979 resultados para Adaptive-behavior Scales
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In this work the turbulent flow of the Non-Newtonian Carreau-Yasuda fluid will be studied. A skin friction equation for the turbulent flow of Carreau-Yasuda fluids will be derived assuming a logarithmic behavior of the turbulent mean velocity for the near wall flow out of the viscous sub layer. An alternative near wall characteristic length scale which takes into account the effects of the relaxation time will be introduced. The characteristic length will be obtained through the analysis of viscous region near the wall. The results compared with experimental data obtained with Tylose (methyl hydroxil cellulose) solutions showing good agreement. The relations between scales integral and dissipative obtained for length, time, velocity, kinetic energy, and vorticity will be derived for this type of fluid. When the power law index approach to unity the relations reduces to Newtonian case.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.
Generalizing the dynamic field theory of spatial cognition across real and developmental time scales
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Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.
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Stereotyped behaviors have been routinely used as characters for phylogeny inference, but the same cannot be said of the plastic aspects of performance, which routinely are taken as a result of ecological processes. In this paper we examine the evolution of one of these plastic behavioral phenotypes, thus fostering a bridge between ecological and evolutionary processes. Foraging behavior in spiders is context dependent in many aspects, since it varies with prey type and size, spider nutritional and developmental state, previous experience and, in webweavers, is dependent on the structure of the web. Reeling is a predatory tactic typical of cobweb weavers (Theridiidae), in which the spider moves the prey toward her by pulling the capture thread (gumfoot) to which it is adhered. Predatory reeling is dependent on the gumfoot for its expression, and has not been previously reported in orbweavers. In order to investigate the evolution of this web dependent behavior, we built artificial, pseudogumfoot lines in orbwebs and registered parameters of the predatory tactics in this modified web. Aspects of the predatory tactics of 240 individuals (12 species in 4 families) were measured, and the resulting data were optimized on the phylogeny of Orbiculariae. All species perform predatory reeling with the pseudogumfoot lines. Thus, predatory reeling is homologous for the whole Orbiculariae group. In nature, holes made by insects in ecribellate orbs produce pseudogumfoot lines (similar to out experimentally modified webs), and thus reeling occurred naturally in ecribellates. Nevertheless, outside lab conditions, predatory reeling does not occur among cribellate orbweavers, so that this behavior could not have been selected for in the cribellate ancester of orbweavers. Cribellate spiders are flexible enough as to present novel and adaptive predatory responses (reeling) even when exposed for the first time to conditions outside their usual environment. Thus, the evolution of reeling suggests and alternative mechanism for the production of evolutionary novelties; that is, the exploration of unusual ecological conditions and of the regular effects these abnormal conditions have on phenotype expression.
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Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.
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BACKGROUND: Evaluations of clinical depression are traditionally based on verbal information. Nonverbal expressive behavior, however, being associated with a person's reflexive responses, may reveal negative emotional or social processes that are not under complete control of the patients. However, investigations of nonverbal behavior in the evaluation of depressed patients are still scarce. This study examines the nonverbal behaviors of a group of Brazilian patients, associating their nonverbal behavior with severity of depression. METHODS: Forty depressed patients were evaluated at baseline (T0) and after a two-week transcranial direct current stimulation treatment (T1), according to rating scales and through a 21-category Ethogram for assessment of the frequency of nonverbal behaviors displayed during an interview. RESULTS: Behaviors that were related to negative feelings and social disinterest decreased with corresponding clinical improvement and were associated with increased severity of symptoms at T0 and greater negative affect and dissatisfaction at T1. Pro-social behaviors were associated with milder symptoms at T0 and increased after treatment. Facial, head and hand expressive movements stood out as important indicators because of their associations with severity of depression. LIMITATIONS: Duration of behaviors was not assessed and there was not a healthy control group with which to compare the findings. CONCLUSIONS: These results support the usefulness of nonverbal behavior as an evaluation technique in the assessment of clinical depression.
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During the last few decades, coral reefs have become a disappearing feature of tropical marine environments, and those reefs that do remain are severely threatened. It is understood that humans have greately altered the environment under which these ecosystems previously have thrived and evoloved. Overharvesting of fish stocks, global warming and pollution are some of the most prominent threats, acting on coral reefs at several spatial and temporal scales. Presently, it is common that coral reefs have been degraded into alternative ecosystem regimes, such as macroalgae-dominated or sea urchin-barren. Although these ecosystems could potentially return to coral dominance in a long-term perspective, when considdering current conditions, it seems likely that they will persist in their degraded states. Thus, recovery of coral reefs cannot be taken for granted on a human timescale. Multiple stressors and disturbances, which are increasingly characteristic of coral reef environments today, are believed to act synergistically and produce ecological surprises. However, current knowledge of effects of compounded disturbances and stress is limited. Based on five papers, this thesis investigates the sublethal response of multiple stressors on coral physiology, as well as the effects of compounded stress and disturbance on coral reef structure and function. Adaptive responses to stress and disturbance in relation to prior experience are highlighted. The thesis further explores how inherent characteristics (traits) of corals and macroalgae may influence regime expression when faced with altered disturbance regimes, in particular overfishing, eutrophication, elevated temperature, and enhanced substrate availability. Finally, possibilities of affecting the resilience of macroalgae-dominaed reefs and shifting the community composition towards a coral-dominated regime are explored.
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Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.
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In the framework of developing defect-based life models, in which breakdown is explicitly associated with partial discharge (PD)-induced damage growth from a defect, ageing tests and PD measurements were carried out in the lab on polyethylene (PE) layered specimens containing artificial cavities. PD activity was monitored continuously during aging. A quasi-deterministic series of stages can be observed in the behavior of the main PD parameters (i.e. discharge repetition rate and amplitude). Phase-resolved PD patterns at various ageing stages were reproduced by numerical simulation which is based on a physical discharge model devoid of adaptive parameters. The evolution of the simulation parameters provides insight into the physical-chemical changes taking place at the dielectric/cavity interface during the aging process. PD activity shows similar time behavior under constant cavity gas volume and constant cavity gas pressure conditions, suggesting that the variation of PD parameters may not be attributed to the variation of the gas pressure. Brownish PD byproducts, consisting of oxygen containing moieties, and degradation pits were found at the dielectric/cavity interface. It is speculated that the change of PD activity is related to the composition of the cavity gas, as well as to the properties of dielectric/cavity interface.
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Over the last three decades, international agricultural trade has grown significantly. Technological advances in transportation logistics and storage have created opportunities to ship anything almost anywhere. Bilateral and multilateral trade agreements have also opened new pathways to an increasingly global market place. Yet, international agricultural trade is often constrained by differences in regulatory regimes. The impact of “regulatory asymmetry” is particularly acute for small and medium sized enterprises (SMEs) that lack resources and expertise to successfully operate in markets that have substantially different regulatory structures. As governments seek to encourage the development of SMEs, policy makers often confront the critical question of what ultimately motivates SME export behavior. Specifically, there is considerable interest in understanding how SMEs confront the challenges of regulatory asymmetry. Neoclassical models of the firm generally emphasize expected profit maximization under uncertainty, however these approaches do not adequately explain the entrepreneurial decision under regulatory asymmetry. Behavioral theories of the firm offer a far richer understanding of decision making by taking into account aspirations and adaptive performance in risky environments. This paper develops an analytical framework for decision making of a single agent. Considering risk, uncertainty and opportunity cost, the analysis focuses on the export behavior response of an SME in a situation of regulatory asymmetry. Drawing on the experience of fruit processor in Muzaffarpur, India, who must consider different regulatory environments when shipping fruit treated with sulfur dioxide, the study dissects the firm-level decision using @Risk, a Monte Carlo computational tool.
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Die vorliegende Arbeit untersucht den Zusammenhang zwischen Skalen in Systemen weicher Materie, der für Multiskalen-Simulationen eine wichtige Rolle spielt. Zu diesem Zweck wurde eine Methode entwickelt, die die Approximation der Separierbarkeit von Variablen für die Molekulardynamik und ähnliche Anwendungen bewertet. Der zweite und größere Teil dieser Arbeit beschäftigt sich mit der konzeptionellen und technischen Erweiterung des Adaptive Resolution Scheme'' (AdResS), einer Methode zur gleichzeitigen Simulation von Systemen mit mehreren Auflösungsebenen. Diese Methode wurde auf Systeme erweitert, in denen klassische und quantenmechanische Effekte eine Rolle spielen.rnrnDie oben genannte erste Methode benötigt nur die analytische Form der Potentiale, wie sie die meisten Molekulardynamik-Programme zur Verfügung stellen. Die Anwendung der Methode auf ein spezielles Problem gibt bei erfolgreichem Ausgang einen numerischen Hinweis auf die Gültigkeit der Variablenseparation. Bei nicht erfolgreichem Ausgang garantiert sie, dass keine Separation der Variablen möglich ist. Die Methode wird exemplarisch auf ein zweiatomiges Molekül auf einer Oberfläche und für die zweidimensionale Version des Rotational Isomer State (RIS) Modells einer Polymerkette angewandt.rnrnDer zweite Teil der Arbeit behandelt die Entwicklung eines Algorithmus zur adaptiven Simulation von Systemen, in denen Quanteneffekte berücksichtigt werden. Die Quantennatur von Atomen wird dabei in der Pfadintegral-Methode durch einen klassischen Polymerring repräsentiert. Die adaptive Pfadintegral-Methode wird zunächst für einatomige Flüssigkeiten und tetraedrische Moleküle unter normalen thermodynamischen Bedingungen getestet. Schließlich wird die Stabilität der Methode durch ihre Anwendung auf flüssigen para-Wasserstoff bei niedrigen Temperaturen geprüft.
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In my dissertation I investigated the influence of behavioral variation between and within ant colonies on group performance. In particular, I analyzed how evolution shapes behavior in response to ecological conditions, and whether within-group diversity improves productivity as suggested by theory. Our field and laboratory experiments showed that behavioral diverse groups are more productive. Different aggression levels within colonies were beneficial under competitive field situations, whereas diversity in brood care and exploratory behavior were favored in non-competitive laboratory situations. We then examined whether population density and social parasite presence shape aggression through phenotypic plasticity and/or natural selection. The importance of selection was indicated by the absence of density or parasite effects on aggression in a field manipulation. Indeed, more aggressive colonies fared better under high density and during parasite attack. When analyzing the proximate causes of individual behavioral variation, ovarian development was shown to be linked to division of labor and aggressiveness. Finally, our studies show that differences in the collective behavior can be linked to immune defense and productivity. My dissertation demonstrates that behavioral variation should be studied on multiple scales and when possible combined with physiological analyses to better understand the evolution of animal personalities in social groups.rn
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In this thesis different approaches for the modeling and simulation of the blood protein fibrinogen are presented. The approaches are meant to systematically connect the multiple time and length scales involved in the dynamics of fibrinogen in solution and at inorganic surfaces. The first part of the thesis will cover simulations of fibrinogen on an all atom level. Simulations of the fibrinogen protomer and dimer are performed in explicit solvent to characterize the dynamics of fibrinogen in solution. These simulations reveal an unexpectedly large and fast bending motion that is facilitated by molecular hinges located in the coiled-coil region of fibrinogen. This behavior is characterized by a bending and a dihedral angle and the distribution of these angles is measured. As a consequence of the atomistic detail of the simulations it is possible to illuminate small scale behavior in the binding pockets of fibrinogen that hints at a previously unknown allosteric effect. In a second step atomistic simulations of the fibrinogen protomer are performed at graphite and mica surfaces to investigate initial adsorption stages. These simulations highlight the different adsorption mechanisms at the hydrophobic graphite surface and the charged, hydrophilic mica surface. It is found that the initial adsorption happens in a preferred orientation on mica. Many effects of practical interest involve aggregates of many fibrinogen molecules. To investigate such systems, time and length scales need to be simulated that are not attainable in atomistic simulations. It is therefore necessary to develop lower resolution models of fibrinogen. This is done in the second part of the thesis. First a systematically coarse grained model is derived and parametrized based on the atomistic simulations of the first part. In this model the fibrinogen molecule is represented by 45 beads instead of nearly 31,000 atoms. The intra-molecular interactions of the beads are modeled as a heterogeneous elastic network while inter-molecular interactions are assumed to be a combination of electrostatic and van der Waals interaction. A method is presented that determines the charges assigned to beads by matching the electrostatic potential in the atomistic simulation. Lastly a phenomenological model is developed that represents fibrinogen by five beads connected by rigid rods with two hinges. This model only captures the large scale dynamics in the atomistic simulations but can shed light on experimental observations of fibrinogen conformations at inorganic surfaces.
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[ITA]La demenza consiste nel deterioramento, spesso progressivo, dello stato cognitivo di un individuo. Chi è affetto da demenza, presenta alterazioni a livello cognitivo, comportamentale e motorio, ad esempio compiendo gesti ossessivi, ripetitivi, senza uno scopo preciso. La condizione dei pazienti affetti da demenza è valutata clinicamente tramite apposite scale e le informazioni relative al comportamento vengono raccolte intervistando chi se ne occupa, come familiari, il personale infermieristico o il medico curante. Spesso queste valutazioni si rivelano inaccurate, possono essere fortemente influenzate da considerazioni soggettive, e sono dispendiose in termini di tempo. Si ha quindi l'esigenza di disporre di metodiche oggettive per valutare il comportamento motorio dei pazienti e le sue alterazioni patologiche; i sensori inerziali indossabili potrebbero costituire una valida soluzione, per questo scopo. L'obiettivo principale della presente attività di tesi è stato definire e implementare un software per una valutazione oggettiva, basata su sensori, del pattern motorio circadiano, in pazienti affetti da demenza ricoverati in un'unità di terapia a lungo termine, che potrebbe evidenziare differenze nei sintomi della malattia che interessano il comportamento motorio, come descritto in ambito clinico. Lo scopo secondario è stato quello di verificare i cambiamenti motori pre- e post-intervento in un sottogruppo di pazienti, a seguito della somministrazione di un programma sperimentale di intervento basato su esercizi fisici. --------------- [ENG]Dementia involves deterioration, often progressive, of a person's cognitive status. Those who suffer from dementia, present alterations in cognitive and motor behavior, for example performing obsessive and repetitive gestures, without a purpose. The condition of patients suffering from dementia is clinically assessed by means of specific scales and information relating to the behavior are collected by interviewing caregivers, such as the family, nurses, or the doctor. Often it turns out that these are inaccurate assessments that may be heavily influenced by subjective evaluations and are costly in terms of time. Therefore, there is the need for objective methods to assess the patients' motor behavior and the pathological changes; wearable inertial sensors may represent a viable option, so this aim. The main objective of this thesis project was to define and implement a software for a sensor-based assessment of the circadian motor pattern in patients suffering from dementia, hospitalized in a long-term care unit, which could highlight differences in the disease symptoms affecting the motor behavior, as described in the clinical setting. The secondary objective was to verify pre- and post-intervention changes in the motor patterns of a subgroup of patients, following the administration of an experimental program of intervention based on physical exercises.