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[pt] O presente relatório objetiva apresentar o quanto as técnicas de negociações de conflitos e tomadas de decisões racionais estão ausentes na crise Venezuela Brasil. A não adoção de boas práticas negociais pelos agentes políticos e diplomáticos agrava o dia a dia dos povos envolvidos no litígio. A opção por modernos instrumentos negociais e a presença de um mediador endógeno é a proposta, pois facilitaria enormemente o desenvolvimento de uma governança regional. Para embasar a pesquisa debruça o relatório na literatura clássica e contemporânea, o que abrange temas como: conflict transformation, black negotiation, newgotiation, process alternative, Theory Problem Solving, o Nobel de economia de 2017 entre outras reflexões marcantes. / [en] This report aims to present how the techniques of conflict negotiation and rational decision making are absent in the Venezuela Brazil crisis. The nonadoption of good business practices by political and diplomatic agents aggravates the day-to-day of the peoples involved in the litigation. The option for modern negotiating instruments and the presence of an endogenous mediator is the proposal, as it would greatly facilitate the development of regional governance. To support the research, the report focuses on classical and contemporary literature, which covers topics such as: conflict transformation, black negotiation, newgotiation, process alternative, Theory Problem Solving, the Nobel economics of 2017 among other striking reflections.

Molecular nonlinear optical (NLO) properties are extensively studied using both theory and experiment because of their use in myriad applications. Experimental measurements of the most interesting molecules’ NLO properties are difficult, so experimental data for molecules with desirable NLO properties is scarce. Theoretical tools don’t suffer from the same limitations and can provide significant insights into the physico-chemical phenomena underlying the nonlinear responses, can help in interpreting response behaviour of molecules, and can guide design the materials with desirable response properties. Here, I present my work on developing methods for accurately calculating the NLO properties of molecules using the finite field (FF) approach. The first chapter provides a background for the finite field and electronic structure methods used in this dissertation. Chapter two is a thorough investigation of the finite field method. The limitations of the method are highlighted and the optimal conditions for overcoming its drawbacks and obtaining meaningful and accurate results are described. Chapter three presents the first systematic study of the dependence of optimal field strengths on molecular descriptors. The first protocol for predicting the optimal field for the second hyperpolarizability is presented and successfully tested, and the dependence of the optimal field strength for the first hyperpolarizability on the molecular structure is investigated. Chapter four is an assessment of various DFT functionals in calculating the second hyperpolarizabilities of organic molecules and oligomers. This study shows the limitations of conventional DFT methods and the importance of electron correlation to response properties. In chapter five we present a new method of calculating NLO properties using a rational function model that is shown to be more robust and have lower computational cost than the traditional Taylor expansion. Finally, chapter six includes a summary of the thesis and an overview of future work. / Thesis / Doctor of Philosophy (PhD)

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An experimental, randomized, control-group, pretest-postest design was employed in this study to examine the efficacy of the use of two short-term group counseling interventions employing Rational Emotive Behavior Therapy with at-risk adolescents in changing their beliefs, altering their attitude toward school, and moderating behaviors that are problematic in an educational setting. Forty-eight subjects were included in this study from an alternative evening high school setting and were assessed in the initial stage of treatment using The Idea Inventory and The Majoribanks Attitude-To-School Inventory. The School Social Behavior Scale was employed at this beginning point to observe these students by teachers and administrators with regard to social competence and anti-social behaviors. Subjects were selected from a pool of regularly attending students in an alternative high school program and randomly assigned to three groups, one employing REBT concepts and techniques alone, one using REBT concepts and techniques in conjunction with the therapeutic board game, Let's Get Rational, and a control group. The treatment and control group designations were also randomly assigned to the counseling groups. Ten weekly 50 minute group counseling sessions were conducted by two master's level counselors employing the tenets of REBT with adolescents. Group participants had the opportunity to learn new interpersonal skills and behaviors that may be helpful to them in staying in school. At the conclusion of the 10 week treatment group sessions, the subjects in the three groups were re-assessed employing the same instruments mentioned before to determine if the activities in the group sessions made significant differences in the rational thinking, attitude to school, and school social behaviors of these at-risk students in an alternative setting. Data were analyzed using descritpive statistics in addition to a factorial analysis of variance (ANOVA) to measure the pretest and posttest performance and understanding of the subjects. Results revealed that the differences in the scores of the treatment groups were significant the REBT group employing the game, Let's Get Rational, contributing to students learning and understanding of the tenets of REBT at the .05 alpha level on the four dependent variables. There were no significant differences between genders regarding the four dependent variables, and there was a lack of a significant interaction between the intervention approach taken and the gender of the group member. There was no significant interaction between the gender of the subject and the treatment group placement. The results from both REBT groups support the efficacy of using the tenets of REBT with school aged populations who are at risk for failure. Appropriate conclusions and recommendations based upon the study findings were made. Implications for secondary school counselors and those counselors working with at-risk students were delineated. / Ed. D.

Bilinear systems are a class of nonlinear dynamical systems that arise in a variety of applications. In order to obtain a sufficiently accurate representation of the underlying physical phenomenon, these models frequently have state-spaces of very large dimension, resulting in the need for model reduction. In this work, we introduce two new methods for the model reduction of bilinear systems in an interpolation framework. Our first approach is to construct reduced models that satisfy multipoint interpolation constraints defined on the Volterra kernels of the full model. We show that this approach can be used to develop an asymptotically optimal solution to the H_2 model reduction problem for bilinear systems. In our second approach, we construct a solution to a bilinear system realization problem posed in terms of constructing a bilinear realization whose kth-order transfer functions satisfy interpolation conditions in k complex variables. The solution to this realization problem can be used to construct a bilinear system realization directly from sampling data on the kth-order transfer functions, without requiring the formation of the realization matrices for the full bilinear system. / Ph. D.

The dependence on Natural Language Processing (NLP) systems has grown significantly in the last decade. Recent advances in deep learning have enabled language models to generate high-quality text at the same level as human-written text. If this growth continues, it can potentially lead to increased misinformation, which is a significant challenge. Although claim verification techniques exist, they lack proper explainability. Numerical scores such as Attention and Lime and visualization techniques such as saliency heat maps are insufficient because they require specialized knowledge. It is inaccessible and challenging for the nonexpert to understand black-box NLP systems. We propose a novel approach called, ExClaim for explainable claim verification using NLP rationalization. We demonstrate that our approach can predict a verdict for the claim but also justify and rationalize its output as a natural language explanation (NLE). We extensively evaluate the system using statistical and Explainable AI (XAI) metrics to ensure the outcomes are valid, verified, and trustworthy to help reinforce the human-AI trust. We propose a new subfield in XAI called Rational AI (RAI) to improve research progress on rationalization and NLE-based explainability techniques. Ensuring that claim verification systems are assured and explainable is a step towards trustworthy AI systems and ultimately helps mitigate misinformation. / Master of Science / The dependence on Natural Language Processing (NLP) systems has grown significantly in the last decade. Recent advances in deep learning have enabled text generation models to generate high-quality text that is at the same level as human-written text. If this growth continues, it can potentially lead to increased misinformation, which is a major societal challenge. Although claim verification techniques exist, they lack proper explainability. It is difficult for the average user to understand the model's decision-making process. Numerical scores and visualization techniques exist to provide explainability, but they are insufficient because they require specialized domain knowledge. This makes it inaccessible and challenging for the nonexpert to understand black-box NLP systems. We propose a novel approach called, ExClaim for explainable claim verification using NLP rationalization. We demonstrate that our approach can predict a verdict for the claim but also justify and rationalize its output as a natural language explanation (NLE). We extensively evaluate the system using statistical and Explainable AI (XAI) metrics to ensure the outcomes are valid, verified, and trustworthy to help reinforce the human-AI trust. We propose a new subfield in XAI called Rational AI (RAI) to improve research progress on rationalization and NLE-based explainability techniques. Ensuring that claim verification systems are assured and explainable is a step towards trustworthy AI systems and ultimately helps mitigate misinformation.