous as a result of time-dependent forcings. We propose a simple yet efficient method for predicting—at any lead time and in an ensemble sense—the change in climate properties resulting from increase in the concentration of CO_2 using test perturbation model runs. We assess strengths and limitations of the response theory in predicting the changes in the globally averaged values of surface temperature and of the yearly total precipitation, as well as in their spatial patterns. The quality of the predictions obtained for the surface temperature fields is rather good, while in the case of precipitation a good skill is observed only for the global average. We also show how it is possible to define accurately concepts like the inertia of the climate system or to predict when climate change is detectable given a scenario of forcing. Our analysis can be extended for dealing with more complex portfolios of forcings and can be adapted to treat, in principle, any climate observable. Our conclusion is that climate change is indeed a problem that can be effectively seen through a statistical mechanical lens, and that there is great potential for optimizing the current coordinated modelling exercises run for the preparation of the subsequent reports of the Intergovernmental Panel for Climate Change.

  2. AGE-DEPENDENT CHANGES IN ACTIVITY OF MALLARD PLASMA CHOLINESTERASES

    Plasma acetylcholinesterase (AChE) and butrylcholinesterase (BChE) activity was measured repeatedly in 27 mallard (Anas platyrhynchos) ducklings between 7 and 85 days of age to determine age-dependent changes in enzyme activity. Plasma AChE, BChe, and total cholinesterase (ChE) a...

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

    Niesz, Tricia; Krishnamurthy, Ramchandar

    2013-01-01

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

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

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

  5. Connectivity Changes Underlying Neurofeedback Training of Visual Cortex Activity

    Frank Scharnowski; Maria Joao Rosa; Narly Golestani; Chloe Hutton; Oliver Josephs; Nikolaus Weiskopf; Geraint Rees

    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 activ...

  6. Subtle stereoconformational change of tryptophanase provoking D-tryptophan activity

    It has been found in this investigation that the stereospecificity of enzyme is full of flexibility and that tryptophanase has an activity also toward D-tryptophan in ammonium phosphate solution at high concentration as L-tryptophan. This fact may show that D-amino acids have physiologically significant activity. It is considered that the appearance of such the activity is related to a stereoconformational change of tryptophanase. This was investigated by the measurement of circular dichroism and fluorescence spectra. Furthermore the change of steric structure was also examined on the denaturated tryptophanase inactivated by gamma irradiation. (M.H.)

  7. Detection of cardiac activity changes from human speech

    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.

  8. Transfer Student Success: Educationally Purposeful Activities Predictive of Undergraduate GPA

    Fauria, Renee M.; Fuller, Matthew B.

    2015-01-01

    Researchers evaluated the effects of Educationally Purposeful Activities (EPAs) on transfer and nontransfer students' cumulative GPAs. Hierarchical, linear, and multiple regression models yielded seven statistically significant educationally purposeful items that influenced undergraduate student GPAs. Statistically significant positive EPAs for…

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

    R.V. Vlasenko; Bialobrzeski, O. V.

    2014-01-01

    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.

  10. Anxiety symptoms and disorder predict activity limitations in the elderly.

    Norton, Joanna; Ancelin, Marie-Laure; Stewart, Rob; BERR, Claudine; Ritchie, Karen; Carrière, Isabelle

    2012-01-01

    International audience BACKGROUND: In the elderly, little attention has been paid to anxiety both on a symptom dimension and as a disorder, as an independent risk factor for the incidence of activity limitations. METHODS: In a community-dwelling cohort of 1581 persons aged 65+, the association between trait anxiety symptoms (Spielberger Trait, third highest tertile) and baseline DSM-IV anxiety disorder, and 7-year incident activity limitations was determined using mixed logistic regression...

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

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

    2014-01-01

    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......: In all, 6,991 participants from the Copenhagen Heart Study attending an examination at age ≥65 years were included. ECG changes were defined as Q waves, ST-segment depression, T-wave changes, ventricular conduction defects, and left ventricular hypertrophy based on the Minnesota code. The primary...... 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 with...

  12. Method of empirical dependences in estimation and prediction of activity of creatine kinase isoenzymes in cerebral ischemia

    Sergeeva, Tatiana F.; Moshkova, Albina N.; Erlykina, Elena I.; Khvatova, Elena M.

    2016-04-01

    Creatine kinase is a key enzyme of energy metabolism in the brain. There are known cytoplasmic and mitochondrial creatine kinase isoenzymes. Mitochondrial creatine kinase exists as a mixture of two oligomeric forms - dimer and octamer. The aim of investigation was to study catalytic properties of cytoplasmic and mitochondrial creatine kinase and using of the method of empirical dependences for the possible prediction of the activity of these enzymes in cerebral ischemia. Ischemia was revealed to be accompanied with the changes of the activity of creatine kinase isoenzymes and oligomeric state of mitochondrial isoform. There were made the models of multiple regression that permit to study the activity of creatine kinase system in cerebral ischemia using a calculating method. Therefore, the mathematical method of empirical dependences can be applied for estimation and prediction of the functional state of the brain by the activity of creatine kinase isoenzymes in cerebral ischemia.

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

    Barata José T; Minderico Cláudia S; Martins Sandra S; Branco Teresa L; Teixeira Pedro J; Palmeira António L; Serpa Sidónio O; Sardinha Luís B

    2007-01-01

    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-wee...

  14. Prediction of pressure induced structural phase transitions and internal mode frequency changes in solid N2+

    A rhombohedral distortion of the Pm3n structure is introduced which shows that a low temperature phase transition occurs from P42/mnm into the R3c calcite structure at P approx. = 19.2 kbar with a volume change of 0.125 cm3/mole. This transition agrees with recent Raman scattering measurements. Another transition from R3c into R3m is predicted at P approx. = 67.5 kbar, with a volume change of 0.1 cm3/mole. The pressure dependence of the intramolecular mode frequencies for the R3c structure is in reasonably good agreement with the two main branches observed experimentally

  15. Weight suppression predicts weight change over 5 years in bulimia nervosa

    Herzog, David B.; Thomas, J. Graham; Kass, Andrea E.; Eddy, Kamryn T.; Franko, Debra L.; Lowe, Michael R.

    2010-01-01

    Recent studies suggest that weight suppression (WS), defined as the discrepancy between current and highest past weight, predicts short-term weight gain in bulimia nervosa (BN) during treatment. The current study was designed to build on this preliminary work by examining the relation between WS and long-term weight change in BN. Treatmentseeking women (N=97) with DSM-IV BN participated in a naturalistic longitudinal follow-up study of eating disorders. At intake, height and weight were measu...

  16. Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

    Thompson, S. E.; Sivapalan, M.; C. J. Harman; V. Srinivasan; M. R. Hipsey; Reed, P.; Montanari, A.; G. Blöschl

    2013-01-01

    Globally, many different kinds of water resources management issues call for policy- and infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal- to century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems....

  17. Imperfect predictability and mutual fund dynamics. How managers use predictors in changing systematic risk.

    Amisano, Gianni; Savona, Roberto

    2008-01-01

    Suppose a fund manager uses predictors in changing port-folio allocations over time. How does predictability translate into portfolio decisions? To answer this question we derive a new model within the Bayesian framework, where managers are assumed to modulate the systematic risk in part by observing how the benchmark returns are related to some set of imperfect predictors, and in part on the basis of their own information set. In this portfolio allocation process, managers concern themselves...

  18. Predicting the change of child’s behavior problems : sociodemographic and maternal parenting stress factors

    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) ...

  19. PREDICTING THE CHANGE OF CHILD’S BEHAVIOR PROBLEMS: SOCIODEMOGRAPHIC AND MATERNAL PARENTING STRESS FACTORS

    Evelina Viduoliene

    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) a...

  20. Organizational Changes to Thyroid Regulation in Alligator mississippiensis: Evidence for Predictive Adaptive Responses

    Boggs, Ashley S. P.; Lowers, Russell H.; Cloy-McCoy, Jessica A.; Guillette, Louis J.

    2013-01-01

    During embryonic development, organisms are sensitive to changes in thyroid hormone signaling which can reset the hypothalamic-pituitary-thyroid axis. It has been hypothesized that this developmental programming is a ‘predictive adaptive response’, a physiological adjustment in accordance with the embryonic environment that will best aid an individual's survival in a similar postnatal environment. When the embryonic environment is a poor predictor of the external environment, the developmenta...

  1. Predictive value and rate of change of blood pressure throughout adolescence : a Belgian prospective study

    Saint-Remy, Annie; Rorive, Georges

    1991-01-01

    We performed a prospective study on the natural course of blood pressure throughout adolescence. The major goals were to assess the predictive value of a high blood pressure level at the age of 12 years and the feasibilty of developing a screening test for the early detection of young subjects at risk of developing chronic hypertension. By measuring the relationship between the initial level and subsequent changes in blood pressure, we looked for a phenomenon previously demonstrated in adults...

  2. Availability of preoperative anxiety scale as a predictive factor for hemodynamic changes during induction of anesthesia

    Kim, Won-Sung; Byeon, Gyeong-Jo; Song, Bong-Jae; Lee, Hyeon Jeong

    2010-01-01

    Background The current study evaluated whether the level of preoperative anxiety assessed by the state-trait anxiety inventory (STAI) affects cardiovascular response during anesthetic induction. Furthermore, we evaluated the utility of the preoperative anxiety scale as a predictive factor for hemodynamic changes. Methods One hundred twenty patients who were scheduled to undergo elective surgery under general anesthesia were enrolled in this prospective study. The patients were asked to fill o...

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

    Robert Redden

    2013-01-01

    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 w...

  4. National Scale Prediction of Soil Carbon Sequestration under Scenarios of Climate Change

    Izaurralde, R. C.; Thomson, A. M.; Potter, S. R.; Atwood, J. D.; Williams, J. R.

    2006-12-01

    Carbon sequestration in agricultural soils is gaining momentum as a tool to mitigate the rate of increase of atmospheric CO2. Researchers from the Pacific Northwest National Laboratory, Texas A&M University, and USDA-NRCS used the EPIC model to develop national-scale predictions of soil carbon sequestration with adoption of no till (NT) under scenarios of climate change. In its current form, the EPIC model simulates soil C changes resulting from heterotrophic respiration and wind / water erosion. Representative modeling units were created to capture the climate, soil, and management variability at the 8-digit hydrologic unit (USGS classification) watershed scale. The soils selected represented at least 70% of the variability within each watershed. This resulted in 7,540 representative modeling units for 1,412 watersheds. Each watershed was assigned a major crop system: corn, soybean, spring wheat, winter wheat, cotton, hay, alfalfa, corn-soybean rotation or wheat-fallow rotation based on information from the National Resource Inventory. Each representative farm was simulated with conventional tillage and no tillage, and with and without irrigation. Climate change scenarios for two future periods (2015-2045 and 2045-2075) were selected from GCM model runs using the IPCC SRES scenarios of A2 and B2 from the UK Hadley Center (HadCM3) and US DOE PCM (PCM) models. Changes in mean and standard deviation of monthly temperature and precipitation were extracted from gridded files and applied to baseline climate (1960-1990) for each of the 1,412 modeled watersheds. Modeled crop yields were validated against historical USDA NASS county yields (1960-1990). The HadCM3 model predicted the most severe changes in climate parameters. Overall, there would be little difference between the A2 and B2 scenarios. Carbon offsets were calculated as the difference in soil C change between conventional and no till. Overall, C offsets during the first 30-y period (513 Tg C) are predicted to

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

    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.

  6. A data mining based approach to predict spatiotemporal changes in satellite images

    Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben

    2011-06-01

    The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

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

    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.

  8. The Predictive Role of Stock Market Return for Real Activity in Thailand

    Jiranyakul, Komain

    2012-01-01

    Stock market return is one of financial variables that contain information to forecast real activity such as industrial production and real GDP growth. However, it is still controversial that stock market return can have a predictive content on real activity. This paper attempts to investigate the ability of stock market return to predict industrial production growth (or real activity) in Thailand, which is an emerging market economy. The standard causality test and the equal forecast evalua...

  9. Efficient and Effective Change Principles in Active Videogames.

    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. PMID:26181680

  10. Predicting Nitrogen Fertilizer Recommendations for Corn using an Active Sensor

    Active sensors, mounted on typical agricultural equipment, can be used to measure N (nitrogen) status in corn (Zea mays L.). This gives a producer the potential to improve N fertilizer recommendations that will reduce nitrate loss to the environment. This study examines the relationship between re...

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

    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 co

  12. Baseline brain activity fluctuations predict somatosensory perception in humans

    Boly, M.; Balteau, E.; Schnakers, C.; Degueldre, C.; Moonen, G.; Luxen, A.; Phillips, C.; Peigneux, P.; Maquet, P.; Laureys, S.

    2007-01-01

    In perceptual experiments, within-individual fluctuations in perception are observed across multiple presentations of the same stimuli, a phenomenon that remains only partially understood. Here, by means of thulium–yttrium/aluminum–garnet laser and event-related functional MRI, we tested whether variability in perception of identical stimuli relates to differences in prestimulus, baseline brain activity. Results indicate a positive relationship between conscious perception of low-intensity somatosensory stimuli and immediately preceding levels of baseline activity in medial thalamus and the lateral frontoparietal network, respectively, which are thought to relate to vigilance and “external monitoring.” Conversely, there was a negative correlation between subsequent reporting of conscious perception and baseline activity in a set of regions encompassing posterior cingulate/precuneus and temporoparietal cortices, possibly relating to introspection and self-oriented processes. At nociceptive levels of stimulation, pain-intensity ratings positively correlated with baseline fluctuations in anterior cingulate cortex in an area known to be involved in the affective dimension of pain. These results suggest that baseline brain-activity fluctuations may profoundly modify our conscious perception of the external world. PMID:17616583

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

    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.

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

    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.

  15. Soil Erosion Prediction Based on Land Use Changes (A Case in Neka Watershed

    Karim Solaimani

    2009-01-01

    Full Text Available Problem statement: Land use change has transformed a vast part of the natural landscapes of the developing world for the last 50 years. Land is a fundamental factor of production and though much of the course of human history, it has been tightly coupled with economic growth. Soil erosion by water is one of the most important land degradation processes in the Mediterranean basins. The unplanned land use change within and near a fast growing agricultural land in Neka River Basin, led to an accelerated erosion of soil in the area. Approach: This study aims to find the relationships between land use pattern, erosion and the sediment yield in the study area. The land use coefficient (Xa has applied in the model of Erosion Potential Method (EPM to forecast the effect of the land type to reduce the erosion. Land cover and land use change was projected for the next decade using topography, geology, land use maps and remote sensing data of the study area. Results: The results of this study indicated that the total sediment yield of the study area has notably decreased to 89.24% after an appropriate land use/cover alteration. The estimated special erosion for the Southern Neka Basin is about 144465.1 m3 km-2 where after management policy is predicted 15542.9 m3 km-2 year?1, therefore the total difference for the study area has estimated about 128922.2 m3 km-2 year-1. Conclusion: The land use changes assessed among the different land cover classes. It is important to mention that conducting of the present study a very severe land cover changes taken place as the result of agricultural land development. These changes in land cover led to the forest degradation of the study area. Relationship between land-use changes and agricultural growth offered a more robust prediction of soil erosion in Neka watershed.

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

    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

  17. Prediction

    Woollard, W.J.

    2006-01-01

    In this chapter we will look at the ways in which you can use ICT in the classroom to support hypothesis and prediction and how modern technology is enabling: pattern seeking, extrapolation and interpolation to meet the challenges of the information explosion of the 21st century.

  18. Predicting ecological changes on benthic estuarine assemblages through decadal climate trends along Brazilian Marine Ecoregions

    Bernardino, Angelo F.; Netto, Sérgio A.; Pagliosa, Paulo R.; Barros, Francisco; Christofoletti, Ronaldo A.; Rosa Filho, José S.; Colling, André; Lana, Paulo C.

    2015-12-01

    Estuaries are threatened coastal ecosystems that support relevant ecological functions worldwide. The predicted global climate changes demand actions to understand, anticipate and avoid further damage to estuarine habitats. In this study we reviewed data on polychaete assemblages, as a surrogate for overall benthic communities, from 51 estuaries along five Marine Ecoregions of Brazil (Amazonia, NE Brazil, E Brazil, SE Brazil and Rio Grande). We critically evaluated the adaptive capacity and ultimately the resilience to decadal changes in temperature and rainfall of the polychaete assemblages. As a support for theoretical predictions on changes linked to global warming we compared the variability of benthic assemblages across the ecoregions with a 40-year time series of temperature and rainfall data. We found a significant upward trend in temperature during the last four decades at all marine ecoregions of Brazil, while rainfall increase was restricted to the SE Brazil ecoregion. Benthic assemblages and climate trends varied significantly among and within ecoregions. The high variability in climate patterns in estuaries within the same ecoregion may lead to correspondingly high levels of noise on the expected responses of benthic fauna. Nonetheless, we expect changes in community structure and productivity of benthic species at marine ecoregions under increasing influence of higher temperatures, extreme events and pollution.

  19. Observed and predicted effects of climate change on species abundance in protected areas

    Johnston, Alison; Ausden, Malcolm; Dodd, Andrew M.; Bradbury, Richard B.; Chamberlain, Dan E.; Jiguet, Frédéric; Thomas, Chris D.; Cook, Aonghais S. C. P.; Newson, Stuart E.; Ockendon, Nancy; Rehfisch, Mark M.; Roos, Staffan; Thaxter, Chris B.; Brown, Andy; Crick, Humphrey Q. P.; Douse, Andrew; McCall, Rob A.; Pontier, Helen; Stroud, David A.; Cadiou, Bernard; Crowe, Olivia; Deceuninck, Bernard; Hornman, Menno; Pearce-Higgins, James W.

    2013-12-01

    The dynamic nature and diversity of species' responses to climate change poses significant difficulties for developing robust, long-term conservation strategies. One key question is whether existing protected area networks will remain effective in a changing climate. To test this, we developed statistical models that link climate to the abundance of internationally important bird populations in northwestern Europe. Spatial climate-abundance models were able to predict 56% of the variation in recent 30-year population trends. Using these models, future climate change resulting in 4.0°C global warming was projected to cause declines of at least 25% for more than half of the internationally important populations considered. Nonetheless, most EU Special Protection Areas in the UK were projected to retain species in sufficient abundances to maintain their legal status, and generally sites that are important now were projected to be important in the future. The biological and legal resilience of this network of protected areas is derived from the capacity for turnover in the important species at each site as species' distributions and abundances alter in response to climate. Current protected areas are therefore predicted to remain important for future conservation in a changing climate.

  20. Predicting the impact of climate change on threatened species in UK waters.

    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.

  1. Baseline brain activity fluctuations predict somatosensory perception in humans

    Boly, M; Balteau, E.; Schnakers, C; Degueldre, C.; Moonen, G.; Luxen, A.; Phillips, C.; Peigneux, P; Maquet, P; Laureys, S.

    2007-01-01

    In perceptual experiments, within-individual fluctuations in perception are observed across multiple presentations of the same stimuli, a phenomenon that remains only partially understood. Here, by means of thulium–yttrium/aluminum–garnet laser and event-related functional MRI, we tested whether variability in perception of identical stimuli relates to differences in prestimulus, baseline brain activity. Results indicate a positive relationship between conscious perception of low-intensity so...

  2. Performance on Indirect Measures of Race Evaluation Predicts Amygdala Activation

    Phelps, Elizabeth A.; O'Connor, Kevin J.; Cunningham, William A.; Funayama, E. Sumie; Gatenby, J. Christopher; Gore, John C.; Banaji, Mahzarin R.

    2000-01-01

    We used fMRI to explore the neural substrates involved in the unconscious evaluation of Black and White social groups. Specifically, we focused on the amygdala, a subcortical structure known to play a role in emotional learning and evaluation. In Experiment 1, White American subjects observed faces of unfamiliar Black and White males. The strength of amygdala activation to Black-versus-White faces was correlated with two indirect (unconscious) measures of race evaluation (Implicit Association...

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

    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…

  4. Role of competition in vegetation change: evolutionarily stable strategy analysis as a means for predicting change in vegetation distributions

    Farrior, C.

    2015-12-01

    One of the clearest differences among major vegetation types is allocation to woody biomass. Whether and to what extent plants invest in this long-lived tissue has a major impact on carbon storage and can have important feedbacks to the rising CO2 in the atmosphere. Wood is a multifaceted structure. It can allow plants to escape from ground fires, the pressure of herbivores, and perhaps most importantly competition with other plants for light. Understanding the result of this final pressure requires an incorporation of individual-based interactions among plants. This can be a particularly difficult because of both high computational demands and errors in implementation and understanding of such complex models. We have made progress on both difficulties for understanding allocation to woody biomass among trees in forests. Across gradients in resource availability within forests, we find a significant influence of individual-based competition on dominant plant allocation to woody biomass. In model predictions and observed differences among forests globally major tradeoffs occur in allocation to woody biomass versus allocation to fine roots. This is driven by shifting importance of individual-based competition for light versus shared resources belowground, in particular water and nitrogen. Moving beyond forests to biome boundaries, transitions between grassland, savanna, and forest we see again that competition can play an important role. In these zones of rapid change however, population dynamics is not as simple as a steady-state closed-canopy forest. Disturbance dynamics including response to fire and drought stress are also important pressures on dominant plant strategies. Here I show progress in incorporating disturbance dynamics with individual based competition to predict and understand dominant plant strategies including allocation to woody biomass. Results indicate that the influence of competition varies with disturbance regime. With stochastic disturbance

  5. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A [Duke University Medical Center, Durham, NC (United States); Ge, Y [University of North Carolina at Charlotte, Charlotte, NC (United States)

    2014-06-15

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

  6. Volume Changes During Active Shape Fluctuations in Cells

    La Porta, Caterina A. M.; Taloni, Alessandro; Kardash, Elena; Salman, Oguz Umut; Truskinovsky, Lev; Zapperi, Stefano

    Cells modify their volume in response to changes in osmotic pressure but it is usually assumed that other active shape variations do not involve significant volume fluctuations. Here we report experiments demonstrating that water transport in and out of the cell is needed for the formation of blebs, commonly observed protrusions in the plasma membrane driven by cortex contraction. We develop and simulate a model of fluid-mediated membrane-cortex deformations and show that a permeable membrane is necessary for bleb formation which is otherwise impaired. Taken together, our experimental and theoretical results emphasize the subtle balance between hydrodynamics and elasticity in actively driven cell morphological changes.

  7. Volume changes during active shape fluctuations in cells

    Taloni, Alessandro; Salman, Oguz Umut; Truskinovsky, Lev; Zapperi, Stefano; La Porta, Caterina A M

    2015-01-01

    Cells modify their volume in response to changes in osmotic pressure but it is usually assumed that other active shape variations do not involve significant volume fluctuations. Here we report experiments demonstrating that water transport in and out of the cell is needed for the formation of blebs, commonly observed protrusions in the plasma membrane driven by cortex contraction. We develop and simulate a model of fluid mediated membrane-cortex deformations and show that a permeable membrane is necessary for bleb formation which is otherwise impaired. Taken together our experimental and theoretical results emphasize the subtle balance between hydrodynamics and elasticity in actively driven cell morphological changes.

  8. A trading-space-for-time approach to probabilistic continuous streamflow predictions in a changing climate

    R. Singh

    2011-07-01

    Full Text Available Understanding the implications of potential future climatic conditions for hydrologic services and hazards is a crucial and current science question. The common approach to this problem is to force a hydrologic model, calibrated on historical data or using a priori parameter estimates, with future scenarios of precipitation and temperature. Recent studies suggest that the climatic regime of the calibration period is reflected in the resulting parameter estimates and that the model performance can be negatively impacted if the climate for which projections are made is significantly different from that during calibration. We address this issue by introducing a framework for probabilistic streamflow predictions in a changing climate wherein we quantify the impact of climate on model parameters. The strategy extends a regionalization approach (used for predictions in ungauged basins by trading space-for-time to account for potential parameter variability in a future climate that is beyond the historically observed one. The developed methodology was tested in five US watersheds located in dry to wet climates using synthetic climate scenarios generated by increasing the historical mean temperature from 0 to 8 °C and by changing historical mean precipitation from −30 % to +40 % of the historical values. Validation on historical data shows that changed parameters perform better if future streamflow differs from historical by more than 25 %. We found that the thresholds of climate change after which the streamflow projections using adjusted parameters were significantly different from those using fixed parameters were 0 to 2 °C for temperature change and −10 % to 20 % for precipitation change depending upon the aridity of the watershed. Adjusted parameter sets simulate a more extreme watershed response for both high and low flows.

  9. COMBINING CLIMATE MODEL PREDICTIONS, HYDROLOGICAL MODELING, AND ECOLOGICAL NICHE MODELING ALGORITHMS TO PREDICT THE IMPACTS OF CLIMATE CHANGE ON AQUATIC BIODIVERSITY

    The results of this research will provide a broad taxonomic and regional assessment of the impacts of climate change on aquatic species in the United States by producing predictions of current and future habitat quality for aquatic taxa based on multiple climate change scen...

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

    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.

  11. Chang Chien’s Ideas and Activities on Constitutional Monarchy

    Shun-chih Sun

    2009-01-01

    Chang Chien was born on July 1st in 1853 in Haimen Kiangsu and died on August 24th in 1926 in Nant’ung Kiangsu. Chang Chien’s ideas and activities on constitutional monarchy are significant and thus this article is to examine them.Constitutional monarchy, according to Chang Chien, was a separation of the three-power political system under an emperor. In order to accomplish constitutional monarchy, local self-government should be strengthened and therefore without local self-government, consti...

  12. Predicting impacts of climate change on medicinal asclepiads of Pakistan using Maxent modeling

    Khanum, Rizwana; Mumtaz, A. S.; Kumar, Sunil

    2013-05-01

    Maximum entropy (Maxent) modeling was used to predict the potential climatic niches of three medicinally important Asclepiad species: Pentatropis spiralis, Tylophora hirsuta, and Vincetoxicum arnottianum. All three species are members of the Asclepiad plant family, yet they differ in ecological requirements, biogeographic importance, and conservation value. Occurrence data were collected from herbarium specimens held in major herbaria of Pakistan and two years (2010 and 2011) of field surveys. The Maxent model performed better than random for the three species with an average test AUC value of 0.74 for P. spiralis, 0.84 for V. arnottianum, and 0.59 for T. hirsuta. Under the future climate change scenario, the Maxent model predicted habitat gains for P. spiralis in southern Punjab and Balochistan, and loss of habitat in south-eastern Sindh. Vincetoxicum arnottianum as well as T. hirsuta would gain habitat in upper Peaks of northern parts of Pakistan. T. hirsuta is predicted to lose most of the habitats in northern Punjab and in parches from lower peaks of Galliat, Zhob, Qalat etc. The predictive modeling approach presented here may be applied to other rare Asclepiad species, especially those under constant extinction threat.

  13. Predicting activities without computing descriptors: graph machines for QSAR.

    Goulon, A; Picot, T; Duprat, A; Dreyfus, G

    2007-01-01

    We describe graph machines, an alternative approach to traditional machine-learning-based QSAR, which circumvents the problem of designing, computing and selecting molecular descriptors. In that approach, which is similar in spirit to recursive networks, molecules are considered as structured data, represented as graphs. For each example of the data set, a mathematical function (graph machine) is built, whose structure reflects the structure of the molecule under consideration; it is the combination of identical parameterised functions, called "node functions" (e.g. a feedforward neural network). The parameters of the node functions, shared both within and across the graph machines, are adjusted during training with the "shared weights" technique. Model selection is then performed by traditional cross-validation. Therefore, the designer's main task consists in finding the optimal complexity for the node function. The efficiency of this new approach has been demonstrated in many QSAR or QSPR tasks, as well as in modelling the activities of complex chemicals (e.g. the toxicity of a family of phenols or the anti-HIV activities of HEPT derivatives). It generally outperforms traditional techniques without requiring the selection and computation of descriptors. PMID:17365965

  14. Performance of a process-based hydrodynamic model in predicting shoreline change

    Safak, I.; Warner, J. C.; List, J. H.

    2012-12-01

    Shoreline change is controlled by a complex combination of processes that include waves, currents, sediment characteristics and availability, geologic framework, human interventions, and sea level rise. A comprehensive data set of shoreline position (14 shorelines between 1978-2002) along the continuous and relatively non-interrupted North Carolina Coast from Oregon Inlet to Cape Hatteras (65 km) reveals a spatial pattern of alternating erosion and accretion, with an erosional average shoreline change rate of -1.6 m/yr and up to -8 m/yr in some locations. This data set gives a unique opportunity to study long-term shoreline change in an area hit by frequent storm events while relatively uninfluenced by human interventions and the effects of tidal inlets. Accurate predictions of long-term shoreline change may require a model that accurately resolves surf zone processes and sediment transport patterns. Conventional methods for predicting shoreline change such as one-line models and regression of shoreline positions have been designed for computational efficiency. These methods, however, not only have several underlying restrictions (validity for small angle of wave approach, assuming bottom contours and shoreline to be parallel, depth of closure, etc.) but also their empirical estimates of sediment transport rates in the surf zone have been shown to vary greatly from the calculations of process-based hydrodynamic models. We focus on hind-casting long-term shoreline change using components of the process-based, three-dimensional coupled-ocean-atmosphere-wave-sediment transport modeling system (COAWST). COAWST is forced with historical predictions of atmospheric and oceanographic data from public-domain global models. Through a method of coupled concurrent grid-refinement approach in COAWST, the finest grid with resolution of O(10 m) that covers the surf zone along the section of interest is forced at its spatial boundaries with waves and currents computed on the grids

  15. Wave climate change, coastline response and hazard prediction in New South Wales, Australia

    Full text: Full text: Considerable research effort has been directed towards understanding and the gross prediction of shoreline response to sea level rise (eg. Cowell ef a/. 2003a, b). In contrast, synoptic prediction of changes in the planform configuration of shorelines in response to changes in wind and wave climates over many decades has been limited by the lack of geohistorical data on shoreline alignment evolution and long time series of wave climate. This paper presents new data sets on monthly mean wave direction variability based on: a. Waverider buoy data; b. a reconstruction of monthly mid-shelf wave direction, 1877 to 2002 AD from historical MSLP data (Goodwin 2005); and c. a multi-decadal reconstruction of wave direction, in association with the Interdecadal Pacific Oscillation and the Southern Annular Mode of climate variability, covering the past millennium. A model of coastline response to the wave climate variability is presented for northern and central New South Wales (NSW) for decadal to multi-decadal time scales, and is based on instrumental and geohistorical data. The sensitivity of the coastline position and alignment, and beach state to mean and extreme wave climate changes is demonstrated (e.g. Goodwin et al. 2006). State changes in geometric shoreline alignment rotation, sand volume (progradation/recession) for NSW and mean wave direction, are shown to be in agreement with the low-frequency change in Pacific-wide climate. Synoptic typing of climate patterns using Self Organised Mapping methods is used to downscale CSIRO GCM output for this century. The synoptic types are correlated to instrumental wave climate data and coastal behaviour. The shifts in downscaled synoptic types for 2030 and 2070 AD are then used as the basis for predicting mean wave climate changes, coastal behaviour and hazards along the NSW coastline. The associated coastal hazards relate to the definition of coastal land loss through rising sea levels and shoreline

  16. Study on active faults and weekly observation around them using cellurose nitrate film for the earthquake prediction research program

    The track etch method, which is one of the geochemical survey methods for the mapping and detection of active faults and evaluation of their activities, has been applied to many sites for the purpose of the earth-quake prediction research program. The method conventionally measures relative radon concentration in the soil gas by counting the track density (tracks per cm2.day) recorded on a piece of cellurose nitrate film (2 x 3 cm) which is sensitive to α particles. Weekly observation to monitor radon concentration changes in the soil gas using it has been carried on, on the several active faults since 1978, as a part of the earthquake prediction research program. (author)

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

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

    2013-01-01

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

  18. Performance on indirect measures of race evaluation predicts amygdala activation.

    Phelps, E A; O'Connor, K J; Cunningham, W A; Funayama, E S; Gatenby, J C; Gore, J C; Banaji, M R

    2000-09-01

    We used fMRI to explore the neural substrates involved in the unconscious evaluation of Black and White social groups. Specifically, we focused on the amygdala, a subcortical structure known to play a role in emotional learning and evaluation. In Experiment 1, White American subjects observed faces of unfamiliar Black and White males. The strength of amygdala activation to Black-versus-White faces was correlated with two indirect (unconscious) measures of race evaluation (Implicit Association Test [IAT] and potentiated startle), but not with the direct (conscious) expression of race attitudes. In Experiment 2, these patterns were not obtained when the stimulus faces belonged to familiar and positively regarded Black and White individuals. Together, these results suggest that amygdala and behavioral responses to Black-versus-White faces in White subjects reflect cultural evaluations of social groups modified by individual experience. PMID:11054916

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

    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.

  20. Continuously Growing Rodent Molars Result from a Predictable Quantitative Evolutionary Change over 50 Million Years

    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.

  1. Predicting the Affects of Climate Change on Evapotranspiration and Agricultural Productivity of Semi-arid Basins

    Peri, L.; Tyler, S. W.; Zheng, C.; Pohll, G. M.; Yao, Y.

    2013-12-01

    Many arid and semi-arid regions around the world are experiencing water shortages that have become increasingly problematic. Since the late 1800s, upstream diversions in Nevada's Walker River have delivered irrigation supply to the surrounding agricultural fields resulting in a dramatic water level decline of the terminal Walker Lake. Salinity has also increased because the only outflow from the lake is evaporation from the lake surface. The Heihe River basin of northwestern China, a similar semi-arid catchment, is also facing losses from evaporation of terminal locations, agricultural diversions and evapotranspiration (ET) of crops. Irrigated agriculture is now experiencing increased competition for use of diminishing water resources while a demand for ecological conservation continues to grow. It is important to understand how the existing agriculture in these regions will respond as climate changes. Predicting the affects of climate change on groundwater flow, surface water flow, ET and agricultural productivity of the Walker and Heihe River basins is essential for future conservation of water resources. ET estimates from remote sensing techniques can provide estimates of crop water consumption. By determining similarities of both hydrologic cycles, critical components missing in both systems can be determined and predictions of impacts of climate change and human management strategies can be assessed.

  2. Switch region for pathogenic structural change in conformational disease and its prediction.

    Xin Liu

    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.

  3. Land use change and prediction in the Baimahe Basin using GIS and CA-Markov model

    Using ArcGIS and IDRISI, land use dynamics and Shannon entropy information were applied in this paper to analyze the quantity and structure change in the Baimahe Basin from 1996 to 2008. A CA-Markov model was applied to predict the land use patterns in 2020. Results showed that farmland, forest and construction land are the dominant land use types in the Baimahe Basin. From 1996 to 2008, areas of farmland and forest decreased and other land use types increased, with construction land increasing the most. The prediction results showed that the changes in land use patterns from 2008 to 2020 would be the same with those from 1996 to 2008. Main changes are the transiting out of farmland and forest and the transiting in of construction land. The order degree of the whole basin goes on decreasing. Measures of farmland protection and grain for green projects should be adopted to enhance the stability of land use system in the Baimahe Basin in order to promote regional sustainable development

  4. Prediction of hospital mortality by changes in the estimated glomerular filtration rate (eGFR).

    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.

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

    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.

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

    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.

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

    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

  8. Failure Rate Prediction of Active Component Using PM Basis Database

    The safety security and efficient management of NPPs (Nuclear Power Plants) have been increased after the accident of TEPCO's Fukushima nuclear power stations. The needs for the safety and efficiency are becoming more important because about 90 percent of the NPPs all over the world are more than 20 operation years old. The preventive maintenance criteria need to be flexible, considering long-term development of the equipment performance and preventive maintenance. The PMBD (Preventive Maintenance Basis Database) program was widely used for optimization of the preventive maintenance criteria. PMBD program contains all kinds of failure mechanisms for each equipment that may occur in the power plant based on RCM(Reliability-Centered Maintenance) and numerically calculate the variation of reliability and failure rate based on PM interval changes. In this study, propriety evaluation of preventive maintenance task, cycle, technical basis for cost effective preventive maintenance strategy and an appropriate evaluation were suggested by the case application of PMBD for major components in the NPPs

  9. Changes in enzyme activities of porcine erythrocytes exposed to radiation

    Changes in activities of superoxide dismutase, catalase, peroxidase and acetylcholinesterase were observed in porcine erythrocytes for doses of 5 - 30 kGy. These enzymes are capable of performing their functions also in irradiated porcine erythrocytes, which seem to be more radioresistant in this respect than bovine erythrocytes investigated previously. (author)

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

    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…

  11. Body image and body change: Predictive factors in an Iranian population

    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.

  12. Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images.

    Bagci, Ulas; Yao, Jianhua; Miller-Jaster, Kirsten; Chen, Xinjian; Mollura, Daniel J

    2013-01-01

    We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 (18)F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75 ± 1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUV(max) (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUV(max). We also found that integrating textural features with SUV

  13. Structure-based activity prediction for an enzyme of unknown function

    Hermann, Johannes C.; Marti-Arbona, Ricardo; Fedorov, Alexander A.; Fedorov, Elena; Almo, Steven C.; Shoichet, Brian K.; Raushel, Frank M.

    2007-01-01

    With many genomes sequenced, a pressing challenge in biology is predicting the function of the proteins that the genes encode. When proteins are unrelated to others of known activity, bioinformatics inference for function becomes problematic. It would thus be useful to interrogate protein structures for function directly. Here, we predict the function of an enzyme of unknown activity, Tm0936 from Thermotoga maritima, by docking high-energy intermediate forms of thousands of candidate metaboli...

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

    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.

  15. Psychosocial Constructs and Postintervention Changes in Physical Activity and Dietary Outcomes in a Lifestyle Intervention, Hub City Steps, 2010

    Landry, Alicia S; Thomson, Jessica L.; Madson, Michael B.; Zoellner, Jamie M.; Mohn, Richard S.; Noble, Jeremy; Connell, Carol L.; Yadrick, Kathy

    2015-01-01

    Introduction Although modifications to dietary and physical activity (PA) behavior can reduce blood pressure, racial disparities in prevalence and control of hypertension persist. Psychosocial constructs (PSCs) of self-regulation, processes of change, and social support are associated with initiation and maintenance of PA in African Americans; which PSCs best predict lifestyle behavior changes is unclear. This study’s objective was to examine relationships among PSC changes and postinterventi...

  16. Changing ideas about others’ intentions: updating prior expectations tunes activity in the human motor system

    Jacquet, Pierre O.; Roy, Alice C.; Chambon, Valérian; Borghi, Anna M.; Salemme, Roméo; Farnè, Alessandro; Reilly, Karen T.

    2016-01-01

    Predicting intentions from observing another agent’s behaviours is often thought to depend on motor resonance – i.e., the motor system’s response to a perceived movement by the activation of its stored motor counterpart, but observers might also rely on prior expectations, especially when actions take place in perceptually uncertain situations. Here we assessed motor resonance during an action prediction task using transcranial magnetic stimulation to probe corticospinal excitability (CSE) and report that experimentally-induced updates in observers’ prior expectations modulate CSE when predictions are made under situations of perceptual uncertainty. We show that prior expectations are updated on the basis of both biomechanical and probabilistic prior information and that the magnitude of the CSE modulation observed across participants is explained by the magnitude of change in their prior expectations. These findings provide the first evidence that when observers predict others’ intentions, motor resonance mechanisms adapt to changes in their prior expectations. We propose that this adaptive adjustment might reflect a regulatory control mechanism that shares some similarities with that observed during action selection. Such a mechanism could help arbitrate the competition between biomechanical and probabilistic prior information when appropriate for prediction. PMID:27243157

  17. The insulin receptor activation process involves localized conformational changes.

    Baron, V; Kaliman, P; Gautier, N; Van Obberghen, E

    1992-11-15

    The molecular process by which insulin binding to the receptor alpha-subunit induces activation of the receptor beta-subunit with ensuing substrate phosphorylation remains unclear. In this study, we aimed at approaching this molecular mechanism of signal transduction and at delineating the cytoplasmic domains implied in this process. To do this, we used antipeptide antibodies to the following sequences of the receptor beta-subunit: (i) positions 962-972 in the juxtamembrane domain, (ii) positions 1247-1261 at the end of the kinase domain, and (iii) positions 1294-1317 and (iv) positions 1309-1326, both in the receptor C terminus. We have previously shown that insulin binding to its receptor induces a conformational change in the beta-subunit C terminus. Here, we demonstrate that receptor autophosphorylation induces an additional conformational change. This process appears to be distinct from the one produced by ligand binding and can be detected in at least three different beta-subunit regions: the juxtamembrane domain, the kinase domain, and the C terminus. Hence, the cytoplasmic part of the receptor beta-subunit appears to undergo an extended conformational change upon autophosphorylation. By contrast, the insulin-induced change does not affect the juxtamembrane domain 962-972 nor the kinase domain 1247-1261 and may be limited to the receptor C terminus. Further, we show that the hormone-dependent conformational change is maintained in a kinase-deficient receptor due to a mutation at lysine 1018. Therefore, during receptor activation, the ligand-induced change could precede ATP binding and receptor autophosphorylation. We propose that insulin binding leads to a transient receptor form that may allow ATP binding and, subsequently, autophosphorylation. The second conformational change could unmask substrate-binding sites and stabilize the receptor in an active conformation. PMID:1331080

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

    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.

  19. Changes in the perceived neighborhood environment in relation to changes in physical activity: A longitudinal study from childhood into adolescence.

    D'Haese, Sara; De Meester, Femke; Cardon, Greet; De Bourdeaudhuij, Ilse; Deforche, Benedicte; Van Dyck, Delfien

    2015-05-01

    The aim was to investigate how physical activity and the perceived neighborhood environment in children change when they enter adolescence. Also the relation between changes in the perceived environment and changes in children's physical activity was investigated. In total, 321 children and one of their parents filled out a physical activity questionnaire and the NEWS-Y at two time points (last grade of elementary school and 2 years later). Children also wore an activity monitor. Changes in children's physical activity were dependent on the physical activity domain. Only less than half of children's perceived neighborhood factors changed and about half of the parental perceived neighborhood factors changed. Most of these factors changed towards higher activity friendliness. Changes in the perceived environment were only limitedly related to changes in children's physical activity. PMID:25840351

  20. Catchment Prediction In Changing Environments (CAPICHE): A Model Inter-Comparison Experiment

    Hutton, Christopher; Nijzink, Remko; Pechlivanidis, Ilias; Capell, René; Wagener, Thorsten; Freer, Jim; Han, Dawei; Hrachowitz, Markus; Arheimer, Berit

    2016-04-01

    In order to improve societal resilience to the impacts of changes in climate and land-use, improved understanding of how catchments respond to changing forcing conditions is required. Such understanding may help better identify the range of effective interventions to improve overall integrated catchment management. For example, re-foresting catchment headwaters may reduce high flows, but also reduce low flows through increased evapotranspiration, creating a potential trade-off that needs to be reliably understood when considering benefits for both water supply and flood mitigation. Catchment modelling may be useful to inform such management decisions by simulating future forcing changes, so that we can assess the relative benefits of different catchment management scenarios. However, numerical models are known to be uncertain, and their ability to simulate future change is compromised by the fact that model parameters can show non-stationary and compensatory effects for different forcing conditions, notwithstanding errors and uncertainties in the future forcings themselves. In order to first identify, and second develop the most appropriate models to simulate catchments under environmental change, we argue that model inter-comparisons are required that move beyond a simple comparison of predictive performance alone, towards a controlled comparison of how different models simulate change. We present the development of a methodology for model inter-comparison under changing forcings to analyse, in this case, how models simulate landscape change, built upon time-varying sensitivity analysis of model parameters. First, for a given catchment, hydrologic signatures are calculated over consecutive windows covering the period of forcing change to analyse how the catchment responds hydrologically to change. Then, each model is calibrated to each window, and within each window, to each signature, which allows us to analyse the time-varying relationship between catchment

  1. PREDICTING THE CHANGE OF CHILD’S BEHAVIOR PROBLEMS: SOCIODEMOGRAPHIC AND MATERNAL PARENTING STRESS FACTORS

    Evelina Viduoliene

    2013-06-01

    Full Text Available 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 Child Behavior Checklist 1.5−5 years (Achenbach, Rescorla, 2000 questionnaires. Findings: Child’s externalizing problems decreased within 12 months period. There were no effects of child’s age, gender and age*gender interaction on externalizing problems change within 12 months period. Higher initial level and more negative change within 12 months period of maternal parenting stress related to child characteristics, more stressful events in family life predicted the increase of child’s externalizing problems. Research limitations/implications: maternal parenting stress and child’s externalizing problems are related and may influence each other simultaneously. Child’s externalizing problems decrease within one year period in overall 2−5 years old children group. The change of child’s aggressive behavior and hyperactivity, distractibility should be evaluated individually, separately from each other. Practical implications: maternal parenting stress and child’s behavior problems are closely related to each other, it may be meaningful organize intervention for mothers in order to prevent child’s externalizing problems increase. Keywords: maternal parenting stress, externalizing problems, childhood, toddlerhood, longitudinal research. Research type: research paper.

  2. Sensitivity to Change and Predictive Validity of the MOODS-SR Questionnaire, Last-Month Version

    Miniati, Mario; Rucci, Paola; Frank, Ellen; Oppo, Annalisa; Kupfer, David J.; Fagiolini, Andrea; Cassano, Giovanni B.

    2014-01-01

    Background Instruments that are intended to measure change over time need to emphasize sensitivity to change as a central property. The aims of this report are to test whether the MOODS-SR, a measure of mood spectrum symptomatology, is sensitive to changes during acute and continuation treatment of depression and whether residual mood spectrum symptoms predict relapse in the subsequent 6 months. Methods The study sample includes 316 patients with nonpsychotic depression participating in the protocol ‘Depression: the search for treatment-relevant phenotypes’. Patients were initially randomized to selective serotonin reuptake inhibitors or interpersonal psychotherapy and then treated for 9 months using an algorithm-based protocol. Measures of mood symptomatology included the self-report version of the structured clinical interview for mood spectrum (MOODS-SR), the Quick Inventory for Depressive Symptomatology and the Hamilton Rating Scale for Depression. Results Repeated-measures ANOVA indicates that during the acute phase MOODS scores decrease significantly from baseline to weeks 6 and 12. This decrease was significantly different (p < 0.001) between those who remitted and those who did not remit on the depressive, the rhythmicity component and the total score. Nonrelapsing subjects had stable scores across the continuation phase, while among relapsing subjects, a significant increase was found in the depressive component (p < 0.001), the rhythmicity component (p = 0.024) and the total score (p < 0.001), at 2 months, followed by a decrease from 2 to 6 months. Scores on the depressive component at the entry into continuation predicted relapse in the subsequent 6 months. Conclusions Our findings suggest that the MOODS-SR is sensitive to change in depression status and may help the clinician to detect symptoms and signs not considered by established symptom severity scales. PMID:19218830

  3. Evaluation of Hydrologic Models to Predict Sediment Export With Changing Land Use in Leeward Hawaiian Watersheds

    Falinski, K. A.; Oleson, K.; Nielson, J.

    2014-12-01

    Land-based sediments are a key threat to shallow coral reef ecosystems in Hawaii. Estimating sediment export is a critical step to being able to connect future land use changes with changes in sediment released to the coastal zone. However, empirically- and process-based hydrological models have proven difficult to adapt to Hawaii's geography, adding significant uncertainty to using available decision support tools. Four soil loss and sediment yield models, InVEST, N-SPECT, SWAT and GSSHA, were compared. Data including precipitation, flow discharge, and suspended sediment concentration were compiled from four leeward watersheds in the Hawaiian Islands. These were combined with the most recently available GIS data on soils, rainfall, land use and 10-m elevation. Results show that annual sediment export is typically underpredicted by an order of magnitude in the models. Moreover, soil loss predictions are spatially incongruent with field observations. Model results overestimate soil loss in the steep forested zones, where field observations show source material to be limited, and are not able to adequately capture human- and animal-disturbed material that connects hydrologically with the stream network. We suggest that the differences stem from a mismatch of processes that source sediments, including stream channel erosion and storage and shallow landslides, which are not included in all the models that are typically used for decision support. Moreover, different modeling platforms use different transport equations, which have not been validated for steep, mountainous watersheds. Changes in land use, such as new developments or cover crops, are obscured by models which consider steeply-sloped areas to be the primary source of sediment. The comparison suggests that decision support tools for Hawaii need a different approach for predicting sediment export with changing land use.

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

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

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

    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.

  6. Prediction

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

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

    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. PMID:23987324

  8. Application of Data Mining Techniques in Weather Prediction and Climate Change Studies

    Folorunsho Olaiya

    2012-02-01

    Full Text Available Weather forecasting is a vital application in meteorology and has been one of the most scientifically and technologically challenging problems around the world in the last century. In this paper, we investigate the use of data mining techniques in forecasting maximum temperature, rainfall, evaporation and wind speed. This was carried out using Artificial Neural Network and Decision Tree algorithms and meteorological data collected between 2000 and 2009 from the city of Ibadan, Nigeria. A data model for the meteorological data was developed and this was used to train the classifier algorithms. The performances of these algorithms were compared using standard performance metrics, and the algorithm which gave the best results used to generate classification rules for the mean weather variables. A predictive Neural Network model was also developed for the weather prediction program and the results compared with actual weather data for the predicted periods. The results show that given enough case data, Data Mining techniques can be used for weather forecasting and climate change studies.

  9. Land colonisation by fish is associated with predictable changes in life history.

    Platt, Edward R M; Fowler, Ashley M; Ord, Terry J

    2016-07-01

    The colonisation of new environments is a central evolutionary process, yet why species make such transitions often remains unknown because of the difficulty in empirically investigating potential mechanisms. The most likely explanation for transitions to new environments is that doing so conveys survival benefits, either in the form of an ecological release or new ecological opportunity. Life history theory makes explicit predictions about how traits linked to survival and reproduction should change with shifts in age-specific mortality. We used these predictions to examine whether a current colonisation of land by fishes might convey survival benefits. We found that blenny species with more terrestrial lifestyles exhibited faster reproductive development and slower growth rates than species with more marine lifestyles; a life history trade off that is consistent with the hypothesis that mortality has become reduced in younger life stages on land. A plausible explanation for such a shift is that an ecological release or opportunity on land has conveyed survival benefits relative to the ancestral marine environment. More generally, our study illustrates how life history theory can be leveraged in novel ways to formulate testable predictions on why organisms might make transitions into novel environments. PMID:26932469

  10. A unified framework for activity recognition-based behavior analysis and action prediction in smart homes.

    Fatima, Iram; Fahim, Muhammad; Lee, Young-Koo; Lee, Sungyoung

    2013-01-01

    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. PMID:23435057

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

    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.

  12. Prediction-Market-Based Quantification of Climate Change Consensus and Uncertainty

    Boslough, M.

    2012-12-01

    Intrade is an online trading exchange that includes climate prediction markets. One such family of contracts can be described as "Global temperature anomaly for 2012 to be greater than x °C or more," where the figure x ranges in increments of .05 from .30 to 1.10 (relative to the 1951-1980 base period), based on data published by NASA GISS. Each market will settle at 10.00 if the published global temperature anomaly for 2012 is equal to or greater than x, and will otherwise settle at 0.00. Similar contracts will be available for 2013. Global warming hypotheses can be cast as probabilistic predictions for future temperatures. The first modern such climate prediction is that of Broecker (1975), whose temperatures are easily separable from his CO2 growth scenario—which he overestimated—by interpolating his table of temperature as a function of CO2 concentration and projecting the current trend into the near future. For the current concentration of 395 ppm, Broecker's equilibrium temperature anomaly prediction relative to pre-industrial is 1.05 °C, or about 0.75 °C relative to the GISS base period. His neglect of lag in response to the changes in radiative forcing was partially compensated by his low sensitivity of 2.4 °C, leading to a slight overestimate. Simple linear extrapolation of the current trend since 1975 yields an estimate of .65 ± .09 °C (net warming of .95 °C) for anthropogenic global warming with a normal distribution of random natural variability. To evaluate an extreme case, we can estimate the prediction Broecker would have made if he had used the Lindzen & Choi (2009) climate sensitivity of 0.5 °C. The net post-industrial warming by 2012 would have been 0.21 °C, for an expected change of -0.09 from the GISS base period. This is the temperature to which the Earth would be expected to revert if the observed warming since the 19th century was merely due to random natural variability that coincidentally mimicked Broecker's anthropogenic

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

    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.

  14. [Prediction of human orthostatic tolerance by changes in arterial and venous hemodynamics in the microgravity environment].

    Kotovskaia, A R; Fomin, G A

    2013-01-01

    The authors intentionally present exclusively the results of their recent studies of arterial and venous hemodynamics as predictors of human orthostatic tolerance (OT) during space flight and on return to Earth. There is a sufficient demonstration of the in-flight OT predictability by arterial hemodynamic reactions to LBNP and venous hemodynamic changes in response to the lower extremities occlusion. Three levels of cerebral blood flow deficits in the course of the lower body negative pressure test (LBNP) performed in microgravity were first defined. The authors offer quantitative arguments for the dependence of cerebral flow deficit on the degree of LBNP tolerance degradation. Patterns of arterial hemodynamics during LBNP were used successfully to diagnose the actual orthostatic tolerance and also to follow its trend as flight extended, which attests to the predictability of OT change in an individual cosmonaut on space flight. Occlusion plethysmography of legs revealed three levels of response of the most informative venous parameters (capacity, distensibility and rate of filling) correlating with severity of OT degradation. PMID:25509869

  15. Projected climate change impacts and short term predictions on staple crops in Sub-Saharan Africa

    Mereu, V.; Spano, D.; Gallo, A.; Carboni, G.

    2013-12-01

    . Multiple combinations of soils and climate conditions, crop management and varieties were considered for the different Agro-Ecological Zones. The climate impact was assessed using future climate prediction, statistically and/or dynamically downscaled, for specific areas. Direct and indirect effects of different CO2 concentrations projected for the future periods were separately explored to estimate their effects on crops. Several adaptation strategies (e.g., introduction of full irrigation, shift of the ordinary sowing/planting date, changes in the ordinary fertilization management) were also evaluated with the aim to reduce the negative impact of climate change on crop production. The results of the study, analyzed at local, AEZ and country level, will be discussed.

  16. A simple water-energy balance framework to predict the sensitivity of streamflow to climate change

    M. Renner

    2011-09-01

    Full Text Available Long term average change in streamflow is a major concern in hydrology and water resources management. Some simple analytical methods exist for the assessment of the sensitivity of streamflow to climatic variations. These are based on the Budyko hypothesis, which assumes that long term average streamflow can be predicted by climate conditions, namely by annual average precipitation and evaporative demand. Recently, Tomer and Schilling (2009 presented an ecohydrological concept to distinguish between effects of climate change and basin characteristics change on streamflow. We provide a theoretical foundation of this concept by showing that it is based on a coupled consideration of the water and energy balance. The concept uses a special condition that the sum of the ratio of annual actual evapotranspiration to precipitation and the ratio of actual to potential evapotranspiration is constant, even when climate conditions are changing.

    Here we apply this assumption and derive analytical solutions to the problem of streamflow sensitivity on climate. We show how climate sensitivity is influenced by different climatic conditions and the actual hydrological response of a basin. Finally, the properties and implications of the new method are compared with established Budyko sensitivity methods.

  17. Predicting impacts of climate change on habitat connectivity of Kalopanax septemlobus in South Korea

    Kang, Wanmo; Minor, Emily S.; Lee, Dowon; Park, Chan-Ryul

    2016-02-01

    Understanding the drivers of habitat distribution patterns and assessing habitat connectivity are crucial for conservation in the face of climate change. In this study, we examined a sparsely distributed tree species, Kalopanax septemlobus (Araliaceae), which has been heavily disturbed by human use in temperate forests of South Korea. We used maximum entropy distribution modeling (MaxEnt) to identify the climatic and topographic factors driving the distribution of the species. Then, we constructed habitat models under current and projected climate conditions for the year 2050 and evaluated changes in the extent and connectivity of the K. septemlobus habitat. Annual mean temperature and terrain slope were the two most important predictors of species distribution. Our models predicted the range shift of K. septemlobus toward higher elevations under medium-low and high emissions scenarios for 2050, with dramatic reductions in suitable habitat (51% and 85%, respectively). In addition, connectivity analysis indicated that climate change is expected to reduce future levels of habitat connectivity. Even under the Representative Construction Pathway (RCP) 4.5 medium-low warming scenario, the projected climate conditions will decrease habitat connectivity by 78%. Overall, suitable habitats for K. septemlobus populations will likely become more isolated depending on the severity of global warming. The approach presented here can be used to efficiently assess species and habitat vulnerability to climate change.

  18. Informatic prediction of Cheddar cheese flavor pathway changes due to sodium substitution.

    Ganesan, Balasubramanian; Brown, Kelly

    2014-01-01

    Increased interest in reduced and low sodium dairy foods generates flavor issues for cheeses. Sodium is partly replaced with potassium or calcium to sustain the salty flavor perception, but the other cations may also alter metabolic routes and the resulting flavor development in aged cheeses. The effect of some cations on selected metabolic enzyme activity and on lactic acid bacterial physiology and enzymology has been documented. Potassium, for example, is an activator of 40 enzymes and inhibits 25 enzymes. Currently, we can visualize the effects of these cations only as lists inside metabolic databases such as MetaCyc. By visualizing the impact of these activating and inhibitory activities as biochemical pathways inside a metabolic database, we can understand their relevance, predict, and eventually dictate the aging process of cheeses with cations that replace sodium. As examples, we reconstructed new metabolic databases that illustrate the effect of potassium on flavor-related enzymes as microbial pathways. After metabolic reconstruction and analysis, we found that 153 pathways of lactic acid bacteria are affected due to enzymes likely to be activated or inactivated by potassium. These pathways are primarily linked to sugar metabolism, acid production, and amino acid biosynthesis and degradation that relate to Cheddar cheese flavor. PMID:24246043

  19. The sensitivity of global ozone predictions to dry deposition schemes and their response to climate change

    Centoni, Federico; Stevenson, David; Fowler, David; Nemitz, Eiko; Coyle, Mhairi

    2015-04-01

    Concentrations of ozone at the surface are strongly affected by deposition to the surface. Deposition processes are very sensitive to temperature and relative humidity at the surface and are expected to respond to global change, with implications for both air quality and ecosystem services. Many studies have shown that ozone stomatal uptake by vegetation typically accounts for 40-60% of total deposition on average and the other part which occurs through non-stomatal pathways is not constant. Flux measurements show that non-stomatal removal increases with temperature and under wet conditions. There are large uncertainties in parameterising the non-stomatal ozone deposition term in climate chemistry models and model predictions vary greatly. In addition, different model treatments of dry deposition constitute a source of inter-model variability in surface ozone predictions. The main features of the original Unified Model-UK Chemistry and Aerosols (UM-UKCA) dry deposition scheme and the Zhang et al. 2003 scheme, which introduces in UM-UKCA a more developed non-stomatal deposition approach, are presented. This study also estimates the relative contributions of ozone flux via stomatal and non-stomatal uptakes at the global scale, and explores the sensitivity of simulated surface ozone and ozone deposition flux by implementing different non-stomatal parameterization terms. With a view to exploring the potential influence of future climate, we present results showing the effects of variations in some meteorological parameters on present day (2000) global ozone predictions. In particular, this study revealed that the implementation of a more mechanistic representation of the non-stomatal deposition in UM-UKCA model along with a decreased stomatal uptake due to the effect of blocking under wet conditions, accounted for a substantial reduction of ozone fluxes to broadleaf trees in the tropics with an increase of annual mean surface ozone. On the contrary, a large increase of

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

    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

  1. The Arctic Boreal Vulnerability Experiment: Observing, Understanding, and Predicting Social-Ecological Change in the Far North

    Mack, M. C.; Goetz, S. J.; Kasischke, E. S.; Kimball, J. S.; Boelman, N.

    2015-12-01

    In the high northern latitudes, climate is warming more rapidly than anywhere else on Earth, transforming vulnerable arctic tundra and boreal forest landscapes. These changes are altering the structure and function of energy, water and carbon cycles, producing significant feedbacks to regional and global climate through changes in energy, water and carbon cycles. These changes are also challenging local and global society. At the local level, communities seek to adapt to new social-ecological regimes. At the global level, changing arctic and boreal systems are increasing becoming the focus of policy discussions at all levels of decision-making. National and international scientific efforts associated with a new NASA field campaign, the Arctic-Boreal Vulnerability Experiment (ABOVE) will advance our ability to observe, understand and predict the complex, multiscale and non-linear processes that are confronting the natural and social systems in this rapidly changing region. Over the next decade, the newly assembled ABOVE Science Team will pursue this overarching question: "How vulnerable or resilient are ecosystems and society to environmental change in the Arctic and boreal region of western North America?" Through integration of remote sensing and in situ observations with modeling of both ecological and social systems, the ABOVE Science Team will advance an interdisciplinary understanding of the Far North. In this presentation, we will discuss the conceptual basis for the ABOVE Field Campaign, describe Science Team composition and timeline, and update the community on activities. In addition, we will reflect on the visionary role of Dr. Diane Wickland, retired NASA Terrestrial Ecology Program Manager and lead of the Carbon Cycle & Ecosystems Focus Area, in the development and commencement of ABOVE.

  2. Changes in external conditions and activity in the petroleum industry

    Tax reductions in the petroleum industry are conductive to increased activity and makes the respective provinces more attractive for investments compared with other regions. Changes in taxation in Great Britain and the Gulf of Mexico, which has been analyzed by ECON, show that reducing taxes on gross income has rendered marginal investments more profitable and that reducing the tax on profits may have advanced investments and cut the costs. The examples also show that it is possible to protect the public tax revenue under taxation rearrangements by essentially limiting the tax reductions to new activities

  3. Early hematologic changes during prostate cancer radiotherapy predictive for late urinary and bowel toxicity

    Pinkawa, Michael; Djukic, Victoria; Klotz, Jens; Holy, Richard; Eble, Michael J. [RWTH Aachen University, Department of Radiation Oncology, Aachen (Germany); Ribbing, Carolina [RWTH Aachen University, Department of Diagnostic and Interventional Radiology, Aachen (Germany)

    2015-10-15

    The primary objective of the study was to identify early hematologic changes predictive for radiotherapy (RT)-associated genitourinary and gastrointestinal toxicity. In a group of 91 prostate cancer patients presenting for primary (n = 51) or postoperative (n = 40) curative RT, blood samples (blood count, acute phase proteins, and cytokines) were analyzed before (T1), three times during (T2-T4), and 6-8 weeks after (T5) radiotherapy. Before RT (baseline), on the last day (acute toxicity), a median of 2 months and 16 months (late toxicity) after RT, patients responded to a validated questionnaire (Expanded Prostate Cancer Index Composite). Acute score changes > 20 points and late changes > 10 points were considered clinically relevant. Radiotherapy resulted in significant changes of hematologic parameters, with the largest effect on lymphocytes (mean decrease of 31-45 %) and significant dependence on target volume. C-reactive protein (CRP) elevation > 5 mg/l and hemoglobin level decrease ≥ 5 G/1 at T2 were found to be independently predictive for acute urinary toxicity (p < 0.01, respectively). CRP elevation was predominantly detected in primary prostate RT (p = 0.02). Early lymphocyte level elevation ≥ 0.3G/l at T2 was protective against late urinary and bowel toxicity (p = 0.02, respectively). Other significant predictive factors for late bowel toxicity were decreasing hemoglobin levels (cut-off ≥ 5 G/l) at T2 (p = 0.04); changes of TNF-α (tumor necrosis factor; p = 0.03) and ferritin levels (p = 0.02) at T5. All patients with late bowel toxicity had interleukin (IL)-6 levels < 1.5 ng/l at T2 (63 % without; p = 0.01). Early hematologic changes during prostate cancer radiotherapy are predictive for late urinary and bowel toxicity. (orig.) [German] Das primaere Ziel der Studie war die Identifikation von fruehen haematologischen Veraenderungen mit praediktiver Bedeutung fuer radiotherapieassoziierte genitourinale und gastrointestinale Toxizitaet. In einer

  4. New active drugs against liver stages of Plasmodium predicted by molecular topology.

    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 we

  5. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

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

    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.…

  7. Predictions of Flow Duration Curve Shifts Due to Anthropogenic and Climatic Changes

    Henry, N. F.; Kroll, C. N.; Endreny, T. A.

    2014-12-01

    Methods are needed to understand and predict streamflows in systems undergoing anthropogenic and climatic alteration. This study is motivated by a need to develop methods to accurately estimate historical and future flow regimes of the Delaware River to inform management decisions for the endangered dwarf wedgemussel (Alasmidonta heterodon). Many streamflow regimes in this system have undergone substantial alteration within the past 100 years. Here, flow duration curves (FDCs), a common hydrologic tool used to assess flow regimes, are created and examined at 145 Delaware River Basin catchments. These catchments have experienced various hydrologic alterations, including land use changes, water withdrawals, and river regulation due to dams and reservoirs. Linear regression models are developed for various percentile flows across a FDC. These models use watershed characteristics that describe observed flow regimes in altered as well as unaltered systems. The characteristics that have the most significant influence on the shape of the FDCs are then identified and isolated as descriptors of the alteration. Once these models are developed to include these key variables, given a specific alteration (e.g. fresh water withdrawals, change in annual precipitation, etc.), a new flow regime can be estimated. Preliminary results indicate that certain watershed characteristics related to alteration (e.g. magnitude of land fragmentation, water withdrawals, hydrologic disturbance index) are significant in our models and influence FDC patterns. The results of this study may prove to have broader applications in regards to water resources management as the methods developed here may serve as a predictive tool as human interference and climatic changes continue to alter flow regimes.

  8. Endosulfan induces changes in spontaneous swimming activity and acetylcholinesterase activity of Jenynsia multidentata (Anablepidae, Cyprinodontiformes)

    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.

  9. Endosulfan induces changes in spontaneous swimming activity and acetylcholinesterase activity of Jenynsia multidentata (Anablepidae, Cyprinodontiformes)

    We assessed changes in spontaneous swimming activity and acetylcholinesterase (AchE) activity of Jenynsia multidentata exposed to Endosulfan (EDS). Females of J. multidentata were exposed to 0.072 and 1.4 μg L-1 EDS. Average speed and movement percentage were recorded during 48 h. We also exposed females to EDS at five concentrations between 0.072 and 1.4 μg L-1 during 24 h, and measured the AchE activity in brain and muscle. At 0.072 μg L-1 EDS swimming motility decreased relative to the control group after 45 h, while at 1.4 μg L-1 EDS swimming motility decreased after 24 h. AchE activity significantly decreased in muscle when J. multidentata were exposed to EDS above 0.072 μg L-1, while no significant changes were observed in brain. Thus, changes in swimming activity and AchE activity in muscle are good biomarkers of exposure to EDS in J. multidentata. - This work reports changes observed in spontaneous swimming activity and AchE activity of Jenynsia multidentata exposed to sublethal concentrations of Endosulfan.

  10. Uncertainty of climate change impacts and consequences on the prediction of future hydrological trends

    In the future, water is very likely to be the resource that will be most severely affected by climate change. It has been shown that small perturbations in precipitation frequency and/or quantity can result in significant impacts on the mean annual discharge. Moreover, modest changes in natural inflows result in larger changes in reservoir storage. There is however great uncertainty linked to changes in both the magnitude and direction of future hydrological trends. This presentation discusses the various sources of this uncertainty and their potential impact on the prediction of future hydrological trends. A companion paper will look at adaptation potential, taking into account some of the sources of uncertainty discussed in this presentation. Uncertainty is separated into two main components: climatic uncertainty and 'model and methods' uncertainty. Climatic uncertainty is linked to uncertainty in future greenhouse gas emission scenarios (GHGES) and to general circulation models (GCMs), whose representation of topography and climate processes is imperfect, in large part due to computational limitations. The uncertainty linked to natural variability (which may or may not increase) is also part of the climatic uncertainty. 'Model and methods' uncertainty regroups the uncertainty linked to the different approaches and models needed to transform climate data so that they can be used by hydrological models (such as downscaling methods) and the uncertainty of the models themselves and of their use in a changed climate. The impacts of the various sources of uncertainty on the hydrology of a watershed are demonstrated on the Peribonka River basin (Quebec, Canada). The results indicate that all sources of uncertainty can be important and outline the importance of taking these sources into account for any impact and adaptation studies. Recommendations are outlined for such studies. (author)

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

    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

  12. Predicting climate change effects on surface soil organic carbon of Louisiana, USA.

    Zhong, Biao; Xu, Yi Jun

    2014-10-01

    This study aimed to assess the degree of potential temperature and precipitation change as predicted by the HadCM3 (Hadley Centre Coupled Model, version 3) climate model for Louisiana, and to investigate the effects of potential climate change on surface soil organic carbon (SOC) across Louisiana using the Rothamsted Carbon Model (RothC) and GIS techniques at the watershed scale. Climate data sets at a grid cell of 0.5° × 0.5° for the entire state of Louisiana were collected from the HadCM3 model output for three climate change scenarios: B2, A2, and A1F1, that represent low, higher, and even higher greenhouse gas emissions, respectively. Geo-referenced datasets including USDA-NRCS Soil Geographic Database (STATSGO), USGS Land Cover Dataset (NLCD), and the Louisiana watershed boundary data were gathered for SOC calculation at the watershed scale. A soil carbon turnover model, RothC, was used to simulate monthly changes in SOC from 2001 to 2100 under the projected temperature and precipitation changes. The simulated SOC changes in 253 watersheds from three time periods, 2001-2010, 2041-2050, and 2091-2100, were tested for the influence of the land covers and emissions scenarios using SAS PROC GLIMMIX and PDMIX800 macro to separate Tukey-Kramer (p forest soils will decrease from 33.0 t/ha in 2001 to 26.9, 28.4, and 29.2 t/ha in 2100, respectively; the mean SOC of Louisiana cropland soils will decrease from 44.4 t/ha in 2001 to 36.3, 38.4, and 39.6 t/ha in 2100, respectively; the mean SOC of Louisiana grassland soils will change from 30.7 t/ha in 2001 to 25.4, 26.6, and 27.0 t/ha in 2100, respectively. Annual SOC changes will be significantly different among the land cover classes including evergreen forest, mixed forest, deciduous forest, small grains, row crops, and pasture/hay (p < 0.0001), emissions scenarios (p < 0.0001), and their interactions (p < 0.0001). PMID:24917151

  13. Evolution of alternative splicing regulation: changes in predicted exonic splicing regulators are not associated with changes in alternative splicing levels in primates

    Irimia, Manuel; Rukov, Jakob Lewin; Roy, Scott William

    2009-01-01

    interspecific differences in these elements on the evolution of alternative splicing levels has not yet been investigated at genomic level. Here we study the effect of interspecific differences in predicted exonic splicing regulators (ESRs) on exon inclusion levels in human and chimpanzee. For this purpose, we...... compiled and studied comprehensive datasets of predicted ESRs, identified by several computational and experimental approaches, as well as microarray data for changes in alternative splicing levels between human and chimpanzee. Surprisingly, we found no association between changes in predicted ESRs and...... or no effect on splicing, and thus interspecific changes at short-time scales may primarily occur in these effectively neutral ESRs. These results underscore the difficulties of using current computational ESR prediction algorithms to identify truly functionally important motifs, and provide a...

  14. Modeling Spatial Recharge in the Arid Southern Okanagan Basin and Impacts of Future Predicted Climate Change

    Allen, D. M.; Toews, M. W.

    2007-12-01

    Groundwater systems in arid regions will be particularly sensitive to climate change owing to the strong dependence of evapotranspiration rates on temperature, and potential shifts in the precipitation amounts and timing. In this study, future predicted climate change from three GCMs (CGCM1 GHG+A, CGCM3.1 A2, and HadCM3 A2) are used to evaluate the sensitivity of recharge in the Oliver region of the Okanagan Valley, south- central British Columbia, where annual precipitation is approximately 300~mm. Temperature data were downscaled using Statistical Downscaling Model (SDSM), while precipitation and solar radiation changes were estimated directly from the GCM data. Results for the region suggest that temperature will increase up to 4°C by the end of the century. Precipitation is expected to decrease in the spring, and increase in the fall. Solar radiation may decrease in the late summer. Shifts in climate, from present to future-predicted, were applied to the LARS-WG stochastic weather generator to generate daily stochastic weather series. Recharge was modeled spatially using output from the HELP hydrologic model applied to one-dimensional soil columns. An extensive valley-bottom soil database was used to determine both the spatial variation and vertical assemblage of soil horizons in the Oliver region. Soil hydraulic parameters were estimated from soil descriptions using pedotransfer functions through the ROSETTA program. Leaf area index (LAI) was estimated from ground-truthed Landsat 5 TM imagery, and surface slope was estimated from a digital elevation model. Irrigation application rates were modified for each climate scenario based on estimates of seasonal crop water demand. Daily irrigation was added to precipitation in irrigation districts using proportions of crop types along with daily climate and evapotranspiration data from LARS-WG. The two dominant crop classes are orchard (including peaches, cherries and apples) and vineyards (grapes). Recharge in

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

    Sungyoung Lee; Iram Fatima; Young-Koo Lee; Muhammad Fahim

    2013-01-01

    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 t...

  16. Structure-Functional Study of Tyrosine and Methionine Dipeptides: An Approach to Antioxidant Activity Prediction

    Anna Torkova; Olga Koroleva; Ekaterina Khrameeva; Tatyana Fedorova; Mikhail Tsentalovich

    2015-01-01

    Quantum chemical methods allow screening and prediction of peptide antioxidant activity on the basis of known experimental data. It can be used to design the selective proteolysis of protein sources in order to obtain products with antioxidant activity. Molecular geometry and electronic descriptors of redox-active amino acids, as well as tyrosine and methionine-containing dipeptides, were studied by Density Functional Theory method. The calculated data was used to reveal several descriptors r...

  17. Multiple and changing cycles of active stars II. Results

    Oláh, K; Granzer, T; Strassmeier, K G; Lanza, A F; Järvinen, S; Korhonen, H; Baliunas, S L; Soon, W; Messina, S; Cutispoto, G

    2009-01-01

    We study the time variations of the cycles of 20 active stars based on decades-long photometric or spectroscopic observations. A method of time-frequency analysis, as discussed in a companion paper, is applied to the data. Fifteen stars definitely show multiple cycles; the records of the rest are too short to verify a timescale for a second cycle. The cycles typically show systematic changes. For three stars, we found two cycles in each of them that are not harmonics, and which vary in parallel, indicating that a common physical mechanism arising from a dynamo construct. The positive relation between the rotational and cycle periods is confirmed for the inhomogeneous set of active stars. Stellar activity cycles are generally multiple and variable.

  18. Describing Changes in Undergraduate Students' Preconceptions of Research Activities

    Cartrette, David P.; Melroe-Lehrman, Bethany M.

    2012-12-01

    Research has shown that students bring naïve scientific conceptions to learning situations which are often incongruous with accepted scientific explanations. These preconceptions are frequently determined to be misconceptions; consequentially instructors spend time to remedy these beliefs and bring students' understanding of scientific concepts to acceptable levels. It is reasonable to assume that students also maintain preconceptions about the processes of authentic scientific research and its associated activities. This study describes the most commonly held preconceptions of authentic research activities among students with little or no previous research experience. Seventeen undergraduate science majors who participated in a ten week research program discussed, at various times during the program, their preconceptions of research and how these ideas changed as a result of direct participation in authentic research activities. The preconceptions included the belief that authentic research is a solitary activity which most closely resembles the type of activity associated with laboratory courses in the undergraduate curriculum. Participants' views showed slight maturation over the research program; they came to understand that authentic research is a detail-oriented activity which is rarely successfully completed alone. These findings and their implications for the teaching and research communities are discussed in the article.

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

    Mansfield, Theodore J; MacDonald Gibson, Jacqueline

    2015-01-01

    Recently, two quantitative tools have emerged for predicting the health impacts of projects that change population physical activity: the Health Economic Assessment Tool (HEAT) and Dynamic Modeling for Health Impact Assessment (DYNAMO-HIA). HEAT has been used to support health impact assessments of transportation infrastructure projects, but DYNAMO-HIA has not been previously employed for this purpose nor have the two tools been compared. To demonstrate the use of DYNAMO-HIA for supporting health impact assessments of transportation infrastructure projects, we employed the model in three communities (urban, suburban, and rural) in North Carolina. We also compared DYNAMO-HIA and HEAT predictions in the urban community. Using DYNAMO-HIA, we estimated benefit-cost ratios of 20.2 (95% C.I.: 8.7-30.6), 0.6 (0.3-0.9), and 4.7 (2.1-7.1) for the urban, suburban, and rural projects, respectively. For a 40-year time period, the HEAT predictions of deaths avoided by the urban infrastructure project were three times as high as DYNAMO-HIA's predictions due to HEAT's inability to account for changing population health characteristics over time. Quantitative health impact assessment coupled with economic valuation is a powerful tool for integrating health considerations into transportation decision-making. However, to avoid overestimating benefits, such quantitative HIAs should use dynamic, rather than static, approaches. PMID:26504832

  20. Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data

    Mestyán, Márton; Kertész, János

    2012-01-01

    Use of socially generated "big data" to access information about collective states of the minds in human societies becomes a new paradigm in the emerging field of computational social science. One of the natural application of this would be prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging between "real time monitoring" and "early predicting" remains as a big challenge. Here, we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie could be predicted well in advance by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.

  1. Human activities and climate and environment changes: an inevitable relation

    The human interference in the environment and the consequent climate change is today a consensus. The climate change can be local, regional and global. The global climate change is mainly caused by the greenhouse gases, and consequently the climate change intervenes in the environment. The interference cycle emerges in several forms and results in several consequences. However, the Global Warming has certainly the most import global impact. The main cause of the increase in the temperature (Greenhouse Effect) is the intensive use of the fossil fuels. Thus, to minimize the climatic changes actions are necessary to reduce, to substitute and to use with more efficient the fossil fuels. Looking at the past, the old agriculturists may have released greenhouse gases since thousand years ago, thus, modifying slowly but in significant form the earth climate much before the Industrial Age. If this theory is confirmed, its consequences would be decisive for the man history in the planet. For example, in parts of the North America and Europe the current temperatures could be even four Celsius degrees smaller. This change in temperature is enough to hinder agricultural used of these regions and consequently to diminish the human development. The main focus of this work is to perform a retrospective in some of civilizations who collapse due to environmental problems and make a historical description of the human activities (agriculture and livestock) since the primordium of the man up to the Industrial Age, aiming at the man interference on the natural dynamics of the global climate and the environment. This work will show through data comparisons and inferences that the gases emissions from these activities had a significant magnitude comparatively by the emissions after the Industrial Age. It is also demonstrated that the climate and environment interference was inevitable because the human evolution was caused by these activities. Another important point of this work is to

  2. Parent weight change predicts child weight change in family-based weight control program for pre-school children (Buffalo healthy tots)

    Title: PARENT WEIGHT CHANGE PREDICTS CHILD WEIGHT CHANGE IN FAMILY-BASED WEIGHT CONTROL PROGRAM FOR PRE-SCHOOL CHILDREN (BUFFALO HEALTHY TOTS), Teresa Quattrin, MOl, James N Roemmich, PhDI, Rocco Paluch, MAl, Jihnhee Yu, PhD2, Leonard H Epstein, PhDI and Michelle A Ecker, RD, CDEI . lpediatrics, Uni...

  3. A Predictive Model of Daily Seismic Activity Induced by Mining, Developed with Data Mining Methods

    Jakubowski, Jacek

    2014-12-01

    The article presents the development and evaluation of a predictive classification model of daily seismic energy emissions induced by longwall mining in sector XVI of the Piast coal mine in Poland. The model uses data on tremor energy, basic characteristics of the longwall face and mined output in this sector over the period from July 1987 to March 2011. The predicted binary variable is the occurrence of a daily sum of tremor seismic energies in a longwall that is greater than or equal to the threshold value of 105 J. Three data mining analytical methods were applied: logistic regression,neural networks, and stochastic gradient boosted trees. The boosted trees model was chosen as the best for the purposes of the prediction. The validation sample results showed its good predictive capability, taking the complex nature of the phenomenon into account. This may indicate the applied model's suitability for a sequential, short-term prediction of mining induced seismic activity.

  4. Experience-based auditory predictions modulate brain activity to silence as do real sounds

    Chouiter, Leila; Tzovara, Athina; Dieguez, Sebastian; Annoni, Jean-Marie; Magezi, David; De Lucia, Marzia; Spierer, Lucas

    2016-01-01

    Interactions between stimuli's acoustic features and experience-based internal models of the environment enable listeners to compensate for the disruptions in auditory streams that are regularly encountered in noisy environments. However, whether auditory gaps are filled in predictively or restored a posteriori remains unclear. The current lack of positive statistical evidence that internal models can actually shape brain activity as would real sounds precludes accepting predictive accou...

  5. PREDICTION OF BIOLOGICAL ACTIVITY SPECTRA FOR SECONDARY METABOLITES FROM MARINE MACROALGAE CAULERPA SPP (CHLOROPHYTA – CAULERPALS

    R. Azhaguraj

    2012-05-01

    Full Text Available This study aims to evaluate the biological activity of Caulerpin β-Sitosterol, Taraxerol and Palmtic acid isolated from the marine macro algae Caulerpa spp. The PASS computer program was used in this study to predict the biological activity profile of the four Phenazine derivates. The results were analyzed to show various biological activities like pharmacological (Kinase inhibitor, Neuroprotector and Antiviral, Effects (Oxidoreductase inhibitor, Acid Phosphatase inhibitor and toxicological activity (Teratogen of these compounds. The PASS software is useful for the study of biological activity of secondary metabolites.

  6. Prediction of ROA and ECD Related to Conformational Changes of Astaxanthin Enantiomers.

    Zajac, Grzegorz; Kaczor, Agnieszka; Buda, Szymon; Młynarski, Jacek; Frelek, Jadwiga; Dobrowolski, Jan Cz; Baranska, Małgorzata

    2015-09-17

    ECD, ROA, and VCD were used to characterize astaxanthin conformers that differ in their arrangements of the β-ionone ring in respect to the chain. We obtained ECD spectra experimentally, and the ECD, ROA, and VCD spectra of both individual conformers and conformation-averaged mixtures were predicted using quantum-chemical calculations at the CAM-B3LYP level of theory using the PCM solvation model. The chiroptical methods employed (particularly ECD and ROA) were considerably more sensitive to conformational changes of astaxanthin compared to "mono-signed" conventional Raman spectroscopy. Strikingly, conformers that are the same optical isomers (e.g., of 3S,3'S-astxanthin), while geometrically nearly mirror images, exhibited sign-inversed ECD and ROA spectra. The conformational sensitivity of these chiroptical methods makes them a promising tool in the study of carotenoids in the natural environment (for instance, in de novo algal or yeast astaxanthin sources). PMID:26305416

  7. Overgeneral autobiographical memory predicts changes in depression in a community sample.

    Van Daele, Tom; Griffith, James W; Van den Bergh, Omer; Hermans, Dirk

    2014-01-01

    This study investigated whether overgeneral autobiographical memory (OGM) predicts the course of symptoms of depression and anxiety in a community sample, after 5, 6, 12 and 18 months. Participants (N=156) completed the Autobiographical Memory Test and the Depression Anxiety Stress Scales-21 (DASS-21) at baseline and were subsequently reassessed using the DASS-21 at four time points over a period of 18 months. Using latent growth curve modelling, we found that OGM was associated with a linear increase in depression. We were unable to detect changes over time in anxiety. OGM may be an important marker to identify people at risk for depression in the future, but more research is needed with anxiety. PMID:24467645

  8. Hemodynamic Changes during a Deep Inspiration Maneuver Predict Fluid Responsiveness in Spontaneously Breathing Patients

    Sébastien Préau

    2012-01-01

    Full Text Available Objective. We hypothesized that the hemodynamic response to a deep inspiration maneuver (DIM indicates fluid responsiveness in spontaneously breathing (SB patients. Design. Prospective study. Setting. ICU of a general hospital. Patients. Consecutive nonintubated patients without mechanical ventilation, considered for volume expansion (VE. Intervention. We assessed hemodynamic status at baseline and after VE. Measurements and Main Results. We measured radial pulse pressure (PP using an arterial catheter and peak velocity of femoral artery flow (VF using continuous Doppler. Changes in PP and VF induced by a DIM (ΔPPdim and ΔVFdim were calculated in 23 patients. ΔPPdim and ΔVFdim ≥12% predicted responders to VE with sensitivity of 90% and specificity of 100%. Conclusions. In a restricted population of SB patients with severe sepsis or acute pancreatitis, ΔPPdim and ΔVFdim are accurate indices for predicting fluid responsiveness. These results should be confirmed in a larger population before validating their use in current practice.

  9. Comparison between measured and predicted resting metabolic rate in moderately active adolescents.

    De Lorenzo A; Bertini, I; Puijia, A; Testolin, G; Testolin, C

    1999-09-01

    The aim of this study was to check the validity of predictive equations for the calculation of resting metabolic rate (RMR) in moderately active adolescents. The RMR was measured in a sample of 25 healthy 15.5-18.2-year-old boys practicing soccer. The RMR was assessed by indirect calorimetry for 30 min following an overnight fast. Body composition was estimated from skinfold thickness measurements. Among the available equations to predict RMR, we decided to use those a of Molnar et al., Harris-Benedict, Schofield, and Cunningham. Measured and predicted values were compared by means of a one-way ANOVA. Also the Bland-Altman test was performed in order to evaluate the accuracy of the prediction equations compared to the measured value. The measured RMR was found to be 1834 +/- 160 kcal/day (mean +/- SD), while the Molnar et al., Schofield, Harris-Benedict, and Cunningham predicted values were 1707 +/- 78, 1866 +/- 89, 1779 +/- 84 and 1830 +/- 87 kcal/day, respectively. On average, compared to the measured values only the Molnar et al. equation differed significantly. On an individual basis, all the equations demonstrated considerable variability between measured and predicted RMRs. The predicted values also differed significantly. As regards the moderately active subjects (16-18 years old), we recommend the use of the Schofield equation, based on simple anthropometric parameters and also that of Cunningham, even if the estimation or measurement of fat-free mass may be cumbersome for everyday pediatric use. PMID:10664318

  10. Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

    Thompson, S. E.; Sivapalan, M.; Harman, C. J.; Srinivasan, V.; Hipsey, M. R.; Reed, P.; Montanari, A.; Blöschl, G.

    2013-12-01

    Globally, many different kinds of water resources management issues call for policy- and infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal- to century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle - a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges from the perspectives of hydrologic science research. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management. Fully realizing the potential of this approach will ultimately require detailed integration of social science and physical science

  11. Latitudinal Variation in Carbon Storage Can Help Predict Changes in Swamps Affected by Global Warming

    Middleton, Beth A.; McKee, Karen

    2004-01-01

    Plants may offer our best hope of removing greenhouse gases (gases that contribute to global warming) emitted to the atmosphere from the burning of fossil fuels. At the same time, global warming could change environments so that natural plant communities will either need to shift into cooler climate zones, or become extirpated (Prasad and Iverson, 1999; Crumpacker and others, 2001; Davis and Shaw, 2001). It is impossible to know the future, but studies combining field observation of production and modeling can help us make predictions about what may happen to these wetland communities in the future. Widespread wetland types such as baldcypress (Taxodium distichum) swamps in the southeastern portion of the United States could be especially good at carbon sequestration (amount of CO2 stored by forests) from the atmosphere. They have high levels of production and sometimes store undecomposed dead plant material in wet conditions with low oxygen, thus keeping gases stored that would otherwise be released into the atmosphere (fig. 1). To study the ability of baldcypress swamps to store carbon, our project has taken two approaches. The first analysis looked at published data to develop an idea (hypothesis) of how production levels change across a temperature gradient in the baldcypress region (published data study). The second study tested this idea by comparing production levels across a latitudinal range by using swamps in similar field conditions (ongoing carbon storage study). These studies will help us make predictions about the future ability of baldcypress swamps to store carbon in soil and plant biomass, as well as the ability of these forests to shift northward with global warming.

  12. Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

    S. E. Thompson

    2013-06-01

    Full Text Available Globally, many different kinds of water resources management issues call for policy and infrastructure based responses. Yet responsible decision making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal-to-century long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle – a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management.

  13. Functional trade-offs in succulent stems predict responses to climate change in columnar cacti.

    Williams, David G; Hultine, Kevin R; Dettman, David L

    2014-07-01

    Columnar cacti occur naturally in many habitats and environments in the Americas but are conspicuously dominant in very dry desert regions. These majestic plants are widely regarded for their cultural, economic, and ecological value and, in many ecosystems, support highly diverse communities of pollinators, seed dispersers, and frugivores. Massive amounts of water and other resources stored in the succulent photosynthetic stems of these species confer a remarkable ability to grow and reproduce during intensely hot and dry periods. Yet many columnar cacti are potentially under severe threat from environmental global changes, including climate change and loss of habitat. Stems in columnar cacti and other cylindrical-stemmed cacti are morphologically diverse; stem volume-to-surface area ratio (V:S) across these taxa varies by almost two orders of magnitude. Intrinsic functional trade-offs are examined here across a broad range of V:S in species of columnar cacti. It is proposed that variation in photosynthetic gas exchange, growth, and response to stress is highly constrained by stem V:S, establishing a mechanistic framework for understanding the sensitivity of columnar cacti to climate change and drought. Specifically, species that develop stems with low V:S, and thus have little storage capacity, are expected to express high mass specific photosynthesis and growth rates under favourable conditions compared with species with high V:S. But the trade-off of having little storage capacity is that low V:S species are likely to be less tolerant of intense or long-duration drought compared with high V:S species. The application of stable isotope measurements of cactus spines as recorders of growth, water relations, and metabolic responses to the environment across species of columnar cacti that vary in V:S is also reviewed. Taken together, our approach provides a coherent theory and required set of observations needed for predicting the responses of columnar cacti to

  14. Evaluation of water-energy balance frameworks to predict the sensitivity of streamflow to climate change

    M. Renner

    2012-05-01

    Full Text Available Long term average change in streamflow is a major concern in hydrology and water resources management. Some simple analytical methods exist for the assessment of the sensitivity of streamflow to climatic variations. These are based on the Budyko hypothesis, which assumes that long term average streamflow can be predicted by climate conditions, namely by annual average precipitation and evaporative demand. Recently, Tomer and Schilling (2009 presented an ecohydrological concept to distinguish between effects of climate change and basin characteristics change on streamflow. We relate the concept to a coupled consideration of the water and energy balance. We show that the concept is equivalent to the assumption that the sum of the ratio of annual actual evapotranspiration to precipitation and the ratio of actual to potential evapotranspiration is constant, even when climate conditions are changing.

    Here, we use this assumption to derive analytical solutions to the problem of streamflow sensitivity to climate. We show how, according to this assumption, climate sensitivity would be influenced by different climatic conditions and the actual hydrological response of a basin. Finally, the properties and implications of the method are compared with established Budyko sensitivity methods and illustrated by three case studies. It appears that the largest differences between both approaches occur under limiting conditions. Specifically, the sensitivity framework based on the ecohydrological concept does not adhere to the water and energy limits, while the Budyko approach accounts for limiting conditions by increasing the sensitivity of streamflow to a catchment parameter encoding basin characteristics. Our findings do not support any application of the ecohydrological concept under conditions close to the water or energy limits, instead we suggest a correction based on the Budyko framework.

  15. Factors Predicting Behavioral Response to a Physical Activity Intervention among Adolescent Females

    Dunton, Genevieve Fridlund; Schneider, Margaret; Cooper, Dan M.

    2007-01-01

    Objective: To determine whether individual factors influenced rates of physical activity change in response to a school-based intervention. Methods: Sedentary adolescent females (N = 63) participated in a 9-month physical activity program. Weekly levels of leisure-time physical activity were reported using an interactive website. Results: Change…

  16. Changes in CVD risk factors in the activity counseling trial

    Meghan Baruth

    2011-01-01

    Full Text Available Meghan Baruth1, Sara Wilcox1, James F Sallis3, Abby C King4,5, Bess H Marcus6, Steven N Blair1,21Department of Exercise Science, 2Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Public Health Research Center, Columbia, SC, USA; 3Department of Psychology, San Diego State University, San Diego, CA, USA; 4Department of Health Research and Policy, 5Stanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA; 6Behavioral and Social Sciences Section, Brown University Program in Public Health, Providence, RI, USAAbstract: Primary care facilities may be a natural setting for delivering interventions that focus on behaviors that improve cardiovascular disease (CVD risk factors. The purpose of this study was to examine the 24-month effects of the Activity Counseling Trial (ACT on CVD risk factors, to examine whether changes in CVD risk factors differed according to baseline risk factor status, and to examine whether changes in fitness were associated with changes in CVD risk factors. ACT was a 24-month multicenter randomized controlled trial to increase physical activity. Participants were 874 inactive men and women aged 35–74 years. Participants were randomly assigned to one of three arms that varied by level of counseling, intensity, and resource requirements. Because there were no significant differences in change over time between arms on any of the CVD risk factors examined, all arms were combined, and the effects of time, independent of arm, were examined separately for men and women. Time × Baseline risk factor status interactions examined whether changes in CVD risk factors differed according to baseline risk factor status. Significant improvements in total cholesterol, high-density lipoprotein cholesterol (HDL-C and low-density lipoprotein cholesterol, the ratio of total cholesterol to HDL-C, and triglycerides were seen in

  17. Changes to coral health and metabolic activity under oxygen deprivation

    Richmond, Robert H.

    2016-01-01

    On Hawaiian reefs, the fast-growing, invasive algae Gracilaria salicornia overgrows coral heads, restricting water flow and light, thereby smothering corals. Field data shows hypoxic conditions (dissolved oxygen (DO2) bleaching and partial tissue loss of shaded corals. To analyze the impact of nighttime oxygen-deprivation on coral health, this study evaluated changes in coral metabolism through the exposure of corals to chronic hypoxic conditions and subsequent analyses of lactate, octopine, alanopine, and strombine dehydrogenase activities, critical enzymes employed through anaerobic respiration. Following treatments, lactate and octopine dehydrogenase activities were found to have no significant response in activities with treatment and time. However, corals subjected to chronic nighttime hypoxia were found to exhibit significant increases in alanopine dehydrogenase activity after three days of exposure and strombine dehydrogenase activity starting after one overnight exposure cycle. These findings provide new insights into coral metabolic shifts in extremely low-oxygen environments and point to ADH and SDH assays as tools for quantifying the impact of hypoxia on coral health. PMID:27114888

  18. Changes to coral health and metabolic activity under oxygen deprivation.

    Murphy, James W A; Richmond, Robert H

    2016-01-01

    On Hawaiian reefs, the fast-growing, invasive algae Gracilaria salicornia overgrows coral heads, restricting water flow and light, thereby smothering corals. Field data shows hypoxic conditions (dissolved oxygen (DO2) bleaching and partial tissue loss of shaded corals. To analyze the impact of nighttime oxygen-deprivation on coral health, this study evaluated changes in coral metabolism through the exposure of corals to chronic hypoxic conditions and subsequent analyses of lactate, octopine, alanopine, and strombine dehydrogenase activities, critical enzymes employed through anaerobic respiration. Following treatments, lactate and octopine dehydrogenase activities were found to have no significant response in activities with treatment and time. However, corals subjected to chronic nighttime hypoxia were found to exhibit significant increases in alanopine dehydrogenase activity after three days of exposure and strombine dehydrogenase activity starting after one overnight exposure cycle. These findings provide new insights into coral metabolic shifts in extremely low-oxygen environments and point to ADH and SDH assays as tools for quantifying the impact of hypoxia on coral health. PMID:27114888

  19. Changes of spontaneous oscillatory activity to tonic heat pain.

    Weiwei Peng

    Full Text Available Transient painful stimuli could induce suppression of alpha oscillatory activities and enhancement of gamma oscillatory activities that also could be greatly modulated by attention. Here, we attempted to characterize changes in cortical activities during tonic heat pain perception and investigated the influence of directed/distracted attention on these responses. We collected 5-minute long continuous Electroencephalography (EEG data from 38 healthy volunteers during four conditions presented in a counterbalanced order: (A resting condition; (B innoxious-distracted condition; (C noxious-distracted condition; (D noxious-attended condition. The effects of tonic heat pain stimulation and selective attention on oscillatory activities were investigated by comparing the EEG power spectra among the four experimental conditions and assessing the relationship between spectral power difference and subjective pain intensity. The change of oscillatory activities in condition D was characterized by stable and persistent decrease of alpha oscillation power over contralateral-central electrodes and widespread increase of gamma oscillation power, which were even significantly correlated with subjective pain intensity. Since EEG responses in the alpha and gamma frequency band were affected by attention in different manners, they are likely related to different aspects of the multidimensional sensory experience of pain. The observed contralateral-central alpha suppression (conditions D vs. B and D vs. C may reflect primarily a top-down cognitive process such as attention, while the widespread gamma enhancement (conditions D vs. A may partly reflect tonic pain processing, representing the summary effects of bottom-up stimulus-related and top-down subject-driven cognitive processes.

  20. Using the Inflection Points and Rates of Growth and Decay to Predict Levels of Solar Activity

    Wilson, Robert M.; Hathaway, David H.

    2008-01-01

    The ascending and descending inflection points and rates of growth and decay at specific times during the sunspot cycle are examined as predictors for future activity. On average, the ascending inflection point occurs about 1-2 yr after sunspot minimum amplitude (Rm) and the descending inflection point occurs about 6-7 yr after Rm. The ascending inflection point and the inferred slope (including the 12-mo moving average (12-mma) of (Delta)R (the month-to-month change in the smoothed monthly mean sunspot number (R)) at the ascending inflection point provide strong indications as to the expected size of the ongoing cycle s sunspot maximum amplitude (RM), while the descending inflection point appears to provide an indication as to the expected length of the ongoing cycle. The value of the 12-mma of (Delta)R at elapsed time T = 27 mo past the epoch of RM (E(RM)) seems to provide a strong indication as to the expected size of Rm for the following cycle. The expected Rm for cycle 24 is 7.6 +/- 4.4 (the 90-percent prediction interval), occurring before September 2008. Evidence is also presented for secular rises in selected cycle-related parameters and for preferential grouping of sunspot cycles by amplitude and/or period.

  1. Changes in the ecosystem structure of the Black Sea under predicted climatological and anthropogenic variations

    Akoglu, Ekin; Salihoglu, Baris; Fach Salihoglu, Bettina; Libralato, Simone; Cannaby, Heather; Oguz, Temel; Solidoro, Cosimo

    2014-05-01

    A dynamic Ecopath with Ecosim higher-trophic-level (HTL) model representation of the Black Sea ecosystem was coupled to the physical (BIMS-CIR) and biogeochemical (BIMS-ECO) models of the Black Sea in order to investigate historical anthropogenic and climatological interactions and feedbacks in the ecosystem. Further, the coupled models were used to assess the likely consequences of these interactions on the ecosystem's structure and functioning under predicted future climate (IPCC A1B) and fishing variability. Therefore, two model scenarios were used; i) a hindcast scenario (1980-1999) to evaluate and understand the impacts of the short-term climate and physical variability and the introduction of invasive species on the Black Sea ecosystem, and ii) a forecast scenario (2080-2099) to investigate the potential implications of climate change and anthropogenic exploitation on living resources of the Black Sea ecosystem by the end of the 21st century. According to the outcomes of the hindcast simulation, fisheries were found to be the main driver in determining the structure and functioning of the Black Sea ecosystem under changing environmental conditions. The coupled physical-biogeochemical forecast simulations predicted a slight but statistically significant basin-wide increase in the Black Sea's primary productivity by the end of the century due to increased stratification induced by basin-wide temperature increase and reduced Cold Intermediate Layer (CIL) formation which increased the residence time of riverine nutrients within the euphotic zone. Despite this increased primary productivity, the HTL model forecast simulation predicted a significant decrease in the commercial fish stocks primarily due to fisheries exploitation if current catch rates are maintained into the future. Results further suggested that some economically important small pelagic fish species are likely to disappear from the ecosystem making the recovery of the already-collapsed piscivorous

  2. Motor Skill Competence and Perceived Motor Competence: Which Best Predicts Physical Activity among Girls?

    Zeinab Khodaverdi

    2013-10-01

    Full Text Available The main purpose of this study was to determine which correlate, perceived motor competence or motor skill competence, best predicts girls' physical activity behavior.A sample of 352 girls (mean age=8.7, SD=0.3 yr participated in this study. To assess motor skill competence and perceived motor competence, each child completed the Test of Gross Motor Development-2 and Physical Ability sub-scale of Marsh's Self-Description Questionnaire. Children's physical activity was assessed by the Physical Activity Questionnaire for Older Children. Multiple linear regression model was used to determine whether perceived motor competence or motor skill competence best predicts moderate-to-vigorous self-report physical activity.Multiple regression analysis indicated that motor skill competence and perceived motor competence predicted 21% variance in physical activity (R(2=0.21, F=48.9, P=0.001, and motor skill competence (R(2=0.15, ᵝ=0.33, P= 0.001 resulted in more variance than perceived motor competence (R(2=0.06, ᵝ=0.25, P=0.001 in physical activity.Results revealed motor skill competence had more influence in comparison with perceived motor competence on physical activity level. We suggest interventional programs based on motor skill competence and perceived motor competence should be administered or implemented to promote physical activity in young girls.

  3. Planning versus action: Different decision-making processes predict plans to change one's diet versus actual dietary behavior.

    Kiviniemi, Marc T; Brown-Kramer, Carolyn R

    2015-05-01

    Most health decision-making models posit that deciding to engage in a health behavior involves forming a behavioral intention which then leads to actual behavior. However, behavioral intentions and actual behavior may not be functionally equivalent. Two studies examined whether decision-making factors predicting dietary behaviors were the same as or distinct from those predicting intentions. Actual dietary behavior was proximally predicted by affective associations with the behavior. By contrast, behavioral intentions were predicted by cognitive beliefs about behaviors, with no contribution of affective associations. This dissociation has implications for understanding individual regulation of health behaviors and for behavior change interventions. PMID:25903243

  4. Detection and prediction of land cover changes using Markov chain model in semi-arid rangeland in western Iran.

    Fathizad, Hassan; Rostami, Noredin; Faramarzi, Marzban

    2015-10-01

    The study of changes and destruction rate in the previous years as well as the possibility of prediction of these changes in the following years has a key role in optimal planning, controlling, and restricting non-normative changes in the future. This research was approached to detecting land use/cover changes (1985-2007) and to forecast the changes in the future (2021) use of multitemporal satellite imagery in semi-arid area in western Iran. A supervised classification of multilayer perceptron (MLP) was applied for detecting land use changes. The study area was classified into five classes, those of forest, rangeland, agriculture, residential, and barren lands. The change detection analysis indicated a decreasing trend in forest cover by 30.42%, while other land uses were increased during 1985 to 2007. The land use changes were predicted using Markov chain model for 2021. The model was calibrated by comparing the simulated map with the real detected classes of land cover in 2007. Then, for further model processing, an acceptable accuracy at 83% was achieved between them. Finally, land use changes were predicted by using transition matrix derived from calibrated approach. The findings of this study demonstrate a rapid change in land use/cover for the coming years. Transforming the forest into other land uses especially rangeland and cropland is the main land cover changes in the future. Therefore, the planning of protection and restoration of forest cover should be an essential program for decision-makers in the study area. PMID:26373304

  5. Laboratory experiments to predict changes in radiocaesium root uptake after flooding events

    Changes in soil solution composition after a flooding event were hypothesised to be one of the key factors in explaining changes in radiocaesium incorporation in the food chain in the areas affected by the Chernobyl accident. A laboratory methodology was set up to monitor changes in the soil solution composition after a sequence of flooding cycles. Experiments were performed using column and batch approaches on test soils with contrasting initial soil solution composition (high and low initial concentrations of K+). Results from column experiments indicated a potential increase in NH4+ concentrations, a parameter which could lead to an increase in the radiocaesium root uptake. Batch results in the soil with high initial K+ concentration showed that after a number of flooding cycles, especially for high ratios of flooding solution/mass of soil, K+ concentration decreased sometimes below a threshold value (around 0.5-1 mmol l-1), a fact that could lead to an increase in radiocaesium transfer. For the soils with a low initial K+ concentration, the flooding solution increased K+ and NH4+ values in the soil solution. The comparison of test soils with soils from Ukraine areas affected by flooding showed that the final stage in soil solution composition was similar in both cases, regardless of the initial composition of the soil solution. Moreover, the comparison with unflooded soils from the same area showed that potential changes in other soil parameters, such as 137Cs activity concentration, clay content, and radiocaesium interception potential, RIP (a parameter that estimates the radiocaesium specific sorption capacity of a soil), should also be monitored for additional effects due to the flooding event. Therefore, the changes in the root uptake would depend on the resulting situation from changes in RIP, K+ and NH4+ values in the soil solution

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

    Mora, Angel

    2014-06-11

    We present unified predictions for the crack onset strain, evolution of crack density, and changes in electrical resistance in indium tin oxide/polymer thin films under tensile loading. We propose a damage mechanics model to quantify and predict such changes as an alternative to fracture mechanics formulations. Our predictions are obtained by assuming that there are no flaws at the onset of loading as opposed to the assumptions of fracture mechanics approaches. We calibrate the crack onset strain and the damage model based on experimental data reported in the literature. We predict crack density and changes in electrical resistance as a function of the damage induced in the films. We implement our model in the commercial finite element software ABAQUS using a user subroutine UMAT. We obtain fair to good agreement with experiments. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  7. Glaciers and hydrological changes in the Tien Shan: simulation and prediction

    In this study, we estimated the current glacier state and forecast the potential impact of global and regional climate change on the glaciers and glacier runoff in the Tien Shan. General (G) and detailed (D) simulations were developed based on assessment of the Tien Shan glacier recession between 1943 and 2003 using an iterative stepwise increase in the equilibrium line altitude of 20 m. The G simulation was developed for 2777 grids each of which covered over 1000 km2 of glacier surface and D for the 15 953 Tien Shan glaciers. Both simulations employed glacier morphometric characteristics derived from Digital Elevation Model based on remote sensing data, high resolution maps and in situ GPS validation. Simulated changes in glacier area demonstrated that a possible increase in air temperature of 1 deg. C at E-barLA must be compensated by a 100 mm increase in precipitation at the same altitude if Tien Shan glaciers are to be maintained in their current state. An increase in mean air temperature of 4 deg. C and precipitation of 1.1 times the current level could increase E-barLA by 570 m during the 21st century. Under these conditions, the number of glaciers, glacier covered area, glacier volume, and glacier runoff are predicted to be 94%, 69%, 75%, and 75% of current values. The maximum glacier runoff may reach as much as 1.25 times current levels while the minimum will likely equal zero

  8. Glaciers and hydrological changes in the Tien Shan: simulation and prediction

    Aizen, V B [Department of Geography, University of Idaho, Moscow, ID 83844-3025 (United States); Aizen, E M [Department of Geography, University of Idaho, Moscow, ID 83844-3025 (United States); Kuzmichonok, V A [Institute of Water Problems and Hydro Power, Kyrgyz National Academy of Science, 533 Frunze Street, Bishkek 720033 (Kyrgyzstan)

    2007-10-15

    In this study, we estimated the current glacier state and forecast the potential impact of global and regional climate change on the glaciers and glacier runoff in the Tien Shan. General (G) and detailed (D) simulations were developed based on assessment of the Tien Shan glacier recession between 1943 and 2003 using an iterative stepwise increase in the equilibrium line altitude of 20 m. The G simulation was developed for 2777 grids each of which covered over 1000 km{sup 2} of glacier surface and D for the 15 953 Tien Shan glaciers. Both simulations employed glacier morphometric characteristics derived from Digital Elevation Model based on remote sensing data, high resolution maps and in situ GPS validation. Simulated changes in glacier area demonstrated that a possible increase in air temperature of 1 deg. C at E-barLA must be compensated by a 100 mm increase in precipitation at the same altitude if Tien Shan glaciers are to be maintained in their current state. An increase in mean air temperature of 4 deg. C and precipitation of 1.1 times the current level could increase E-barLA by 570 m during the 21st century. Under these conditions, the number of glaciers, glacier covered area, glacier volume, and glacier runoff are predicted to be 94%, 69%, 75%, and 75% of current values. The maximum glacier runoff may reach as much as 1.25 times current levels while the minimum will likely equal zero.

  9. Early radiation-induced mucosal changes evaluated by proctoscopy: Predictive role of dosimetric parameters

    Background and purpose: Late rectal complications are assessed according to different scoring systems. Endoscopy can provide a more sensitive estimation of early radiation damage. The aim of this paper is to investigate the correlation between dosimetric parameters and rectal mucosal changes after radiotherapy (RT). Materials and methods: Patients with prostate adenocarcinoma treated with curative or adjuvant RT underwent endoscopy 1 year after RT. Receiver operating characteristics (ROC) analysis was performed to analyze the predictive capability of the dosimetric variables in determining mucosal changes classified by Vienna Rectoscopy Score (VRS). Results: The best dosimetric predictors of grade ⩾2 telangiectasia were rectal (r) V60Gy (p = 0.014), rV70Gy (p = 0.017) and rDmean (p = 0.018). Similar results were obtained for grade ⩾2 VRS. The set of rV60Gy 70Gy mean 60Gy, rV70Gy and rDmean were the strongest predictors of rectal mucosal alterations. In-depth analysis is required to correlate each mucosal alteration with late rectal toxicity in order to suggest early proctoscopy as surrogate end-point for rectal late toxicity in studies aimed at reducing this important complication.

  10. CHANGE OF CONTRACTOR FOR THE FACILITIES MANAGEMENT ACTIVITIES AT CERN

    2003-01-01

    The Facilities Management contract at CERN, under the responsibility of ST Division, Group FM, is in charge of the maintenance and minor works on tertiary installations (i.e. all structures and installations that have no direct relation to the running of the accelerators) for the following trades: - Technical: heating, ventilation, air conditioning, plumbing, electricity, civil engineering (painting, roofing, glazing, blinds, fencing, masonry etc.), cleansing, passenger and goods lifts, automatic and powered doors, kitchen equipment, roads, signs, keys and locks, office furniture, - Services: waste collection, security, green areas, cleaning and sanitary supplies, disinfection, rodent control and insect control. Starting from the 1st June the present contractor will stop some activities that will be taken under its responsibility by the new one, INGEST Facility. Others activities will be moved on the 1st July. Minor perturbation in the service might occur. The contact number will not change and will be opera...

  11. Modeled impacts of predicted climate change on recharge and groundwater levels

    Scibek, J.; Allen, D. M.

    2006-11-01

    A methodology is developed for linking climate models and groundwater models to investigate future impacts of climate change on groundwater resources. An unconfined aquifer, situated near Grand Forks in south central British Columbia, Canada, is used to test the methodology. Climate change scenarios from the Canadian Global Coupled Model 1 (CGCM1) model runs are downscaled to local conditions using Statistical Downscaling Model (SDSM), and the change factors are extracted and applied in LARS-WG stochastic weather generator and then input to the recharge model. The recharge model simulated the direct recharge to the aquifer from infiltration of precipitation and consisted of spatially distributed recharge zones, represented in the Hydrologic Evaluation of Landfill Performance (HELP) hydrologic model linked to a geographic information system (GIS). A three-dimensional transient groundwater flow model, implemented in MODFLOW, is then used to simulate four climate scenarios in 1-year runs (1961-1999 present, 2010-2039, 2040-2069, and 2070-2099) and compare groundwater levels to present. The effect of spatial distribution of recharge on groundwater levels, compared to that of a single uniform recharge zone, is much larger than that of temporal variation in recharge, compared to a mean annual recharge representation. The predicted future climate for the Grand Forks area from the downscaled CGCM1 model will result in more recharge to the unconfined aquifer from spring to the summer season. However, the overall effect of recharge on the water balance is small because of dominant river-aquifer interactions and river water recharge.

  12. CADrx for GBM Brain Tumors: Predicting Treatment Response from Changes in Diffusion-Weighted MRI

    Matthew S. Brown

    2009-11-01

    Full Text Available The goal of this study was to develop a computer-aided therapeutic response (CADrx system for early prediction of drug treatment response for glioblastoma multiforme (GBM brain tumors with diffusion weighted (DW MR images. In conventional Macdonald assessment, tumor response is assessed nine weeks or more post-treatment. However, we will investigate the ability of DW-MRI to assess response earlier, at five weeks post treatment. The apparent diffusion coefficient (ADC map, calculated from DW images, has been shown to reveal changes in the tumor’s microenvironment preceding morphologic tumor changes. ADC values in treated brain tumors could theoretically both increase due to the cell kill (and thus reduced cell density and decrease due to inhibition of edema. In this study, we investigated the effectiveness of features that quantify changes from pre- and post-treatment tumor ADC histograms to detect treatment response. There are three parts to this study: first, tumor regions were segmented on T1w contrast enhanced images by Otsu’s thresholding method, and mapped from T1w images onto ADC images by a 3D region of interest (ROI mapping tool using DICOM header information; second, ADC histograms of the tumor region were extracted from both pre- and five weeks post-treatment scans, and fitted by a two-component Gaussian mixture model (GMM. The GMM features as well as standard histogram-based features were extracted. Finally, supervised machine learning techniques were applied for classification of responders or non-responders. The approach was evaluated with a dataset of 85 patients with GBM under chemotherapy, in which 39 responded and 46 did not, based on tumor volume reduction. We compared adaBoost, random forest and support vector machine classification algorithms, using ten-fold cross validation, resulting in the best accuracy of 69.41% and the corresponding area under the curve (Az of 0.70.

  13. Predicting glacio-hydrologic change in the headwaters of the Zongo River, Cordillera Real, Bolivia

    Frans, Chris; Istanbulluoglu, Erkan; Lettenmaier, Dennis P.; Naz, Bibi S.; Clarke, Garry K. C.; Condom, Thomas; Burns, Pat; Nolin, Anne W.

    2015-11-01

    In many partially glacierized watersheds glacier recession driven by a warming climate could lead to complex patterns of streamflow response over time, often marked with rapid increases followed by sharp declines, depending on initial glacier ice cover and rate of climate change. Capturing such "phases" of hydrologic response is critical in regions where communities rely on glacier meltwater, particularly during low flows. In this paper, we investigate glacio-hydrologic response in the headwaters of the Zongo River, Bolivia, under climate change using a distributed glacio-hydrological model over the period of 1987-2100. Model predictions are evaluated through comparisons with satellite-derived glacier extent estimates, glacier surface velocity, in situ glacier mass balance, surface energy flux, and stream discharge measurements. Historically (1987-2010) modeled glacier melt accounts for 27% of annual runoff, and 61% of dry season (JJA) runoff on average. During this period the relative glacier cover was observed to decline from 35 to 21% of the watershed. In the future, annual and dry season discharge is projected to decrease by 4% and 27% by midcentury and 25% and 57% by the end of the century, respectively, following the loss of 81% of the ice in the watershed. Modeled runoff patterns evolve through the interplay of positive and negative trends in glacier melt and increased evapotranspiration as the climate warms. Sensitivity analyses demonstrate that the selection of model surface energy balance parameters greatly influences the trajectory of hydrological change projected during the first half of the 21st century. These model results underscore the importance of coupled glacio-hydrology modeling.

  14. A global remote sensing mission to detect and predict plant functional biodiversity change

    Cavender-Bares, J.; Jetz, W.; Pavlick, R.; Schimel, D.; Gamon, J. A.; Hobbie, S. E.; Townsend, P. A.

    2015-12-01

    Global biodiversity is one of the most crucial and least-observed dimensions of the earth system and increasingly important for anticipating changes to both the climate system and ecosystem services. Parallel developments in biodiversity science and remote sensing show that new satellite observations could directly provide global monitoring of one key dimension of global biodiversity, plant functional trait diversity. Remote sensing has already proven a pivotal aid to address the biodiversity data gap. Data on plant productivity, phenology, land-cover and other environmental parameters from MODIS and Landsat satellites currently serve as highly effective covariates for spatiotemporal biodiversity models. The growing functional trait paradigm in ecology, supported by the development of a global plant trait database that includes information for more than one-third of the global flora, highlights the importance of detecting functional diversity globally. Functional traits such as nutrient concentrations, characteristic growth forms and wood density drive both, how organisms respond to environmental change and the effects of organisms on ecosystems. Additionally, the ever more complete tree of life for plants, which presents a link to the shared evolutionary history of plant traits within lineages, coupled with advances in macroevolutionary models and data gap filling techniques, allows predictions of traits that cannot be directly observed. Using experimental manipulations of plant functional and phylogenetic diversity, our team is testing the extent to which we can link above and belowground measurements of biodiversity to remotely sensed optical diversity using hyperspectral data. These efforts will provide the means to fruitfully harness functional diversity data from space from the envisioned Global Biodiversity Observatory (GBO) mission. In turn, remotely sensed hyperspectral data from GBO will allow fundamental breakthroughs and resolve one of the most

  15. Predicting changes in aquatic toxicity of chemicals resulting from solvent or dispersant use as vehicle.

    Kikuchi, Mikio; Nakagawa, Masamitsu; Tone, Suguru; Saito, Hotaka; Niino, Tatsuhiro; Nagasawa, Natsumi; Sawai, Jun

    2016-07-01

    The influence of two vehicles (N,N-dimethylformamide [DMF] as solvent and polyoxyethylene hydrogenated castor oil [HCO-40] as a dispersant) on the acute toxicity of eight hydrophobic chemicals with a non-specific mode of action to Daphnia magna was investigated according to the OECD Guidelines for the Testing of Chemicals, No. 202. An increased 48-h EC50 value for D. magna or reduced toxicity resulting from the addition of HCO-40 to the test medium was observed for five of the eight chemicals examined. Each of eight chemicals was dissolved in water at a concentration of either 10 mg/L or 1.0 mg/L, with or without DMF or HCO-40. Silicone film as a model of a biological membrane was then immersed in each solution, and the concentration of each chemical in the water was monitored until equilibrium was reached for each test substance, after which the adsorbed amount of each chemical was determined. The amounts of p-pentylphenol and four other substances with log Pow (1-octanol/water partition coefficient) values greater than 3.4 adsorbed onto the silicone film decreased with increasing concentrations of HCO-40. However, 3-chloro-4-fluoronitrobenzene and two other substances with log Pow values less than 2.6 demonstrated no changes in adsorption with either increasing HCO-40 concentration or the addition of DMF. The reduced adsorption in the presence of a vehicle on the silicone film correlated closely with changes in toxicity. These results indicate that the methodology developed in this study enables the prediction of changes in toxicity resulting from the addition of vehicles to a test system. PMID:27037772

  16. A step-response approach for predicting and understanding non-linear precipitation changes

    Good, Peter; Lowe, Jason A.; Webb, Mark J.; Ringer, Mark A.; Wu, Peili [Met Office Hadley Centre, Exeter (United Kingdom); Ingram, William [Met Office Hadley Centre, Exeter (United Kingdom); University of Oxford, Atmospheric, Oceanic and Planetary Physics, Department of Physics, Oxford (United Kingdom); Lambert, F.H. [University of Exeter, College of Engineering, Mathematics and Physical Sciences, Exeter (United Kingdom); Gregory, Jonathan M. [Met Office Hadley Centre, Exeter (United Kingdom); University of Reading, Department of Meteorology, Walker Institute for Climate System Research, Reading (United Kingdom)

    2012-12-15

    Future changes in precipitation represent one of the most important and uncertain possible effects of future climate change. We demonstrate a new approach based on idealised CO{sub 2} step-change general circulation model (GCM) experiments, and test it using the HadCM3 GCM. The approach has two purposes: to help understand GCM projections, and to build and test a fast simple model for precipitation projections under a wide range of forcing scenarios. Overall, we find that the CO{sub 2} step experiments contain much information that is relevant to transient projections, but that is more easily extracted due to the idealised experimental design. We find that the temporary acceleration of global-mean precipitation in this GCM following CO{sub 2} ramp-down cannot be fully explained simply using linear responses to CO{sub 2} and temperature. A more complete explanation can be achieved with an additional term representing interaction between CO{sub 2} and temperature effects. Energy budget analysis of this term is dominated by clear-sky outgoing long-wave radiation (CSOLR) and sensible heating, but cloud and short-wave terms also contribute. The dominant CSOLR interaction is attributable to increased CO{sub 2} raising the mean emission level to colder altitudes, which reduces the rate of increase of OLR with warming. This behaviour can be reproduced by our simple model. On regional scales, we compare our approach with linear 'pattern-scaling' (scaling regional responses by global-mean temperature change). In regions where our model predicts linear change, pattern-scaling works equally well. In some regions, however, substantial deviations from linear scaling with global-mean temperature are found, and our simple model provides more accurate projections. The idealised experiments reveal a complex pattern of non-linear behaviour. There are likely to be a range of controlling physical mechanisms, different from those dominating the global-mean response, requiring

  17. Diurnal changes of earthquake activity and geomagnetic Sq-variations

    Duma, G.; Ruzhin, Y.

    Statistic analyses demonstrate that the probability of earthquake occurrence in many earthquake regions strongly depends on the time of day, that is on Local Time (e.g. Conrad, 1909, 1932; Shimshoni, 1971; Duma, 1997; Duma and Vilardo, 1998). This also applies to strong earthquake activity. Moreover, recent observations reveal an involvement of the regular diurnal variations of the Earth's magnetic field, commonly known as Sq-variations, in this geodynamic process of changing earthquake activity with the time of day (Duma, 1996, 1999). In the article it is attempted to quantify the forces which result from the interaction between the induced Sq-variation currents in the Earth's lithosphere and the regional Earth's magnetic field, in order to assess the influence on the tectonic stress field and on seismic activity. A reliable model is obtained, which indicates a high energy involved in this process. The effect of Sq-induction is compared with the results of the large scale electromagnetic experiment "Khibiny" (Velikhov, 1989), where a giant artificial current loop was activated in the Barents Sea.

  18. Diurnal changes of earthquake activity and geomagnetic Sq-variations

    G. Duma

    2003-01-01

    Full Text Available Statistic analyses demonstrate that the probability of earthquake occurrence in many earthquake regions strongly depends on the time of day, that is on Local Time (e.g. Conrad, 1909, 1932; Shimshoni, 1971; Duma, 1997; Duma and Vilardo, 1998. This also applies to strong earthquake activity. Moreover, recent observations reveal an involvement of the regular diurnal variations of the Earth’s magnetic field, commonly known as Sq-variations, in this geodynamic process of changing earthquake activity with the time of day (Duma, 1996, 1999. In the article it is attempted to quantify the forces which result from the interaction between the induced Sq-variation currents in the Earth’s lithosphere and the regional Earth’s magnetic field, in order to assess the influence on the tectonic stress field and on seismic activity. A reliable model is obtained, which indicates a high energy involved in this process. The effect of Sq-induction is compared with the results of the large scale electromagnetic experiment "Khibiny" (Velikhov, 1989, where a giant artificial current loop was activated in the Barents Sea.

  19. Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

    Tucker James R

    2009-06-01

    Full Text Available Abstract Background Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Results Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948 and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Conclusion Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources

  20. Music-induced emotions can be predicted from a combination of brain activity and acoustic features.

    Daly, Ian; Williams, Duncan; Hallowell, James; Hwang, Faustina; Kirke, Alexis; Malik, Asad; Weaver, James; Miranda, Eduardo; Nasuto, Slawomir J

    2015-12-01

    It is widely acknowledged that music can communicate and induce a wide range of emotions in the listener. However, music is a highly-complex audio signal composed of a wide range of complex time- and frequency-varying components. Additionally, music-induced emotions are known to differ greatly between listeners. Therefore, it is not immediately clear what emotions will be induced in a given individual by a piece of music. We attempt to predict the music-induced emotional response in a listener by measuring the activity in the listeners electroencephalogram (EEG). We combine these measures with acoustic descriptors of the music, an approach that allows us to consider music as a complex set of time-varying acoustic features, independently of any specific music theory. Regression models are found which allow us to predict the music-induced emotions of our participants with a correlation between the actual and predicted responses of up to r=0.234,pmusic induced emotions can be predicted by their neural activity and the properties of the music. Given the large amount of noise, non-stationarity, and non-linearity in both EEG and music, this is an encouraging result. Additionally, the combination of measures of brain activity and acoustic features describing the music played to our participants allows us to predict music-induced emotions with significantly higher accuracies than either feature type alone (p<0.01). PMID:26544602

  1. The CR‐Ω+ Classification Algorithm for Spatio‐Temporal Prediction of Criminal Activity

    S. Godoy‐Calderón

    2010-04-01

    Full Text Available We present a spatio‐temporal prediction model that allows forecasting of the criminal activity behavior in a particular region byusing supervised classification. The degree of membership of each pattern is interpreted as the forecasted increase or decreasein the criminal activity for the specified time and location. The proposed forecasting model (CR‐Ω+ is based on the family ofKora‐Ω Logical‐Combinatorial algorithms operating on large data volumes from several heterogeneous sources using aninductive learning process. We propose several modifications to the original algorithms by Bongard and Baskakova andZhuravlëv which improve the prediction performance on the studied dataset of criminal activity. We perform two analyses:punctual prediction and tendency analysis, which show that it is possible to predict punctually one of four crimes to beperpetrated (crime family, in a specific space and time, and 66% of effectiveness in the prediction of the place of crime, despiteof the noise of the dataset. The tendency analysis yielded an STRMSE (Spatio‐Temporal RMSE of less than 1.0.

  2. Structure-Functional Study of Tyrosine and Methionine Dipeptides: An Approach to Antioxidant Activity Prediction

    Anna Torkova

    2015-10-01

    Full Text Available Quantum chemical methods allow screening and prediction of peptide antioxidant activity on the basis of known experimental data. It can be used to design the selective proteolysis of protein sources in order to obtain products with antioxidant activity. Molecular geometry and electronic descriptors of redox-active amino acids, as well as tyrosine and methionine-containing dipeptides, were studied by Density Functional Theory method. The calculated data was used to reveal several descriptors responsible for the antioxidant capacities of the model compounds based on their experimentally obtained antioxidant capacities against ABTS (2,2′-Azino-bis-(3-ethyl-benzothiazoline-6-sulfonate and peroxyl radical. A formula to predict antioxidant activity of peptides was proposed.

  3. A chemometric approach for prediction of antifungal activity of some benzoxazole derivatives against Candida albicans

    Podunavac-Kuzmanović Sanja O.

    2012-01-01

    Full Text Available The purpose of the article is to promote and facilitate prediction of antifungal activity of the investigated series of benzoxazoles against Candida albicans. The clinical importance of this investigation is to simplify design of new antifungal agents against the fungi which can cause serious illnesses in humans. Quantitative structure activity relationship analysis was applied on nineteen benzoxazole derivatives. A multiple linear regression (MLR procedure was used to model the relationships between the molecular descriptors and the antifungal activity of benzoxazole derivatives. Two mathematical models have been developed as a calibration models for predicting the inhibitory activity of this class of compounds against Candida albicans. The quality of the models was validated by the leave-one-out technique, as well as by the calculation of statistical parameters for the established model. [Projekat Ministarstva nauke Republike Srbije, br. 172012 i br. 172014

  4. Predictive Duty Cycle Control of Three-Phase Active-Front-End Rectifiers

    Song, Zhanfeng; Tian, Yanjun; Chen, Wei;

    2016-01-01

    This paper proposed an on-line optimizing duty cycle control approach for three-phase active-front-end rectifiers, aiming to obtain the optimal control actions under different operating conditions. Similar to finite control set model predictive control strategy, a cost function previously...... constructed based on the desired control performance is adopted here, which is essential for the solving process of the optimizing problem. On the other hand, differently, with respect to the proposed strategy, duty cycle signals are optimized, instead of possible switching states. The determination...... of optimal duty cycles is made by predicting the effect of duty cycles on instantaneous current variations and minimizing the cost function. Due to the adoption of behavior prediction, the proposed controller inherits the excellent dynamic characteristics of predictive controllers. Moreover, the application...

  5. Utilizing Organizational Culture to Predict Responses to Planned Change in a Public School: A Test of the OC[superscript 3] Model

    Sandberg, Eric Christian

    2012-01-01

    The primary purpose of this research was to test the capability of the Organizational Change in Cultural Context (OC[superscript 3]) Model (Latta, 2009, 2011) to predict responses to change. According to Latta, predictions of resistance to or facilitation of change can be predicted by utilizing organizational culture and its alignment with the…

  6. Prediction of solvent-induced morphological changes of polyelectrolyte diblock copolymer micelles.

    Li, Nan K; Fuss, William H; Tang, Lei; Gu, Renpeng; Chilkoti, Ashutosh; Zauscher, Stefan; Yingling, Yaroslava G

    2015-11-14

    Self-assembly processes of polyelectrolyte block copolymers are ubiquitous in industrial and biological processes; understanding their physical properties can also provide insights into the design of polyelectrolyte materials with novel and tailored properties. Here, we report systematic analysis on how the ionic strength of the solvent and the length of the polyelectrolyte block affect the self-assembly and morphology of the polyelectrolyte block copolymer materials by constructing a salt-dependent morphological phase diagram using an implicit solvent ionic strength (ISIS) method for dissipative particle dynamics (DPD) simulations. This diagram permits the determination of the conditions for the morphological transition into a specific shape, namely vesicles or lamellar aggregates, wormlike/cylindrical micelles, and spherical micelles. The scaling behavior for the size of spherical micelles is predicted, in terms of radius of gyration (R(g,m)) and thickness of corona (Hcorona), as a function of solvent ionic strength (c(s)) and polyelectrolyte length (NA), which are R(g,m) ∼ c(s)(-0.06)N(A)(0.54) and Hcorona ∼ c(s)(-0.11)N(A)(0.75). The simulation results were corroborated through AFM and static light scattering measurements on the example of the self-assembly of monodisperse, single-stranded DNA block-copolynucleotides (polyT50-b-F-dUTP). Overall, we were able to predict the salt-responsive morphology of polyelectrolyte materials in aqueous solution and show that a spherical-cylindrical-lamellar change in morphology can be obtained through an increase in solvent ionic strength or a decrease of polyelectrolyte length. PMID:26315065

  7. Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

    Brown, Kerry A.; Parks, Katherine E; Bethell, Colin; Johnson, Steig E; Mulligan, Mark

    2015-01-01

    Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence r...

  8. Predicting plant diversity patterns in madagascar:Understanding the effects of climate and land cover change in a biodiversity hotspot

    Brown, Kerry A.; Parks, Katherine E; Bethell, Colin A.; Johnson, Steig E; Mulligan, Mark

    2015-01-01

    Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence r...

  9. Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot

    Kumar, Lalit; Brown, Kerry A.; Parks, Katherine E; Bethell, Colin A.; Johnson, Steig E; Mulligan, Mark

    2015-01-01

    Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence r...

  10. Predicting Kinase Activity in Angiotensin Receptor Phosphoproteomes Based on Sequence-Motifs and Interactions

    Bøgebo, Rikke; Horn, Heiko; Olsen, Jesper V;

    2014-01-01

    -arrestin dependent signalling. Two complimentary global phosphoproteomics studies have analyzed the complex signalling induced by the AT1aR. Here we integrate the data sets from these studies and perform a joint analysis using a novel method for prediction of differential kinase activity from phosphoproteomics data...... developed a new method for kinase-centric analysis of phosphoproteomes to pinpoint differential kinase activity in large-scale data sets....

  11. Application of Artificial Intelligence to the Prediction of the Antimicrobial Activity of Essential Oils

    Mathieu Daynac; Alvaro Cortes-Cabrera; Prieto, Jose M.

    2015-01-01

    Essential oils (EOs) are vastly used as natural antibiotics in Complementary and Alternative Medicine (CAM). Their intrinsic chemical variability and synergisms/antagonisms between its components make difficult to ensure consistent effects through different batches. Our aim is to evaluate the use of artificial neural networks (ANNs) for the prediction of their antimicrobial activity. Methods. The chemical composition and antimicrobial activity of 49 EOs, extracts, and/or fractions was extract...

  12. Brain Activity in Valuation Regions while Thinking about the Future Predicts Individual Discount Rates

    Cooper, Nicole; Kable, Joseph W.; Kim, B. Kyu; Zauberman, Gal

    2013-01-01

    People vary widely in how much they discount delayed rewards, yet little is known about the sources of these differences. Here we demonstrate that neural activity in ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) when human subjects are asked to merely think about the future—specifically, to judge the subjective length of future time intervals—predicts delay discounting. High discounters showed lower activity for longer time delays, while low discounters showed the opposite ...

  13. BRAIN REWARD ACTIVITY TO MASKED IN-GROUP SMILING FACES PREDICTS FRIENDSHIP DEVELOPMENT

    Chen, Pin-Hao A.; Whalen, Paul J.; Freeman, Jonathan B.; Taylor, James M.; Heatherton, Todd F.

    2015-01-01

    This study examined whether neural responses in the ventral striatum (VS) to in-group facial expressions—presented without explicit awareness—could predict friendship patterns in newly arrived individuals from China six months later. Individuals who initially showed greater VS activity in response to in-group happy expressions during functional neuroimaging later made considerably more in-group friends, suggesting that VS activity might reflect reward processes that drive in-group approach behaviors. PMID:26185595

  14. Multinationals' Political Activities on Climate Change

    Kolk, A.; Pinkse, J. [University of Amsterdam Business School, Amsterdam (Netherlands)

    2007-06-15

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

  15. A general model for predicting coolant activity behaviour for fuel-failure monitoring analysis

    El-Jaby, A., E-mail: Ali.El-Jaby@cnsc-ccsn.gc.c [Department of Chemistry and Chemical Engineering, Royal Military College of Canada, P.O. Box 17000, Station Forces, Kingston, Ontario, K7K 7B4 (Canada); Lewis, B.J.; Thompson, W.T. [Department of Chemistry and Chemical Engineering, Royal Military College of Canada, P.O. Box 17000, Station Forces, Kingston, Ontario, K7K 7B4 (Canada); Iglesias, F. [Candesco Corporation, 230 Richmond Street West, 10th Floor, Toronto, Ontario, M5V 1V6 (Canada); Ip, M. [Bruce Power, 123 Front Street West, 4th Floor, Toronto, Ontario, M5J 2M2 (Canada)

    2010-04-01

    A mathematical treatment has been developed to predict the release of volatile fission products from operating defective nuclear fuel elements. The fission product activity in both the fuel-to-sheath gap and primary heat transport system as a function of time can be predicted during all reactor operating conditions, including: startup, steady-state, shutdown, and bundle-shifting manoeuvres. In addition, an improved ability to predict the coolant activity of the {sup 135}Xe isotope in commercial reactors is discussed. A method is also proposed to estimate both the burnup and the amount of tramp uranium deposits in-core. The model has been validated against in-reactor experiments conducted with defective fuel elements containing natural and artificial failures at the Chalk River Laboratories. Lastly, the model has been benchmarked against a defective fuel occurrence in a commercial reactor.

  16. A general model for predicting coolant activity behaviour for fuel-failure monitoring analysis

    A mathematical treatment has been developed to predict the release of volatile fission products from operating defective nuclear fuel elements. The fission product activity in both the fuel-to-sheath gap and primary heat transport system as a function of time can be predicted during all reactor operating conditions, including: startup, steady-state, shutdown, and bundle-shifting manoeuvres. In addition, an improved ability to predict the coolant activity of the 135Xe isotope in commercial reactors is discussed. A method is also proposed to estimate both the burnup and the amount of tramp uranium deposits in-core. The model has been validated against in-reactor experiments conducted with defective fuel elements containing natural and artificial failures at the Chalk River Laboratories. Lastly, the model has been benchmarked against a defective fuel occurrence in a commercial reactor.

  17. Predicting Atlantic seasonal hurricane activity using outgoing longwave radiation over Africa

    Karnauskas, Kristopher B.; Li, Laifang

    2016-07-01

    Seasonal hurricane activity is a function of the amount of initial disturbances (e.g., easterly waves) and the background environment in which they develop into tropical storms (i.e., the main development region). Focusing on the former, a set of indices based solely upon the meridional structure of satellite-derived outgoing longwave radiation (OLR) over the African continent are shown to be capable of predicting Atlantic seasonal hurricane activity with very high rates of success. Predictions of named storms based on the July OLR field and trained only on the time period prior to the year being predicted yield a success rate of 87%, compared to the success rate of NOAA's August outlooks of 53% over the same period and with the same average uncertainty range (±2). The resulting OLR indices are statistically robust, highly detectable, physically linked to the predictand, and may account for longer-term observed trends.

  18. A general model for predicting coolant activity behaviour for fuel-failure monitoring analysis

    El-Jaby, A.; Lewis, B. J.; Thompson, W. T.; Iglesias, F.; Ip, M.

    2010-04-01

    A mathematical treatment has been developed to predict the release of volatile fission products from operating defective nuclear fuel elements. The fission product activity in both the fuel-to-sheath gap and primary heat transport system as a function of time can be predicted during all reactor operating conditions, including: startup, steady-state, shutdown, and bundle-shifting manoeuvres. In addition, an improved ability to predict the coolant activity of the 135Xe isotope in commercial reactors is discussed. A method is also proposed to estimate both the burnup and the amount of tramp uranium deposits in-core. The model has been validated against in-reactor experiments conducted with defective fuel elements containing natural and artificial failures at the Chalk River Laboratories. Lastly, the model has been benchmarked against a defective fuel occurrence in a commercial reactor.

  19. RELATIONS OF SELF-APPRAISAL AND MOOD CHANGES WITH VOLUNTARY PHYSICAL ACTIVITY CHANGES IN AFRICAN AMERICAN PREADOLESCENTS IN AN AFTER-SCHOOL CARE INTERVENTION

    James J. Annesi; Avery D. Faigenbaum; Wayne L. Westcott; Smith, Alice E

    2008-01-01

    There is an increasing prevalence of overweight in preadolescents that predicts physical problems over the lifespan. Physical inactivity has been implicated as an associated factor, with African American youth being at an increased risk. Based on social cognitive theory, and proposed correlates of physical activity in youth, changes over 12 weeks in measures of self-appraisal (general self, physical appearance, physical self-concept, exercise barriers self-efficacy) and mood (tension, vigor),...

  20. Engineering design activities and conceptual change in middle school science

    Schnittka, Christine G.

    The purpose of this research was to investigate the impact of engineering design classroom activities on conceptual change in science, and on attitudes toward and knowledge about engineering. Students were given a situated learning context and a rationale for learning science in an active, inquiry-based method, and worked in small collaborative groups. One eighth-grade physical science teacher and her students participated in a unit on heat transfer and thermal energy. One class served as the control while two others received variations of an engineering design treatment. Data were gathered from teacher and student entrance and exit interviews, audio recordings of student dialog during group work, video recordings and observations of all classes, pre- and posttests on science content and engineering attitudes, and artifacts and all assignments completed by students. Qualitative and quantitative data were collected concurrently, but analysis took place in two phases. Qualitative data were analyzed in an ongoing manner so that the researcher could explore emerging theories and trends as the study progressed. These results were compared to and combined with the results of the quantitative data analysis. Analysis of the data was carried out in the interpretive framework of analytic induction. Findings indicated that students overwhelmingly possessed alternative conceptions about heat transfer, thermal energy, and engineering prior to the interventions. While all three classes made statistically significant gains in their knowledge about heat and energy, students in the engineering design class with the targeted demonstrations made the most significant gains over the other two other classes. Engineering attitudes changed significantly in the two classes that received the engineering design intervention. Implications from this study can inform teachers' use of engineering design activities in science classrooms. These implications are: (1) Alternative conceptions will

  1. Prediction of muscle activities from electrocorticograms in primary motor cortex of primates.

    Duk Shin

    Full Text Available Electrocorticography (ECoG has drawn attention as an effective recording approach for brain-machine interfaces (BMI. Previous studies have succeeded in classifying movement intention and predicting hand trajectories from ECoG. Despite such successes, however, there still remains considerable work for the realization of ECoG-based BMIs as neuroprosthetics. We developed a method to predict multiple muscle activities from ECoG measurements. We also verified that ECoG signals are effective for predicting muscle activities in time varying series when performing sequential movements. ECoG signals were band-pass filtered into separate sensorimotor rhythm bands, z-score normalized, and smoothed with a Gaussian filter. We used sparse linear regression to find the best fit between frequency bands of ECoG and electromyographic activity. The best average correlation coefficient and the normalized root-mean-square error were 0.92±0.06 and 0.06±0.10, respectively, in the flexor digitorum profundus finger muscle. The δ (1.5∼4Hz and γ2 (50∼90Hz bands contributed significantly more strongly than other frequency bands (P<0.001. These results demonstrate the feasibility of predicting muscle activity from ECoG signals in an online fashion.

  2. Early Prediction of Outcome of Activities of Daily Living After Stroke A Systematic Review

    Veerbeek, Janne M.; Kwakkel, Gert; van Wegen, Erwin E. H.; Ket, Johannes C. F.; Heymans, Martijn W.

    2011-01-01

    Background and Purpose-Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables t

  3. The Physical Activity Scale for the Elderly (PASE Questionnaire; Does It Predict Physical Health?

    Lawrence L. Spriet

    2013-08-01

    Full Text Available A lack of physical activity is common in older adults. With the increasing Canadian senior population, identifying the minimum amount of physical activity required to maintain the health of older adults is essential. This study determined whether relationships existed between the Physical Activity Scale for the Elderly (PASE questionnaire scores and health-related measurements in community-dwelling older adults who were meal delivery volunteers. Based on observed relationships between PASE scores and health parameters, the study attempted to predict an optimal PASE score that would ensure health parameters fell in desired ranges for older adults. 297 community-dwelling older adults (61.3% female 60–88 years (72.1 ± 6.5 completed the PASE and were measured for body composition, cardiovascular and blood parameters, flexibility, and handgrip strength. Significant regression models using PASE were produced for the health-related measures, but the relationships were not meaningful due to low predictive capacity. However, correlational data suggested that a minimum PASE score of ~140 for males and ~120 for females predicted a favorable waist circumference. In conclusion, findings demonstrated that PASE scores cannot be used to predict healthy physical measures, although the relationships between PASE and WC could be used to encourage older adults to become more physically active.

  4. M-ficolin levels reflect disease activity and predict remission in early rheumatoid arthritis

    Ammitzbøll, Christian Gytz; Thiel, Steffen; Jensenius, Jens Christian;

    2013-01-01

    To assess plasma M-ficolin concentrations in disease-modifying antirheumatic drug (DMARD)-naive patients with early rheumatoid arthritis (RA), to investigate the correlation of M-ficolin concentrations with disease activity markers, and to determine the predictive value of M-ficolin with respect ...

  5. Shallow outgassing changes disrupt steady lava lake activity, Kilauea Volcano

    Patrick, M. R.; Orr, T. R.; Swanson, D. A.; Lev, E.

    2015-12-01

    Persistent lava lakes are a testament to sustained magma supply and outgassing in basaltic systems, and the surface activity of lava lakes has been used to infer processes in the underlying magmatic system. At Kilauea Volcano, Hawai`i, the lava lake in Halema`uma`u Crater has been closely studied for several years with webcam imagery, geophysical, petrological and gas emission techniques. The lava lake in Halema`uma`u is now the second largest on Earth, and provides an unprecedented opportunity for detailed observations of lava lake outgassing processes. We observe that steady activity is characterized by continuous southward motion of the lake's surface and slow changes in lava level, seismic tremor and gas emissions. This normal, steady activity can be abruptly interrupted by the appearance of spattering - sometimes triggered by rockfalls - on the lake surface, which abruptly shifts the lake surface motion, lava level and gas emissions to a more variable, unstable regime. The lake commonly alternates between this a) normal, steady activity and b) unstable behavior several times per day. The spattering represents outgassing of shallowly accumulated gas in the lake. Therefore, although steady lava lake behavior at Halema`uma`u may be deeply driven by upwelling of magma, we argue that the sporadic interruptions to this behavior are the result of shallow processes occurring near the lake surface. These observations provide a cautionary note that some lava lake behavior is not representative of deep-seated processes. This behavior also highlights the complex and dynamic nature of lava lake activity.

  6. A correction factor to f-chart predictions of active solar fraction in active-passive heating systems

    Evans, B. L.; Beckman, W. A.; Duffie, J. A.; Mitchell, J. W.; Klein, S. A.

    1983-11-01

    The extent to which a passive system degrades the performance of an active solar space heating system was investigated, and a correction factor to account for these interactions was developed. The transient system simulation program TRNSYS is used to simulate the hour-by-hour performance of combined active-passive (hybrid) space heating systems in order to compare the active system performance with simplified design method predictions. The TRNSYS simulations were compared to results obtained using the simplified design calculations of the f-Chart method. Comparisons of TRNSYS and f-Chart were used to establish the accuracy of the f-Charts for active systems. A correlation was then developed to correct the monthly loads input into the f-Chart method to account for controller deadbands in both hybrid and active only buildings. A general correction factor was generated to be applied to the f-Chart method to produce more accurate and useful results for hybrid systems.

  7. Early functional magnetic resonance imaging activations predict language outcome after stroke.

    Saur, Dorothee; Ronneberger, Olaf; Kümmerer, Dorothee; Mader, Irina; Weiller, Cornelius; Klöppel, Stefan

    2010-04-01

    An accurate prediction of system-specific recovery after stroke is essential to provide rehabilitation therapy based on the individual needs. We explored the usefulness of functional magnetic resonance imaging scans from an auditory language comprehension experiment to predict individual language recovery in 21 aphasic stroke patients. Subjects with an at least moderate language impairment received extensive language testing 2 weeks and 6 months after left-hemispheric stroke. A multivariate machine learning technique was used to predict language outcome 6 months after stroke. In addition, we aimed to predict the degree of language improvement over 6 months. 76% of patients were correctly separated into those with good and bad language performance 6 months after stroke when based on functional magnetic resonance imaging data from language relevant areas. Accuracy further improved (86% correct assignments) when age and language score were entered alongside functional magnetic resonance imaging data into the fully automatic classifier. A similar accuracy was reached when predicting the degree of language improvement based on imaging, age and language performance. No prediction better than chance level was achieved when exploring the usefulness of diffusion weighted imaging as well as functional magnetic resonance imaging acquired two days after stroke. This study demonstrates the high potential of current machine learning techniques to predict system-specific clinical outcome even for a disease as heterogeneous as stroke. Best prediction of language recovery is achieved when the brain activation potential after system-specific stimulation is assessed in the second week post stroke. More intensive early rehabilitation could be provided for those with a predicted poor recovery and the extension to other systems, for example, motor and attention seems feasible. PMID:20299389

  8. Human activity and landscape change at Adjiyska Vodenitsa, central Bulgaria

    Chiverrell, R. C.; Archibald, Z.

    2009-04-01

    The Classical and early Hellenistic settlement located at Adjiyska Vodenitsa, near Vetren, in the centre of ancient Thrace, is somewhat unusual in displaying well-preserved evidence for the commercial and cultural interactions associated with a river port. The settlement evolved through a series of phases, with traces of activity emerging around the beginning of the fifth, advancing to a progressive close in the second century BCE. The settlement at Adjiyska Vodenitsa owed its raison d'être to river traffic, with the river as the primary means for importing commodities (non-local amphorae and roof tiles). The Pistiros inscription indicates that overland traffic was also important, presumably over the Rhodopes Mountains to the south. The relationship between the site and the Maritsa River is thus important. Located towards the head of the Maritsa basin downstream of the Momina Klissoura gorge near Belovo, the settlement is perched on a steeply-edged toe of the Vetren tributary alluvial fan, with the bluff trimmed by the migrating River Maritsa. The site is c.12-14 metres above the current bed of the River Maritsa, high and dry away from contemporary flooding, intriguing given evidence for flooding during occupation. The fluvial system has clearly been dynamic and changed much during the last 3000 years. Changes in the Maritsa have been constrained with radiocarbon ages obtained for two fan terrace levels. Active channel and overbank environments of the higher B1 terrace are dated to c. 520-400 cal. BC and provide a terminus post quem for the incision to the lower terrace (B2). The radiocarbon dating of basal contexts from the lower terrace palaeo-channels provides a terminus ante quem for abandonment of the higher terrace of cal. AD 1010-1150. Thus basal lowering and a shift to greater lateral channel activity appear to coincide with the abandonment of Adjiyska Vodenitsa. Upstream of the Momina Klissoura Gorge evidence for heightened geomorphic activity probably

  9. Climate Change Adaptation Science Activities at NASA Johnson Space Center

    Stefanov, William L.; Lulla, Kamlesh

    2012-01-01

    The Johnson Space Center (JSC), located in the southeast metropolitan region of Houston, TX is the prime NASA center for human spaceflight operations and astronaut training, but it also houses the unique collection of returned extraterrestrial samples, including lunar samples from the Apollo missions. The Center's location adjacent to Clear Lake and the Clear Creek watershed, an estuary of Galveston Bay, puts it at direct annual risk from hurricanes, but also from a number of other climate-related hazards including drought, floods, sea level rise, heat waves, and high wind events all assigned Threat Levels of 2 or 3 in the most recent NASA Center Disaster/Risk Matrix produced by the Climate Adaptation Science Investigator Working Group. Based on prior CASI workshops at other NASA centers, it is recognized that JSC is highly vulnerable to climate-change related hazards and has a need for adaptation strategies. We will present an overview of prior CASI-related work at JSC, including publication of a climate change and adaptation informational data brochure, and a Resilience and Adaptation to Climate Risks Workshop that was held at JSC in early March 2012. Major outcomes of that workshop that form a basis for work going forward are 1) a realization that JSC is embedded in a regional environmental and social context, and that potential climate change effects and adaptation strategies will not, and should not, be constrained by the Center fence line; 2) a desire to coordinate data collection and adaptation planning activities with interested stakeholders to form a regional climate change adaptation center that could facilitate interaction with CASI; 3) recognition that there is a wide array of basic data (remotely sensed, in situ, GIS/mapping, and historical) available through JSC and other stakeholders, but this data is not yet centrally accessible for planning purposes.

  10. Narrative Focus Predicts Symptom Change Trajectories in Group Treatment for Traumatized and Bereaved Adolescents.

    Grassetti, Stevie N; Herres, Joanna; Williamson, Ariel A; Yarger, Heather A; Layne, Christopher M; Kobak, Roger

    2015-01-01

    Growing evidence supports the effectiveness of Trauma and Grief Component Therapy for Adolescents (TGCT-A) in reducing posttraumatic stress disorder (PTSD) symptoms and maladaptive grief (MG) reactions. This pilot study explored whether the specific focus of students' narratives (i.e., focus on trauma vs. focus on loss) as shared by TGCT-A group members would predict initial pretreatment levels, as well as pre- to posttreatment change trajectories, of PTSD symptoms and MG reactions. Thirty-three adolescents from three middle schools completed a 17-week course of group-based TGCT-A. PTSD and MG symptoms were assessed at pretreatment, twice during treatment, and at posttreatment. The focus (trauma vs. loss) of each student's narrative was coded using transcripts of members' narratives as shared within the groups. The reliable change index showed that 61% of students reported reliable pre-post improvement in either PTSD symptoms or MG reactions. Students whose narratives focused on loss both reported higher starting levels and showed steeper rates of decline in MG reactions than students whose narratives focused on trauma. In contrast, students whose narratives focused on trauma reported higher starting levels of PTSD than students who narrated loss experiences. However, narrative focus was not significantly linked to the rate at which PTSD symptoms declined over the course of treatment. This study provides preliminary evidence that TGCT-A treatment components are associated with reduced PTSD symptoms and MG reactions. Loss-focused narratives, in particular, appear to be associated with greater decreases in MG reactions. PMID:24927497

  11. Anxiety Sensitivity Uniquely Predicts Exercise Behaviors in Young Adults Seeking to Increase Physical Activity.

    Moshier, Samantha J; Szuhany, Kristin L; Hearon, Bridget A; Smits, Jasper A J; Otto, Michael W

    2016-01-01

    Individuals with elevated levels of anxiety sensitivity (AS) may be motivated to avoid aversive emotional or physical states, and therefore may have greater difficulty achieving healthy behavioral change. This may be particularly true for exercise, which produces many of the somatic sensations within the domain of AS concerns. Cross-sectional studies show a negative association between AS and exercise. However, little is known about how AS may prospectively affect attempts at behavior change in individuals who are motivated to increase their exercise. We recruited 145 young adults who self-identified as having a desire to increase their exercise behavior. Participants completed a web survey assessing AS and additional variables identified as important for behavior change-impulsivity, grit, perceived behavioral control, and action planning-and set a specific goal for exercising in the next week. One week later, a second survey assessed participants' success in meeting their exercise goals. We hypothesized that individuals with higher AS would choose lower exercise goals and would complete less exercise at the second survey. AS was not significantly associated with exercise goal level, but significantly and negatively predicted exercise at Time 2 and was the only variable to offer significant prediction beyond consideration of baseline exercise levels. These results underscore the importance of considering AS in relation to health behavior intentions. This is particularly apt given the absence of prediction offered by other traditional predictors of behavior change. PMID:26342011

  12. Climate change impact on the activities of Electricite de France

    Water resource is of prime importance for a producer of electricity like Electricite de France. As a matter of fact, EDF manages about 75 % of the French surface waters through hydro electricity which represents about 13 % of its production. EDF also needs access to water for the cooling of its thermal power plants, especially nuclear power plants which represent between 75 and 80 % of its electric production. Climate change is then studied with much care in order to be able to predict its effects on the future water repartition in time and place. The paper presents the results of studies carried out on the French Loire and Rhone rivers, using different climate models, with the assumption of doubling CO2 in the atmosphere (which could happen during the second half of the century). Future river temperatures and flows have been quantified, showing in particular an increase of river flows in winter, and a rather large decrease in summer. These results will have to be taken into account for the future management of the power plants (some experience has already been drawn after the very hot 2003 summer), especially during dry periods when scarce waters will have to be shared between the various users (drinking water, irrigation, tourism, industries and hydroelectricity). (authors)

  13. Hydrophysical conditions and periphyton in natural rivers. Analysis and predictive modelling of periphyton by changed regulations

    The objective of this thesis has been to examine the interaction between hydrodynamical and physical factors and the temporal and spatial dynamics of periphyton in natural steep rivers. The study strategy has been to work with quantitative system variables to be able to evaluate the potential usability of a predictive model for periphyton changes as a response to river regulations. The thesis is constituted by a theoretical and an empirical study. The theoretical study is aimed at presenting a conceptual model of the relevant factors based on an analysis of published studies. Effort has been made to evaluate and present the background material in a structured way. To concurrently handle the spatial and temporal dynamics of periphyton a new method for data collection has been developed. A procedure for quantifying the photo registrations has been developed. The simple hydrodynamical parameters were estimated from a set of standard formulas whereas the complex parameters were estimated from a three dimensional simulation model called SSIIM. The main conclusion from the analysis is that flood events are the major controlling factors wrt. periphyton biomass and that water temperature is of major importance for the periphyton resistance. Low temperature clearly increases the periphyton erosion resistance. Thus, to model or control the temporal dynamics the river periphyton, the water temperature and the frequency and size of floods should be regarded the most significant controlling factors. The data in this study has been collected from a river with a stable water quality and frequent floods. 109 refs., 41 figs., 34 tabs

  14. Predicting Impacts of Future Climate Change on the Distribution of the Widespread Conifer Platycladus orientalis.

    Xian-Ge Hu

    Full Text Available Chinese thuja (Platycladus orientalis has a wide but fragmented distribution in China. It is an important conifer tree in reforestation and plays important roles in ecological restoration in the arid mountains of northern China. Based on high-resolution environmental data for current and future scenarios, we modeled the present and future suitable habitat for P. orientalis, evaluated the importance of environmental factors in shaping the species' distribution, and identified regions of high risk under climate change scenarios. The niche models showed that P. orientalis has suitable habitat of ca. 4.2×106 km2 across most of eastern China and identified annual temperature, monthly minimum and maximum ultraviolet-B radiation and wet-day frequency as the critical factors shaping habitat availability for P. orientalis. Under the low concentration greenhouse gas emissions scenario, the range of the species may increase as global warming intensifies; however, under the higher concentrations of emissions scenario, we predicted a slight expansion followed by contraction in distribution. Overall, the range shift to higher latitudes and elevations would become gradually more significant. The information gained from this study should be an useful reference for implementing long-term conservation and management strategies for the species.

  15. Ontogeny constrains phenology: opportunities for activity and reproduction interact to dictate potential phenologies in a changing climate.

    Levy, Ofir; Buckley, Lauren B; Keitt, Timothy H; Angilletta, Michael J

    2016-06-01

    As global warming has lengthened the active seasons of many species, we need a framework for predicting how advances in phenology shape the life history and the resulting fitness of organisms. Using an individual-based model, we show how warming differently affects annual cycles of development, growth, reproduction and activity in a group of North American lizards. Populations in cold regions can grow and reproduce more when warming lengthens their active season. However, future warming of currently warm regions advances the reproductive season but reduces the survival of embryos and juveniles. Hence, stressful temperatures during summer can offset predicted gains from extended growth seasons and select for lizards that reproduce after the warm summer months. Understanding these cascading effects of climate change may be crucial to predict shifts in the life history and demography of species. PMID:26970104

  16. Five-year change in physical activity is associated with changes in cardiovascular disease risk factors: the Inter99 study

    Aadahl, Mette; von Huth Smith, L; Pisinger, Charlotte;

    2009-01-01

    OBJECTIVE: To evaluate whether five-year changes in self-reported physical activity level were associated with changes in waist circumference, weight, serum lipids and blood pressure. METHODS: In the Inter99 study (1999-2006) in Copenhagen, Denmark, 4039 men and women (30-60 years) answered quest....... Change in physical activity level induced a significant change in HDL concentration in men only. Women's use of hormone replacement therapy may partly explain this gender difference....

  17. Can we better use existing and emerging computing hardware to embed activity coefficient predictions in complex atmospheric aerosol models?

    Topping, David; Alibay, Irfan; Ruske, Simon; Hindriksen, Vincent; Noisternig, Michael

    2016-04-01

    To predict the evolving concentration, chemical composition and ability of aerosol particles to act as cloud droplets, we rely on numerical modeling. Mechanistic models attempt to account for the movement of compounds between the gaseous and condensed phases at a molecular level. This 'bottom up' approach is designed to increase our fundamental understanding. However, such models rely on predicting the properties of molecules and subsequent mixtures. For partitioning between the gaseous and condensed phases this includes: saturation vapour pressures; Henrys law coefficients; activity coefficients; diffusion coefficients and reaction rates. Current gas phase chemical mechanisms predict the existence of potentially millions of individual species. Within a dynamic ensemble model, this can often be used as justification for neglecting computationally expensive process descriptions. Indeed, on whether we can quantify the true sensitivity to uncertainties in molecular properties, even at the single aerosol particle level it has been impossible to embed fully coupled representations of process level knowledge with all possible compounds, typically relying on heavily parameterised descriptions. Relying on emerging numerical frameworks, and designed for the changing landscape of high-performance computing (HPC), in this study we show that comprehensive microphysical models from single particle to larger scales can be developed to encompass a complete state-of-the-art knowledge of aerosol chemical and process diversity. We focus specifically on the ability to capture activity coefficients in liquid solutions using the UNIFAC method, profiling traditional coding strategies and those that exploit emerging hardware.

  18. PASS-Predicted Hepatoprotective Activity of Caesalpinia sappan in Thioacetamide-Induced Liver Fibrosis in Rats

    Farkaad A. Kadir

    2014-01-01

    Full Text Available The antifibrotic effects of traditional medicinal herb Caesalpinia sappan (CS extract on liver fibrosis induced by thioacetamide (TAA and the expression of transforming growth factor β1 (TGF-β1, α-smooth muscle actin (αSMA, and proliferating cell nuclear antigen (PCNA in rats were studied. A computer-aided prediction of antioxidant and hepatoprotective activities was primarily performed with the Prediction Activity Spectra of the Substance (PASS Program. Liver fibrosis was induced in male Sprague Dawley rats by TAA administration (0.03% w/v in drinking water for a period of 12 weeks. Rats were divided into seven groups: control, TAA, Silymarin (SY, and CS 300 mg/kg body weight and 100 mg/kg groups. The effect of CS on liver fibrogenesis was determined by Masson’s trichrome staining, immunohistochemical analysis, and western blotting. In vivo determination of hepatic antioxidant activities, cytochrome P450 2E1 (CYP2E1, and matrix metalloproteinases (MPPS was employed. CS treatment had significantly increased hepatic antioxidant enzymes activity in the TAA-treated rats. Liver fibrosis was greatly alleviated in rats when treated with CS extract. CS treatment was noted to normalize the expression of TGF-β1, αSMA, PCNA, MMPs, and TIMP1 proteins. PASS-predicted plant activity could efficiently guide in selecting a promising pharmaceutical lead with high accuracy and required antioxidant and hepatoprotective properties.

  19. Predicting kinase activity in angiotensin receptor phosphoproteomes based on sequence-motifs and interactions.

    Rikke Bøgebo

    Full Text Available Recent progress in the understanding of seven-transmembrane receptor (7TMR signalling has promoted the development of a new generation of pathway selective ligands. The angiotensin II type I receptor (AT1aR is one of the most studied 7TMRs with respect to selective activation of the β-arrestin dependent signalling. Two complimentary global phosphoproteomics studies have analyzed the complex signalling induced by the AT1aR. Here we integrate the data sets from these studies and perform a joint analysis using a novel method for prediction of differential kinase activity from phosphoproteomics data. The method builds upon NetworKIN, which applies sophisticated linear motif analysis in combination with contextual network modelling to predict kinase-substrate associations with high accuracy and sensitivity. These predictions form the basis for subsequently nonparametric statistical analysis to identify likely activated kinases. This suggested that AT1aR-dependent signalling activates 48 of the 285 kinases detected in HEK293 cells. Of these, Aurora B, CLK3 and PKG1 have not previously been described in the pathway whereas others, such as PKA, PKB and PKC, are well known. In summary, we have developed a new method for kinase-centric analysis of phosphoproteomes to pinpoint differential kinase activity in large-scale data sets.

  20. Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors

    Avval Zhila Mohajeri

    2015-01-01

    Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.

  1. Solar activity, geomagnetic perturbations and Vrancea (Romania) earthquake short-term predictability

    The paper presents the main results of applying the electromagnetic method for the short- term prediction of Vrancea earthquakes. The results are based on electromagnetic records made at Muntele Rosu Geophysical Observatory in Romania during the period December 1997 to July 2003. The paper highlights the importance as a precursor factor of the magnetic impedance BZ/BX, where BZ is the vertical component of the geomagnetic flux density and BX its horizontal component. The time variation of BZ/BX is closely examined in correlation with Vrancea seismic activity. The variations are compared to the geomagnetic perturbation of Ak > 20 (magnetic storms) that are generated by solar activity. Relations between these three factors, i.e. the BZ/BX ratio, magnetic storms, and Vrancea seismic activity are seen to combine into five distinct situations. The feasibility and difficulties of using the electromagnetic method for the short-term prediction of Vrancea earthquakes are examined in the final section. (authors)

  2. Do Cardiovascular Responses to Active and Passive Coping Tasks predict Future Blood Pressure over a 10-Month Later?

    Yuenyongchaiwat, Kornanong; Baker, Ian; Maratos, Frankie; Sheffield, David

    2016-01-01

    The study examined whether cardiovascular responses to active or passive coping tasks and single or multiple tasks predicted changes in resting blood pressure (BP) over a ten-month period. Heart rate (HR), BP, cardiac output (CO), and total peripheral resistance (TPR) were measured at rest, and during mental stress tests (mental arithmetic, speech, and cold pressor tasks). A total of 104 eligible participants participated in the initial study, and 77 (74.04%) normotensive adult participants' resting BP were re-evaluated at ten-month follow-up. Regression analyses indicated that after adjustment for baseline BP, initial age, gender, body mass index, family history of cardiovascular disease, and current cigarette smoking, heighted systolic blood pressure (SBP) and HR responses to an active coping task (mental arithmetic) were associated with increased future SBP (ΔR2 = .060, ΔR2 = .045, respectively). Further, aggregated SBP responsivity (over the three tasks) to the predictor models resulted in significant, but smaller increases in ΔR2 accounting for .040 of the variance of follow-up SBP. These findings suggest that cardiovascular responses to active coping tasks predict future SBP. Further, compared with single tasks, the findings revealed that SBP responses to three tasks were less predictive compared to an individual task (i.e., mental arithmetic). Of importance, hemodynamic reactivity (namely CO and TPR) did not predict future BP suggesting that more general psychophysiological processes (e.g., inflammation, platelet aggregation) may be implicated, or that BP, but not hemodynamic reactivity may be a marker of hypertension. PMID:26972632

  3. Predicting fire activity in the US over the next 50 years using new IPCC climate projections

    Wang, D.; Morton, D. C.; Collatz, G. J.

    2012-12-01

    Fire is an integral part of the Earth system with both direct and indirect effects on terrestrial ecosystems, the atmosphere, and human societies (Bowman et al. 2009). Climate conditions regulate fire activities through a variety of ways, e.g., influencing the conditions for ignition and fire spread, changing vegetation growth and decay and thus the accumulation of fuels for combustion (Arora and Boer 2005). Our recent study disclosed the burned area (BA) in US is strongly correlated with potential evaporation (PE), a measurement of climatic dryness derived from National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) climate data (Morton et al. 2012). The correlation varies spatially and temporally. With regard to fire of peak fire seasons, Northwestern US, Great Plains and Alaska have the strongest BA/PE relationship. Using the recently released the Global Fire Emissions Database (GFED) Version 3 (van der Werf et al. 2010), we showed increasing BA in the last decade in most of NCA regions. Longer time series of Monitoring Trends in Burn Severity (MTBS) (Eidenshink et al. 2007) data showed the increasing trends occurred in all NCA regions from 1984 to 2010. This relationship between BA and PE provides us the basis to predict the future fire activities in the projected climate conditions. In this study, we build spatially explicit predictors using the historic PE/BA relationship. PE from 2011 to 2060 is calculated from the Coupled Model Intercomparison Project Phase 5 (CMIP5) data and the historic PE/BA relationship is then used to estimate BA. This study examines the spatial pattern and temporal dynamics of the future US fires driven by new climate predictions for the next 50 years. Reference: Arora, V.K., & Boer, G.J. (2005). Fire as an interactive component of dynamic vegetation models. Journal of Geophysical Research-Biogeosciences, 110 Bowman, D.M.J.S., Balch, J.K., Artaxo, P., Bond, W.J., Carlson, J.M., Cochrane, M.A., D

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

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

    2013-01-01

    The theory of planned behaviour (TPB) can identify cognitions that predict differences in behaviour between individuals. However, it is not clear whether the TPB can predict the behaviour of an individual person. This study employs a series of n-of-1 studies and time series analyses to examine the ability of the TPB to predict physical activity (PA) behaviours of six individuals. Six n-of-1 studies were conducted, in which TPB cognitions and up to three PA behaviours (walking, gym workout and a personally defined PA) were measured twice daily for six weeks. Walking was measured by pedometer step count, gym attendance by self-report with objective validation of gym entry and the personally defined PA behaviour by self-report. Intra-individual variability in TPB cognitions and PA behaviour was observed in all participants. The TPB showed variable predictive utility within individuals and across behaviours. The TPB predicted at least one PA behaviour for five participants but had no predictive utility for one participant. Thus, n-of-1 designs and time series analyses can be used to test theory in an individual. PMID:22943555

  5. Prediction of future climate change for the Blue Nile, using a nested Regional Climate Model

    Soliman, E.; Jeuland, M.

    2009-04-01

    Although the Nile River Basin is rich in natural resources, it faces many challenges. Rainfall is highly variable across the region, on both seasonal and inter-annual scales. This variability makes the region vulnerable to droughts and floods. Many development projects involving Nile waters are currently underway, or being studied. These projects will lead to land-use patterns changes and water distribution and availability. It is thus important to assess the effects of a) these projects and b) evolving water resource management and policies, on regional hydrological processes. This paper seeks to establish a basis for evaluation of such impacts within the Blue Nile River sub-basin, using the RegCM3 Regional Climate Model to simulate interactions between the land surface and climatic processes. We first present results from application of this RCM model nested with downscaled outputs obtained from the ECHAM5/MPI-OM1 transient simulations for the 20th Century. We then investigate changes associated with mid-21st century emissions forcing of the SRES A1B scenario. The results obtained from the climate model are then fed as inputs to the Nile Forecast System (NFS), a hydrologic distributed rainfall runoff model of the Nile Basin, The interaction between climatic and hydrological processes on the land surface has been fully coupled. Rainfall patterns and evaporation rates have been generated using RegCM3, and the resulting runoff and Blue Nile streamflow patterns have been simulated using the NFS. This paper compares the results obtained from the RegCM3 climate model with observational datasets for precipitation and temperature from the Climate Research Unit (UK) and the NASA Goddard Space Flight Center GPCP (USA) for 1985-2000. The validity of the streamflow predictions from the NFS is assessed using historical gauge records. Finally, we present results from modeling of the A1B emissions scenario of the IPCC for the years 2034-2055. Our results indicate that future

  6. Prediction of future climate change for the Blue Nile, using RCM nested in GCM

    Sayed, E.; Jeuland, M.; Aty, M.

    2009-04-01

    Although the Nile River Basin is rich in natural resources, it faces many challenges. Rainfall is highly variable across the region, on both seasonal and inter-annual scales. This variability makes the region vulnerable to droughts and floods. Many development projects involving Nile waters are currently underway, or being studied. These projects will lead to land-use patterns changes and water distribution and availability. It is thus important to assess the effects of a) these projects and b) evolving water resource management and policies, on regional hydrological processes. This paper seeks to establish a basis for evaluation of such impacts within the Blue Nile River sub-basin, using the RegCM3 Regional Climate Model to simulate interactions between the land surface and climatic processes. We first present results from application of this RCM model nested with downscaled outputs obtained from the ECHAM5/MPI-OM1 transient simulations for the 20th Century. We then investigate changes associated with mid-21st century emissions forcing of the SRES A1B scenario. The results obtained from the climate model are then fed as inputs to the Nile Forecast System (NFS), a hydrologic distributed rainfall runoff model of the Nile Basin, The interaction between climatic and hydrological processes on the land surface has been fully coupled. Rainfall patterns and evaporation rates have been generated using RegCM3, and the resulting runoff and Blue Nile streamflow patterns have been simulated using the NFS. This paper compares the results obtained from the RegCM3 climate model with observational datasets for precipitation and temperature from the Climate Research Unit (UK) and the NASA Goddard Space Flight Center GPCP (USA) for 1985-2000. The validity of the streamflow predictions from the NFS is assessed using historical gauge records. Finally, we present results from modeling of the A1B emissions scenario of the IPCC for the years 2034-2055. Our results indicate that future

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

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

    2012-01-01

    Abstract Background Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model’s predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children’s active school travel. Method Participants (N = 126 children aged 8–9 years; 5...

  8. Development of a robotized sample changing system for activation analysis

    An automatic sample changing system with a small robot has been developed and constructed for instrumental neutron activation analysis (INAA). The developed system composed of a model A151 small robot (CRS Plus Inc., Canada), a NEC PC-980m2 personal computer having two of 1 Mbyte floppy-disk drivers, a NAIG NLAB-MCA multichannel analyzer (Toshiba), Ge detector settled in a low background shield and a tray stored 20 dishes containing a sample. The robot has a five-axis articulated arm (reach: 560 mm, payload: 2 kg, speed: 17 m/s, repeatability: 0.13 mm, weight: 17 kg). The robot and the multichannel analyzer (MCA) are controlled by the personal computer via RS-232C or GP-IB interface. (author)

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

    Manenti, Tommaso

    such as anti-predator behaviours or the activation of mechanisms to prevent thermal stress injuries suggest that plasticity is an adaptive response, favoured by natural selection. At the same time, organisms do show limited plastic responses, indicating that this ability is not for free. Costs and...... benefits of a plastic response are expected to depend on the environmental conditions experienced by organisms. Thus, in populations exposed to a non-changing environment, the plastic machinery might be a waste of resources. Contrary, in populations experiencing varying environmental conditions, plasticity...... selected Drosophila simulans for many generations in three thermal regimes, specifically designed to affect the levels of plasticity. The three environments were found to induce high levels of plasticity and to affect stress resistance and life history traits differently. However, flies selected in...

  10. Structural change in the petroleum activities; Strukturendringer i petroleumsvirksomheten

    2009-07-01

    The report is twofold. First it is described a reference situation for the petroleum industry based on qualitative and quantitative parameters. The purpose of this section is to form a basis of a future observation can be assessed. Then referred the views and reviews a wide range of stake holders in the industry has about how the structures in the petroleum industry will evolve in the years ahead. The views and reviews that are reproduced are from players in the petroleum industry itself, represented by 48 companies and organizations, and are not the views or opinions of Ministry of Petroleum and Energy. Participants' attention is mainly focused on how StatoilHydro will affect the industry, but it is also a general perception that there are many other factors that are just as important for how the industry will evolve in the long term. Participants' views will help to identify trends that may affect the player image. The project is not intended to constitute a strategy for or how to accommodate structural changes in the petroleum industry. The report discusses not systematically the structural changes that will be positive or negative for the industry and proposes no measures that will affect them. In Chapter 5, however, rendered what the various players in the interview rounds have proposed measures to counter the various structural changes. Finally touches the report not the significance of structural changes in the industry may have on health, safety and environment (HSE) in activity. The views and reviews from the players were passed in 2008, before the problems in the financial industry gained a considerable extent. Data and forecasts are also prepared during this period. Reviews in the report were accordingly given before one learned about the extent of the economic development and are not revised in the afterwards. Ministry of Petroleum and Energy will in the years ahead have to have a continuous attention to the issues described in this report. It

  11. An improved model for predicting coolant activity behaviour for fuel-failure monitoring analysis

    El-Jaby, A.; Lewis, B.J.; Thompson, W.T. [Department of Chemistry and Chemical Engineering, Royal Military College of Canada, Kingston, Ontario, K7K 7B4 (Canada); Iglesias, F.C. [Candesco Corporation, 230 Richmond Street West, 10th Floor, Toronto, Ontario, M5V 1V6 (Canada); Ip, Monique [Bruce Power, 123 Front Street West, 4th Floor Toronto, Ontario, M5J 2M2 (Canada)

    2009-06-15

    ), that is applicable in all operating reactor conditions, and which accounts for the changing condition of the defect. Previous work focused on the development of a general fission product release model for defective fuel using the COMSOL Multiphysics finite-element commercial platform. The current work synthesizes all previous theoretical treatments with the solution of the general time-dependent model using a custom-developed finite-difference variable mesh (FDVM) numerical treatment as a stand-alone tool (code). This model, entitled STAR (Steady-state and Transient Activity Release), is able to specifically predict the fission product activity behaviour in the UO{sub 2} fuel matrix, fuel-to-sheath gap, and PHTS coolant, while respecting the overall fission product mass-balance under all reactor operating conditions, including: startup, steady-state, shutdown, and bundle-shifting manoeuvres. In addition, an improved ability to predict the PHTS coolant activity of the Xe-135 isotope in commercial reactors is discussed. Moreover, a method to approximate both the burnup and the amount of the tramp uranium deposits in-core, as well as the tramp uranium fission rate is proposed. The model parameters are derived from in-reactor experiments conducted with defective fuel elements containing natural and artificial failures at the Chalk River Laboratories (CRL). The STAR code has also been successfully validated against analytical solutions to the release-to-birth ratio R/B of both short and long-lived fission product species, as well as the specific analytical solution to the coolant activity of {sup 129}I. In addition, STAR has been benchmarked against several documented defect occurrences in a commercial reactor. Lastly, the performance of the FDVM numerical algorithm implemented in the stand-alone STAR C++ code has been benchmarked against the COMSOL Multiphysics finite-element implementation. (authors)

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

    Langer, Shelby L; 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 predi...

  13. Changing physical activity and sedentary behaviour in people with COPD.

    Cavalheri, Vinicius; Straker, Leon; Gucciardi, Daniel F; Gardiner, Paul A; Hill, Kylie

    2016-04-01

    People with chronic obstructive pulmonary disease (COPD) engage in low levels of physical activity (PA). Given the evidence for the health benefits associated with participating in 150 min of moderate-to-vigorous intensity PA each week, there is considerable interest in methods to increase PA in people with COPD. Studies to date have focused largely on exercise training and behavioural approaches, and many have demonstrated minimal, if any effect. An intermediate goal that focuses on reducing time spent in sedentary behaviour (SB) and increasing participation in light intensity PA is a more realistic goal in this population and offers a gateway to higher intensity PA. Although strategies that are capable of reducing time spent in SB in COPD are unknown, studies that have shown some increase in PA in this population often provide individualized goal setting, motivational interviewing and frequent contact with health-care professionals to provide advice regarding strategies to overcome barriers. Therefore, these approaches should be considered in interventions to reduce time in SB. There are a range of devices available to monitor time in SB for use in both clinical and research settings. To move this area forward, a theoretically informed and systematic approach to behaviour change is needed. The theoretical model, the 'behaviour change wheel', is described and an example is provided of how it can be applied to a person with COPD. PMID:26560834

  14. Complexity in relational processing predicts changes in functional brain network dynamics.

    Cocchi, Luca; Halford, Graeme S; Zalesky, Andrew; Harding, Ian H; Ramm, Brentyn J; Cutmore, Tim; Shum, David H K; Mattingley, Jason B

    2014-09-01

    The ability to link variables is critical to many high-order cognitive functions, including reasoning. It has been proposed that limits in relating variables depend critically on relational complexity, defined formally as the number of variables to be related in solving a problem. In humans, the prefrontal cortex is known to be important for reasoning, but recent studies have suggested that such processes are likely to involve widespread functional brain networks. To test this hypothesis, we used functional magnetic resonance imaging and a classic measure of deductive reasoning to examine changes in brain networks as a function of relational complexity. As expected, behavioral performance declined as the number of variables to be related increased. Likewise, increments in relational complexity were associated with proportional enhancements in brain activity and task-based connectivity within and between 2 cognitive control networks: A cingulo-opercular network for maintaining task set, and a fronto-parietal network for implementing trial-by-trial control. Changes in effective connectivity as a function of increased relational complexity suggested a key role for the left dorsolateral prefrontal cortex in integrating and implementing task set in a trial-by-trial manner. Our findings show that limits in relational processing are manifested in the brain as complexity-dependent modulations of large-scale networks. PMID:23563963

  15. Numerical model predictions of autogenic fluvial terraces and comparison to climate change expectations

    Limaye, Ajay B. S.; Lamb, Michael P.

    2016-03-01

    Terraces eroded into sediment (alluvial) and bedrock (strath) preserve an important history of river activity. River terraces are thought to form when a river switches from a period of slow vertical incision and valley widening to fast vertical incision and terrace abandonment. Consequently, terraces are often interpreted to reflect changing external drivers including tectonics, sea level, and climate. In contrast, the intrinsic unsteadiness of lateral migration in rivers may generate terraces even under constant rates of vertical incision without external forcing. To explore this mechanism, we simulate landscape evolution by a vertically incising, meandering river and isolate the age and geometry of autogenic river terraces. Modeled autogenic terraces form for a wide range of lateral and vertical incision rates and are often paired and longitudinally extensive for intermediate ratios of vertical-to-lateral erosion rate. Autogenic terraces have a characteristic reoccurrence time that scales with the time for relief generation. There is a preservation bias against older terraces due to reworking of previously visited parts of the valley. Evolving, spatial differences in bank strength between bedrock and sediment reduce terrace formation frequency and length, favor pairing, and can explain sublinear terrace margins at valley boundaries. Age differences and geometries for modeled autogenic terraces are consistent, in cases, with natural terraces and overlap with metrics commonly attributed to terrace formation due to climate change. We suggest a new phase space of terrace properties that may allow differentiation of autogenic terraces from terraces formed by external drivers.

  16. 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; Debasish Mitra; Tuhin Ghosh

    2014-08-01

    In the Himalayan states of India, with increasing population and activities, large areas of forested land are being converted into other land-use features. There is a definite cause and effect relationship between changing practice for development and changes in land use. So, an estimation of land use dynamics and a futuristic trend pattern is essential. A combination of geospatial and statistical techniques were applied to assess the present and future land use/land cover scenario of Gangtok, the subHimalayan capital of Sikkim. Multi-temporal satellite imageries of the Landsat series were used to map the changes in land use of Gangtok from 1990 to 2010. Only three major land use classes (built-up area and bare land, step cultivated area, and forest) were considered as the most dynamic land use practices of Gangtok. The conventional supervised classification, and spectral indices-based thresholding using NDVI (Normalized Difference Vegetation Index) and SAVI (Soil Adjusted Vegetation Index) were applied along with the accuracy assessments. Markov modelling was applied for prediction of land use/land cover change and was validated. SAVI provides the most accurate estimate, i.e., the difference between predicted and actual data is minimal. Finally, a combination of Markov modelling and SAVI was used to predict the probable land-use scenario in Gangtok in 2020 AD, which indicted that more forest areas will be converted for step cultivation by the year 2020.

  17. Predicting Changes in High-Intensity Intermittent Running Performance with Acute Responses to Short Jump Rope Workouts in Children

    Martin Buchheit

    2014-09-01

    Full Text Available The aims of the present study were to 1 examine whether individual HR and RPE responses to a jump rope workout could be used to predict changes in high-intensity intermittent running performance in young athletes, and 2 examine the effect of using different methods to determine a smallest worthwhile change (SWC on the interpretation of group-average and individual changes in the variables. Before and after an 8-week high-intensity training program, 13 children athletes (10.6 ± 0.9 yr performed a high-intensity running test (30-15 Intermittent Fitness Test, VIFT and three jump rope workouts, where HR and RPE were collected. The SWC was defined as either 1/5th of the between-subjects standard deviation or the variable typical error (CV. After training, the large ~9% improvement in VIFT was very likely, irrespective of the SWC. Standardized changes were greater for RPE (very likely-to-almost certain, ~30-60% changes, ~4-16 times >SWC than for HR (likely-to-very likely, ~2-6% changes, ~1-6 times >SWC responses. Using the CV as the SWC lead to the smallest and greatest changes for HR and RPE, respectively. The predictive value for individual performance changes tended to be better for HR (74-92% than RPE (69%, and greater when using the CV as the SWC. The predictive value for no-performance change was low for both measures (<26%. Substantial decreases in HR and RPE responses to short jump rope workouts can predict substantial improvements in high-intensity running performance at the individual level. Using the CV of test measures as the SWC might be the better option.

  18. Final technical report. Can microbial functional traits predict the response and resilience of decomposition to global change?

    Allison, Steven D. [Univ. of California, Irvine, CA (United States)

    2015-09-24

    The role of specific micro-organisms in the carbon cycle, and their responses to environmental change, are unknown in most ecosystems. This knowledge gap limits scientists’ ability to predict how important ecosystem processes, like soil carbon storage and loss, will change with climate and other environmental factors. The investigators addressed this knowledge gap by transplanting microbial communities from different environments into new environments and measuring the response of community composition and carbon cycling over time. Using state-of-the-art sequencing techniques, computational tools, and nanotechnology, the investigators showed that microbial communities on decomposing plant material shift dramatically with natural and experimentally-imposed drought. Microbial communities also shifted in response to added nitrogen, but the effects were smaller. These changes had implications for carbon cycling, with lower rates of carbon loss under drought conditions, and changes in the efficiency of decomposition with nitrogen addition. Even when transplanted into the same conditions, microbial communities from different environments remained distinct in composition and functioning for up to one year. Changes in functioning were related to differences in enzyme gene content across different microbial groups. Computational approaches developed for this project allowed the conclusions to be tested more broadly in other ecosystems, and new computer models will facilitate the prediction of microbial traits and functioning across environments. The data and models resulting from this project benefit the public by improving the ability to predict how microbial communities and carbon cycling functions respond to climate change, nutrient enrichment, and other large-scale environmental changes.

  19. CHANGE@CERN:Task Force 4: Matching personnel to activities

    2002-01-01

    Our series on the work of the Task Forces moves on to Human Ressources at CERN. Staff mobility and topics related to contract policy were the main personnel issues to be considered by Task Force 4, led by John Ferguson, head of AS Division. The aim, as with the other Task Forces, was to find ways to focus resources on the LHC, and once again the recommendations recognise the opportunity to make constructive changes, in this case in Human Resources policy at CERN. Movement of staff between divisions at CERN has generally not been easy, with 'staff complements' (total numbers) set for each sector (research, accelerator, technical and administration). However, the restructuring of the accelerator sector (proposed by Task Force 5 and already agreed in principle) should allow some staff to move to LHC activities. More generally, Task Force 4 recommends that the Laboratory carries out a review of all activities, at a relatively detailed level, so as to identify the resources required to achieve specific goals (t...

  20. Predicting demographically sustainable rates of adaptation : Can great tit breeding time keep pace with climate change?

    Gienapp, Phillip; Lof, Marjolein; Reed, Thomas E.; McNamara, John; Verhulst, Simon; Visser, Marcel E.

    2013-01-01

    Populations need to adapt to sustained climate change, which requires micro-evolutionary change in the long term. A key question is how the rate of this micro-evolutionary change compares with the rate of environmental change, given that theoretically there is a 'critical rate of environmental chang

  1. A model for signal processing and predictive control of semi-active structural control system

    M-H Shih; W-P Sung; Ching-Jong Wang

    2009-06-01

    The theory for structural control has been well developed and applied to perform excellent energy dissipation using dampers. Both active and semi-active control systems may be used to decide on the optimal switch point of the damper based on the current and past structural responses to the excitation of external forces. However, numerous noises may occur when the control signals are accessed and transported thus causing a delay of the damper. Therefore, a predictive control technique that integrates an improved method of detecting the control signal based on the direction of the structural motion, and a calculator for detecting the velocity using the least-square polynomial regression is proposed in this research. Comparisons of the analytical data and experimental results show that this predictor is effective in switching the moving direction of the semi-active damper. This conclusion is further verified using the component and shaking table test with constant amplitude but various frequencies, and the El Centro earthquake test. All tests confirm that this predictive control technique is effective to alleviate the time delay problem of semi-active dampers. This predictive control technique promotes about 30% to 40% reduction of the structural displacement response and about 35% to 45% reduction of the structural acceleration response.

  2. Resting lateralized activity predicts the cortical response and appraisal of emotions: an fNIRS study.

    Balconi, Michela; Grippa, Elisabetta; Vanutelli, Maria Elide

    2015-12-01

    This study explored the effect of lateralized left-right resting brain activity on prefrontal cortical responsiveness to emotional cues and on the explicit appraisal (stimulus evaluation) of emotions based on their valence. Indeed subjective responses to different emotional stimuli should be predicted by brain resting activity and should be lateralized and valence-related (positive vs negative valence). A hemodynamic measure was considered (functional near-infrared spectroscopy). Indeed hemodynamic resting activity and brain response to emotional cues were registered when subjects (N = 19) viewed emotional positive vs negative stimuli (IAPS). Lateralized index response during resting state, LI (lateralized index) during emotional processing and self-assessment manikin rating were considered. Regression analysis showed the significant predictive effect of resting activity (more left or right lateralized) on both brain response and appraisal of emotional cues based on stimuli valence. Moreover, significant effects were found as a function of valence (more right response to negative stimuli; more left response to positive stimuli) during emotion processing. Therefore, resting state may be considered a predictive marker of the successive cortical responsiveness to emotions. The significance of resting condition for emotional behavior was discussed. PMID:25862673

  3. Development of a predictive model to determine micropollutant removal using granular activated carbon

    D. J. de Ridder

    2009-10-01

    Full Text Available The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log Kow, solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal.

    Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values.

  4. Development of a predictive model to determine micropollutant removal using granular activated carbon

    D. J. de Ridder

    2009-12-01

    Full Text Available The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log Kow, solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal.

    Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values for most solutes.

  5. Statistical analysis and verification of 3-hourly geomagnetic activity probability predictions

    Wang, Jingjing; Zhong, Qiuzhen; Liu, Siqing; Miao, Juan; Liu, Fanghua; Li, Zhitao; Tang, Weiwei

    2015-12-01

    The Space Environment Prediction Center (SEPC) has classified geomagnetic activity into four levels: quiet to unsettled (Kp 6). The 3-hourly Kp index prediction product provided by the SEPC is updated half hourly. In this study, the statistical conditional forecast models for the 3-hourly geomagnetic activity level were developed based on 10 years of data and applied to more than 3 years of data, using the previous Kp index, interplanetary magnetic field, and solar wind parameters measured by the Advanced Composition Explorer as conditional parameters. The quality of the forecast models was measured and compared against verifications of accuracy, reliability, discrimination capability, and skill of predicting all geomagnetic activity levels, especially the probability of reaching the storm level given a previous "calm" (nonstorm level) or "storm" (storm level) condition. It was found that the conditional models that used the previous Kp index, the peak value of BtV (the product of the total interplanetary magnetic field and speed), the average value of Bz (the southerly component of the interplanetary magnetic field), and BzV (the product of the southerly component of the interplanetary magnetic field and speed) over the last 6 h as conditional parameters provide a relative operating characteristic area of 0.64 and can be an appropriate predictor for the probability forecast of geomagnetic activity level.

  6. Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives.

    Zhang, Shuqun; Hou, Bo; Yang, Huaiyu; Zuo, Zhili

    2016-05-01

    Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer's disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r (2) = 0.988, q (2) = 0.757, ONC = 6; r (2) = 0.966, q (2) = 0.645, ONC = 5; and r (2) = 0.957, q (2) = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r (2) values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors. PMID:26832327

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

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

    2015-09-01

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

  8. Climate change impacts on chosen activities from the energy sector

    The present work, results of a study carried out about the possible impact of climate change on the energy sector in the province Camaguey are shown. First of all, the main activities in companies, utilities, and farms related to the most significant energy consumption were chosen in order to model corresponding equivalent fuel consumption. Impacts were determined taking into account differences between present and future consumptions for each kind of energy. In developed countries, this kind of work is done using well-known empirical-statistical models, which usually require a lot of data at a nation-wide scale, but to attempt it in an undeveloped country demands the use of specific methodology, which in this case was non-existent and required us to create it. This resulted in a carefully posed question since we had to take into consideration that the spatial scale is only that of a province, and so it was necessary, above all, to study specific characteristics of provincial fuel consumption. We used the Magic-Scengen system and SRES scenarios, and outputs of general circulation models like HadCM2 to obtain values of chosen climatic variables for use in energy consumption regression models, previously developed for each kind of activity in the corresponding companies, firm, and facilities included in the present research. It made possible to estimate energy consumption in each activity at the selected time periods centered at 2020, 2050, and 2080. The study shows that impact could rise the consumption by 2,5% of the present energy level in this territory

  9. Broca's region and Visual Word Form Area activation differ during a predictive Stroop task

    Wallentin, Mikkel; Gravholt, Claus Højbjerg; Skakkebæk, Anne

    2015-01-01

    Competing theories attempt to explain the function of Broca's area in single word processing. Studies have found the region to be more active during processing of pseudo words than real words and during infrequent words relative to frequent words and during Stroop (incongruent) color words compared...... to Non-Stroop (congruent) words. Two related theories explain these findings as reflecting either “cognitive control” processing in the face of conflicting input or a linguistic prediction error signal, based on a predictive coding approach. The latter implies that processing cost refers to...... violations of expectations based on the statistical distributions of input. In this fMRI experiment we attempted to disentangle single word processing cost originating from cognitive conflict and that stemming from predictive expectation violation. Participants (N = 49) responded to whether the words “GREEN...

  10. Prediction of the antiglycation activity of polysaccharides from Benincasa hispida using a response surface methodology.

    Jiang, Xiang; Kuang, Fei; Kong, Fansheng; Yan, Chunyan

    2016-10-20

    Benincasa hispida is a popular vegetable in China. Our previous experiments suggested that polysaccharides isolated from B. hispida fruits (PBH) have antiglycation effect and DPPH free radical scavenging activity. Ultrasonic treatments can be used to extract polysaccharides from Benincasa hispida (PBH). The aim of this study was to investigate the correlation between the ultrasonic treatment conditions and the antiglycation activity of PBH. A mathematical model was generated with an artificial neural network (ANN) toolbox from MATLAB to analyze the effects of ultrasonic treatment conditions on antiglycation activity. The response surface plots showed relationships between ultrasonic extraction conditions and bioactivity. The R(2) value of the model was 0.9919, which suggested good fitness of the neural network. The application of genetic algorithms showed that the optimal ultrasonic extraction conditions resulted in the highest antiglycation activity for PBH. These were 150W, 46°C, and 35min. These conditions produced a predicted antiglycation activity of 41.2%; the actual activity was 40.9% under optimal conditions. This is very close to the predicted value. The experimental data indicated that the PBH possessed both antiglycation and antioxidant activities. The maximum actual value of antiglycation was 101.7% that of the positive control, and the PBH inhibited the DPPH free radicals with an EC50 value of 0.98mg/mL. This is 66.2% that of ascorbic acid. These results explained the observations that B. hispida can decrease glucose levels in diabetic patients. The experimental results also showed that the ANN could be used for optimization and prediction. PMID:27474577

  11. Nestling activity levels during begging behaviour predicts activity level and body mass in adulthood

    McCowan, Luke S.C.; Griffith, Simon C

    2014-01-01

    Across a range of species including humans, personality traits, or differences in behaviour between individuals that are consistent over time, have been demonstrated. However, few studies have measured whether these consistent differences are evident in very young animals, and whether they persist over an individual’s entire lifespan. Here we investigated the begging behaviour of very young cross-fostered zebra finch nestlings and the relationship between that and adult activity levels. We fo...

  12. Predicting trace organic compound attenuation with spectroscopic parameters in powdered activated carbon processes.

    Ziska, Austin D; Park, Minkyu; Anumol, Tarun; Snyder, Shane A

    2016-08-01

    The removal of trace organic compounds (TOrCs) is of growing interest in water research and society. Powdered activated carbon (PAC) has been proven to be an effective method of removal for TOrCs in water, with the degree of effectiveness depending on dosage, contact time, and activated carbon type. In this study, the attenuation of TOrCs in three different secondary wastewater effluents using four PAC materials was studied in order to elucidate the effectiveness and efficacy of PAC for TOrC removal. With the notable exception of hydrochlorothiazide, all 14 TOrC indicators tested in this study exhibited a positive correlation of removal rate with their log Dow values, demonstrating that the main adsorption mechanism was hydrophobic interaction. As a predictive model, the modified Chick-Watson model, often used for the prediction of microorganism inactivation by disinfectants, was applied. The applied model exhibited good predictive power for TOrC attenuation by PAC in wastewater. In addition, surrogate models based upon spectroscopic measurements including UV absorbance at 254 nm and total fluorescence were applied to predict TOrC removal by PAC. The surrogate model was found to provide an excellent prediction of TOrC attenuation for all combinations of water quality and PAC type included in this study. The success of spectrometric parameters as surrogates in predicting TOrC attenuation by PAC are particularly useful because of their potential application in real-time on-line sensor monitoring and process control at full-scale water treatment plants, which could lead to significantly reduced operator response times and PAC operational optimization. PMID:27174829

  13. Repeated Predictable Stress Causes Resilience against Colitis-Induced Behavioral Changes in Mice

    Ahmed M Hassan

    2014-11-01

    Full Text Available Inflammatory bowel disease is associated with an increased risk of mental disorders and can be exacerbated by stress. In this study which was performed with male 10-week old C57Bl/6N mice, we used dextran sulfate sodium (DSS-induced colitis to evaluate behavioral changes caused by intestinal inflammation, to assess the interaction between repeated psychological stress (water avoidance stress, WAS and colitis in modifying behavior, and to analyze neurochemical correlates of this interaction. A 7-day treatment with DSS (2 % in drinking water decreased locomotion and enhanced anxiety-like behavior in the open field test and reduced social interaction. Repeated exposure to WAS for 7 days had little influence on behavior but prevented the DSS-induced behavioral disturbances in the open field and social interaction tests. In contrast, repeated WAS did not modify colon length, colonic myeloperoxidase content and circulating proinflammatory cytokines, parameters used to assess colitis severity. DSS-induced colitis was associated with an increase in circulating neuropeptide Y (NPY, a rise in the hypothalamic expression of cyclooxygenase-2 mRNA and a decrease in the hippocampal expression of NPY mRNA, brain-derived neurotrophic factor mRNA and mineralocorticoid receptor mRNA. Repeated WAS significantly decreased the relative expression of corticotropin-releasing factor mRNA in the hippocampus. The effect of repeated WAS to blunt the DSS-evoked behavioral disturbances was associated with a rise of circulating corticosterone and an increase in the expression of hypothalamic NPY mRNA. These results show that experimental colitis leads to a particular range of behavioral alterations which can be prevented by repeated WAS, a model of predictable chronic stress, while the severity of colitis remains unabated. We conclude that the mechanisms underlying the resilience effect of repeated WAS involves hypothalamic NPY and the hypothalamic-pituitary-adrenal axis.

  14. Prediction of radiosensitivity of oral cancers by serial cytological assay of nuclear changes

    Background and purpose: To identify the relationship between the radiosensitivity of oral cancers and the induction of micronucleation, nuclear budding and multinucleation (polynucleation) evaluated by serial cytology during fractionated radiotherapy. Materials and methods: Forty-four patients with epidermoid cancer of the oral cavity receiving radiotherapy (60 Gy in 25 fractions over 5 weeks) were studied. Serial scrape smears were taken from the tumour before and during radiotherapy and stained by Giemsa and the frequency of micronucleated cells (MNC), nuclear budded cells (NBC) and multinucleated cells (PNC) was evaluated by light microscopy. After a minimum follow-up period of 30 months the patients were classified as having resistant or sensitive tumours, depending on whether the primary tumour had recurred or not within that time. Within-group and between-group analysis on the induction of the above individual parameters and two combined parameters, the micro- or multinucleated cell (MPC) count and the abnormally nucleated cell (ANC) count, was done. The counts were expressed per 1000 uni-nucleated cells. Results: In both groups each parameter showed a statistically significant increase with dose, the increase being higher in the sensitive group. The ANC count showed the greatest increase, the mean counts before treatment and after 28.8 Gy being 24.3 and 157.8 (P<0.0005), respectively, in the sensitive group and 21.0 and 65.2 (P<0.0005), respectively, in the resistant group. After 28.8 Gy the sensitive tumours had significantly higher ANC (P=0.01), MPC (P<0.05) and PNC (P<0.05) counts. Conclusion: The study shows that serial cytological assay of nuclear changes (SCANCing) during radiotherapy is a potentially useful test to predict radiosensitivity. The fact that multinucleation showed the greatest relation with radiosensitivity suggests that injury to the cytokinetic apparatus is important in determining tumour radiosensitivity. (Copyright (c) 1998 Elsevier

  15. Predictive Models for Pulmonary Function Changes After Radiotherapy for Breast Cancer and Lymphoma

    Sanchez-Nieto, Beatriz, E-mail: bsanchez@fis.puc.cl [Facultad de Fisica, Pontificia Universidad Catolica de Chile, Santiago (Chile); Goset, Karen C. [Unidad de Radioterapia, Clinica Alemana de Santiago, Santiago (Chile); Caviedes, Ivan [Servicio y Laboratorio Broncopulmonar, Clinica Alemana de Santiago, Santiago (Chile); Departamento de Medicina, Facultad de Medicina, Clinica Alemana-Universidad del Desarrollo, Santiago (Chile); Delgado, Iris O. [Instituto de Epidemiologia y Politicas de Salud Publica, Facultad de Medicina, Clinica Alemana-Universidad del Desarrollo, Santiago (Chile); Cordova, Andres [Unidad de Radioterapia, Clinica Alemana de Santiago, Santiago (Chile)

    2012-02-01

    Purpose: To propose multivariate predictive models for changes in pulmonary function tests ({Delta}PFTs) with respect to preradiotherapy (pre-RT) values in patients undergoing RT for breast cancer and lymphoma. Methods and Materials: A prospective study was designed to measure {Delta}PFTs of patients undergoing RT. Sixty-six patients were included. Spirometry, lung capacity (measured by helium dilution), and diffusing capacity of carbon monoxide tests were used to measure lung function. Two lung definitions were considered: paired lung vs. irradiated lung (IL). Correlation analysis of dosimetric parameters (mean lung dose and the percentage of lung volume receiving more than a threshold dose) and {Delta}PFTs was carried out to find the best dosimetric predictor. Chemotherapy, age, smoking, and the selected dose-volume parameter were considered as single and interaction terms in a multivariate analysis. Stability of results was checked by bootstrapping. Results: Both lung definitions proved to be similar. Modeling was carried out for IL. Acute and late damage showed the highest correlations with volumes irradiated above {approx}20 Gy (maximum R{sup 2} = 0.28) and {approx}40 Gy (maximum R{sup 2} = 0.21), respectively. RT alone induced a minor and transitory restrictive defect (p = 0.013). Doxorubicin-cyclophosphamide-paclitaxel (Taxol), when administered pre-RT, induced a late, large restrictive effect, independent of RT (p = 0.031). Bootstrap values confirmed the results. Conclusions: None of the dose-volume parameters was a perfect predictor of outcome. Thus, different predictor models for {Delta}PFTs were derived for the IL, which incorporated other nondosimetric parameters mainly through interaction terms. Late {Delta}PFTs seem to behave more serially than early ones. Large restrictive defects were demonstrated in patients pretreated with doxorubicin-cyclophosphamide-paclitaxel.

  16. Land-cover changes predict steep declines for the Sumatran orangutan (Pongo abelii).

    Wich, Serge A; Singleton, Ian; Nowak, Matthew G; Utami Atmoko, Sri Suci; Nisam, Gonda; Arif, Sugesti Mhd; Putra, Rudi H; Ardi, Rio; Fredriksson, Gabriella; Usher, Graham; Gaveau, David L A; Kühl, Hjalmar S

    2016-03-01

    Positive news about Sumatran orangutans is rare. The species is critically endangered because of forest loss and poaching, and therefore, determining the impact of future land-use change on this species is important. To date, the total Sumatran orangutan population has been estimated at 6600 individuals. On the basis of new transect surveys, we estimate a population of 14,613 in 2015. This higher estimate is due to three factors. First, orangutans were found at higher elevations, elevations previously considered outside of their range and, consequently, not surveyed previously. Second, orangutans were found more widely distributed in logged forests. Third, orangutans were found in areas west of the Toba Lake that were not previously surveyed. This increase in numbers is therefore due to a more wide-ranging survey effort and is not indicative of an increase in the orangutan population in Sumatra. There are evidently more Sumatran orangutans remaining in the wild than we thought, but the species remains under serious threat. Current scenarios for future forest loss predict that as many as 4500 individuals could vanish by 2030. Despite the positive finding that the population is double the size previously estimated, our results indicate that future deforestation will continue to be the cause of rapid declines in orangutan numbers. Hence, we urge that all developmental planning involving forest loss be accompanied by appropriate environmental impact assessments conforming with the current national and provincial legislations, and, through these, implement specific measures to reduce or, better, avoid negative impacts on forests where orangutans occur. PMID:26973868

  17. Predictive Models for Pulmonary Function Changes After Radiotherapy for Breast Cancer and Lymphoma

    Purpose: To propose multivariate predictive models for changes in pulmonary function tests (ΔPFTs) with respect to preradiotherapy (pre-RT) values in patients undergoing RT for breast cancer and lymphoma. Methods and Materials: A prospective study was designed to measure ΔPFTs of patients undergoing RT. Sixty-six patients were included. Spirometry, lung capacity (measured by helium dilution), and diffusing capacity of carbon monoxide tests were used to measure lung function. Two lung definitions were considered: paired lung vs. irradiated lung (IL). Correlation analysis of dosimetric parameters (mean lung dose and the percentage of lung volume receiving more than a threshold dose) and ΔPFTs was carried out to find the best dosimetric predictor. Chemotherapy, age, smoking, and the selected dose-volume parameter were considered as single and interaction terms in a multivariate analysis. Stability of results was checked by bootstrapping. Results: Both lung definitions proved to be similar. Modeling was carried out for IL. Acute and late damage showed the highest correlations with volumes irradiated above ∼20 Gy (maximum R2 = 0.28) and ∼40 Gy (maximum R2 = 0.21), respectively. RT alone induced a minor and transitory restrictive defect (p = 0.013). Doxorubicin-cyclophosphamide-paclitaxel (Taxol), when administered pre-RT, induced a late, large restrictive effect, independent of RT (p = 0.031). Bootstrap values confirmed the results. Conclusions: None of the dose-volume parameters was a perfect predictor of outcome. Thus, different predictor models for ΔPFTs were derived for the IL, which incorporated other nondosimetric parameters mainly through interaction terms. Late ΔPFTs seem to behave more serially than early ones. Large restrictive defects were demonstrated in patients pretreated with doxorubicin-cyclophosphamide-paclitaxel.

  18. Aspen Global Change Institute (AGCI) Interdisciplinary Science Workshop: Decadal Climate Prediction; Aspen, CO; June 22-28, 2008

    Katzenberger, John

    2010-03-12

    Decadal prediction lies between seasonal/interannual forecasting and longer-term climate change projections, and focuses on time-evolving regional climate conditions over the next 10?30 yr. Numerous assessments of climate information user needs have identified this time scale as being important to infrastructure planners, water resource managers, and many others. It is central to the information portfolio required to adapt effectively to and through climatic changes.

  19. Uncertainties in predicting species distributions under climate change: a case study using Tetranychus evansi (Acari: Tetranychidae), a widespread agricultural pest

    Meynard, Christine N.; Alain Migeon; Maria Navajas

    2013-01-01

    Many species are shifting their distributions due to climate change and to increasing international trade that allows dispersal of individuals across the globe. In the case of agricultural pests, such range shifts may heavily impact agriculture. Species distribution modelling may help to predict potential changes in pest distributions. However, these modelling strategies are subject to large uncertainties coming from different sources. Here we used the case of the tomato red spider mite (Tetr...

  20. Thermal Tolerance of the Coffee Berry Borer Hypothenemus hampei: Predictions of Climate Change Impact on a Tropical Insect Pest

    Juliana Jaramillo; Adenirin Chabi-Olaye; Charles Kamonjo; Alvaro Jaramillo; Fernando E. Vega; Hans-Michael Poehling; Christian Borgemeister

    2009-01-01

    Coffee is predicted to be severely affected by climate change. We determined the thermal tolerance of the coffee berry borer, Hypothenemus hampei, the most devastating pest of coffee worldwide, and make inferences on the possible effects of climate change using climatic data from Colombia, Kenya, Tanzania, and Ethiopia. For this, the effect of eight temperature regimes (15, 20, 23, 25, 27, 30, 33 and 35 degrees C) on the bionomics of H. hampei was studied. Successful egg to adult development ...

  1. Real-time prediction of neuronal population spiking activity using FPGA.

    Li, Will X Y; Cheung, Ray C C; Chan, Rosa H M; Song, Dong; Berger, Theodore W

    2013-08-01

    A field-programmable gate array (FPGA)-based hardware architecture is proposed and utilized for prediction of neuronal population firing activity. The hardware system adopts the multi-input multi-output (MIMO) generalized Laguerre-Volterra model (GLVM) structure to describe the nonlinear dynamic neural process of mammalian brain and can switch between the two important functions: estimation of GLVM coefficients and prediction of neuronal population spiking activity (model outputs). The model coefficients are first estimated using the in-sample training data; then the output is predicted using the out-of-sample testing data and the field estimated coefficients. Test results show that compared with previous software implementation of the generalized Laguerre-Volterra algorithm running on an Intel Core i7-2620M CPU, the FPGA-based hardware system can achieve up to 2.66×10(3) speedup in doing model parameters estimation and 698.84 speedup in doing model output prediction. The proposed hardware platform will facilitate research on the highly nonlinear neural process of the mammal brain, and the cognitive neural prosthesis design. PMID:23893208

  2. Testing multi-theory model (MTM) in predicting initiation and sustenance of physical activity behavior among college students

    Nahar, Vinayak K.; Sharma, Manoj; Catalano, Hannah Priest; Ickes, Melinda J.; Johnson, Paul; Ford, M. Allison

    2016-01-01

    Background: Most college students do not adequately participate in enough physical activity (PA) to attain health benefits. A theory-based approach is critical in developing effective interventions to promote PA. The purpose of this study was to examine the utility of the newly proposed multi-theory model (MTM) of health behavior change in predicting initiation and sustenance of PA among college students. Methods: Using a cross-sectional design, a valid and reliable survey was administered in October 2015 electronically to students enrolled at a large Southern US University. The internal consistency Cronbach alphas of the subscales were acceptable (0.65-0.92). Only those who did not engage in more than 150 minutes of moderate to vigorous intensity aerobic PA during the past week were included in this study. Results: Of the 495 respondents, 190 met the inclusion criteria of which 141 completed the survey. The majority of participants were females (72.3%) and Caucasians (70.9%). Findings of the confirmatory factor analysis (CFA) confirmed construct validity of subscales (initiation model: χ2 = 253.92 [df = 143], P < 0.001, CFI = 0.91, RMSEA = 0.07, SRMR = 0.07; sustenance model: χ2= 19.40 [df = 22], P < 0.001, CFI = 1.00, RMSEA = 0.00, SRMR = 0.03). Multivariate regression analysis showed that 26% of the variance in the PA initiation was explained by advantages outweighing disadvantages, behavioral confidence, work status, and changes in physical environment. Additionally, 29.7% of the variance in PA sustenance was explained by emotional transformation, practice for change, and changes in social environment. Conclusion: Based on this study’s findings, MTM appears to be a robust theoretical framework for predicting PA behavior change. Future research directions and development of suitable intervention strategies are discussed. PMID:27386419

  3. Quantitative structure-activity relationship to predict acute fish toxicity of organic solvents.

    Levet, A; Bordes, C; Clément, Y; Mignon, P; Chermette, H; Marote, P; Cren-Olivé, C; Lantéri, P

    2013-10-01

    REACH regulation requires ecotoxicological data to characterize industrial chemicals. To limit in vivo testing, Quantitative Structure-Activity Relationships (QSARs) are advocated to predict toxicity of a molecule. In this context, the topic of this work was to develop a reliable QSAR explaining the experimental acute toxicity of organic solvents for fish trophic level. Toxicity was expressed as log(LC50), the concentration in mmol.L(-1) producing the 50% death of fish. The 141 chemically heterogeneous solvents of the dataset were described by physico-chemical descriptors and quantum theoretical parameters calculated via Density Functional Theory. The best subsets of solvent descriptors for LC50 prediction were chosen both through the Kubinyi function associated with Enhanced Replacement Method and a stepwise forward multiple linear regressions. The 4-parameters selected in the model were the octanol-water partition coefficient, LUMO energy, dielectric constant and surface tension. The predictive power and robustness of the QSAR developed were assessed by internal and external validations. Several techniques for training sets selection were evaluated: a random selection, a LC50-based selection, a balanced selection in terms of toxic and non-toxic solvents, a solvent profile-based selection with a space filling technique and a D-optimality onions-based selection. A comparison with fish LC50 predicted by ECOSAR model validated for neutral organics confirmed the interest of the QSAR developed for the prediction of organic solvent aquatic toxicity regardless of the mechanism of toxic action involved. PMID:23866172

  4. Single-trial prediction of reaction time variability from MEG brain activity.

    Ohata, Ryu; Ogawa, Kenji; Imamizu, Hiroshi

    2016-01-01

    Neural activity prior to movement onset contains essential information for predictive assistance for humans using brain-machine-interfaces (BMIs). Even though previous studies successfully predicted different goals for upcoming movements, it is unclear whether non-invasive recording signals contain the information to predict trial-by-trial behavioral variability under the same movement. In this paper, we examined the predictability of subsequent short or long reaction times (RTs) from magnetoencephalography (MEG) signals in a delayed-reach task. The difference in RTs was classified significantly above chance from 550 ms before the go-signal onset using the cortical currents in the premotor cortex. Significantly above-chance classification was performed in the lateral prefrontal and the right inferior parietal cortices at the late stage of the delay period. Thus, inter-trial variability in RTs is predictable information. Our study provides a proof-of-concept of the future development of non-invasive BMIs to prevent delayed movements. PMID:27250872

  5. Quantitative perturbation-based analysis of gene expression predicts enhancer activity in early Drosophila embryo.

    Sayal, Rupinder; Dresch, Jacqueline M; Pushel, Irina; Taylor, Benjamin R; Arnosti, David N

    2016-01-01

    Enhancers constitute one of the major components of regulatory machinery of metazoans. Although several genome-wide studies have focused on finding and locating enhancers in the genomes, the fundamental principles governing their internal architecture and cis-regulatory grammar remain elusive. Here, we describe an extensive, quantitative perturbation analysis targeting the dorsal-ventral patterning gene regulatory network (GRN) controlled by Drosophila NF-κB homolog Dorsal. To understand transcription factor interactions on enhancers, we employed an ensemble of mathematical models, testing effects of cooperativity, repression, and factor potency. Models trained on the dataset correctly predict activity of evolutionarily divergent regulatory regions, providing insights into spatial relationships between repressor and activator binding sites. Importantly, the collective predictions of sets of models were effective at novel enhancer identification and characterization. Our study demonstrates how experimental dataset and modeling can be effectively combined to provide quantitative insights into cis-regulatory information on a genome-wide scale. PMID:27152947

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

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

    2016-04-01

    The current longitudinal study examined which individual symptoms of depression uniquely predicted a subsequent Major Depressive Episode (MDE) in adolescents, and whether these relations differed by sex. Adolescents (N = 240) were first interviewed in grade 6 (M = 11.86 years old; SD = 0.56; 54% female; 81.5% Caucasian) and then annually through grade 12 regarding their individual symptoms of depression as well as the occurrence of MDEs. Individual symptoms of depression were assessed with the Children's Depression Rating Scale-Revised (CDRS-R) and depressive episodes were assessed with the Longitudinal Interval Follow-up Evaluation (LIFE). Results showed that within-person changes in sleep problems and low self-esteem/excessive guilt positively predicted an increased likelihood of an MDE for both boys and girls. Significant sex differences also were found. Within-person changes in anhedonia predicted an increased likelihood of a subsequent MDE among boys, whereas irritability predicted a decreased likelihood of a future MDE among boys, and concentration difficulties predicted a decreased likelihood of an MDE in girls. These results identified individual depressive symptoms that predicted subsequent depressive episodes in male and female adolescents, and may be used to guide the early detection, treatment, and prevention of depressive disorders in youth. PMID:26105209

  7. Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer

    Wang, SY; Cowan, JE; Clint Cary, K; Chan, JM; Carroll, PR; Cooperberg, MR

    2014-01-01

    Objective: To assess the ability of current nomograms to predict disease progression at repeat biopsy or at delayed radical prostatectomy (RP) in a prospectively accrued cohort of patients managed by active surveillance (AS). Materials and Methods: A total of 273 patients meeting low-risk criteria who were managed by AS and who underwent multiple biopsies and/or delayed RP were included in the study. The Kattan (base, medium and full), Steyerberg, Nakanishi and Chun nomograms were used to cal...

  8. Using activity-based modeling to predict spatial and temporal electrical vehicle power demand in Flanders

    Knapen, Luk; Kochan, Bruno; BELLEMANS, Tom; JANSSENS, Davy; Wets, Geert

    2012-01-01

    Electric power demand for household generated traffic is estimated as a function of time and space for the region of Flanders. An activity-based model is used to predict traffic demand. Electric vehicle (EV) type and charger characteristics are determined on the basis of car ownership and by assuming that EV categories market shares will be similar to the current ones for internal combustion engine vehicles (ICEV) published in government statistics. Charging opportunities at home and work locat...

  9. Prediction-error in the context of real social relationships modulates reward system activity

    Joshua ePoore; Jennifer ePfeifer; Elliot eBerkman; Tristen eInagaki; Benjamin Locke Welborn; Matthew eLieberman

    2012-01-01

    The human reward system is sensitive to both social (e.g., validation) and non-social rewards (e.g., money) and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to...

  10. Drug Predictive Cues Activate Aversion-Sensitive Striatal Neurons That Encode Drug Seeking

    Wheeler, Daniel S.; Robble, Mykel A.; Hebron, Emily M.; Dupont, Matthew J.; Ebben, Amanda L.; Wheeler, Robert A

    2015-01-01

    Drug-associated cues have profound effects on an addict's emotional state and drug-seeking behavior. Although this influence must involve the motivational neural system that initiates and encodes the drug-seeking act, surprisingly little is known about the nature of such physiological events and their motivational consequences. Three experiments investigated the effect of a cocaine-predictive stimulus on dopamine signaling, neuronal activity, and reinstatement of cocaine seeking. In all exper...

  11. Macrophage activation marker soluble CD163 may predict disease progression in hepatocellular carcinoma

    Kazankov, Konstantin; Rode, Anthony; Simonsen, Kira;

    2016-01-01

    BACKGROUND: Tumor associated macrophages are present in hepatocellular carcinoma (HCC) and associated with a poor prognosis. The aim of the present study was to investigate the levels and dynamics of soluble (s)CD163, a specific macrophage activation marker, in patients with HCC. METHODS: In a......, baseline sCD163 appeared to predict a rapid HCC progression, as sCD163 increased during follow-up in HCC patients who showed progression....

  12. Prediction of vehicle activity for emissions estimation under oversaturated conditions along signalized arterials

    Skabardonis, Alexander; Geroliminis, Nikolaos; Christofa, Eleni

    2013-01-01

    The traditional methodology for estimating vehicle emissions based on vehicle miles traveled and average speed is not reliable because it does not consider the effects of congestion, control devices, and driving mode (cruise, acceleration, deceleration, and idle). We developed an analytical model to predict vehicle activity on signalized arterials with emphasis on oversaturated traffic conditions. The model depends only on loop detector data and signal settings as inputs and provides estimate...

  13. The influence of active region information on the prediction of solar flares: an empirical model using data mining

    M. Núñez

    2005-11-01

    Full Text Available Predicting the occurrence of solar flares is a challenge of great importance for many space weather scientists and users. We introduce a data mining approach, called Behavior Pattern Learning (BPL, for automatically discovering correlations between solar flares and active region data, in order to predict the former. The goal of BPL is to predict the interval of time to the next solar flare and provide a confidence value for the associated prediction. The discovered correlations are described in terms of easy-to-read rules. The results indicate that active region dynamics is essential for predicting solar flares.

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

    Sahlqvist, S; Goodman, A.; Cooper, AR; Ogilvie, D; iConnect consortium

    2013-01-01

    BACKGROUND 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. METHODS These analyses, carried out in April 2012, use longitudinal data from 1628 adult respondents (mean age 54 years; 47% male) in the UK-based iConnect study. Travel and recreational physical activity were measured using detailed seven-day recall instruments. Adjusted l...

  15. Media Selection during the Implementation of Planned Organizational Change: A Predictive Framework Based on Implementation Approach and Phase.

    Timmerman, C. Erik

    2003-01-01

    Integrates literature that addresses implementation approaches and phases with media selection research to provide a descriptive framework for understanding and predicting media use during planned change implementation. Concludes by synthesizing the findings that emerge from the integration of these bodies of literature and describing implications…

  16. Angiography-based prediction of outcome after coronary artery bypass surgery versus changes in myocardial perfusion scintigraphy

    Eckardt, Rozy; Kjeldsen, Bo Juel; Haghfelt, Torben; Grupe, Peter; Johansen, Allan; Andersen, Lars Ib; Hesse, Birger

    2011-01-01

    scintigraphy before and 6 months after CABG, the results being kept secret from the surgeon. Based on clinical and angiographic findings, the surgeons filled in a questionnaire indicating the predicted changes in coronary blood flow in each of the three coronary artery territories and in the LVEF. Symptomatic...

  17. Interactions between MAOA Genotype and Receipt of Public Assistance: Predicting Change in Depressive Symptoms and Body Mass Index

    Marmorstein, Naomi R.; Hart, Daniel

    2011-01-01

    Response to stress is determined in part by genetically influenced regulation of the monoamine system (MAOA). We examined the interaction of a stressor (receipt of public assistance) and a gene regulating MAOA in the prediction of change in adolescent depressive symptoms and body mass index (BMI). Participants were drawn from the National…

  18. Thrombin time and anti-IIa dabigatran's activity: hypothesis of thrombin time's predictive value.

    Le Guyader, Maïlys; Kaabar, Mohammed; Lemaire, Pierre; Pineau Vincent, Fabienne

    2015-01-01

    Dabigatran etexilate (Pradaxa®) is a new oral anticoagulant, competitive inhibitor, selective, fast, direct and reversible of thrombin. Dabigatran has an impact on a large panel of used coagulation tests. There is no relationship between thrombin time's lengthening and anti-IIa activity. This study defines thrombin time's predictive value, when its time is normal. The result of negative value is 97,6%. 255 patients were studied between January 2013 and July 2014. Thrombin time and anti-IIa activity were dosed for each patient. This study can be an assistant for therapeutic decision for laboratories without specialized test. PMID:26489812

  19. Climate Change Science Activities of the U.S. Geological Survey in New England

    Lent, Robert M.

    2016-01-01

    The U.S. Geological Survey (USGS) has actively pursued research in the effects of climate change on the hydrology of New England. Ongoing focus areas of climate change science activities of the USGS in New England include the following:

  20. Creative elements: network-based predictions of active centres in proteins, cellular and social networks

    Csermely, Peter

    2008-01-01

    Active centres and hot spots of proteins have a paramount importance in enzyme action, protein complex formation and drug design. Recently a number of publications successfully applied the analysis of residue networks to predict active centres in proteins. Most real-world networks show a number of properties, such as small-worldness or scale-free degree distribution, which are rather general features of networks from molecules to the society. Based on extensive analogies I propose that the existing findings and methodology enable us to detect active centres in cells, social networks and ecosystems. Members of these active centres are creative elements of the respective networks, which may help them to survive unprecedented, novel challenges, and play a key role in the development, survival and evolvability of complex systems.

  1. Interdecadal changes in summer TC activity in East China Sea

    Choi, Ki-Seon; Cha, Yu-Mi; Kang, Sung-Dae; Kim, Hae-Dong

    2015-04-01

    The study analyzed the time series of the tropical cyclone (TC) frequencies which passed through the East China Sea between July and September from 1963 to 2012. The result of applying the statistical change-point analysis to this time series shows that a climate regime shift occurred in 1983 when the TC frequencies which pass the East China Sea area started increasing. The study then analyzed the average difference after 1983 (1984-2012) and before 1983 (1963-1983). The TC genesis frequency shows a tendency in mainly appearing in the tropical and subtropical Northwestern Pacific between 1963 and 1983 and the southern part between 1984 and 2012. The TC passage frequency shows a pattern that the TCs move from the far northeast sea of Philippines and change direction to Korea and Japan, passing through the East China Sea between 1984 and 2012. Meanwhile, the TC passage frequency shows a pattern which moves from the far southeast sea of the Philippines to southern China in the west direction in the previous period (1963-1983). These TC movement patterns coincide with the development status of the subtropical western North Pacific high (SWNPH) which averages for each period. It shows that the SWNPH in the second period stays away from the SWNPH in the second period from the northeast direction, but that the SWNPH in the first period expands to western Taiwan. This study analyzes the difference between the two periods in the 500-hPa streamline to understand the changes in such TC activities in the two groups. The anomalous anticyclonic circulations centered in the southern part of Japan are fortified in most of the subtropical Northwestern Pacific. The anomalous southerlies from the anomalous circulations are outstanding in the East China Sea area, Korea, and Japan. Therefore, the TCs generated in the tropical and subtropical Northwestern Pacific move along with the anomalous steering flow (anomalous southwesterlies) and up toward the East China Sea area, Korea, and

  2. The influence of active region information on the prediction of solar flares: an empirical model using data mining

    Núñez, M.; Fidalgo, R.; Baena, M.; R Morales

    2005-01-01

    Predicting the occurrence of solar flares is a challenge of great importance for many space weather scientists and users. We introduce a data mining approach, called Behavior Pattern Learning (BPL), for automatically discovering correlations between solar flares and active region data, in order to predict the former. The goal of BPL is to predict the interval of time to the next solar flare and provide a confidence value for the associated prediction. The discovered correlations are described...

  3. The influence of active region information on the prediction of solar flares: an empirical model using data mining

    Núñez, M.; Fidalgo, R.; Baena, M.; R Morales

    2005-01-01

    Predicting the occurrence of solar flares is a challenge of great importance for many space weather scientists and users. We introduce a data mining approach, called Behavior Pattern Learning (BPL), for automatically discovering correlations between solar flares and active region data, in order to predict the former. The goal of BPL is to predict the interval of time to the next solar flare and provide a confidence value for the associated prediction. The discovered correlat...

  4. The influence of active region information on the prediction of solar flares: an empirical model using data mining

    Núñez, M.; Fidalgo, R.; Baena, M.; Morales, R.

    2005-01-01

    International audience Predicting the occurrence of solar flares is a challenge of great importance for many space weather scientists and users. We introduce a data mining approach, called Behavior Pattern Learning (BPL), for automatically discovering correlations between solar flares and active region data, in order to predict the former. The goal of BPL is to predict the interval of time to the next solar flare and provide a confidence value for the associated prediction. The discovered ...

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

    Annewandter, Robert

    2014-05-01

    The Non-Proliferation Experiment (NPE) has demonstrated and modelled the usefulness of barometric pumping induced gas transport and subsequent soil gas sampling during On-Site inspections. Generally, gas transport has been widely studied with different numerical codes. However, gas transport of radioxenons and radioiodines in the post-detonation regime and their possible fractionation is still neglected in the open peer-reviewed literature. Atmospheric concentrations of the radioxenons Xe-135, Xe-133m, Xe-133 and Xe-131m can be used to discriminate between civilian releases (nuclear power plants or medical isotope facilities), and nuclear explosion sources. It is based on the multiple isotopic activity ratio method. Yet it is not clear whether subsurface migration of the radionuclides, with eventual release into the atmosphere, can affect the activity ratios due to fractionation. Fractionation can be caused by different mass diffusivities due to mass differences between the radionuclides. Cyclical changes in atmospheric pressure can drive subsurface gas transport. This barometric pumping phenomenon causes an oscillatoric flow in upward trending fractures or highly conductive faults which, combined with diffusion into the porous matrix, leads to a net transport of gaseous components - a so-called ratcheting effect. We use a general purpose reservoir simulator (Complex System Modelling Platform, CSMP++) which is recognized by the oil industry as leading in Discrete Fracture-Matrix (DFM) simulations. It has been applied in a range of fields such as deep geothermal systems, three-phase black oil simulations, fracture propagation in fractured, porous media, and Navier-Stokes pore-scale modelling among others. It is specifically designed to account for structurally complex geologic situation of fractured, porous media. Parabolic differential equations are solved by a continuous Galerkin finite-element method, hyperbolic differential equations by a complementary finite

  6. Predictive value of QuantiFERON-TB Gold test for the risk of active tuberculosis

    Amalia I. Găvriluţ

    2013-03-01

    Full Text Available Objective: The aim of this study was to determine the predictive value of QuantiFERON-TB Gold (QFT-G test in screening for latenttuberculosis (TB progression to active TB in subjects with recent contact with active TB cases. Material and method: The study included72 subjects aged over 18 who had close contact with active TB cases in the last 3 months. Subjects have been evaluated clinically and radiographicallyevery six months after inclusion in the study, over a period of 2 years. Two immunological tests were used for estimation of latentTB: tuberculin skin testing and QFT-G test. Results: During follow-up (2 years, 7 subjects (10.1% were diagnosed with active TB. HepatitisB, type 2 diabetes, cancer, COPD, poor living conditions, positive tuberculine skin testing and QFT-G were associated with a high risk for onsetof active TB in univariate analysis (p<0.05. In multivariate analysis a positve QFT-G test showed a risk of developing active TB 2 yearsafter contact with patients with active disease, 8 times higher than a negative result (HR (hazard ratio, 8, CI95% 1.3% - 46.7%, p=0.02, whileHR given by the presence of diabetes was 5 (CI95% 1% - 23.8%, p=0.03. Conclusions: QFT-G test and the presence of type 2 diabetes wereindependent predictors for risk of active TB.

  7. How to change GEBCO outreach activities with Information technologies?

    Chang, E.; Park, K.

    2014-12-01

    Since 1995, when National Geographic Information Project began, we have great advance in mapping itself and information service on the earth surface in Korea whether paper maps or online service map. By reviewing geological and mine-related information service in current and comparisons of demands, GEBCO outreach master plan has been prepared. Information service cannot be separated from data production and on dissemination policies. We suggest the potential impact of the changes in information technologies such as mobile service and data fusion, and big data on GEBCO maps based. Less cost and high performance in data service will stimulate more information service; therefore it is necessary to have more customer-oriented manipulation on the data. By inquiring questionnaire, we can draw the potential needs on GEBCO products in various aspects: such as education, accessibility. The gap between experts and non-experts will decrease by digital service from the private and public organizations such as international academic societies since research funds and policies tend to pursue "openness" and "interoperability" among the domains. Some background why and how to prepare outreach activities in GEBCO will be shown.

  8. Predicting the Trend of Land Use Changes Using Artificial Neural Network and Markov Chain Model (Case Study: Kermanshah City)

    Behzad Saeedi Razavi

    2014-01-01

    Nowadays, cities are expanding and developing with a rapid growth, so that the urban development process is currently one of the most important issues facing researchers in urban issues. In addition to the growth of the cities, how land use changes in macro level is also considered. Studying the changes and degradation of the resources in the past few years, as well as feasibility study and predicting these changes in the future years may play a significant role in planning and optimal use of...

  9. 48 CFR 9903.201-8 - Compliant accounting changes due to external restructuring activities.

    2010-10-01

    ... changes due to external restructuring activities. 9903.201-8 Section 9903.201-8 Federal Acquisition... Requirements 9903.201-8 Compliant accounting changes due to external restructuring activities. The contract... practice changes directly associated with external restructuring activities that are subject to and...

  10. Predicting physical activity intentions using a goal perspectives approach: a study of Finnish youth.

    Lintunen, T; Valkonen, A; Leskinen, E; Biddle, S J

    1999-12-01

    Physical activity intentions were studied in 12- to 16-year-old Finnish girls (n= 186) and boys (n=215). Theoretical predictions were used to establish a model that was then tested separately for each sex using path analysis. Firstly, it was hypothesised that malleable conceptions of the nature of sport ability positively influence enjoyment in physical activity and intentions to participate in physical activity, mediated by a task-oriented achievement goal independent of variations in perceptions of competence. Secondly, it was hypothesised that fixed conceptions of the nature of ability decrease enjoyment in physical activity and intentions to participate, mediated by an ego-oriented achievement goal and by perceived competence. The modified models were shown to fit the data. Overall, the results showed that 63% (boys) and 45% (girls) of the variance in intentions was explained by the model. The motivational importance of task orientation and, among the boys, perceived physical competence was confirmed with their direct prediction of intentions. PMID:10606099

  11. Significant change of predictions related to the future of nuclear power

    .6 Gwe (minimal), or 20.7 Gwe (maximal); in Taiwan, from 4.884 Gwe (1999) to 7.514 Gwe (2020, ref.); in India, from 1.897 Gwe (1999) to 7.571 Gwe (2020, ref.); in Japan, from 43.7 Gwe (1999) to 56.6 Gwe (2020, ref.); in Korea, from 13.0 Gwe (1999), to 22.1 Gwe (2020, ref.). An ambitious increase is related to the prognosis in Brazil, from 0.626 Gwe (1999) to 3.084 Gwe (2020, ref.) For the group of the all non-developed countries, other than the Eastern European ones, the predicted increase of the installed nuclear power is from 25.466 Gwe (1999) to 65.824 Gwe (2020, ref.). The decrease of the fission contribution in the European countries that are against new NPP is not very fast in the 1999-2020 period of forecast: Germany, from 21.122 Gwe to 13.134 Gwe; Sweden, from 9.432 Gwe to 6.077 Gwe; Belgium, from 5.712 Gwe to 3.966 Gwe. In Romania, a National Nuclear Plan will schedule the commissioning of the next Cernavoda NPP Units. The intention to complete the work for all the 5 Units before 2020 is clear. There are predictions that indicate 5 Units in operation at Cernavoda NPP several years earlier. A major change in the nuclear power field is related to the advanced reactors. The 'Generation III' will cover the needs for the next 10-20 years. These advanced reactors are significantly safer, cheaper, and the initial time for construction and commissioning is reduced. Most of the already available designs are based on the 'innovative concepts' and, mainly, on the 'evolutionary solutions' related to the operation of the existent NPP. The 'Generation IV' is one of the main R and D tasks of DOE, USA. Any concept and idea is accepted for development and evaluation. The needed advanced reactors are expected in the 2020-2030 period. In conclusion, the recent forecasts of the future of fission based nuclear power indicate a significant contribution to the electricity generation worldwide, at least for the first half of the century. (author)

  12. Predicting Future European Breeding Distributions of British Seabird Species under Climate Change and Unlimited/No Dispersal Scenarios

    Deborah J.F. Russell

    2015-11-01

    Full Text Available Understanding which traits make species vulnerable to climatic change and predicting future distributions permits conservation efforts to be focused on the most vulnerable species and the most appropriate sites. Here, we combine climate envelope models with predicted bioclimatic data from two emission scenarios leading up to 2100, to predict European breeding distributions of 23 seabird species that currently breed in the British Isles. Assuming unlimited dispersal, some species would be “winners” (increase the size of their range, but over 65% would lose range, some by up to 80%. These “losers” have a high vulnerability to low prey availability, and a northerly distribution meaning they would lack space to move into. Under the worst-case scenario of no dispersal, species are predicted to lose between 25% and 100% of their range, so dispersal ability is a key constraint on future range sizes. More globally, the results indicate, based on foraging ecology, which seabird species are likely to be most affected by climatic change. Neither of the emissions scenarios used in this study is extreme, yet they generate very different predictions for some species, illustrating that even small decreases in emissions could yield large benefits for conservation.

  13. Implicit theories about willpower predict the activation of a rest goal following self-control exertion.

    Job, Veronika; Bernecker, Katharina; Miketta, Stefanie; Friese, Malte

    2015-10-01

    Past research indicates that peoples' implicit theories about the nature of willpower moderate the ego-depletion effect. Only people who believe or were led to believe that willpower is a limited resource (limited-resource theory) showed lower self-control performance after an initial demanding task. As of yet, the underlying processes explaining this moderating effect by theories about willpower remain unknown. Here, we propose that the exertion of self-control activates the goal to preserve and replenish mental resources (rest goal) in people with a limited-resource theory. Five studies tested this hypothesis. In Study 1, individual differences in implicit theories about willpower predicted increased accessibility of a rest goal after self-control exertion. Furthermore, measured (Study 2) and manipulated (Study 3) willpower theories predicted an increased preference for rest-conducive objects. Finally, Studies 4 and 5 provide evidence that theories about willpower predict actual resting behavior: In Study 4, participants who held a limited-resource theory took a longer break following self-control exertion than participants with a nonlimited-resource theory. Longer resting time predicted decreased rest goal accessibility afterward. In Study 5, participants with an induced limited-resource theory sat longer on chairs in an ostensible product-testing task when they had engaged in a task requiring self-control beforehand. This research provides consistent support for a motivational shift toward rest after self-control exertion in people holding a limited-resource theory about willpower. PMID:26075793

  14. Predicting daily photosynthetically active radiation from global solar radiation in the Contiguous United States

    Highlights: • Relationships between the daily PAR and Rs are explored across the United States. • Ten existing models for the PAR fraction estimation are analyzed by 3 years data. • Validation of all obtained models by four statistical parameters. • Introduce the best model of the daily PAR prediction for seven SURFRAD sites. - Abstract: An investigation on the daily photosynthetically active radiation (PAR) with the global solar radiation (Rs) is conducted at 7 surface radiation budget monitoring stations across the Mainland United States by exploiting a 3 years (2009–2011) data achieve. The clearness index, the diffuse fraction and the skylight brightness along with the dew point temperature and the cosine of solar zenith angle are used to generate empirical relationships for predicting PAR from Rs. Records of 2009 and 2010 are employed for model establishment, while records of 2011 are used for validation. The accuracy of the models’ predictions is evaluated by four statistics parameters, including the coefficient of determination, the root mean square error, the mean percentage error and the relative standard deviation. Results show that the polynomial model taking the clearness index as main parameter plus the cosine of solar zenith angle has the best performance out of ten proposed models. And the clearness index is capable to be the indicator for PAR prediction, as a substitute of the combination of the diffuse fraction and the skylight brightness

  15. Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach

    Chen-Peng Chen

    2014-01-01

    Full Text Available The flash point (FP of a compound is the primary property used in the assessment of fire hazards for flammable liquids and is amongst the crucial information that people handling flammable liquids must possess as far as industrial safety is concerned. In this work, the FPs of 236 organosilicon compounds were collected and used to construct a quantitative structure activity relationship (QSAR model for predicting their FPs. The CODESSA PRO software was adopted to calculate the required molecular descriptors, and 350 molecular descriptors were developed for each compound. A modified stepwise regression algorithm was applied to choose descriptors that were highly correlated with the FP of organosilicon compounds. The proposed model was a linear regression model consisting of six descriptors. This 6-descriptor model gave an R2 value of 0.9174, QLOO2 value of 0.9106, and Q2 value of 0.8989. The average fitting error and the average predictive error were found to be of 10.34 K and 11.22 K, respectively, and the average fitting error in percentage and the average predictive error in percentage were found to be of 3.30 and 3.60%, respectively. Compared with the known reproducibility of FP measurement using standard test method, these predicted results were of a satisfactory precision.

  16. Prediction of ground motion and dynamic stress change in Baekdusan (Changbaishan) volcano caused by a North Korean nuclear explosion

    Tae-Kyung Hong; Eunseo Choi; Seongjun Park; Jin Soo Shin

    2016-01-01

    Strong ground motions induce large dynamic stress changes that may disturb the magma chamber of a volcano, thus accelerating the volcanic activity. An underground nuclear explosion test near an active volcano constitutes a direct treat to the volcano. This study examined the dynamic stress changes of the magma chamber of Baekdusan (Changbaishan) that can be induced by hypothetical North Korean nuclear explosions. Seismic waveforms for hypothetical underground nuclear explosions at North Korea...

  17. Does an 'activity-permissive' workplace change office workers' sitting and activity time?

    Erin Gorman

    Full Text Available INTRODUCTION: To describe changes in workplace physical activity, and health-, and work-related outcomes, in workers who transitioned from a conventional to an 'activity-permissive' workplace. METHODS: A natural pre-post experiment conducted in Vancouver, Canada in 2011. A convenience sample of office-based workers (n=24, 75% women, mean [SD] age = 34.5 [8.1] years were examined four months following relocation from a conventional workplace (pre to a newly-constructed, purpose-built, movement-oriented physical environment (post. Workplace activity- (activPAL3-derived stepping, standing, and sitting time, health- (body composition and fasting cardio-metabolic blood profile, and work- (performance; job satisfaction related outcomes were measured pre- and post-move and compared using paired t-tests. RESULTS: Pre-move, on average (mean [SD] the majority of the day was spent sitting (364 [43.0] mins/8-hr workday, followed by standing (78.2 [32.1] mins/8-hr workday and stepping (37.7 [15.6] mins/8-hr workday. The transition to the 'activity-permissive' workplace resulted in a significant increase in standing time (+18.5, 95% CI: 1.8, 35.2 mins/8-hr workday, likely driven by reduced sitting time (-19.7, 95% CI: -42.1, 2.8 mins/8-hr workday rather than increased stepping time (+1.2, 95% CI: -6.2, 8.5 mins/8-hr workday. There were no statistically significant differences observed in health- or work-related outcomes. DISCUSSION: This novel, opportunistic study demonstrated that the broader workplace physical environment can beneficially impact on standing time in office workers. The long-term health and work-related benefits, and the influence of individual, organizational, and social factors on this change, requires further evaluation.

  18. A Deterministic Model for Predicting Hourly Dissolved Oxygen Change: Development and Application to a Shallow Eutrophic Lake

    Zhen Xu

    2016-01-01

    Full Text Available Predicting dissolved oxygen (DO change at a high frequency in water bodies is useful for water quality management. In this study, we developed a deterministic model that can predict hourly DO change in a water body with high frequency weather parameters. The study was conducted during August 2008–July 2009 in a eutrophic shallow lake in Louisiana, USA. An environment monitoring buoy was deployed to record DO, water temperature and chlorophyll-a concentration at 15-min intervals, and hourly weather data including air temperature, precipitation, wind speed, relative humidity, and solar radiation were gathered from a nearby weather station. These data formed a foundation for developing a DO model that predicts rapid change of source and sink components including photosynthesis, re-aeration, respiration, and oxygen consumption by sediments. We then applied the model to a studied shallow lake that is widely representative of lake water conditions in the subtropical southern United States. Overall, the model successfully simulated high-time fluctuation of DO in the studied lake, showing good predictability for extreme algal bloom events. However, a knowledge gap still exists in accurately quantifying oxygen source produced by photosynthesis in high frequency DO modeling.

  19. Predicting risk-taking behavior from prefrontal resting-state activity and personality.

    Bettina Studer

    Full Text Available Risk-taking is subject to considerable individual differences. In the current study, we tested whether resting-state activity in the prefrontal cortex and trait sensitivity to reward and punishment can help predict risk-taking behavior. Prefrontal activity at rest was assessed in seventy healthy volunteers using electroencephalography, and compared to their choice behavior on an economic risk-taking task. The Behavioral Inhibition System/Behavioral Activation System scale was used to measure participants' trait sensitivity to reward and punishment. Our results confirmed both prefrontal resting-state activity and personality traits as sources of individual differences in risk-taking behavior. Right-left asymmetry in prefrontal activity and scores on the Behavioral Inhibition System scale, reflecting trait sensitivity to punishment, were correlated with the level of risk-taking on the task. We further discovered that scores on the Behavioral Inhibition System scale modulated the relationship between asymmetry in prefrontal resting-state activity and risk-taking. The results of this study demonstrate that heterogeneity in risk-taking behavior can be traced back to differences in the basic physiology of decision-makers' brains, and suggest that baseline prefrontal activity and personality traits might interplay in guiding risk-taking behavior.

  20. Visual cortex activity predicts subjective experience after reading books with colored letters.

    Colizoli, Olympia; Murre, Jaap M J; Scholte, H Steven; van Es, Daniel M; Knapen, Tomas; Rouw, Romke

    2016-07-29

    One of the most astonishing properties of synesthesia is that the evoked concurrent experiences are perceptual. Is it possible to acquire similar effects after learning cross-modal associations that resemble synesthetic mappings? In this study, we examine whether brain activation in early visual areas can be directly related to letter-color associations acquired by training. Non-synesthetes read specially prepared books with colored letters for several weeks and were scanned using functional magnetic resonance imaging. If the acquired letter-color associations were visual in nature, then brain activation in visual cortex while viewing the trained black letters (compared to untrained black letters) should predict the strength of the associations, the quality of the color experience, or the vividness of visual mental imagery. Results showed that training-related activation of area V4 was correlated with differences in reported subjective color experience. Trainees who were classified as having stronger 'associator' types of color experiences also had more negative activation for trained compared to untrained achromatic letters in area V4. In contrast, the strength of the acquired associations (measured as the Stroop effect) was not reliably reflected in visual cortex activity. The reported vividness of visual mental imagery was related to veridical color activation in early visual cortex, but not to the acquired color associations. We show for the first time that subjective experience related to a synesthesia-training paradigm was reflected in visual brain activation. PMID:26162617