10 resultados para ethical dimension of time

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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(The ethical dimension f analyst's interventions facing institutional demands of CAPS) Considering the complexities involved in setting up clinical work in the psychosocial field, analyst must question their own contributions toward improvements in this area. This issue is presented here as a considerable challenge, due to the limitations of psychoanalytic practice and, especially, the differences between conventional clinical practice and that carried out in institutional and political settings. From this perspective, we call attention to the notion of ethics as a differentiating and guiding concept for psychoanalytic practice in its contribution toward the treatment provided at CAPS.

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The aim of this study was to compare time-motion indicators during judo matches performed by athletes from different age groups. The following age groups were analysed: Pre-Juvenile (13-14 years, n=522), Juvenile (15-16 years, n 353); Junior (19 years, n = 349) and Senior (>20 years, n = 587). The time-motion indicators included: Total Combat Time, Standing Combat Time, Displacement Without Contact, Gripping Time, Groundwork Combat Time and Pause Time. Analysis of variance (ANOVA) one-way and the Tukey test, as well as the Kruskal-Wallis test and Mann-Whitney (for non-parametric data), were conducted, using P < 0.05 as significance level. The results showed that all analysed groups obtained a median of 7 (first quantile - 3, third quantile - 12) sequences of combat/pause cycles. In total time of combat, the result was: for Total Combat Time, Standing Combat Time and Gripping Time: Pre-Juvenile and Senior were significantly longer than Juvenile and Junior. Considering Displacement Without Contact, Junior was significantly longer than all other age groups. For Groundwork Combat Time, Senior was significantly longer than all other age groups and Pre-Juvenile was longer than Junior. These results can be used to improve the physiological performance in intermittent practices, as well as technicaltactical training during judo sessions.

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This paper is dedicated to estimate the fractal dimension of exponential global attractors of some generalized gradient-like semigroups in a general Banach space in terms of the maximum of the dimension of the local unstable manifolds of the isolated invariant sets, Lipschitz properties of the semigroup and the rate of exponential attraction. We also generalize this result for some special evolution processes, introducing a concept of Morse decomposition with pullback attractivity. Under suitable assumptions, if (A, A*) is an attractor-repeller pair for the attractor A of a semigroup {T(t) : t >= 0}, then the fractal dimension of A can be estimated in terms of the fractal dimension of the local unstable manifold of A*, the fractal dimension of A, the Lipschitz properties of the semigroup and the rate of the exponential attraction. The ingredients of the proof are the notion of generalized gradient-like semigroups and their regular attractors, Morse decomposition and a fine analysis of the structure of the attractors. As we said previously, we generalize this result for some evolution processes using the same basic ideas. (C) 2012 Elsevier Ltd. All rights reserved.

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Subterranean organisms are excellent models for chronobiological studies, yet relatively few taxa have been investigated with this focus. Former results were interpreted as a pattern of regression of circadian locomotor activity rhythms in troglobitic (exclusively subterranean) species. In this paper we report results of experiments with cave fishes showing variable degrees of troglomorphism (reduction of eyes, melanic pigmentation and other specializations related to the hypogean life) submitted to light-dark cycles, preceded and followed by several days in constant darkness. Samples from seven species have been monitored in our laboratory for the detection of significant circadian rhythms in locomotor activity: S. typhlops, an extremely troglomophic species, presented the lowest number of significant components in the circadian range (only one individual out of eight in DD1 and three other fish in LD), all weak (low values of spectral power). Higher incidence of circadian components was observed for P. kronei - only one among six studied catfish without significant circadian rhythms under DD1 and DD2; spectral powers were generally high. Intermediate situations were observed for the remaining species, however all of them presented relatively strong significant rhythms under LD. Residual oscillations (circadian rhythms in DD2) were detected in at least part of the studied individuals of all species but S. typhlops, without a correlation with spectral powers of LD rhythms, i.e., individuals exhibiting residual oscillations were not necessarily those with the strongest LD rhythms. In conclusion, the accumulated evidence for troglobitic fishes strongly supports the hypothesis of external, environmental selection for circadian locomotor rhythms.

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Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

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Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

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Background: A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results: In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions: This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them.

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OBJECTIVE: To review scientific literature relating to the spiritual dimension of children and adolescents with cancer. METHODS: We conducted an integrative literature review in the LILACS, SciELO, PsycINFO and MEDLINE databases in the period between 1990 to 2011. RESULTS: Twenty-one studies were analyzed and grouped into thematic categories: quality of life and elements of spirituality; alternative and complementary therapies: spirituality as a therapeutic resource; spirituality as a coping strategy and spirituality as an attribute of existential transformations. It was found that spirituality is present at different stages of the disease experience and that its forms of expression may vary, according to age and cognitive development. CONCLUSION: There is a scarcity of specific scales for this age range and a need for scientific production relating to the spiritual dimension of children and adolescents with cancer. Descriptors: Neoplasms; Children; Adolescents; Spirituality

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OBJECTIVE: To assess the effects of rapid maxillary expansion on facial morphology and on nasal cavity dimensions of mouth breathing children by acoustic rhinometry and computed rhinomanometry. METHODS: Cohort; 29 mouth breathing children with posterior crossbite were evaluated. Orthodontic and otorhinolaryngologic documentation were performed at three different times, i.e., before expansion, immediately after and 90 days following expansion. RESULTS: The expansion was accompanied by an increase of the maxillary and nasal bone transversal width. However, there were no significant differences in relation to mucosal area of the nose. Acoustic rhinometry showed no difference in the minimal cross-sectional area at the level of the valve and inferior turbinate between the periods analyzed, although rhinomanometry showed a statistically significant reduction in nasal resistance right after expansion, but were similar to pre-treatment values 90 days after expansion. CONCLUSION: The maxillary expansion increased the maxilla and nasal bony area, but was inefficient to increase the nasal mucosal area, and may lessen the nasal resistance, although there was no difference in nasal geometry. Significance: Nasal bony expansion is followed by a mucosal compensation.

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This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.