984 resultados para subset sum problems
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Companion piece to my earlier article in Literature Conmpass: 'Modern Problems of Editing: The Two Texts of Doctor Faustus'. Provides a model for a module based on the topic of that article.
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It is often assumed that membership in a stigmatized group has negative consequences for the self-concept. However, this relationship is neither straightforward nor inevitable, and there is evidence suggesting that negative consequences may not necessarily occur (Psychol. Rev. 96(4) (1989) 608). This paper argues that the relationship has not been sufficiently theorized, and that a more detailed analysis is called for in order to understand the relationship between stigma and the self. The paper presents a critical examination of modified labeling theory (Am. Sociol. Rev. 52 (1987) 96), with examples from a study examining perceptions of stigma and their relationship to self-evaluation in women with chronic mental health problems. Open-ended interviews and qualitative analyses were used in preference to global measures of self-esteem. It was found that although the women were aware of society's unfavorable representations of mental illness, and the effects this had on their lives, they did not accept these representations as valid and therefore rejected them as applicable to the self. The participants did not deny their mental health problems, but their acceptance of labels was critical and pragmatic. Labels were rejected when they were perceived as carrying an unrealistic and negative stereotype, or when the women felt that their symptoms did not fit with the diagnostic criteria. The research illustrates the importance of considering people's subjective understandings of stigmatized conditions and societal reactions in order to understand the relation between stigma and the self. (C) 2002 Elsevier Science Ltd. All rights reserved.
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In the perceived hierarchy of research designs, the results from randomized controlled trials are considered to provide the highest level of evidence. Indeed these trials have been upheld as the gold standard in research. The benefits and limitations of the randomized controlled trial as a method of evaluating the effectiveness of healthcare interventions are presented. The article then examines the different levels of complexity within healthcare interventions and the problems this poses in determining effectiveness. In an effort to provide a solution to this problem, the Medical Research Council produced a framework to assist investigators to develop and evaluate complex healthcare interventions. The framework is described with reference to an example of implementing and evaluating protocols for weaning patients in the intensive care unit. The framework is critiqued on the basis that it involves an ambiguous or contradictory ontology, which fails to articulate the relationship between the positivism of randomized controlled trials with the relativism of qualitative approaches. It is concluded that the use of realist strategies in combination with randomized controlled trials provides the most coherent solution to this quandary
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A growing literature has emerged on employee silence, located within the field of organisational behaviour. Scholars have investigated when and how employees articulate voice and when and how they will opt for silence. While offering many insights, this analysis is inherently one-sided in its interpretation of silence as a product of employee motivations. An alternative reading of silence is offered which focuses on the role of management. Using the non-union employee representation literature for illustrative purposes, the significance of management in structuring employee silence is considered. Highlighted are the ways in which management, through agenda-setting and institutional structures, can perpetuate silence over a range of issues, thereby organising employees out of the voice process. These considerations are redeployed to offer a dialectical interpretation of employee silence in a conceptual framework to assist further research and analysis.
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BACKGROUND & AIMS: C/EBP alpha (cebpa) is a putative tumor suppressor. However, initial results indicated that cebpa was up-regulated in a subset of human hepatocellular carcinomas (HCCs). The regulation and function of C/EBP alpha was investigated in HCC cell lines to clarify its role in liver carcinogenesis. METHODS: The regulation of C/EBP alpha expression was studied by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), Western blotting, immunohistochemistry, methylation-specific PCR, and chromatin immunoprecipitation assays. C/EBP alpha expression was knocked-down by small interfering RNA or short hairpin RNA. Functional assays included colony formation, methylthiotetrazole, bromodeoxyuridine incorporation, and luciferase-reporter assays. RESULTS: Cebpa was up-regulated at least 2-fold in a subset (approximately 55%) of human HCCs compared with adjacent non tumor tissues. None of the up-regulated samples were positive for hepatitis C infection. The HCC cell lines Hep3B and Huh7 expressed high, PLC/PRF/5 intermediate, HepG2 and HCC-M low levels of C/EBP alpha, recapitulating the pattern of expression observed in HCCs. No mutations were detected in the CEBP alpha gene in HCCs and cell lines. C/EBP alpha was localized to the nucleus and functional in Hep3B and Huh7 cells; knocking-down its expression reduced target-gene expression, colony formation, and cell growth, associated with a decrease in cyclin A and CDK4 concentrations and E2F transcriptional activity. Epigenetic mechanisms including DNA methylation, and the binding of acetylated histone H3 to the CEBP alpha promoter-regulated cebpa expression in the HCC cells. CONCLUSIONS: C/EBP alpha is up-regulated in a subset of HCCs and has growth-promoting activities in HCC cells. Novel oncogenic mechanisms involving C/EBP alpha may be amenable to epigenetic regulation to improve treatment outcomes.
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This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.