We perform micromagnetic simulations in MuMax3 on various magneticnanostructures to study their magnetic state and response to external fields. Theinteraction and ordering of nanomagnetic arrays is investigated by calculating themagnetostatic energies for various configurations. These energies are then used inMonte Carlo simulation to study the thermal behaviour of systems of nanomagneticarrays. We find that the magnetic state of the nanostructures are related to theirshape and size and furthermore affect the emergent properties of the system, givingrise to temperature dependent ordering among the individual structures. Results fromboth micromagnetic and statistical mechanic simulations agree well with availableexperimental data, although the Monte Carlo algorithm encounter problems at lowsimulation temperatures.

The purpose of this study is to reveal the matter of legal practice of institutes of transactions accomplished under influence of error and performance of contractual obligations in a case of change of circumstances. In the first chapter author provides the conception of contracts accomplished under influence of error, classification into mutual and unilateral mistakes, separate bases that misleads a person, also legal consequences of anullement of such a transactions. In the second chapter author provides the conception of performance of contractual obligations in a case of change of circumstances, analyses connection between aforementioned institute and frustration and legal consequences of anullement or modifying of contract in a case of change of circumstances. The last chapter compares institutes of anullement of transactions accomplished under influence of error and performance of contractual obligations in a case of change of circumstances.

The diploma thesis is focused on the motivation of students to study at the Hussite theological faculty of Charles University. The diploma thesis is divided into two main parts. The aim of the theoretical part of the thesis is to provide summary information on the given topic. The aim of the practical part is to find out and analyze the motivation of the students of social and charity work. Part of the practical part is a questionnaire, finding the motives of students to study this field and their needs to continue studying and learning. The questionnaire survey showed that students are most often attracted by the inadequacy of the admission procedure together with the personal interest in studying this faculty. For the field itself, they decided in the first place mainly because of the desire to help people and to be beneficial. Since graduating from the field, they have been promising to increase their professional qualifications, a better chance of good job and getting a degree. Students at the Hussite Theological Faculty appreciate mainly the ambience of a smaller faculty with family atmosphere, tolerance and openness prevail.

Esta tese apresenta uma pesquisa para detectar os alunos que evidenciam sinais de frustração em atividades de ensino e de aprendizagem na área de Algoritmos, para então, auxiliá-los com ações proativas de apoio. A motivação para o desenvolvimento deste trabalho advém da dificuldade dos alunos na aprendizagem dos conceitos e técnicas de construção de Algoritmos, que se constitui num dos principais fatores que levam os cursos de formação em Computação a atingir altas taxas de evasão. Na busca por diminuir tal evasão, esta pesquisa destaca a importância de considerar os estados afetivos dos alunos, procurando motivá-los a estudar e resolver suas dificuldades de entendimento da resolução de problemas usando como suporte os sistemas computacionais. Para fins de validação da pesquisa foi construída uma ferramenta para: a) inferir o estado afetivo de frustração do aluno durante a resolução dos exercícios de Algoritmos, b) ao detectar sinais associados à frustração, apresentar recursos de apoio ao aprendizado do aluno. A inferência da frustração ocorre a partir da análise das variáveis comportamentais produzidas pelas interações dos alunos com a ferramenta. O apoio consiste na exibição de um tutorial com a resolução passo a passo do exercício no qual o aluno apresenta dificuldades e na recomendação de um novo exercício com níveis de complexidade mais lineares aos conceitos trabalhados até aquele ponto da disciplina. A partir destas ações, pretende-se auxiliar a fazer com que a frustração do aluno possa ser transformada em uma oportunidade de aprendizado. Estudos de Caso foram realizados com alunos de Algoritmos do curso de Tecnologia em Análise e Desenvolvimento de Sistemas da Faculdade de Tecnologia Senac Pelotas durante os anos de 2011 e 2012. Para identificar os padrões de comportamento dos alunos foram utilizadas técnicas de Mineração de Dados. Os resultados dos experimentos demonstraram que evidências como, o alto número de tentativas de compilação de um programa sem sucesso, o grande número de erros em um mesmo programa ou a quantidade de tempo gasto na tentativa de resolver um algoritmo, podem estar relacionadas ao estado de frustração do aluno. Além disso, em um dos experimentos foi realizado um comparativo de pré e pós-teste que demonstrou importantes avanços no aprendizado dos alunos participantes da pesquisa. / This thesis presents a research work on the detection of students who show signs of frustration in learning activities in the area of algorithms, to then assist them with proactive support actions. Our motivation for the development of this work comes from students' difficulty in learning the concepts and techniques for building algorithms, which constitutes one of the main factors for the high dropout rates of computing courses. With the intent of giving a contribution to the reduction of such evasion, this research highlights the importance of considering students' affective states, trying to motivate them to study and work out their difficulties, with the assistance of computer systems. For research validation purposes, a tool was built to: a) infer the student’s affective state of frustration while solving exercises of algorithms; b) detect signs associated with frustration, to provide resources to support student learning. The inference of frustration comes from the analysis of behavioral variables produced by the interactions of students with the tool. The support consists in displaying a tutorial with a step by step solution for the exercise in which the student shows difficulties, and the recommendation of a new exercise with more linear levels of complexity than the concepts worked until that point in the course. With these actions, our intention is to turn student's frustration into a learning opportunity. Case studies were conducted with students of Algorithms at the Faculty of Technology Senac Pelotas, in 2011 and 2012. Data mining techniques were used to identify patterns of student behavior. The experiment results showed that evidence such as the high number of attempts to compile a program without success, the large number of errors in a program or even the amount of time spent trying to solve an algorithm, might be related to the student’s frustration state. Additionally, a pre and post-test comparison showed significant progress in students' learning.

The objective of this diploma thesis is to provide basic orientation in the topic of the adolescents stress and key concepts of this topic. The next objektive of the thesis is to compare the individual effects of Adolescents stress at grammar schools. Theoretical part of the thesis defins the basic terms - difficult life situation, stress, frustration, conflicts, escape, aggression, coping strategies, stress management programs and concepts related to adolescence - age groups, pubescence, adolescence, results of adolescents stress. Practical part of thesis defines the objectives and assumtions for evaluation, describes used method of evaluation, approximate research course and in the end verifies the assumptions.

Esta tese apresenta uma pesquisa para detectar os alunos que evidenciam sinais de frustração em atividades de ensino e de aprendizagem na área de Algoritmos, para então, auxiliá-los com ações proativas de apoio. A motivação para o desenvolvimento deste trabalho advém da dificuldade dos alunos na aprendizagem dos conceitos e técnicas de construção de Algoritmos, que se constitui num dos principais fatores que levam os cursos de formação em Computação a atingir altas taxas de evasão. Na busca por diminuir tal evasão, esta pesquisa destaca a importância de considerar os estados afetivos dos alunos, procurando motivá-los a estudar e resolver suas dificuldades de entendimento da resolução de problemas usando como suporte os sistemas computacionais. Para fins de validação da pesquisa foi construída uma ferramenta para: a) inferir o estado afetivo de frustração do aluno durante a resolução dos exercícios de Algoritmos, b) ao detectar sinais associados à frustração, apresentar recursos de apoio ao aprendizado do aluno. A inferência da frustração ocorre a partir da análise das variáveis comportamentais produzidas pelas interações dos alunos com a ferramenta. O apoio consiste na exibição de um tutorial com a resolução passo a passo do exercício no qual o aluno apresenta dificuldades e na recomendação de um novo exercício com níveis de complexidade mais lineares aos conceitos trabalhados até aquele ponto da disciplina. A partir destas ações, pretende-se auxiliar a fazer com que a frustração do aluno possa ser transformada em uma oportunidade de aprendizado. Estudos de Caso foram realizados com alunos de Algoritmos do curso de Tecnologia em Análise e Desenvolvimento de Sistemas da Faculdade de Tecnologia Senac Pelotas durante os anos de 2011 e 2012. Para identificar os padrões de comportamento dos alunos foram utilizadas técnicas de Mineração de Dados. Os resultados dos experimentos demonstraram que evidências como, o alto número de tentativas de compilação de um programa sem sucesso, o grande número de erros em um mesmo programa ou a quantidade de tempo gasto na tentativa de resolver um algoritmo, podem estar relacionadas ao estado de frustração do aluno. Além disso, em um dos experimentos foi realizado um comparativo de pré e pós-teste que demonstrou importantes avanços no aprendizado dos alunos participantes da pesquisa. / This thesis presents a research work on the detection of students who show signs of frustration in learning activities in the area of algorithms, to then assist them with proactive support actions. Our motivation for the development of this work comes from students' difficulty in learning the concepts and techniques for building algorithms, which constitutes one of the main factors for the high dropout rates of computing courses. With the intent of giving a contribution to the reduction of such evasion, this research highlights the importance of considering students' affective states, trying to motivate them to study and work out their difficulties, with the assistance of computer systems. For research validation purposes, a tool was built to: a) infer the student’s affective state of frustration while solving exercises of algorithms; b) detect signs associated with frustration, to provide resources to support student learning. The inference of frustration comes from the analysis of behavioral variables produced by the interactions of students with the tool. The support consists in displaying a tutorial with a step by step solution for the exercise in which the student shows difficulties, and the recommendation of a new exercise with more linear levels of complexity than the concepts worked until that point in the course. With these actions, our intention is to turn student's frustration into a learning opportunity. Case studies were conducted with students of Algorithms at the Faculty of Technology Senac Pelotas, in 2011 and 2012. Data mining techniques were used to identify patterns of student behavior. The experiment results showed that evidence such as the high number of attempts to compile a program without success, the large number of errors in a program or even the amount of time spent trying to solve an algorithm, might be related to the student’s frustration state. Additionally, a pre and post-test comparison showed significant progress in students' learning.

Esta tese apresenta uma pesquisa para detectar os alunos que evidenciam sinais de frustração em atividades de ensino e de aprendizagem na área de Algoritmos, para então, auxiliá-los com ações proativas de apoio. A motivação para o desenvolvimento deste trabalho advém da dificuldade dos alunos na aprendizagem dos conceitos e técnicas de construção de Algoritmos, que se constitui num dos principais fatores que levam os cursos de formação em Computação a atingir altas taxas de evasão. Na busca por diminuir tal evasão, esta pesquisa destaca a importância de considerar os estados afetivos dos alunos, procurando motivá-los a estudar e resolver suas dificuldades de entendimento da resolução de problemas usando como suporte os sistemas computacionais. Para fins de validação da pesquisa foi construída uma ferramenta para: a) inferir o estado afetivo de frustração do aluno durante a resolução dos exercícios de Algoritmos, b) ao detectar sinais associados à frustração, apresentar recursos de apoio ao aprendizado do aluno. A inferência da frustração ocorre a partir da análise das variáveis comportamentais produzidas pelas interações dos alunos com a ferramenta. O apoio consiste na exibição de um tutorial com a resolução passo a passo do exercício no qual o aluno apresenta dificuldades e na recomendação de um novo exercício com níveis de complexidade mais lineares aos conceitos trabalhados até aquele ponto da disciplina. A partir destas ações, pretende-se auxiliar a fazer com que a frustração do aluno possa ser transformada em uma oportunidade de aprendizado. Estudos de Caso foram realizados com alunos de Algoritmos do curso de Tecnologia em Análise e Desenvolvimento de Sistemas da Faculdade de Tecnologia Senac Pelotas durante os anos de 2011 e 2012. Para identificar os padrões de comportamento dos alunos foram utilizadas técnicas de Mineração de Dados. Os resultados dos experimentos demonstraram que evidências como, o alto número de tentativas de compilação de um programa sem sucesso, o grande número de erros em um mesmo programa ou a quantidade de tempo gasto na tentativa de resolver um algoritmo, podem estar relacionadas ao estado de frustração do aluno. Além disso, em um dos experimentos foi realizado um comparativo de pré e pós-teste que demonstrou importantes avanços no aprendizado dos alunos participantes da pesquisa. / This thesis presents a research work on the detection of students who show signs of frustration in learning activities in the area of algorithms, to then assist them with proactive support actions. Our motivation for the development of this work comes from students' difficulty in learning the concepts and techniques for building algorithms, which constitutes one of the main factors for the high dropout rates of computing courses. With the intent of giving a contribution to the reduction of such evasion, this research highlights the importance of considering students' affective states, trying to motivate them to study and work out their difficulties, with the assistance of computer systems. For research validation purposes, a tool was built to: a) infer the student’s affective state of frustration while solving exercises of algorithms; b) detect signs associated with frustration, to provide resources to support student learning. The inference of frustration comes from the analysis of behavioral variables produced by the interactions of students with the tool. The support consists in displaying a tutorial with a step by step solution for the exercise in which the student shows difficulties, and the recommendation of a new exercise with more linear levels of complexity than the concepts worked until that point in the course. With these actions, our intention is to turn student's frustration into a learning opportunity. Case studies were conducted with students of Algorithms at the Faculty of Technology Senac Pelotas, in 2011 and 2012. Data mining techniques were used to identify patterns of student behavior. The experiment results showed that evidence such as the high number of attempts to compile a program without success, the large number of errors in a program or even the amount of time spent trying to solve an algorithm, might be related to the student’s frustration state. Additionally, a pre and post-test comparison showed significant progress in students' learning.

The aim of this diploma thesis is to find out how do adolescents using addictive substances cope with everyday stress and whether their answers differ from the ordinary population of their peers. For this purpose, the Czech version of Rosenzweig's picture frustration test (C-W) was used. The theoretical part summarizes our knowledge about frustration and possible manifestations of reactions to frustrationand it places this phenomenon into a terminological and theoretical framework. It also deals with adolescence from the point of view of potential stress situations and presents possible adolescents' responses to these circumstances. Finally, this part describes possible causes and manifestations of addiction in adolescents. The aim of the practical part is to present how the responses of 40 adolescent users of psychoactive substances to common frustrating situations compare with ones of the normal peer population. The results of the survey from the point of view of the direction of aggression show that drug-using adolescents most often blame their social surrounding for the frustrating situation or expect a solution to come from their surrounding. More often they choose a self-accusatory reaction rather than trying to get over the frustration or to avoid aggression. From the point of view of the...

The thesis deals with reactivity in response to a frustrating situation for convicted offenders. The main issue in the theoretical element is reactivity; or rather the behaviour and manifestation of reactions in the moment when an individual gets into stressful situations, is impeded or blocked in achieving their target. The definition of frustration is an equally important area, which, in the thesis is initially described from the perspective of classic theorists, and then the various ways how we examine and diagnose frustration. The last and equally important chapter consists of the offender's personality, which is defined in the context of the aforementioned frustration and reactivity. The aim of the empirical component is to obtain quantitative data on the most frequent reactions among criminal offenders in the moment before they face the obstacle that is blocking their achievement of goals or satisfaction. The research sample was composed of 69 convicted criminal offenders from remand prisons Pankrác, Hradec Kralové and prison Plzeň. The Picture Rosenzweig frustration method was used to examine the reactivity as a result of frustration. Four hypothesis was determined and only one hypothesis was confirmed. Extragression, outside oriented response, is the most frequently response in comparison...

LnBaCo2O5+δ (Ln-112) where Ln = lanthanide element; 0 ≤ δ ≤1 and LnBaCo4O7+δ (Ln-114) are highly correlated cobalt oxides. Synchrotron photoemission spectroscopy of LnBaCo2O5+δ (Ln = Gd, Dy, Dy1-xTbx) and LnBaCo4O7 (Ln = Yb) has been undertaken at the UK Synchrotron Radiation Source (Daresbury Laboratory).During the photoemission experiments, the samples were observed to be contaminated due to residual gases inside the main vacuum chamber. The surface degradation of the samples is studied using the difference spectra generated from the valence band spectra of freshly scraped and contaminated samples and the nature of contaminated species on these samples is identified in the light of the reviewed literature. High-resolution photoemission is carried out to study the metal-insulator (MI) transition in double perovskites LnBaCo2O5+δ (Ln = Gd, Dy, Dy1-xTbx - Ln-112; 0 ≤ δ ≤ 1) as a function of temperature. The high-resolution photoemission results of single crystal samples of GdBaCo2O5.5, DyBaCo2O5.5 and Dy1-xTbxBaCo2O5+δ show that the temperature-based MI transitions in these compounds occur in the 300-400 K temperature range. A post-growth oxygen annealing treatment for as-grown single crystals of Ln-112 is necessary, achieving oxygen contents close to 5.50, to observe a marked nonmetal-to-metal transition. Resonant photoemission is used to identify the atomic parentage of the valence band states. A comparison of the electronic structure of LnBaCo2O5+δ (Ln = Gd, Dy, Dy1-xTbx - Ln-112; 0 ≤ δ ≤ 1) and LnBaCo4O7 (Ln = Yb - Ln-114) single-crystal surfaces is made using synchrotron photoemission spectroscopy. In both cases, the states close to the Fermi energy are found to be of mixed Co 3d/O 2p character, and the comparison allows identification of states due to low spin Co³⁺ in octahedral environments. The contributions from Ln elements to the valence band are found at higher binding energies.