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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. 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…

  12. 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...

  13. 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

  14. 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

  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. 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 .

  19. 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...

  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. 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.

  5. 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

  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. 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...

  16. 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

  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. 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

  15. 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

  16. 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...

  17. 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 ...

  18. 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...

  19. 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...

  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 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.…

  3. 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...

  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. 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...

  14. 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.

  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. 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

  14. 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.

  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. 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

  20. 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.

  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. 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.

  8. 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....

  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. 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.

  10. 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...

  11. 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...

  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. 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...

  18. 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...

  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. 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

  3. 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.

  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. 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.

  10. 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.

  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. 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

  13. 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.

  14. 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

  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. 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.

  20. 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

  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. 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.

  9. 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…

  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. 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.

  12. 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...

  13. 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

  14. 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...

  15. 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...

  16. 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...

  17. 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....

  18. 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...

  19. 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) ...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  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...