892 resultados para Criminal behavior, Prediction of


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Includes indexes.

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Includes index.

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La psychopathie et le trouble de personnalité antisociale sont deux syndromes reliés qui ont été identifiés comme prédicteurs importants de comportements violents et de criminalité. Cependant, la recherche indique que les facteurs de la psychopathie centrés sur la personnalité ne sont pas des prédicteurs fiables de récidive violente chez les personnes atteintes de maladies mentales. Toutefois, peu d’études se sont centrées sur l’identification des facteurs associés au patron des antécédents criminels. Les 96 hommes de l’étude ont été déclarés non criminellement responsables en raison de troubles mentaux. Ils ont été évalués quant au trouble de la personnalité antisociale ainsi qu’à la psychopathie. Les dossiers criminels de la Gendarmerie Royale du Canada ont également été consultés afin de reconstituer l’histoire criminelle. Les résultats suggèrent que ni les traits de personnalité antisociaux, ni les facteurs de la psychopathie ne démontrent une validité prédictive incrémentielle les uns sur les autres quant au nombre ou à la sévérité des délits. La présence d’un grand nombre de traits antisociaux est associée à un plus grand nombre et à une plus importante sévérité d’actes criminels non-violents. Les résultats sont discutés en termes de l’utilité d’une classification du trouble de personnalité antisociale, et de la pertinence du construit de la psychopathie pour les personnes atteintes de maladies mentales graves.

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Process scheduling techniques consider the current load situation to allocate computing resources. Those techniques make approximations such as the average of communication, processing, and memory access to improve the process scheduling, although processes may present different behaviors during their whole execution. They may start with high communication requirements and later just processing. By discovering how processes behave over time, we believe it is possible to improve the resource allocation. This has motivated this paper which adopts chaos theory concepts and nonlinear prediction techniques in order to model and predict process behavior. Results confirm the radial basis function technique which presents good predictions and also low processing demands show what is essential in a real distributed environment.

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Two experiments examined the effects of majority and minority influence on attitude-consistent behavioral intentions. In the first experiment, when attitudes were changed via minority influence there was a greater likelihood to engage in an attitude-consistent behavioral intention than when attitudes were changed via majority influence. This suggests that minority influence leads to stronger attitudes (based on systematic processing) that are more predictive of behavioral intentions, while attitude change via majority influence is due to compliance through non-systematic processing. Further support for this interpretation comes from the finding that the amount of message-congruent elaboration mediated behavioral intention. When there was no attitude change, there was no impact on behavioral intention to engage in an attitude-consistent behavior. Experiment 2 explored the role of personal relevance of the topic and also included a real behavioral measure. When the topic was of low personal relevance, the same pattern was found as Experiment 1. When the topic was of high personal relevance, thus increasing the motivation to engage in systematic processing, attitudes changed by both a majority and minority source increased behavioral intention and actual behavior. The results are consistent with the view that both majorities and minorities can lead to different processes and consequences under different situations. © 2006 Elsevier Inc. All rights reserved.

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The present study examined the relative importance of outcome expectancies and self-efficacy [1] in the prediction of alcohol dependence [2] and alcohol consumption in a sample of young adult drinkers drawn from a milieu previously reported as supportive of risky drinking. In predicting alcohol dependence, outcome expectancies were found to mediate self-efficacy and the same pattern was found for both males and females. This suggests that male and female drinkers may become more similar as they progress along the drinking continuum from risky drinking to dependent drinking. However, in women, in comparison to men, a greater array of expectancies and self-efficacy scales were found to predict heavy drinking, as measured by quantity and frequency. These results suggest that heavy drinking women are particularly at risk of developing drinking related complications and that preventative education needs to take into account gender differences.

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This paper outlines research on the processes taking place within the coal mineral matter at high temperatures and development of the relationship between ash fusion temperatures (AFT) and phase equilibria of the coal ash slags. A new thermodynamic database for the Al-Ca-Fe-O-Si system developed by the author was used in conjunction with the thermodynamic computer package F*A*C*T for these purposes. In addition, high temperature experimental studies were undertaken that involved heat treatment and quenching of the ash cones followed by the analyses using different techniques. The study provided new information on the processes taking place during AFT test and demonstrated the validity of the AFTs predictions with F*A*C*T. Examples of practical applications of the AFT prediction method are given in the paper. The results of this study are important not only for the AFT predictions, but also in general for the application of phase equilibrium science to the characterisation of the coal mineral matter interactions at high temperature. (C) 2002 Elsevier Science Ltd. All rights reserved.

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This article investigates the limit cycle (LC) prediction of systems with backlash by means of the describing function (DF) when using discrete fractional-order (FO) algorithms. The DF is an approximate method that gives good estimates of LCs. The implementation of FO controllers requires the use of rational approximations, but such realizations produce distinct dynamic types of behavior. This study analyzes the accuracy in the prediction of LCs, namely their amplitude and frequency, when using several different algorithms. To illustrate this problem we use FO-PID algorithms in the control of systems with backlash.

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Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputsanddefined bytwo thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt andmold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.

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Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted in developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas little has been done to predict the hydrolytic activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES1. The study involves both docking analyses of known substrates to develop predictive models, and molecular dynamics (MD) simulations to reveal the in situ behavior of substrates and products, with particular attention being paid to the influence of their ionization state. The results emphasize some crucial properties of the hCES1 catalytic cavity, confirming that as a trend with several exceptions, hCES1 prefers substrates with relatively smaller and somewhat polar alkyl/aryl groups and larger hydrophobic acyl moieties. The docking results underline the usefulness of the hydrophobic interaction score proposed here, which allows a robust prediction of hCES1 catalysis, while the MD simulations show the different behavior of substrates and products in the enzyme cavity, suggesting in particular that basic substrates interact with the enzyme in their unprotonated form.

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Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

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This report is concerned with the prediction of the long-time creep and shrinkage behavior of concrete. It is divided into three main areas. l. The development of general prediction methods that can be used by a design engineer when specific experimental data are not available. 2. The development of prediction methods based on experimental data. These methods take advantage of equations developed in item l, and can be used to accurately predict creep and shrinkage after only 28 days of data collection. 3. Experimental verification of items l and 2, and the development of specific prediction equations for four sand-lightweight aggregate concretes tested in the experimental program. The general prediction equations and methods are developed in Chapter II. Standard Equations to estimate the creep of normal weight concrete (Eq. 9), sand-lightweight concrete (Eq. 12), and lightweight concrete (Eq. 15) are recommended. These equations are developed for standard conditions (see Sec. 2. 1) and correction factors required to convert creep coefficients obtained from equations 9, 12, and 15 to valid predictions for other conditions are given in Equations 17 through 23. The correction factors are shown graphically in Figs. 6 through 13. Similar equations and methods are developed for the prediction of the shrinkage of moist cured normal weight concrete (Eq. 30}, moist cured sand-lightweight concrete (Eq. 33}, and moist cured lightweight concrete (Eq. 36). For steam cured concrete the equations are Eq. 42 for normal weight concrete, and Eq. 45 for lightweight concrete. Correction factors are given in Equations 47 through 52 and Figs., 18 through 24. Chapter III summarizes and illustrates, by examples, the prediction methods developed in Chapter II. Chapters IV and V describe an experimental program in which specific prediction equations are developed for concretes made with Haydite manufactured by Hydraulic Press Brick Co. (Eqs. 53 and 54}, Haydite manufactured by Buildex Inc. (Eqs. 55 and 56), Haydite manufactured by The Cater-Waters Corp. (Eqs. 57 and 58}, and Idealite manufactured by Idealite Co. (Eqs. 59 and 60). General prediction equations are also developed from the data obtained in the experimental program (Eqs. 61 and 62) and are compared to similar equations developed in Chapter II. Creep and Shrinkage prediction methods based on 28 day experimental data are developed in Chapter VI. The methods are verified by comparing predicted and measured values of the long-time creep and shrinkage of specimens tested at the University of Iowa (see Chapters IV and V) and elsewhere. The accuracy obtained is shown to be superior to other similar methods available to the design engineer.

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Solid mixtures for refreshment are already totally integrated to the Brazilian consumers' daily routine, because of their quick preparation method, yield and reasonable price - quite lower if compared to 'ready-to-drink' products or products for prompt consumption, what makes them economically more accessible to low-income populations. Within such a context, the aim of this work was to evaluate the physicochemical and mineral composition, as well as the hygroscopic behavior of four different brands of solid mixture for mango refreshment. The BET, GAB, Oswim and Henderson mathematical models were built through the adjustment of experimental data to the isotherms of adsorption. Results from the physiochemical evaluation showed that the solid mixtures for refreshments are considerable sources of ascorbic acid and reductor sugar; and regarding mineral compounds, they are significant sources of calcium, sodium and potassium. It was also verified that the solid mixtures for refreshments of the four studied brands are considered highly hygroscopic.

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Personality traits and personal values are two important domains of individual differences. Traits are enduring and distinguishable patterns of behaviour whereas values are societally taught, stable, individual preferences that guide behaviour in order to reach a specific end state. The purpose of the present study was to investigate the relations between self and peer report within the domains of personality traits and values, to examine the correlations between values and traits, and to explore the amount of incremental validity of traits and values in predicting behaviour. Two hundred and fiftytwo men and women from a university setting completed self and peer reports on three questionnaires. In order to assess personality traits, the HEXACO-PI (Lee & Ashton, 2004) was used to identify levels of 6 major dimensions of personality in participants. To assess values, the Schwartz Value Survey (Schwartz, 1992) was used to identify the importance each participant placed on each of Schwartz's 10 value types. To measure behaviour, a Behavior Scale, created by Bardi and Schwartz (2003), consisting of items designed to measure the frequency of value-expressive behaviour was used. As expected, correlations between self and peer reports for the personality scales were high indicating that personality traits are easily observable to other people. Correlations between self and peer reports for the values and behaviour scales were only moderate, suggesting that some goals, and behaviours expressive of those goals, may not always be observable to others. Consistent with previous research, there were many strong correlations between traits and values. In addition to the similarities with past research, the present study found that the personality factor Honesty-Humility was correlated strongly with values scales (with five correlations exceeding .25). In the prediction of behaviour, it was found that both personahty and values were able to account for significant and similar amounts of variance. Personality outpredicted values for some behaviours, but the opposite was true of other behaviours. Each domain provided incremental validity beyond the other domain. The impUcations for these findings, along with limitations, and possibilities for future research are also discussed.

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In this contribution we aim at anchoring Agent-Based Modeling (ABM) simulations in actual models of human psychology. More specifically, we apply unidirectional ABM to social psychological models using low level agents (i.e., intra-individual) to examine whether they generate better predictions, in comparison to standard statistical approaches, concerning the intentions of performing a behavior and the behavior. Moreover, this contribution tests to what extent the predictive validity of models of attitude such as the Theory of Planned Behavior (TPB) or Model of Goal-directed Behavior (MGB) depends on the assumption that peoples’ decisions and actions are purely rational. Simulations were therefore run by considering different deviations from rationality of the agents with a trembling hand method. Two data sets concerning respectively the consumption of soft drinks and physical activity were used. Three key findings emerged from the simulations. First, compared to standard statistical approach the agent-based simulation generally improves the prediction of behavior from intention. Second, the improvement in prediction is inversely proportional to the complexity of the underlying theoretical model. Finally, the introduction of varying degrees of deviation from rationality in agents’ behavior can lead to an improvement in the goodness of fit of the simulations. By demonstrating the potential of ABM as a complementary perspective to evaluating social psychological models, this contribution underlines the necessity of better defining agents in terms of psychological processes before examining higher levels such as the interactions between individuals.