Isotactics as a foundation for alignment and abstraction of behavioral models

There are many use cases in business process management that require the comparison of behavioral models. For instance, verifying equivalence is the basis for assessing whether a technical workflow correctly implements a business process, or whether a process realization conforms to a reference process. This paper proposes an equivalence relation for models that describe behaviors based on the concurrency semantics of net theory and for which an alignment relation has been defined. This equivalence, called isotactics, preserves the level of concurrency of aligned operations. Furthermore, we elaborate on the conditions under which an alignment relation can be classified as an abstraction. Finally, we show that alignment relations induced by structural refinements of behavioral models are indeed behavioral abstractions.

Discovery of Novel Allosteric Modulators of Metabotropic Glutamate Receptor Subtype 5 Reveals Chemical and Functional Diversity and In Vivo Activity in Rat Behavioral Models of Anxiolytic and Antipsychotic Activity

Modulators of metabotropic glutamate receptor subtype 5 (mGluR5) may provide novel treatments for multiple central nervous system (CNS) disorders, including anxiety and schizophrenia. Although compounds have been developed to better understand the physiological roles of mGluR5 and potential usefulness for the treatment of these disorders, there are limitations in the tools available, including poor selectivity, low potency, and limited solubility. To address these issues, we developed an innovative assay that allows simultaneous screening for mGluR5 agonists, antagonists, and potentiators. We identified multiple scaffolds that possess diverse modes of activity at mGluR5, including both positive and negative allosteric modulators (PAMs and NAMs, respectively). 3-Fluoro-5-(3-(pyridine-2-yl)-1,2,4-oxadiazol-5-yl) benzonitrile (VU0285683) was developed as a novel selective mGluR5 NAM with high affinity for the 2-methyl-6-(phenyl-ethynyl)-pyridine (MPEP) binding site. VU0285683 had anxiolytic-like activity in two rodent models for anxiety but did not potentiate phen-cyclidine-induced hyperlocomotor activity. (4-Hydroxypiperidin-1-yl)(4-phenylethynyl) phenyl) methanone (VU0092273) was identified as a novel mGluR5 PAM that also binds to the MPEP site. VU0092273 was chemically optimized to an orally active analog, N-cyclobutyl-6-((3-fluorophenyl) ethynyl) nicotinamide hydrochloride (VU0360172), which is selective for mGluR5. This novel mGluR5 PAM produced a dose-dependent reversal of amphetamine-induced hyperlocomotion, a rodent model predictive of antipsychotic activity. Discovery of structurally and functionally diverse allosteric modulators of mGluR5 that demonstrate in vivo efficacy in rodent models of anxiety and antipsychotic activity provide further support for the tremendous diversity of chemical scaffolds and modes of efficacy of mGluR5 ligands. In addition, these studies provide strong support for the hypothesis that multiple structurally distinct mGluR5 modulators have robust activity in animal models that predict efficacy in the treatment of CNS disorders.

Construct validity of behavioral models of anxiety: where experimental psychopathology meets ecology and evolution

In experimental psychopathology, construct validity is usually enhanced by addressing theories from other fields in its nomological network. In the field of anxiety research, this construct is related to antipredator behavior, conserved across phylogeny in its functions and neural basis, but not necessarily on its topography. Even though the relations between behavioral models of anxiety and statements from behavioral ecology and evolutionary biology are commonly made in anxiety research, these are rarely tested, at least explicitly. However, in order to increase construct validity in experimental anxiety, testing predictions from those theories is highly desirable. This article discusses these questions, suggesting a few ways in which behavioral ecological and evolutionary hypotheses of anxiety-like behavior may be tested.

Behavioral Model Generation from Use Cases Based on Ontology Mapping and GRASP Patterns

This paper contributes a new approach for developing UML software designs from Natural Language (NL), making use of a meta-domain oriented ontology, well established software design principles and Natural Language Processing (NLP) tools. In the approach described here, banks of grammatical rules are used to assign event flows from essential use cases. A domain specific ontology is also constructed, permitting semantic mapping between the NL input and the modeled domain. Rules based on the widely-used General Responsibility Assignment Software Principles (GRASP) are then applied to derive behavioral models.

Behavioral modeling optimization and enhancement for high-speed analog mixed-signal I/O interfaces

A integridade do sinal em sistemas digitais interligados de alta velocidade, e avaliada através da simulação de modelos físicos (de nível de transístor) é custosa de ponto vista computacional (por exemplo, em tempo de execução de CPU e armazenamento de memória), e exige a disponibilização de detalhes físicos da estrutura interna do dispositivo. Esse cenário aumenta o interesse pela alternativa de modelação comportamental que descreve as características de operação do equipamento a partir da observação dos sinais eléctrico de entrada/saída (E/S). Os interfaces de E/S em chips de memória, que mais contribuem em carga computacional, desempenham funções complexas e incluem, por isso, um elevado número de pinos. Particularmente, os buffers de saída são obrigados a distorcer os sinais devido à sua dinâmica e não linearidade. Portanto, constituem o ponto crítico nos de circuitos integrados (CI) para a garantia da transmissão confiável em comunicações digitais de alta velocidade. Neste trabalho de doutoramento, os efeitos dinâmicos não-lineares anteriormente negligenciados do buffer de saída são estudados e modulados de forma eficiente para reduzir a complexidade da modelação do tipo caixa-negra paramétrica, melhorando assim o modelo standard IBIS. Isto é conseguido seguindo a abordagem semi-física que combina as características de formulação do modelo caixa-negra, a análise dos sinais eléctricos observados na E/S e propriedades na estrutura física do buffer em condições de operação práticas. Esta abordagem leva a um processo de construção do modelo comportamental fisicamente inspirado que supera os problemas das abordagens anteriores, optimizando os recursos utilizados em diferentes etapas de geração do modelo (ou seja, caracterização, formulação, extracção e implementação) para simular o comportamento dinâmico não-linear do buffer. Em consequência, contributo mais significativo desta tese é o desenvolvimento de um novo modelo comportamental analógico de duas portas adequado à simulação em overclocking que reveste de um particular interesse nas mais recentes usos de interfaces de E/S para memória de elevadas taxas de transmissão. A eficácia e a precisão dos modelos comportamentais desenvolvidos e implementados são qualitativa e quantitativamente avaliados comparando os resultados numéricos de extracção das suas funções e de simulação transitória com o correspondente modelo de referência do estado-da-arte, IBIS.

Essays in behavioral economics

In this work we conduct an experimental analysis on different behavioral models of economic choice. In particular, we analyze the role of overconfidence in shaping the beliefs of economics agents about the future path of their consumption or investment. We discuss the relevance of this bias in expectation formation both from a static and from a dynamic point of view and we analyze the effect of possible interventions aimed to achieve some policy goals. The methodology we follow is both theoretical and empirical. In particular, we make large use of controlled economic field experiments in order to test the predictions of the theoretical models we propose. In the second part of the thesis we discuss the role of cognition and personality in affecting economic preferences and choices. In this way we make a bridge between established psychological research and novel findings in economics. Finally, we conduct a field study on the role of incentives on education. We design different incentive schemes and we test, on randomized groups of students, their effectiveness in improving academic performance.

Estimating dynamic models with aggregate shocks and an application to mortgage default in Colombia

We estimate a dynamic model of mortgage default for a cohort of Colombian debtors between 1997 and 2004. We use the estimated model to study the effects on default of a class of policies that affected the evolution of mortgage balances in Colombia during the 1990's. We propose a framework for estimating dynamic behavioral models accounting for the presence of unobserved state variables that are correlated across individuals and across time periods. We extend the standard literature on the structural estimation of dynamic models by incorporating an unobserved common correlated shock that affects all individuals' static payoffs and the dynamic continuation payoffs associated with different decisions. Given a standard parametric specification the dynamic problem, we show that the aggregate shocks are identified from the variation in the observed aggregate behavior. The shocks and their transition are separately identified, provided there is enough cross-sectionavl ariation of the observeds tates.

Connectivity of workflow nets : the foundations of stepwise verification

Behavioral models capture operational principles of real-world or designed systems. Formally, each behavioral model defines the state space of a system, i.e., its states and the principles of state transitions. Such a model is the basis for analysis of the system’s properties. In practice, state spaces of systems are immense, which results in huge computational complexity for their analysis. Behavioral models are typically described as executable graphs, whose execution semantics encodes a state space. The structure theory of behavioral models studies the relations between the structure of a model and the properties of its state space. In this article, we use the connectivity property of graphs to achieve an efficient and extensive discovery of the compositional structure of behavioral models; behavioral models get stepwise decomposed into components with clear structural characteristics and inter-component relations. At each decomposition step, the discovered compositional structure of a model is used for reasoning on properties of the whole state space of the system. The approach is exemplified by means of a concrete behavioral model and verification criterion. That is, we analyze workflow nets, a well-established tool for modeling behavior of distributed systems, with respect to the soundness property, a basic correctness property of workflow nets. Stepwise verification allows the detection of violations of the soundness property by inspecting small portions of a model, thereby considerably reducing the amount of work to be done to perform soundness checks. Besides formal results, we also report on findings from applying our approach to an industry model collection.

The strategic behavior of rational novices

There is a growing amount of experimental evidence that suggests people often deviate from the predictions of game theory. Some scholars attempt to explain the observations by introducing errors into behavioral models. However, most of these modifications are situation dependent and do not generalize. A new theory, called the rational novice model, is introduced as an attempt to provide a general theory that takes account of erroneous behavior. The rational novice model is based on two central principals. The first is that people systematically make inaccurate guesses when they are evaluating their options in a game-like situation. The second is that people treat their decisions similar to a portfolio problem. As a result, non optimal actions in a game theoretic sense may be included in the rational novice strategy profile with positive weights.

The rational novice model can be divided into two parts: the behavioral model and the equilibrium concept. In a theoretical chapter, the mathematics of the behavioral model and the equilibrium concept are introduced. The existence of the equilibrium is established. In addition, the Nash equilibrium is shown to be a special case of the rational novice equilibrium. In another chapter, the rational novice model is applied to a voluntary contribution game. Numerical methods were used to obtain the solution. The model is estimated with data obtained from the Palfrey and Prisbrey experimental study of the voluntary contribution game. It is found that the rational novice model explains the data better than the Nash model. Although a formal statistical test was not used, pseudo R^2 analysis indicates that the rational novice model is better than a Probit model similar to the one used in the Palfrey and Prisbrey study.

The rational novice model is also applied to a first price sealed bid auction. Again, computing techniques were used to obtain a numerical solution. The data obtained from the Chen and Plott study were used to estimate the model. The rational novice model outperforms the CRRAM, the primary Nash model studied in the Chen and Plott study. However, the rational novice model is not the best amongst all models. A sophisticated rule-of-thumb, called the SOPAM, offers the best explanation of the data.

An economic approach to consumer product ratings

In three essays we examine user-generated product ratings with aggregation. While recommendation systems have been studied extensively, this simple type of recommendation system has been neglected, despite its prevalence in the field. We develop a novel theoretical model of user-generated ratings. This model improves upon previous work in three ways: it considers rational agents and allows them to abstain from rating when rating is costly; it incorporates rating aggregation (such as averaging ratings); and it considers the effect on rating strategies of multiple simultaneous raters. In the first essay we provide a partial characterization of equilibrium behavior. In the second essay we test this theoretical model in laboratory, and in the third we apply established behavioral models to the data generated in the lab. This study provides clues to the prevalence of extreme-valued ratings in field implementations. We show theoretically that in equilibrium, ratings distributions do not represent the value distributions of sincere ratings. Indeed, we show that if rating strategies follow a set of regularity conditions, then in equilibrium the rate at which players participate is increasing in the extremity of agents' valuations of the product. This theoretical prediction is realized in the lab. We also find that human subjects show a disproportionate predilection for sincere rating, and that when they do send insincere ratings, they are almost always in the direction of exaggeration. Both sincere and exaggerated ratings occur with great frequency despite the fact that such rating strategies are not in subjects' best interest. We therefore apply the behavioral concepts of quantal response equilibrium (QRE) and cursed equilibrium (CE) to the experimental data. Together, these theories explain the data significantly better than does a theory of rational, Bayesian behavior -- accurately predicting key comparative statics. However, the theories fail to predict the high rates of sincerity, and it is clear that a better theory is needed.

影响吗啡动物行为效应的因素及其机制

Credible and stable animal behavioral models are necessary to research the mechanisms of addiction in vivo, especially to study the relationship between memory or stress and drug addiction, which has been one of the focuses in this field. So the object of this study was to observe the influences of several factors on the behavioral effects of morphine shown in the paradigms of conditioned place preference (CPP) and locomotor activity (LA), and to explore the effects of adrenalectomy on LA induced by morphine in rats. In addition, the cortexes of rats were examined, which were exposed to chronic administration of several doses of morphine with or without foot shock. Moreover, a new behavioral model was built to quantify the motivation of drug seeking. The results showed that CPP was more sensitive to low dose of morphine than to high dose. The period of experiment could be shortened by increasing the training times everyday, whereas in this way the dose of morphine should be low enough to avoid the impact between the near two exposures to morphine. Effects of chronic administration of morphine on LA in rats were dose- and time- dependent, which supplied evidence to choose parameters in other behavioral models. The results obtained by the simplified LA paradigm showed that hyperactivity of low dose of morphine following hypoactivity, and naloxone had no effects on LA but blocked the locomotion effects of morphine. Obvious effects of morphine on LA of rats might depend on a reasonable level of plasma corticosterone, which may determine individual vulnerability to drug addiction. Stress may also potentiate the vulnerability by aggravating damage to cortex of rats induced by drug dose-dependently, which is suggested by the results of histological examination. The result that frontal and temporal cortexes and hippocampus were injured suggests that there may be a close relationship between memory and drug addiction. It was showed that the new behavioral model on the basis of Morris water maze might be used to quantify the motivation of drug-craving.

Do Low-Priced Stocks Drive Long-Term Contrarian Performance on the London Stock Exchange?

We investigate whether low-priced stocks drive long-term contrarian performance on the U.K. market. We find that contrarian performance at low, middle, and high price levels is positive. On the Fama-French risk adjusted basis, we find both low-priced and middle-priced losers have significantly positive returns. When we adjust returns by market and liquidity risk, only middle-priced losers maintain their positive returns. Our results reveal that low-priced stocks are not fully responsible for contrarian performance. Our empirical evidence is generally consistent with the overreaction hypothesis and behavioral models of value investing.

Prospective control of manual interceptive actions:comparative simulations of extant and new model constructs

Two prospective controllers of hand movements in catching-both based on required velocity control-were simulated. Under certain conditions, this required velocity control led to overshoots of the future interception point. These overshoots were absent in pertinent experiments. To remedy this shortcoming, the required velocity model was reformulated in terms of a neural network, the Vector Integration To Endpoint model, to create a Required Velocity Integration To Endpoint model. Addition of a parallel relative velocity channel, resulting in the Relative and Required Velocity Integration To Endpoint model, provided a better account for the experimentally observed kinematics than the existing, purely behavioral models. Simulations of reaching to intercept decelerating and accelerating objects in the presence of background motion were performed to make distinct predictions for future experiments.

Passive Intermodulation of Analog and Digital Signals on Transmission Lines with Distributed Nonlinearities: Modelling and Characterization

Passive intermodulation (PIM) often limits the performance of communication systems with analog and digitally-modulated signals and especially of systems supporting multiple carriers. Since the origins of the apparently multiple physical sources of nonlinearity causing PIM are not fully understood, the behavioral models are frequently used to describe the process of PIM generation. In this paper a polynomial model of memoryless nonlinearity is deduced from PIM measurements of a microstrip line with distributed nonlinearity with two-tone CW signals. The analytical model of nonlinearity is incorporated in Keysight Technology’s ADS simulator to evaluate the metrics of signal fidelity in the receive band for analog and digitally-modulated signals. PIM-induced distortion and cross-band interference with modulated signals are compared to those with two-tone CW signals. It is shown that conventional metrics can be applied to quantify the effect of distributed nonlinearities on signal fidelity. It is found that the two-tone CW test provides a worst-case estimate of cross-band interference for two-carrier modulated signals whereas with a three-carrier signal PIM interference in the receive band is noticeably overestimated. The simulated constellation diagrams for QPSK signals demonstrate that PIM interference exhibits the distinctive signatures of correlated distortion and this indicates that there are opportunities for mitigating PIM interference and that PIM interference cannot be treated as noise. One of the interesting results is that PIM distortion on a transmission line results in asymmetrical regrowth of output PIM interference for modulated signals.

Characterization of RSOA modulators in radio over fiber links

In this work physical and behavioral models for a bulk Reflective Semiconductor Optical Amplifier (RSOA) modulator in Radio over Fiber (RoF) links are proposed. The transmission performance of the RSOA modulator is predicted under broadband signal drive. At first, the simplified physical model for the RSOA modulator in RoF links is proposed, which is based on the rate equation and traveling-wave equations with several assumptions. The model is implemented with the Symbolically Defined Devices (SDD) in Advanced Design System (ADS) and validated with experimental results. Detailed analysis regarding optical gain, harmonic and intermodulation distortions, and transmission performance is performed. The distribution of the carrier and Amplified Spontaneous Emission (ASE) is also demonstrated. Behavioral modeling of the RSOA modulator is to enable us to investigate the nonlinear distortion of the RSOA modulator from another perspective in system level. The Amplitude-to-Amplitude Conversion (AM-AM) and Amplitude-to-Phase Conversion (AM-PM) distortions of the RSOA modulator are demonstrated based on an Artificial Neural Network (ANN) and a generalized polynomial model. Another behavioral model based on Xparameters was obtained from the physical model. Compensation of the nonlinearity of the RSOA modulator is carried out based on a memory polynomial model. The nonlinear distortion of the RSOA modulator is reduced successfully. The improvement of the 3rd order intermodulation distortion is up to 17 dB. The Error Vector Magnitude (EVM) is improved from 6.1% to 2.0%. In the last part of this work, the performance of Fibre Optic Networks for Distributed and Extendible Heterogeneous Radio Architectures and Service Provisioning (FUTON) systems, which is the four-channel virtual Multiple Input Multiple Output (MIMO), is predicted by using the developed physical model. Based on Subcarrier Multiplexing (SCM) techniques, four-channel signals with 100 MHz bandwidth per channel are generated and used to drive the RSOA modulator. The transmission performance of the RSOA modulator under the broadband multi channels is depicted with the figure of merit, EVM under di erent adrature Amplitude Modulation (QAM) level of 64 and 254 for various number of Orthogonal Frequency Division Multiplexing (OFDM) subcarriers of 64, 512, 1024 and 2048.