902 resultados para Context-dependency


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Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.

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Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

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We have analyzed a large set of alpha + alpha elastic scattering data for bombarding energies ranging from 0.6 to 29.5 MeV. Because of the complete lack of open reaction channels, the optical interaction at these energies must have a vanishing imaginary part. Thus, this system is particularly important because the corresponding elastic scattering cross sections are very sensitive to the real part of the interaction. The data were analyzed in the context of the velocity-dependent Sao Paulo potential, which is a successful theoretical model for the description of heavy-ion reactions from sub-barrier to intermediate energies. We have verified that, even in this low-energy region, the velocity dependence of the model is quite important for describing the data of the alpha + alpha system.

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Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

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Science education is under revision. Recent changes in society require changes in education to respond to new demands. Scientific literacy can be considered a new goal of science education and the epistemological gap between natural sciences and literacy disciplines must be overcome. The history of science is a possible bridge to link these `two cultures` and to foster an interdisciplinary approach in the classroom. This paper acknowledges Darwin`s legacy and proposes the use of cartoons and narrative expositions to put this interesting chapter of science into its historical context. A five-lesson didactic sequence was developed to tell part of the story of Darwin`s expedition through South America for students from 10 to 12 years of age. Beyond geological and biological perspectives, the inclusion of historical, social and geographical facts demonstrated the beauty and complexity of the findings that Darwin employed to propose the theory of evolution.

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One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

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Selenium (Se) is an essential element and deficit or excess of dietary Se is associated with health disorders. Relatively elevated Se levels have been reported in the Brazilian Amazon, where there are also important annual variations in the availability of different foods. The present study was conducted among six riparian communities of the Tapajos River to evaluate seasonal variations in blood and sequential hair cm Se concentrations, and to examine the relationships between Se in blood and hair, and blood and urine. Two cross-sectional studies were conducted, at the descending water (DWS, n = 259) and the rising water (RWS, n = 137) seasons, with repeated measures for a subgroup (n = 112). Blood Se (B-Se), hair Se (H-Se) and urine Se (U-Se) were determined. Match-paired analyses were used for seasonal comparisons and the method of best fit was used to describe the relationships between biomarkers. B-Se levels presented a very large range (142-2447 mu g/l) with no overall seasonal variation (median 284 and 292 mu g/l, respectively). Sequential analysis of 13 cm hair strands showed significant variations over time: Se concentrations at the DWS were significantly lower compared with the rising water season (medians: 0.7 and 0.9 mu g/g; ranges: 0.2-4.3 mu g/g and 0.2-5.4 mu g/g, respectively). At both seasons, the relationships between B-Se and H-Se were linear and highly significant (r(2) = 67.9 and 63.6, respectively), while the relationship between B-Se and U-Se was best described by a sigmoid curve. Gender, age, education and smoking did not influence Se status or biomarker relationships. Variations in H-Se suggest that there may be seasonal availability of Se sources in local food. For populations presenting a large range and/or elevated Se exposure, sequential analyses of H-Se may provide a good reflection of variations in Se status.

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Physical education, now often explicitly identified with health in contemporary school curricula, continues to be implicated in the (re)production of the 'cult of the body'. We argue that HPE is a form of health promotion that attempts to 'make' healthy citizens of young people in the context of the 'risk society'. In our view there is still work to be done in understanding how and why physical education (as HPE) continues to be implicated in the reproduction of values associated with the cult of body. We are keen to understand why HPE continues to be ineffective in helping young people gain some measure of analytic and embodied 'distance' from the problematic aspects of the cult of the body. This paper offers an analysis of this enduring issue by using some contemporary analytic discourses including 'governmentality', 'risk society' and the 'new public health'.

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This study examined the effects of political identity and the changing intergroup context on communication perceptions during an election campaign. Perceptions of media bias and of campaign impact on self and others were assessed before and after the election. The responses of politically aligned voters reflected their membership in a dominant or subordinate group preelection and in a losing or winning group postelection. Dominant group members were initially less biased in their views of the campaign and its impact but sought to blame their party's loss on media bias and on the gullibility of political out-group members and voters in general. Subordinate group members initially showed strong in-group-serving biases but were less critical of the media and the electorate after their party had won. Results highlight the dynamic, intergroup, nature of media perceptions.

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The study aimed to describe the types of care allocated at the end of acute care to people diagnosed with TBI and to identify the factors associated with variations in referral to care. A retrospective analysis of medical records of 61 patients was conducted based on a sample from two hospitals. While 60.7% of the study sample were referred to formal rehabilitation care, this was primarily non-inpatient rehabilitation care (32.8%). Discriminant analysis was used to determine medical and non-medical predictors of referral. Results indicated that place of treatment and age contribute to group differences and were significant in separating the inpatient rehabilitation group from the non-inpatient and no rehabilitation groups. Review by a rehabilitation physician was associated with referral to inpatient rehabilitation but was not adequate to explain referral to non-inpatient rehabilitation. An in-depth exploration of post-acute referral is warranted to improve policy and practice in relation to continuity of care following TBI.

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Continuous-valued recurrent neural networks can learn mechanisms for processing context-free languages. The dynamics of such networks is usually based on damped oscillation around fixed points in state space and requires that the dynamical components are arranged in certain ways. It is shown that qualitatively similar dynamics with similar constraints hold for a(n)b(n)c(n), a context-sensitive language. The additional difficulty with a(n)b(n)c(n), compared with the context-free language a(n)b(n), consists of 'counting up' and 'counting down' letters simultaneously. The network solution is to oscillate in two principal dimensions, one for counting up and one for counting down. This study focuses on the dynamics employed by the sequential cascaded network, in contrast to the simple recurrent network, and the use of backpropagation through time. Found solutions generalize well beyond training data, however, learning is not reliable. The contribution of this study lies in demonstrating how the dynamics in recurrent neural networks that process context-free languages can also be employed in processing some context-sensitive languages (traditionally thought of as requiring additional computation resources). This continuity of mechanism between language classes contributes to our understanding of neural networks in modelling language learning and processing.

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This paper surveys current work on the design of alarms for anesthesia environments and notes some of the problems arising from the need to interpret alarms in context. Anesthetists' responses to audible alarms in the operating room were observed across four types of surgical procedure (laparoscopic, arthroscopic, cardiac, and intracranial) and across three phases of a procedure (induction, maintenance, and emergence). Alarms were classified as (a) requiring a corrective response, (b) being the intended result of a decision, (c) being ignored as a nuisance alarm, or (d) functioning as a reminder. Results revealed strong effects of the type of procedure and phase of procedure on the number and rate of audible alarms. Some alarms were relatively confined to specific phases; others were seen across phases, and responses differed according to phase. These results were interpreted in light of their significance for the development of effective alarm systems. Actual or potential applications of this research include the design of alarm systems that are more informative and more sensitive to operative context than are current systems.