57 resultados para Tool command language
Resumo:
Background: Genetic polymorphisms of the TCF7L2 gene are strongly associated with large increments in type 2 diabetes risk in different populations worldwide. In this study, we aimed to confirm the effect of the TCF7L2 polymorphism rs7903146 on diabetes risk in a Brazilian population and to assess the use of this genetic marker in improving diabetes risk prediction in the general population. Methods: We genotyped the single nucleotide polymorphisms (SNP) rs7903146 of the TCF7L2 gene in 560 patients with known coronary disease enrolled in the MASS II (Medicine, Angioplasty, or Surgery Study) Trial and in 1,449 residents of Vitoria, in Southeast Brazil. The associations of this gene variant to diabetes risk and metabolic characteristics in these two different populations were analyzed. To access the potential benefit of using this marker for diabetes risk prediction in the general population we analyzed the impact of this genetic variant on a validated diabetes risk prediction tool based on clinical characteristics developed for the Brazilian general population. Results: SNP rs7903146 of the TCF7L2 gene was significantly associated with type 2 diabetes in the MASS-II population (OR = 1.57 per T allele, p = 0.0032), confirming, in the Brazilian population, previous reports of the literature. Addition of this polymorphism to an established clinical risk prediction score did not increased model accuracy (both area under ROC curve equal to 0.776). Conclusion: TCF7L2 rs7903146 T allele is associated with a 1.57 increased risk for type 2 diabetes in a Brazilian cohort of patients with known coronary heart disease. However, the inclusion of this polymorphism in a risk prediction tool developed for the general population resulted in no improvement of performance. This is the first study, to our knowledge, that has confirmed this recent association in a South American population and adds to the great consistency of this finding in studies around the world. Finally, confirming the biological association of a genetic marker does not guarantee improvement on already established screening tools based solely on demographic variables.
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Introduction: Laparoscopic liver resections are becoming a common procedure, and bleeding remains the major concern during parenchymal transection. Total vascular inflow occlusion can be performed, but ischemic reperfusion injuries can lead to postoperative morbidity. On the other hand, hemihepatic inflow occlusion, leading to hemiliver ischemia, decreases the amount of liver parenchyma submitted to reperfusion damage and offers the advantage of reduced blood loss. Objective: The aim of this work was to describe our experience with laparoscopic the half-Pringle maneuver for segmentar or nonanatomic liver resctions. Patients and Methods: Eight patients submitted to laparoscopic liver resection in a single tertiary center. Results: There were 5 women and 3 men with a mean age of 40.2 years (range, 26-54). Mean tumor size was 4.1 cm (range, 2.6-6.0), and mean hospital stay was 3.1 days (1-5). There were 3 liver adenomas, 2 hepatocellular carcinomas, 1 metastatic melanoma, 1 metastatic colorectal carcinoma, and 1 peripheral colangiocarcinoma. No postoperative complications or mortalities were observed. Conclusions: Results demonstrate that laparoscopic liver resection with the half-Pringle maneuver is feasible and safe and may be included in the technical armamentarium of laparoscopic liver resections for a selected group of patients.
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Melanoma is a highly aggressive and therapy resistant tumor for which the identification of specific markers and therapeutic targets is highly desirable. We describe here the development and use of a bioinformatic pipeline tool, made publicly available under the name of EST2TSE, for the in silico detection of candidate genes with tissue-specific expression. Using this tool we mined the human EST (Expressed Sequence Tag) database for sequences derived exclusively from melanoma. We found 29 UniGene clusters of multiple ESTs with the potential to predict novel genes with melanoma-specific expression. Using a diverse panel of human tissues and cell lines, we validated the expression of a subset of three previously uncharacterized genes (clusters Hs.295012, Hs.518391, and Hs.559350) to be highly restricted to melanoma/melanocytes and named them RMEL1, 2 and 3, respectively. Expression analysis in nevi, primary melanomas, and metastatic melanomas revealed RMEL1 as a novel melanocytic lineage-specific gene up-regulated during melanoma development. RMEL2 expression was restricted to melanoma tissues and glioblastoma. RMEL3 showed strong up-regulation in nevi and was lost in metastatic tumors. Interestingly, we found correlations of RMEL2 and RMEL3 expression with improved patient outcome, suggesting tumor and/or metastasis suppressor functions for these genes. The three genes are composed of multiple exons and map to 2q12.2, 1q25.3, and 5q11.2, respectively. They are well conserved throughout primates, but not other genomes, and were predicted as having no coding potential, although primate-conserved and human-specific short ORFs could be found. Hairpin RNA secondary structures were also predicted. Concluding, this work offers new melanoma-specific genes for future validation as prognostic markers or as targets for the development of therapeutic strategies to treat melanoma.
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In Natural Language Processing (NLP) symbolic systems, several linguistic phenomena, for instance, the thematic role relationships between sentence constituents, such as AGENT, PATIENT, and LOCATION, can be accounted for by the employment of a rule-based grammar. Another approach to NLP concerns the use of the connectionist model, which has the benefits of learning, generalization and fault tolerance, among others. A third option merges the two previous approaches into a hybrid one: a symbolic thematic theory is used to supply the connectionist network with initial knowledge. Inspired on neuroscience, it is proposed a symbolic-connectionist hybrid system called BIO theta PRED (BIOlogically plausible thematic (theta) symbolic-connectionist PREDictor), designed to reveal the thematic grid assigned to a sentence. Its connectionist architecture comprises, as input, a featural representation of the words (based on the verb/noun WordNet classification and on the classical semantic microfeature representation), and, as output, the thematic grid assigned to the sentence. BIO theta PRED is designed to ""predict"" thematic (semantic) roles assigned to words in a sentence context, employing biologically inspired training algorithm and architecture, and adopting a psycholinguistic view of thematic theory.
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Quasielastic excitation functions for the (16,18)O + (60)Ni systems were measured at energies near and below the Coulomb barrier, at the backward angle theta(LAB) = 161 degrees. The corresponding quasielastic barrier distributions were derived. The data were compared with predictions from coupled channel calculations using a double-folding potential as a bare potential. For the (16)O-induced scattering, good agreement was obtained for the barrier distribution by using the projectile default nuclear matter diffuseness obtained from the Sao Paulo potential systematic, that is, 0.56 fm. However, for the (18)O-induced scattering, good agreement was obtained only when the projectile nuclear matter diffuseness was changed to 0.62 fm. Therefore, in this paper we show how near-barrier quasielastic scattering can be used as a sensitive tool to derive nuclear matter diffuseness.
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Introduction: Internet users are increasingly using the worldwide web to search for information relating to their health. This situation makes it necessary to create specialized tools capable of supporting users in their searches. Objective: To apply and compare strategies that were developed to investigate the use of the Portuguese version of Medical Subject Headings (MeSH) for constructing an automated classifier for Brazilian Portuguese-language web-based content within or outside of the field of healthcare, focusing on the lay public. Methods: 3658 Brazilian web pages were used to train the classifier and 606 Brazilian web pages were used to validate it. The strategies proposed were constructed using content-based vector methods for text classification, such that Naive Bayes was used for the task of classifying vector patterns with characteristics obtained through the proposed strategies. Results: A strategy named InDeCS was developed specifically to adapt MeSH for the problem that was put forward. This approach achieved better accuracy for this pattern classification task (0.94 sensitivity, specificity and area under the ROC curve). Conclusions: Because of the significant results achieved by InDeCS, this tool has been successfully applied to the Brazilian healthcare search portal known as Busca Saude. Furthermore, it could be shown that MeSH presents important results when used for the task of classifying web-based content focusing on the lay public. It was also possible to show from this study that MeSH was able to map out mutable non-deterministic characteristics of the web. (c) 2010 Elsevier Inc. All rights reserved.
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There is little empirical data about the impact of digital inclusion on cognition among older adults. This paper aimed at investigating the effects of a digital inclusion program in the cognitive performance of older individuals who participated in a computer learning workshop named ""Idosos On-Line`` (Elderly Online). Forty-two aged individuals participated in the research study: 22 completed the computer training workshop and 20 constituted the control group. All subjects answered a sociodemographic questionnaire and completed the Addenbrooke`s cognitive examination, revised (ACE-R), which examines five cognitive domains: orientation and attention, memory, verbal fluency, language, and visuo-spatial skills. It was noted that the experimental group`s cognitive performance significantly improved after the program, particularly in the language and memory domains, when compared to the control group. These findings suggest that the acquisition of new knowledge and the use of a new tool, that makes it possible to access the Internet, may bring gains to cognition. (C) 2010 Elsevier Ireland Ltd. All rights reserved.
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An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work intends to bring to natural language processing research, the use of a more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may bring an increase in computational efficiency when compared to the sa-called biologically implausible algorithms.
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Appropriate pain assessment is very important for managing chronic pain. Given the cultural differences in verbally expressing pain and in psychosocial problems, specific tools are needed. The goal of this study was to identify and validate Brazilian pain descriptors. A purposive sample of health professionals and chronic pain patients was recruited. Four studies were conducted using direct and indirect psychophysical methods: category estimation, magnitude estimation, and magnitude estimation and tine-length. Results showed the descriptors which best describe chronic pain in Brazilian culture and demonstrated that there is not a significant correlation between patients and health professionals and that the psychophysical scale of judgment of pain descriptors is valid, stable, and consistent. Results reinforced that the translations of word descriptors and research tools into another language may be inappropriate, owing to differences in perception and communication and the inadequacy of exact translations to reflect the intended meaning. Given the complexity of the chronic pain, personal suffering involved, and the need for accurate assessment of chronic pain using descriptors stemming from Brazilian culture and language, it is essential to investigate the most adequate words to describe chronic pain. Although it requires more refinement, the Brazilian chronic pain descriptors can be used further to develop a multidimensional pain assessment tool that is culturally sensitive. (C) 2009 by the American Society for Pain Management Nursing
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The activity of validating identified requirements for an information system helps to improve the quality of a requirements specification document and, consequently, the success of a project. Although various different support tools to requirements engineering exist in the market, there is still a lack of automated support for validation activity. In this context, the purpose of this paper is to make up for that deficiency, with the use of an automated tool, to provide the resources for the execution of an adequate validation activity. The contribution of this study is to enable an agile and effective follow-up of the scope established for the requirements, so as to lead the development to a solution which would satisfy the real necessities of the users, as well as to supply project managers with relevant information about the maturity of the analysts involved in requirements specification.
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Effluents from pulp mill are usually toxic and mutagenic. This characteristic is mainly a consequence of xenobiotic compounds that are formed during the process. Global parameters such as chemical oxidation demand, total organic carbon and others, do not permit identify whether the toxic potential was remedied by the treatments or not. The objective of this research was to evaluate the performance of an horizontal-flow anaerobic immobilized biomass reactor (HAIB) treating the bleaching effluent from a Kraft pulp mill using toxicological (Daphnia similis - Ceriodaphnia sdvestrii) mutagenicity and citotoxicological assays (Allium cepa L). The results showed high sensibility of the test-organisms and capability of the anaerobic reactor to remove compounds that are exerting toxic and mutagenic effects. The bioassays represented an attractive alternative to water quality analyzes and the performance evaluation of treatments.
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AISI D2 is the most commonly used cold-work tool steel of its grade. It offers high hardenability, low distortion after quenching, high resistance to softening and good wear resistance. The use of appropriate hard coatings on this steel can further improve its wear resistance. Boronizing is a surface treatment of Boron diffusion into the substrate. In this work boride layers were formed on AISI D2 steel using borax baths containing iron-titanium and aluminium, at 800 degrees C and 1000 degrees C during 4 h. The borided treated steel was characterized by optical microscopy, Vickers microhardness, X-ray diffraction (XRD) and glow discharge optical spectroscopy (GDOS) to verify the effect of the bath compositions and treatment temperatures in the layer formation. Depending on the bath composition, Fe(2)B or FeB was the predominant phase in the boride layers. The layers exhibited ""saw-tooth"" morphology at the substrate interface; layer thicknesses varied from 60 to 120 mu m, and hardness in the range of 1596-1744 HV were obtained. (C) 2009 Elsevier Ltd. All rights reserved.
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High urban transport energy consumption is directly influenced by transport energy dependence. Dramatic reductions in urban transport energy dependence or consumption are not yet being widely observed despite the variety of urban planning tools currently available. A new urban development framework is presented to tackle this issue that makes use of a recently developed and successfully trialed GIS-based tool, the Transport Energy Specification (TES). The TES was simulated on a neighborhood in Sao Carlos, Brazil. In the simulation, energy dependence was reduced by a factor of 8 through activity location or infrastructure modifications to the built environment.
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This paper proposes a simple high-level programming language, endowed with resources that help encoding self-modifying programs. With this purpose, a conventional imperative language syntax (not explicitly stated in this paper) is incremented with special commands and statements forming an adaptive layer specially designed with focus on the dynamical changes to be applied to the code at run-time. The resulting language allows programmers to easily specify dynamic changes to their own program`s code. Such a language succeeds to allow programmers to effortless describe the dynamic logic of their adaptive applications. In this paper, we describe the most important aspects of the design and implementation of such a language. A small example is finally presented for illustration purposes.
Resumo:
AISI H13 tool steel discs were pulsed plasma minded during different times at a constant temperature of 400 degrees C Wear tests were performed in order to study the acting wear mechanisms The samples were characterized by X-ray diffraction, scanning electron microscopy and hardness measurements The results showed that longer nitriding times reduce the wear volumes. The friction coefficient was 0.20 +/- 0 05 for all tested conditions and depends strongly on the presence of debris After wear tests, the wear tracks were characterized by optical and scanning electron microscopy and the wear mechanisms were observed to change from low cycle fatigue or plastic shakedown to long cycle fatigue These mechanisms were correlated to the microstructure and hardness of the nitrided layer (C) 2010 Elsevier B V All rights reserved