Lithium-ion batteries are complex systems and making a simulation model of them is always challenging. A method for producing an accurate model with high capabilities for predicting the behavior of the battery in a time and cost efficient way is desired in this field of work. The aim of this thesis has been to develop a method to be close to the desired method as much as possible, especially in two important aspects, time and cost. The method which is the goal of this thesis should fulfill the below five requirements: 1. Able to produce a generic battery model for different types of lithium-ion batteries 2. No or low cost for the development of the model 3. A time span around one week for obtaining the model 4. Able to predict the most aspects of the battery’s behavior like the voltage, SOC, temperature and, preferably, simulate the degradation effects, safety and thermal aspects 5. Accuracy with less than 15% error The start point of this thesis was the study of current methods for cell modeling. Based on their approach, they are divided into three categories, abstract, black box and white box methods. Each of these methods has its own advantages and disadvantages, but none of them are able to fulfill the above requirements. This thesis presents a method, called “gray box”, which is, partially, a mix of the black and white boxes’ concepts. The gray box method uses values for model’s parameters from different sources. Firstly, some chemical/physical measurements like in the case of the white box method, secondly, some of the physical tests/experiments used in the case of the black box method and thirdly, information provided by cell datasheets, books, papers, journals and scientific databases. As practical part of this thesis, a prismatic cell, EIG C20 with 20Ah capacity was selected as the sample cell and its electrochemical model was produced with the proposed method. Some of the model’s parameters are measured and some others are estimated. Also, the abilities of AutoLion, a specialized software for lithium-ion battery modeling were used to accelerate the modeling process. Finally, the physical tests were used as part of the references for calculating the accuracy of the produced model. The results show that the gray box method can produce a model with nearly no cost, in less than one week and with error around 30% for the HPPC tests and, less than this, for the OCV and voltage tests. The proposed method could, largely, fulfill the five mentioned requirements. These results were achieved even without using any physical tests/experimental data for tuning the parameters, which is expected to reduce the error considerably. These are promising results for the idea of the gray box which is in its nascent stages and needs time to develop and be useful for commercial purposes.

ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / This paper addresses the research conducted at U.C. Berkeley Space Sciences Laboratory, Center for Extreme Ultra Violet Astrophysics between 1994 and 1995 on the NASA EUVE ion-orbit satellite. It includes the results from conducting a scientific analysis called a prognostic analysis completed on all satellite subsystem equipment. A prognostic analysis uses equipment analog telemetry to measure equipment remaining usable life. The analysis relates equipment transient behavior, often referred to as "cannot duplicates" in a variety of industries caused from accelerated aging to the equipment end-of-life with certainty. The analysis was confirmed by using proprietary, pattern recognition software by Lockheed Martin personnel Lockheed Martin personnel completed an exploration into the application of statistical pattern recognition methods to identify the behavior caused from accelerated aging that experts in probability reliability analysis claims cannot exist. Both visual and statistical methods were successful in detecting suspect accelerated aging and this behavior was related to equipment end of life with certainty. The long-term objective of this research was to confirm that satellite subsystem equipment failures could be predicted so that satellite subsystem and payload engineering personnel could be allocated for only the time that equipment failures were predicted to occur, lowering the cost of mission operations. This research concluded that satellite subsystem equipment remaining usable life could be measured and equipment failures could be predicted with certainty so that engineering support for mission operations could be greatly reduced.

The problem of this study was to determine the value of Scholastic Aptitude Test scores and high school percentile rank for predicting a student's achievement in American history at North Texas State University. The study also sought to determine what, if any, difference existed between male and female students, students of different ethnic backgrounds, and students of different semester classification with respect to learning achievement in American history.

This study explores the relationship between internal-external locus of control and some characteristics of overweight subjects in a weight-control program in the summer and fall of 1973. Only white, female, over-weight, and obese subjects were used. From this study, it appears that Rotter's I-E concept applies to weight loss. This one significant finding lends support to research that internals control their impulses better than externals and that internals seem to learn and retain relevant information better than externals.

The purpose of the study was to investigate how the online, computer-based learner's personal learning profile (Preference), the content delivery method supplemented with visual content based on Neil Fleming's VARK (visual, aural, read/write, kinesthetic) model (Content), and the interaction of Preference and Content, influenced learner performance (Performance) and/or learner self-reported satisfaction (Satisfaction). Participants were drawn from a population of undergraduates enrolled in a large public southwestern research university during the fall 2015 semester. The 165 student participants (13.79% completion rate) were comprised of 52 (31.5%) females and 113 (68.5%) males age 18-58+ years with 126 (76.4%) age 18-24 years. For race/ethnicity, participants self-identified as 1 (0.66%) American Indian/Alaska Native, 21 (12.7%) Asian/Pacific Islander, 27 (16.4%) Black, non-Hispanic, 28 (17%) Hispanic, 78 (47.3%) White, non-Hispanic, 10 (6.1%) other. Reported socioeconomic status was 22 (13.3%) withheld, 53 (32.1%) did not know, 45 (27.3%) low, 13 (7.9%) moderately low, 16 (9.7%) middle, 8 (4.8%) upper middle, and 8 (4.8%) upper. This causal-comparative and quasi-experimental, mixed-method, longitudinal study used researcher-developed web-based modules to measure Performance and Satisfaction, and used the criterion p < .05 for statistical significance. A two-way, 4 x 3 repeated measures (Time) analysis of variance (RM-ANOVA) using Preference and Content was statistically significant on each Performance measure over Time, and at two measures on Satisfaction over Time. The RM-ANOVA was statistically significant on between-subjects main effect Performance for read/write modality Content compared to aural and kinesthetic Content. There were no statistically significant main effects observed for Satisfaction. A Pearson r correlation analysis showed that participants that were older, married, and of higher socioeconomic status performed better. The correlation analysis also showed that participants who performed better reported greater likelihood to take online courses in the future, higher motivation, sufficient time and support for studies, and sufficient funding for and access to the Internet. The study results suggested that regardless of Preference, using read/write modality Content based on the VARK model while maintaining the verbal language can yield better Performance outcomes. The study results also suggested that while maintaining the verbal language, Preference, and Content based on the VARK model do not distinguish learner Satisfaction outcomes. However, because Satisfaction has been shown to impact Performance, efficacy, and retention, it matters to educational institutions. Future research should consider more granular models and factorial research methods, because models that utilize a single representative construct score can mask effects when analyzing Performance and Satisfaction.

[pt] Este trabalho mostra que o VIX e sua versão de mais curto prazo tem poder preditivo sobre a variância realizada do S e P 500 em dias de FOMC (reuniões do Banco Central do Estados Unidos – FED). Apesar disto, o resultado não persiste quando utilizamos o Índice de Volatilidade do S e P 500 de Longo Prazo (3 meses). / [en] This work shows that the VIX and its shorter-term version have predictive power over the variance of the S and P 500 on FOMC days (meetings of the United States Central Bank - FED). Despite this, the result does not persist when we use the Long Term S and P 500 Volatility Index (3 months).

Dispositional optimism, as a stable outcome expectancy, has been shown to predict health outcomes in several contexts. Research has demonstrated that health-impaired subjects with optimistic outlooks fared better than those with a pessimistic outlook. Choice of coping strategies has been theorized as the mediating factor through which optimism operates. However, the construct of dispositional optimism has been challenged as a polar opposite of neuroticism, thus contending that optimism is not an independent notion. The present study was designed to evaluate further the theoretical underpinnings of dispositional optimism theory. Subjects were selected from a population of cardiac patients who received an automatic implantable cardioverter defibrillator (AICD). This device, designed to save the patient from sudden cardiac death, dispenses an electric shock to the heart should it exhibit sustained ventricular tachycardia or fibrillation. This research project examined the relationship of dispositional optimism, coping, and neuroticism to psychological distress, life satisfaction, health perception, and frequency of prior AICD discharges. Intact data from 50 of the 60 participants were examined in multiple regression analyses. The results of the analyses were diverse. Principal findings were (a) general psychological distress was predicted solely by neuroticism but optimism predicted the majority of unique variance in the "style" with which subjects approach the assessment of distress; (b) optimism was subsumed under neuroticism in predicting health perception; (c) avoidance coping interacted with optimism in predicting a significant amount of unique variance over and above neuroticism in the number of AICD discharges experienced by the patients. In this latter finding, pessimistic patients who did not use avoidance coping received a greater number of discharges. Thus, optimism and neuroticism were not parallel constructs in all dependent variables. Also, the optimism/avoidance coping interaction in predicting an actual medical outcome was unprecedented. Limitations and directions for future research were discussed.

<p>The overall aim was to study factors that affect behaviour related to CVD (cardiovascular diseases). Study I tested whether gender, education and so-cioeconomic status correlated to knowledge about risk factors, and Study II studied knowledge and risk behaviour from a national perspective (Sweden versus Poland). Furthermore, Study III examined whether obese people dif-fered from people of normal weight regarding knowledge about risk factors, and Study IV examined whether risk behaviour is affected by personal ex-perience of illness and family history of CVD. </p><p>The studies are population-based with cross-sectional design. Data were obtained by questionnaires and by screening results of risk factors related to CVD. The studies were carried out among 50-year old men and women in Västmanland, Sweden (n=1011) and in Wroclaw, Poland (n=1043).</p><p>The results show that women are more knowledgeable than men about the risk factors for CVD, and that low education is associated with insufficient knowledge about CVD (Study I). The discrepancy between knowledge and behaviour was greater among the Poles than it was among the Swedes (Study II). Obese individuals did not differ significantly from individuals with a normal weight regarding knowledge of cardiovascular risk factors when education was controlled for (Study III). Individuals with a personal experience of illness may be more inclined to change smoking behaviour than the average person (Study IV).</p><p>In conclusion, knowledge about risk factors for CVD varies with education, gender and, to a certain degree, nationality. However, knowledge does not only consist of the conditions of behaviour change. The results in the thesis substantiate theories suggesting that change in risk behaviour is a process over time. Predictors of risk behaviours on the individual level as well as national level are of importance, and needs to be considered in the every day practice of health care professionals.</p>

The overall aim was to study factors that affect behaviour related to CVD (cardiovascular diseases). Study I tested whether gender, education and so-cioeconomic status correlated to knowledge about risk factors, and Study II studied knowledge and risk behaviour from a national perspective (Sweden versus Poland). Furthermore, Study III examined whether obese people dif-fered from people of normal weight regarding knowledge about risk factors, and Study IV examined whether risk behaviour is affected by personal ex-perience of illness and family history of CVD. The studies are population-based with cross-sectional design. Data were obtained by questionnaires and by screening results of risk factors related to CVD. The studies were carried out among 50-year old men and women in Västmanland, Sweden (n=1011) and in Wroclaw, Poland (n=1043). The results show that women are more knowledgeable than men about the risk factors for CVD, and that low education is associated with insufficient knowledge about CVD (Study I). The discrepancy between knowledge and behaviour was greater among the Poles than it was among the Swedes (Study II). Obese individuals did not differ significantly from individuals with a normal weight regarding knowledge of cardiovascular risk factors when education was controlled for (Study III). Individuals with a personal experience of illness may be more inclined to change smoking behaviour than the average person (Study IV). In conclusion, knowledge about risk factors for CVD varies with education, gender and, to a certain degree, nationality. However, knowledge does not only consist of the conditions of behaviour change. The results in the thesis substantiate theories suggesting that change in risk behaviour is a process over time. Predictors of risk behaviours on the individual level as well as national level are of importance, and needs to be considered in the every day practice of health care professionals.

The availability of new technologies supplied life scientists with large amounts of experimental data. The data sets are large not only in terms of the number of observations, but also in terms of the number of recorded features. One of the aims of modeling is to explain a given phenomenon in possibly the simplest way, hence the need for selection of suitable features. We extended a Monte Carlo-based approach to selecting statistically significant features with discovery of feature interdependencies and used it in modeling sequence-function relationships in proteins. Our approach led to compact and easy-to-interpret predictive models. First, we represented protein sequences in terms of their physicochemical properties. This was followed by our feature selection and discovery of feature interdependencies. Finally, predictive models based on e.g., decision trees or rough sets were constructed. We applied the method to model two important biological problems: 1) HIV-1 resistance to reverse transcriptase-targeted drugs and 2) post-translational modifications of proteins. In the case of HIV resistance, we were not only able to predict whether the mutated protein is resistant to a drug or not, but we also suggested some new, previously neglected, mutations that possibly contribute to drug resistance. For all these mutations we proposed probable molecular mechanisms of action using literature and 3D structure studies. In the case of predicting PTMs, we built high accuracy models of modifications. In comparison to other methods, we were able to resolve whether the closest neighborhood of a residue (the nanomer) is sufficient to determine its modification status. Importantly, the application of our method yields networks of interdependent physicochemical properties of amino acids that show how these properties collaborate in establishing a given modification. We believe that the presented methods will help researchers to analyze a large class of important biological problems and will guide them in their research.