19 resultados para building information model
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Modeling methods to derive 3D-structure of proteins have been recently developed. Protein homology-modeling, also known as comparative protein modeling, is nowadays the most accurate protein modeling method. This technique can produce useful models for about an order of magnitude more protein sequences than there have been structures determined by experiment in the same amount of time. All current protein homology-modeling methods consist of four sequential steps: fold assignment and template selection, template-target alignment, model building, and model evaluation. In this paper we discuss in some detail the protein-homology paradigm, its predictive power and its limitations.
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With the purpose of at lowering costs and reendering the demanded information available to users with no access to the internet, service companies have adopted automated interaction technologies in their call centers, which may or may not meet the expectations of users. Based on different areas of knowledge (man-machine interaction, consumer behavior and use of IT) 13 propositions are raised and a research is carried out in three parts: focus group, field study with users and interviews with experts. Eleven automated service characteristics which support the explanation for user satisfaction are listed, a preferences model is proposed and evidence in favor or against each of the 13 propositions is brought in. With balance scorecard concepts, a managerial assessment model is proposed for the use of automated call center technology. In future works, the propositions may become verifiable hypotheses through conclusive empirical research.
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Abstract:Through the development of a proposal to categorize accountability into four stages - classical, cross-sectional, systemic, and diffused -, this article aims to identify characteristics of co-production of information and socio-political control of public administration in the work of Brazilian social observatories in relationship with government control agencies. The study analyses data from 20 social observatories and, particularly, three experiences of co-production of information and control, based on a systemic perspective on accountability and a model with four categories: Political and cultural; valuing; systemic-organizational, and production. The conclusions summarize characteristics of these practices, specific phases in the accountability processes, as well as the potentialities and challenges of co-production of information and control, which not only influences, but it is also influenced by the accountability system.
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Theory building is one of the most crucial challenges faced by basic, clinical and population research, which form the scientific foundations of health practices in contemporary societies. The objective of the study is to propose a Unified Theory of Health-Disease as a conceptual tool for modeling health-disease-care in the light of complexity approaches. With this aim, the epistemological basis of theoretical work in the health field and concepts related to complexity theory as concerned to health problems are discussed. Secondly, the concepts of model-object, multi-planes of occurrence, modes of health and disease-illness-sickness complex are introduced and integrated into a unified theoretical framework. Finally, in the light of recent epistemological developments, the concept of Health-Disease-Care Integrals is updated as a complex reference object fit for modeling health-related processes and phenomena.
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INTRODUCTION: Forecasting dengue cases in a population by using time-series models can provide useful information that can be used to facilitate the planning of public health interventions. The objective of this article was to develop a forecasting model for dengue incidence in Campinas, southeast Brazil, considering the Box-Jenkins modeling approach. METHODS: The forecasting model for dengue incidence was performed with R software using the seasonal autoregressive integrated moving average (SARIMA) model. We fitted a model based on the reported monthly incidence of dengue from 1998 to 2008, and we validated the model using the data collected between January and December of 2009. RESULTS: SARIMA (2,1,2) (1,1,1)12 was the model with the best fit for data. This model indicated that the number of dengue cases in a given month can be estimated by the number of dengue cases occurring one, two and twelve months prior. The predicted values for 2009 are relatively close to the observed values. CONCLUSIONS: The results of this article indicate that SARIMA models are useful tools for monitoring dengue incidence. We also observe that the SARIMA model is capable of representing with relative precision the number of cases in a next year.
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INTRODUCTION: For a long time, the importance of Chagas disease in Mexico, where many regarded it as an exotic malady, was questioned. Considering the great genetic diversity among isolates of Trypanosoma cruzi, the importance of this biological characterization, and the paucity of information on the clinical and biological aspects of Chagas disease in Mexico, this study aimed to identify the molecular and biological characterization of Trypanosoma cruzi isolates from different endemic areas of this country, especially of the State of Jalisco. METHODS: Eight Mexican Trypanosoma cruzi strains were biologically and genetically characterized (PCR specific for Trypanosoma cruzi, multiplex-PCR, amplification of space no transcript of the genes of the mini-exon, amplification of polymorphic regions of the mini-exon, classification by amplification of intergenic regions of the spliced leader genes, RAPD - (random amplified polymorphic DNA). RESULTS: Two profiles of parasitaemia were observed, patent (peak parasitaemia of 4.6×10(6) to 10(7) parasites/mL) and subpatent. In addition, all isolates were able to infect 100% of the animals. The isolates mainly displayed tropism for striated (cardiac and skeletal) muscle. PCR amplification of the mini-exon gene classified the eight strains as TcI. The RAPD technique revealed intraspecies variation among isolates, distinguishing strains isolated from humans and triatomines and according to geographic origin. CONCLUSIONS: The Mexican T. cruzi strains are myotrophic and belong to group TcI.
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Mosquito cell cultures infected with human sera from dengue-1 and dengue-2 outbreaks, started in Rio de Janeiro by 1986 and 1990 respectively, were examined by electron microscopy at different times post the infection of cell cultures. More information was obtained about cell penetration of virus particles in the presence or not of antibodies, their pathway inside the cells, replication mode and exit. Infectiveness of the virus at those different stages can only be attributed to the particles appearing inside the trans-Golgi vesicles; most of all newly formed virus particles remain inside the RER-derived cell vesicles or inside lysosomes, even during cell lysis. Groups of larges particles, 65-75 nm in diameter at dengue-2 infections, persist during cell passage. The large amounts of smooth membrane structures, as vesicles or tabules inside the RER are attributed to a cell response to viral infection.
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Toxoplasma gondii is an important cause of clinical disease in fetuses, infants and immunocompromised patients. Since the discovery of T. gondii 100 years ago, this pathogen and the host's immune response to toxoplasmosis have been studied intensely. This has led to the development of a working model of immunity to T. gondii, and has also resulted in fundamental new insights into the role of various cytokines in resistance to infection. By examining this organism, researchers have identified many of the requirements for resistance to intracellular pathogens and characterized numerous regulatory factors, including interleukin-10 (IL-10) and IL-27, which control inflammatory processes. In the next 100 years of T. gondii immunobiology, researchers will have the opportunity to answer some of the long-standing questions in the field using new techniques and reagents. These future studies will be vital in building a more comprehensive model of immunity to this pathogen and in advancing our understanding of immunoregulation, particularly in humans. Ultimately, the challenge will be to use this information to develop new vaccines and therapies to manage disease in affected patients.
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This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.
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The aim of this study is to present an updated view of the writings on the endophenotype model for bipolar disorder using analytical methodologies. A review and analysis of networks was performed through descriptors and keywords that characterize the composition of the endophenotype model as a model of health. Information was collected from between 1992 and 2014, and the main thematic areas covered in the articles were identified. We discuss the results and question their cohesion, emphasizing the need to strengthen and identify the points of connection between etiological factors and characteristics that make up the model of endophenotypes for bipolar disorder.
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Information technology will affect academic activities as well as the nature of the high education sector. This sector besides the need to assimilate these technologies will need to attend the requisites of market globalization and, as consequence, all theses changes will be reflected in the university library. Prospectives impacts will affect the structure (emphasis in user services, outsourcing of several services), in the financing aspect (growing of consortia in order to reduce costs), in services (electronic reference, support to long distance education programs, intelligent agents) and in the clientele (attending the great demand por high education which implies a diversity of people).
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The objective of this work was to determine the sensitivity of maize (Zea mays) genotypes to water deficit, using a simple agrometeorological crop yield model. Crop actual yield and agronomic data of 26 genotypes were obtained from the Maize National Assays carried out in ten locations, in four Brazilian states, from 1998 to 2006. Weather information for each experimental location and period were obtained from the closest weather station. Water deficit sensitivity index (Ky) was determined using the crop yield depletion model. Genotypes can be divided into two groups according to their resistance to water deficit. Normal resistance genotypes had Ky ranging from 0.4 to 0.5 in vegetative period, 1.4 to 1.5 in flowering, 0.3 to 0.6 in fruiting, and 0.1 to 0.3 in maturing period, whereas the higher resistance genotypes had lower values, respectively 0.2-0.4, 0.7-1.2, 0.2-0.4, and 0.1-0.2. The general Ky for the total growing season was 2.15 for sensitive genotypes and 1.56 for the resistant ones. Model performance was acceptable to evaluate crop actual yield, whose average errors estimated for each genotype ranged from -5.7% to +5.8%, and whose general mean absolute error was 960 kg ha-1 (10%).
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The Annonaceae includes cultivated species of economic interest and represents an important source of information for better understanding the evolution of tropical rainforests. In phylogenetic analyses of DNA sequence data that are used to address evolutionary questions, it is imperative to use appropriate statistical models. Annonaceae are cases in point: Two sister clades, the subfamilies Annonoideae and Malmeoideae, contain the majority of Annonaceae species diversity. The Annonoideae generally show a greater degree of sequence divergence compared to the Malmeoideae, resulting in stark differences in branch lengths in phylogenetic trees. Uncertainty in how to interpret and analyse these differences has led to inconsistent results when estimating the ages of clades in Annonaceae using molecular dating techniques. We ask whether these differences may be attributed to inappropriate modelling assumptions in the phylogenetic analyses. Specifically, we test for (clade-specific) differences in rates of non-synonymous and synonymous substitutions. A high ratio of nonsynonymous to synonymous substitutions may lead to similarity of DNA sequences due to convergence instead of common ancestry, and as a result confound phylogenetic analyses. We use a dataset of three chloroplast genes (rbcL, matK, ndhF) for 129 species representative of the family. We find that differences in branch lengths between major clades are not attributable to different rates of non-synonymous and synonymous substitutions. The differences in evolutionary rate between the major clades of Annonaceae pose a challenge for current molecular dating techniques that should be seen as a warning for the interpretation of such results in other organisms.
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ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.
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We explore a DNA statistical model to obtain information about the behavior of the thermodynamics quantities. Special attention is given to the thermal denaturation of this macromolecule.