889 resultados para anion gap


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Swelling properties of four commercial anion-exchange membranes with different structure have been analyzed in several hydro-organic media. With this target, the liquid uptake and the surface expansion of the membranes in contact with different pure liquids, water and alcohols (methanol, ethanol and 1-propanol), and with water alcohol mixtures with different concentrations have been experimentally determined in presence and in absence of an alkaline medium (LiOH, NaOH and KOH of different concentrations). The alkali-metal doping effect on the membrane water uptake has also been investigated, analyzing the influence of the hydroxide concentration and the presence of an alcohol in the doping solution. The results show that the membrane structure plays an essential role in the influence that alcohol nature and alkaline media has on the selective properties of the membrane. The heterogeneous membranes, with lower density, show higher liquid uptakes and dimensional changes than the homogeneous membranes, regardless of the doping conditions. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

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New materials for OLED applications with low singlet–triplet energy splitting have been recently synthesized in order to allow for the conversion of triplet into singlet excitons (emitting light) via a Thermally Activated Delayed Fluorescence (TADF) process, which involves excited-states with a non-negligible amount of Charge-Transfer (CT). The accurate modeling of these states with Time-Dependent Density Functional Theory (TD-DFT), the most used method so far because of the favorable trade-off between accuracy and computational cost, is however particularly challenging. We carefully address this issue here by considering materials with small (high) singlet–triplet gap acting as emitter (host) in OLEDs and by comparing the accuracy of TD-DFT and the corresponding Tamm-Dancoff Approximation (TDA), which is found to greatly reduce error bars with respect to experiments thanks to better estimates for the lowest singlet–triplet transition. Finally, we quantitatively correlate the singlet–triplet splitting values with the extent of CT, using for it a simple metric extracted from calculations with double-hybrid functionals, that might be applied in further molecular engineering studies.

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My dissertation emphasizes the use of narrative structuralism and narrative theories about storytelling in order to build a discourse between the fields of New Media and Rhetoric and Composition. Propp's morphological analysis and the breaking down of stories into component pieces aides in the discussion of storytelling as it appears in and is mediated by digital and computer technologies. New Media and Rhetoric and Composition are aided by shared concerns for textual production and consumption. In using the notion of "kairotic reading" (KR), I show the interconnectedness and interdisciplinarity required in the development of pedagogy utilized to teach students to develop into reflective practitioners that are aware of their rhetorical surroundings and can made sound judgments concerning their own message generation and consumption in the workplace. KR is a transferable skill that is beneficial to students and teachers alike. The dissertation research utilizes theories of New Media and New Media-influenced practitioners, including Jenkins' theory of convergence, Bourdieu's notion of taste, Gee's term "semiotic domains," and Manovich's "modification." These theoretical pieces are combined in order to show how KR can be extended by convergent narrative practices. In order to build connections with New Media, the consideration and inclusion of Kress and van Leeuwen's multimodality, Selber's "reflective practitioners," and Selfe's definition of multimodal composing allow for a greater establishment of conversation order to create a richer conversation around the implications of metacognitive development and practitioner reflexivity with scholars in New Media. My research also includes analysis of two popular media franchises Deborah Harkness' A Discovery of Witches and Fox's Bones television series to show similarities and differences among convergence-linked and multimodal narratives. Lastly, I also provide example assignments that can be taken, further developed, and utilized in classrooms engaging in multimodal composing practices. This dissertation pushes consideration of New Media into the work already being performed by those in Rhetoric and Composition.

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A rapid and efficient method to identify the weak points of the complex chemical structure of low band gap (LBG) polymers, designed for efficient solar cells, when submitted to light exposure is reported. This tool combines Electron Paramagnetic Resonance (EPR) using the 'spin trapping method' coupled with density functional theory modelling (DFT). First, the nature of the short life-time radicals formed during the early-stages of photo-degradation processes are determined by a spin-trapping technique. Two kinds of short life-time radical (R and R′O) are formed after 'short-duration' illumination in an inert atmosphere and in ambient air, respectively. Second, simulation allows the identification of the chemical structures of these radicals revealing the most probable photochemical process, namely homolytical scission between the Si atom of the conjugated skeleton and its pendent side-chains. Finally, DFT calculations confirm the homolytical cleavage observed by EPR, as well as the presence of a group that is highly susceptible to photooxidative attack. Therefore, the synergetic coupling of a spin trapping method with DFT calculations is shown to be a rapid and efficient method for providing unprecedented information on photochemical mechanisms. This approach will allow the design of LBG polymers without the need to trial the material within actual solar cell devices, an often long and costly screening procedure.

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Cytokinesis in animal cells requires the constriction of an actomyosin contractile ring, whose architecture and mechanism remain poorly understood. We use laser microsurgery to explore the biophysical properties of constricting rings in Caenorhabditis elegans embryos. Laser cutting causes rings to snap open. However, instead of disintegrating, ring topology recovers and constriction proceeds. In response to severing, a finite gap forms and is repaired by recruitment of new material in an actin polymerization-dependent manner. An open ring is able to constrict, and rings repair from successive cuts. After gap repair, an increase in constriction velocity allows cytokinesis to complete at the same time as controls. Our analysis demonstrates that tension in the ring increases while net cortical tension at the site of ingression decreases throughout constriction and suggests that cytokinesis is accomplished by contractile modules that assemble and contract autonomously, enabling local repair of the actomyosin network. Consequently, cytokinesis is a highly robust process impervious to discontinuities in contractile ring structure.

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The uncertainty about the future of firms must be modeled and incorporated in the valuation of enterprises outside the explicit period of analysis, i.e., in the continuing or terminal value (TV). There is a multiplicity of factors that influence the TV of firms which are not being considered within current evaluation models. This aspect leads to the incurring of unrecoverable errors, thus leading to values of goodwill or bad will far away from the substantial value of intrinsic assets. As a consequence, the evaluation results will be presented markedly different from market values. There is no consensus in the scientific community about the method of computation of the TV as a forecast in an infinite horizon. The size of the terminal, or non-explicit period, assumed as infinite, is never called into question by scientific literature, or the probability of business bankruptcy. This paper aims to promote a study of the existing literature on the TV, to highlight the fragility of the evaluation models of companies that have been used by the academic community and by financial analysts, and to point out lines for future research to minimize these errors.

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Thesis (Master, Community Health & Epidemiology) -- Queen's University, 2016-10-02 21:02:07.735

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Semiconductor nanowires, based on silicon (Si) or germanium (Ge) are leading candidates for many ICT applications, including next generation transistors, optoelectronics, gas and biosensing and photovoltaics. Key to these applications is the possibility to tune the band gap by changing the diameter of the nanowire. Ge nanowires of different diameter have been studied with H termination, but, using ideas from chemistry, changing the surface terminating group can be used to modulate the band gap. In this paper we apply the generalised gradient approximation of density functional theory (GGA-DFT) and hybrid DFT to study the effect of diameter and surface termination using –H, –NH2 and –OH groups on the band gap of (001), (110) and (111) oriented germanium nanowires. We show that the surface terminating group allows both the magnitude and the nature of the band gap to be changed. We further show that the absorption edge shifts to longer wavelength with the –NH2 and –OH terminations compared to the –H termination and we trace the origin of this effect to valence band modifications upon modifying the nanowire with –NH2 or –OH. These results show that it is possible to tune the band gap of small diameter Ge nanowires over a range of ca. 1.1 eV by simple surface chemistry.

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...este libro es el resultado de la implementación de la educación legal clínica, evidenciando, de un lado, la importancia de involucrar en la formación de los estudiantes de Jurisprudencia el componente práctico, al llevar a escenarios reales la aplicación de los conocimientos adquiridos en su carrera, incluso en asuntos de orden transnacional, y de otro lado, la imperiosa necesidad de poner en marcha el ejercicio responsable de su profesión, comprometiéndose con la realidad social de nuestro país. Adicionalmente, este libro es una herramienta de aprendizaje para clínicas de interés público en formación, para universidades y organizaciones que buscan implementar la enseñanza clínica en sus programas, para las comunidades y sus líderes, y en general para quienes buscan la forma responsable de ayudar a la comunidad a partir de la aplicación de sus conocimientos jurídicos..."--presentación.

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This exploratory research project developed a cognitive situated approach to studying aspects of simultaneous interpreting with quantitative, confirmatory methods. To do so, it explored how to determine the potential benefits of using a computer-assisted interpreting tool, InterpretBank, among 22 Chinese interpreting trainees with Chinese L1 and English L2. The informants were mostly 2nd-year female students with an average age of 24.7 enrolled in Chinese MA interpreting programs. The study adopted a pretest and posttest design with three cycles. The independent variable was using Excel or InterpretBank. After Cycle I (pre-test), the sample split into control (Excel) and experimental (InterpretBank) groups. Tool choice was compulsory in Cycle II but not Cycle III. The source materials for each cycle were pairs of matching transcripts from popular science podcasts. Informants compiled glossaries out of one transcript, while the other one was edited for simultaneous interpreting, with 39 terms as potential problem triggers. Quantitative profiling results showed that InterpretBank informants spent less time on glossary compilation, generated more terms faster than Excel informants, but their glossaries were less diverse (personal) and longer. The booth tasks yielded no significant differences in fluency indicators except for more bumps (200-600ms silent time gaps) for InterpretBank in Cycle II. InterpretBank informants had more correct renditions in Cycles II and III but there was no statistically significant difference among accuracy indicators per cycle. Holistic quality assessments by PhD raters showed InterpretBank consistently outperforming Excel, suggesting a positive InterpretBank impact on SI quality. However, some InterpretBank implementations raised cognitive ergonomic concerns for Chinese, potentially undermining its utility. Overall, results were mixed regarding InterpretBank benefits for Chinese trainees, but the project was successful in developing cognitive situated interpreting study methods, constructs and indicators.

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Riding the wave of recent groundbreaking achievements, artificial intelligence (AI) is currently the buzzword on everybody’s lips and, allowing algorithms to learn from historical data, Machine Learning (ML) emerged as its pinnacle. The multitude of algorithms, each with unique strengths and weaknesses, highlights the absence of a universal solution and poses a challenging optimization problem. In response, automated machine learning (AutoML) navigates vast search spaces within minimal time constraints. By lowering entry barriers, AutoML emerged as promising the democratization of AI, yet facing some challenges. In data-centric AI, the discipline of systematically engineering data used to build an AI system, the challenge of configuring data pipelines is rather simple. We devise a methodology for building effective data pre-processing pipelines in supervised learning as well as a data-centric AutoML solution for unsupervised learning. In human-centric AI, many current AutoML tools were not built around the user but rather around algorithmic ideas, raising ethical and social bias concerns. We contribute by deploying AutoML tools aiming at complementing, instead of replacing, human intelligence. In particular, we provide solutions for single-objective and multi-objective optimization and showcase the challenges and potential of novel interfaces featuring large language models. Finally, there are application areas that rely on numerical simulators, often related to earth observations, they tend to be particularly high-impact and address important challenges such as climate change and crop life cycles. We commit to coupling these physical simulators with (Auto)ML solutions towards a physics-aware AI. Specifically, in precision farming, we design a smart irrigation platform that: allows real-time monitoring of soil moisture, predicts future moisture values, and estimates water demand to schedule the irrigation.