2 resultados para Excited electronic state

em Coffee Science - Universidade Federal de Lavras


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There has been very little research that has studied the capacities that can be fostered to mitigate the risk for involvement in electronic bullying or victimization and almost no research examining positive electronic behavior. The primary goal of this dissertation was to use the General Aggression Model and Anxious Apprehension Model of Trauma to explore the underlying cognitive, emotional, and self-regulation processes that are related to electronic bullying, victimization, and prosocial behavior. In Study 1, we explored several potential interpretations of the General Aggression Model that would accurately describe the relationship that electronic self-conscious appraisal, cognitive reappraisal, and activational control may have with electronic bullying and victimization. In Study 2, we used the Anxious Apprehension Model of Trauma to explore rejection cognitions as the mediator of the relationships among emotionality (emotionality, shame, state emotion responses, and physiological arousal) and electronic bullying and victimization using structural equation modelling. In addition, we explored the role of rejection cognitions in mediating the relationship of moral disengagement with electronic bullying. In Study 3, we examined predictors of electronic prosocial behavior, such as bullying, victimization, time online, electronic proficiency, electronic self-conscious appraisals, emotionality, and self-regulation. All three studies supported the General Aggression Model as a framework to guide the study of electronic behavior, and suggest the importance of cognitive, emotional, and behavioral means of regulation in shaping electronic behavior. In addition, each study has implications for the development of high quality electronic bullying prevention and intervention research.

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Lithium Ion (Li-Ion) batteries have got attention in recent decades because of their undisputable advantages over other types of batteries. They are used in so many our devices which we need in our daily life such as cell phones, lap top computers, cameras, and so many electronic devices. They also are being used in smart grids technology, stand-alone wind and solar systems, Hybrid Electric Vehicles (HEV), and Plug in Hybrid Electric Vehicles (PHEV). Despite the rapid increase in the use of Lit-ion batteries, the existence of limited battery models also inadequate and very complex models developed by chemists is the lack of useful models a significant matter. A battery management system (BMS) aims to optimize the use of the battery, making the whole system more reliable, durable and cost effective. Perhaps the most important function of the BMS is to provide an estimate of the State of Charge (SOC). SOC is the ratio of available ampere-hour (Ah) in the battery to the total Ah of a fully charged battery. The Open Circuit Voltage (OCV) of a fully relaxed battery has an approximate one-to-one relationship with the SOC. Therefore, if this voltage is known, the SOC can be found. However, the relaxed OCV can only be measured when the battery is relaxed and the internal battery chemistry has reached equilibrium. This thesis focuses on Li-ion battery cell modelling and SOC estimation. In particular, the thesis, introduces a simple but comprehensive model for the battery and a novel on-line, accurate and fast SOC estimation algorithm for the primary purpose of use in electric and hybrid-electric vehicles, and microgrid systems. The thesis aims to (i) form a baseline characterization for dynamic modeling; (ii) provide a tool for use in state-of-charge estimation. The proposed modelling and SOC estimation schemes are validated through comprehensive simulation and experimental results.