46 resultados para ADEPT


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In this action research study, I investigated the use of journaling in my seventh grade mathematics classroom. I discovered that journaling can be a very rewarding and beneficial experience for me and for my students. Through journaling, my students became more adept at using correct mathematical terminology in writing and in speaking. The students also believed that they learned the content more deeply and retained it better. Additionally, implementing mathematical journals caused me to emphasize the use of correct terminology and thorough explanations of mathematical thinking in classroom discussions. As a result of this research, I plan to refine my journaling process and continue to use mathematical journals with my future classes.

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Primates as a taxonomic Order have the largest brains corrected for body size in the animal kingdom. These large brains have allowed primates to evolve the capacity to demonstrate advanced cognitive processes across a wide array of abilities. Nonhuman primates are particularly adept at social learning, defined as the modification of behavior by observing the actions of others. Additionally, primates often exploit resources differently depending on their social context. In this study, capuchin monkeys (Cebus apella) were tested on a cognitive task in three social contexts to determine if social context influenced their performance on the task. The three social contexts included: alone, having a dominant individual in an adjacent compartment, and having a subordinate individual in the adjacent compartment. The benefits to this design were thatthe social context was the only variable influencing performance, whereas in previous studies investigating audience effects other animals could physically and directly influence a subject's performance in an open testing situation. Based on past studies, Ipredicted that the presence of a dominant individual would reduce cognitive task performance compared to the other conditions. The cognitive test used was a match-tosample discrimination task in which animals matched combinations of eight geometric shapes. Animals were trained on this task in an isolated context until they reached a baseline level of proficiency and were then tested in the three social contexts in a random order multiple times. Two subjects (Mt and Dv) have successfully completed trials under all conditions. Results indicated that there were no significant difference in taskperformance across the three conditions (Dv x^2 (1) = 0.42, p=0.58; Mt x^2 (1) = 0.02, p=0.88). In all conditions, subjects performed significantly above chance (i.e., 39/60 trials determined by a binomial distribution). Results are contrary to previous studies thatreport low status monkeys 'play dumb' when testing in a mixed social context, possibly because other studies did not account for aggressive interference by dominants while testing. Results of this study suggest that the mere presence of a dominant individualdoes not necessarily affect performance on a cognitive task, but rather the imminence of physical aggression is the most important factor influencing testing in a social context.

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The means through which the nervous system perceives its environment is one of the most fascinating questions in contemporary science. Our endeavors to comprehend the principles of neural science provide an instance of how biological processes may inspire novel methods in mathematical modeling and engineering. The application ofmathematical models towards understanding neural signals and systems represents a vibrant field of research that has spanned over half a century. During this period, multiple approaches to neuronal modeling have been adopted, and each approach is adept at elucidating a specific aspect of nervous system function. Thus while bio-physical models have strived to comprehend the dynamics of actual physical processes occurring within a nerve cell, the phenomenological approach has conceived models that relate the ionic properties of nerve cells to transitions in neural activity. Further-more, the field of neural networks has endeavored to explore how distributed parallel processing systems may become capable of storing memory. Through this project, we strive to explore how some of the insights gained from biophysical neuronal modeling may be incorporated within the field of neural net-works. We specifically study the capabilities of a simple neural model, the Resonate-and-Fire (RAF) neuron, whose derivation is inspired by biophysical neural modeling. While reflecting further biological plausibility, the RAF neuron is also analytically tractable, and thus may be implemented within neural networks. In the following thesis, we provide a brief overview of the different approaches that have been adopted towards comprehending the properties of nerve cells, along with the framework under which our specific neuron model relates to the field of neuronal modeling. Subsequently, we explore some of the time-dependent neurocomputational capabilities of the RAF neuron, and we utilize the model to classify logic gates, and solve the classic XOR problem. Finally we explore how the resonate-and-fire neuron may be implemented within neural networks, and how such a network could be adapted through the temporal backpropagation algorithm.

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Immunoglobulin A (IgA) is the main secretory immunoglobulin of mucous membranes and is powerfully induced by the presence of commensal microbes in the intestine. B cells undergo class switch recombination to IgA in the mucosa-associated lymphoid tissues, particularly mesenteric lymph nodes (MLNs) and Peyer's patches, through both T-dependent and T-independent pathways. IgA B cells primed in the mucosa traffic from the intestinal lymphoid structures, initially through the lymphatics and then join the bloodstream, to home back to the intestinal mucosa as IgA-secreting plasma cells. Once induced, anti-bacterial IgA can be extremely long-lived but is replaced if there is induction of additional IgA specificities by other microbes. The mucosal immune system is anatomically separated from the systemic immune system by the MLNs, which act as a firewall to prevent penetration of live intestinal bacteria to systemic sites. Dendritic cells sample intestinal bacteria and induce B cells to switch to IgA. In contrast, intestinal macrophages are adept at killing extracellular bacteria and are able to clear bacteria that have crossed the mucus and epithelial barriers. There is both a continuum between innate and adaptive immune mechanisms and compartmentalization of the mucosal immune system from systemic immunity that function to preserve host microbial mutualism.

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The urate transporter, GLUT9, is responsible for the basolateral transport of urate in the proximal tubule of human kidneys and in the placenta, playing a central role in uric acid homeostasis. GLUT9 shares the least homology with other members of the glucose transporter family, especially with the glucose transporting members GLUT1-4 and is the only member of the GLUT family to transport urate. The recently published high-resolution structure of XylE, a bacterial D-xylose transporting homologue, yields new insights into the structural foundation of this GLUT family of proteins. While this represents a huge milestone, it is unclear if human GLUT9 can benefit from this advancement through subsequent structural based targeting and mutagenesis. Little progress has been made toward understanding the mechanism of GLUT9 since its discovery in 2000. Before work can begin on resolving the mechanisms of urate transport we must determine methods to express, purify and analyze hGLUT9 using a model system adept in expressing human membrane proteins. Here, we describe the surface expression, purification and isolation of monomeric protein, and functional analysis of recombinant hGLUT9 using the Xenopus laevis oocyte system. In addition, we generated a new homology-based high-resolution model of hGLUT9 from the XylE crystal structure and utilized our purified protein to generate a low-resolution single particle reconstruction. Interestingly, we demonstrate that the functional protein extracted from the Xenopus system fits well with the homology-based model allowing us to generate the predicted urate-binding pocket and pave a path for subsequent mutagenesis and structure-function studies.

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BACKGROUND Listeria (L.) monocytogenes causes fatal infections in many species including ruminants and humans. In ruminants, rhombencephalitis is the most prevalent form of listeriosis. Using multilocus variable number tandem repeat analysis (MLVA) we recently showed that L. monocytogenes isolates from ruminant rhombencephalitis cases are distributed over three genetic complexes (designated A, B and C). However, the majority of rhombencephalitis strains and virtually all those isolated from cattle cluster in MLVA complex A, indicating that strains of this complex may have increased neurotropism and neurovirulence. The aim of this study was to investigate whether ruminant rhombencephalitis strains have an increased ability to propagate in the bovine hippocampal brain-slice model and can be discriminated from strains of other sources. For this study, forty-seven strains were selected and assayed on brain-slice cultures, a bovine macrophage cell line (BoMac) and a human colorectal adenocarcinoma cell line (Caco-2). They were isolated from ruminant rhombencephalitis cases (n = 21) and other sources including the environment, food, human neurolisteriosis cases and ruminant/human non-encephalitic infection cases (n = 26). RESULTS All but one L. monocytogenes strain replicated in brain slices, irrespectively of the source of the isolate or MLVA complex. The replication of strains from MLVA complex A was increased in hippocampal brain-slice cultures compared to complex C. Immunofluorescence revealed that microglia are the main target cells for L. monocytogenes and that strains from MLVA complex A caused larger infection foci than strains from MLVA complex C. Additionally, they caused larger plaques in BoMac cells, but not CaCo-2 cells. CONCLUSIONS Our brain slice model data shows that all L. monocytogenes strains should be considered potentially neurovirulent. Secondly, encephalitis strains cannot be conclusively discriminated from non-encephalitis strains with the bovine organotypic brain slice model. The data indicates that MLVA complex A strains are particularly adept at establishing encephalitis possibly by virtue of their higher resistance to antibacterial defense mechanisms in microglia cells, the main target of L. monocytogenes.

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Antibody-directed enzyme prodrug therapy, ADEPT, is a recent approach to targeted cancer chemotherapy intended to diminish the nonspecific toxicity associated with many commonly used chemotherapeutic agents. Most ADEPT systems incorporate a bacterial enzyme, and thus their potential is reduced because of the immunogenicity of that component of the conjugate. This limitation can be circumvented by the use of a catalytic antibody, which can be "humanized," in place of the bacterial enzyme catalyst. We have explored the scope of such antibody-directed "abzyme" prodrug therapy, ADAPT, to evaluate the potential for a repeatable targeted cancer chemotherapy. We report the production of a catalytic antibody that can hydrolyze the carbamate prodrug 4-[N,N-bis(2-chloroethyl)]aminophenyl-N-[(1S)-(1,3- dicarboxy)propyl]carbamate (1) to generate the corresponding cytotoxic nitrogen mustard (Km = 201 microM, kcat = 1.88 min-1). In vitro studies with this abzyme, EA11-D7, and prodrug 1 lead to a marked reduction in viability of cultured human colonic carcinoma (LoVo) cells relative to appropriate controls. In addition, we have found a good correlation between antibody catalysis as determined by this cytotoxicity assay in vitro and competitive binding studies of candidate abzymes to the truncated transition-state analogue ethyl 4-nitrophenylmethylphosphonate. This cell-kill assay heralds a general approach to direct and rapid screening of antibody libraries for catalysts.

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‘Adolescence’ has become increasingly recognised as a nebulous concept. Previous conceptualisations of adolescence have adopted a ‘deficit’ view, regarding teenagers as ‘unfinished’ adults. The deficit view of adolescence is highly problematic in an era where adulthood itself is difficult to define. The terms ‘kidult’ or ‘adultescent’ have emerged to describe adult-age people whose interests and priorities match those of their teenage counterparts. Rather than relying on ‘lock-step’ models of physical, cognitive and social growth put forward by developmental psychology, adolescence can be more usefully defined by looking at the common experiences of people in their teenage years. Common experiences arise at an institutional level; for example, all adolescents are treated as the same by legal and education systems. The transition from primary to secondary schooling is a milestone for all children, exposing them to a new type of educational environment. Shared experiences also arise from generational factors. Today’s adolescents belong to the millennial generation, characterised by technological competence, global perspectives, high susceptibility to media influence, individualisation and rapid interactions. This generation focuses on teamwork, achievement, modesty and good conduct, and has great potential for significant collective accomplishments. These generational factors challenge educators to provide relevant learning experiences for today’s students. Many classrooms still utilise textbook-based pedagogy more suited to previous generations, resulting in disengagement among millennial students. Curriculum content must also be tailored to generational needs. The rapid pace of change, as well as the fluidity of identity created by dissolving geographical and vocational boundaries, mean that the millennial generation will need more than a fixed set of skills and knowledge to enter adulthood. Teachers must enable their students to think like ‘expert novices’, adept at assimilating new concepts in depth and prepared to engage in lifelong learning.

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This thesis begins with a sociolinguistic correlational study of three phonetic variables - (h), (t) and (ing) - as used by four occupational groups - nurses, chefs, hairdressers and taxi-drivers. The groups were selected to incorporate three independent variables: sex (male-dominated versus female-dominated occupations); training (length and specialisation - nurses and chefs being more specialised than hairdressers and taxi-drivers) and location (the populations were selected from two cities - Liverpool and Birmingham). Although the correlational work demonstrates intra-sex and occupation consistency in speakers' choice of linguistic variants (females (particularly nurses) being significantly closer to the prestige norm), it is essentially non-explanatory and cannot accout for narrative dynamics and style shift. Therefore, an in-depth qualitative examination of the data (which draws mainly on Narrative and Discourse Analysis) forms the major part of the analysis. The study first analyses features common to all the narratives, direct speech, expressive phonology and linguistic ambiguity emerging as characteristic of all humorous storytelling. Secondly, three major sources of inter-personal variation are invetigated: narrator perspective, sex and occuptational role. Perspective is found to vary with topic and personality, greater narrator involvement coinciding with a higher proportion of internal evaluation devices. Sex differences include topic choice and bonding in the storytelling sessions. Sex differences are also evident in style shifting, where the narrator mimics the voice of a character in the narrative (aodpting segmental and/or prosodic tokens to signal a change of persona). The research finds that female narrators rarely employ segmental accommodation downwards on the social scale (whereas men do), but are on the other hand adept at using prosodic effects for mimicry. Taxi-drivers emerge as the group with the most distinctive narrative flair, a fact which is related to their occupation. The conclusion stresses a need for both quantitative and qualitative approaches to data; the importance of occupational role, as opposed to sex role per se in determining narrative conventions; the view of narrative as a negotiable entity, which is the product of relationships among participants; and the importance of considering the totality of the communicative act.

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This dissertation is the first systematic study of Armenia’s foreign policy during the post-independence period, between 1991 and 2004. It argues that a small state’s foreign policy is best understood when looking at the regional level. Armenia’s geographic proximity to Iran, Russia and Turkey, places it in an area of heightened geopolitical interest by various great powers. This dissertation explores four sets of relationships with Armenia’s major historical ‘partners’: Russia, Iran, Turkey and the West (Europe and the United States). Each relationship reveals a complex reality of a continuous negotiation between ideas of history, collective memory, nationalism and geopolitics. A detailed study of Armenia’s relations with these powers demonstrates how actors’ relations of amity and enmity are formed to constitute a regional security complex. Turkey represents the ultimate “other”, while both Europe and Iran are seen as ideational “others”, whose role in Armenia’s foreign policy, aside from pragmatic policy considerations, reflects a normative quest. Russia and the United States, on the other hand, represent the powerful structural forces that define the regional security complex, in which Armenia operates. This dissertation argues that although Armenia has been severely constrained in certain foreign policy choices, it was adept at carving a space for action that privileged the issue of Nagorno-Karabakh over other geopolitical imperatives.

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This dissertation is the first systematic study of Armenia’s foreign policy during the post-independence period, between 1991 and 2004. It argues that a small state’s foreign policy is best understood when looking at the regional level. Armenia’s geographic proximity to Iran, Russia and Turkey, places it in an area of heightened geopolitical interest by various great powers. This dissertation explores four sets of relationships with Armenia’s major historical ‘partners’: Russia, Iran, Turkey and the West (Europe and the United States). Each relationship reveals a complex reality of a continuous negotiation between ideas of history, collective memory, nationalism and geopolitics. A detailed study of Armenia’s relations with these powers demonstrates how actors’ relations of amity and enmity are formed to constitute a regional security complex. Turkey represents the ultimate “other”, while both Europe and Iran are seen as ideational “others”, whose role in Armenia’s foreign policy, aside from pragmatic policy considerations, reflects a normative quest. Russia and the United States, on the other hand, represent the powerful structural forces that define the regional security complex, in which Armenia operates. This dissertation argues that although Armenia has been severely constrained in certain foreign policy choices, it was adept at carving a space for action that privileged the issue of Nagorno-Karabakh over other geopolitical imperatives.

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Dissertação (mestrado)—Universidade de Brasília, Instituto de Física, Programa de Pós-Graduação em Física, 2015.

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In the presented thesis work, the meshfree method with distance fields was coupled with the lattice Boltzmann method to obtain solutions of fluid-structure interaction problems. The thesis work involved development and implementation of numerical algorithms, data structure, and software. Numerical and computational properties of the coupling algorithm combining the meshfree method with distance fields and the lattice Boltzmann method were investigated. Convergence and accuracy of the methodology was validated by analytical solutions. The research was focused on fluid-structure interaction solutions in complex, mesh-resistant domains as both the lattice Boltzmann method and the meshfree method with distance fields are particularly adept in these situations. Furthermore, the fluid solution provided by the lattice Boltzmann method is massively scalable, allowing extensive use of cutting edge parallel computing resources to accelerate this phase of the solution process. The meshfree method with distance fields allows for exact satisfaction of boundary conditions making it possible to exactly capture the effects of the fluid field on the solid structure.