241 resultados para temporal-logic model


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In Brazil, the study of pedestrian-induced vibration on footbridges has been undertaken since the early 1990s, for concrete and steel footbridges. However, there are no recorded studies of this kind for timber footbridges. Brazilian code ABNT NBR 7190 (1997) gives design requirements only for static loads in the case of timber footbridges, without considering the serviceability limit state from pedestrian-induced vibrations. The aim of this work is to perform a theoretical dynamic, numerical and experimental analysis on simply-supported timber footbridges, by using a small-scale model developed from a 24 m span and 2 m width timber footbridge, with two main timber beams. Span and width were scaled down (1:4) to 6 m e 0.5 in, respectively. Among the conclusions reached herein, it is emphasized that the Euler-Bernoulli beam theory is suitable for calculating the vertical and lateral first natural frequencies in simply-supported timber footbridges; however, special attention should be given to the evaluation of lateral bending stiffness, as it leads to conservative values.

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The alkali-aggregate reaction (AAR) is a chemical reaction that provokes a heterogeneous expansion of concrete and reduces important properties such as Young's modulus, leading to a reduction in the structure's useful life. In this study, a parametric model is employed to determine the spatial distribution of the concrete expansion, combining normalized factors that influence the reaction through an AAR expansion law. Optimization techniques were employed to adjust the numerical results and observations in a real structure. A three-dimensional version of the model has been implemented in a finite element commercial package (ANSYS(C)) and verified in the analysis of an accelerated mortar test. Comparisons were made between two AAR mathematical descriptions for the mechanical phenomenon, using the same methodology, and an expansion curve obtained from experiment. Some parametric studies are also presented. The numerical results compared very well with the experimental data validating the proposed method.

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The implementation of confidential contracts between a container liner carrier and its customers, because of the Ocean Shipping Reform Act (OSRA) 1998, demands a revision in the methodology applied in the carrier's planning of marketing and sales. The marketing and sales planning process should be more scientific and with a better use of operational research tools considering the selection of the customers under contracts, the duration of the contracts, the freight, and the container imbalances of these contracts are basic factors for the carrier's yield. This work aims to develop a decision support system based on a linear programming model to generate the business plan for a container liner carrier, maximizing the contribution margin of its freight.

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A susceptible-infective-recovered (SIR) epidemiological model based on probabilistic cellular automaton (PCA) is employed for simulating the temporal evolution of the registered cases of chickenpox in Arizona, USA, between 1994 and 2004. At each time step, every individual is in one of the states S, I, or R. The parameters of this model are the probabilities of each individual (each cell forming the PCA lattice ) passing from a state to another state. Here, the values of these probabilities are identified by using a genetic algorithm. If nonrealistic values are allowed to the parameters, the predictions present better agreement with the historical series than if they are forced to present realistic values. A discussion about how the size of the PCA lattice affects the quality of the model predictions is presented. Copyright (C) 2009 L. H. A. Monteiro et al.

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Identification, prediction, and control of a system are engineering subjects, regardless of the nature of the system. Here, the temporal evolution of the number of individuals with dengue fever weekly recorded in the city of Rio de Janeiro, Brazil, during 2007, is used to identify SIS (susceptible-infective-susceptible) and SIR (susceptible-infective-removed) models formulated in terms of cellular automaton (CA). In the identification process, a genetic algorithm (GA) is utilized to find the probabilities of the state transition S -> I able of reproducing in the CA lattice the historical series of 2007. These probabilities depend on the number of infective neighbors. Time-varying and non-time-varying probabilities, three different sizes of lattices, and two kinds of coupling topology among the cells are taken into consideration. Then, these epidemiological models built by combining CA and GA are employed for predicting the cases of sick persons in 2008. Such models can be useful for forecasting and controlling the spreading of this infectious disease.

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Compartmental epidemiological models have been developed since the 1920s and successfully applied to study the propagation of infectious diseases. Besides, due to their structure, in the 1960s an interesting version of these models was developed to clarify some aspects of rumor propagation, considering that spreading an infectious disease or disseminating information is analogous phenomena. Here, in an analogy with the SIR (Susceptible-Infected-Removed) epidemiological model, the ISS (Ignorant-Spreader-Stifler) rumor spreading model is studied. By using concepts from the Dynamical Systems Theory, stability of equilibrium points is established, according to propagation parameters and initial conditions. Some numerical experiments are conducted in order to validate the model.

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Background: The tomato (Solanum lycopersicum L.) plant is both an economically important food crop and an ideal dicot model to investigate various physiological phenomena not possible in Arabidopsis thaliana. Due to the great diversity of tomato cultivars used by the research community, it is often difficult to reliably compare phenotypes. The lack of tomato developmental mutants in a single genetic background prevents the stacking of mutations to facilitate analysis of double and multiple mutants, often required for elucidating developmental pathways. Results: We took advantage of the small size and rapid life cycle of the tomato cultivar Micro-Tom (MT) to create near-isogenic lines (NILs) by introgressing a suite of hormonal and photomorphogenetic mutations (altered sensitivity or endogenous levels of auxin, ethylene, abscisic acid, gibberellin, brassinosteroid, and light response) into this genetic background. To demonstrate the usefulness of this collection, we compared developmental traits between the produced NILs. All expected mutant phenotypes were expressed in the NILs. We also created NILs harboring the wild type alleles for dwarf, self-pruning and uniform fruit, which are mutations characteristic of MT. This amplified both the applications of the mutant collection presented here and of MT as a genetic model system. Conclusions: The community resource presented here is a useful toolkit for plant research, particularly for future studies in plant development, which will require the simultaneous observation of the effect of various hormones, signaling pathways and crosstalk.

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Background: Population antimicrobial use may influence resistance emergence. Resistance is an ecological phenomenon due to potential transmissibility. We investigated spatial and temporal patterns of ciprofloxacin (CIP) population consumption related to E. coli resistance emergence and dissemination in a major Brazilian city. A total of 4,372 urinary tract infection E. coli cases, with 723 CIP resistant, were identified in 2002 from two outpatient centres. Cases were address geocoded in a digital map. Raw CIP consumption data was transformed into usage density in DDDs by CIP selling points influence zones determination. A stochastic model coupled with a Geographical Information System was applied for relating resistance and usage density and for detecting city areas of high/low resistance risk. Results: E. coli CIP resistant cluster emergence was detected and significantly related to usage density at a level of 5 to 9 CIP DDDs. There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. Conclusions: There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. The usage density of 5-9 CIP DDDs per 1,000 inhabitants within the same influence zone was the resistance triggering level. This level led to E. coli resistance clustering, proving that individual resistance emergence and dissemination was affected by antimicrobial population consumption.

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Background: Francisella tularensis causes severe pulmonary disease, and nasal vaccination could be the ideal measure to effectively prevent it. Nevertheless, the efficacy of this type of vaccine is influenced by the lack of an effective mucosal adjuvant. Methodology/Principal Findings: Mice were immunized via the nasal route with lipopolysaccharide isolated from F. tularensis and neisserial recombinant PorB as an adjuvant candidate. Then, mice were challenged via the same route with the F. tularensis attenuated live vaccine strain (LVS). Mouse survival and analysis of a number of immune parameters were conducted following intranasal challenge. Vaccination induced a systemic antibody response and 70% of mice were protected from challenge as showed by their improved survival and weight regain. Lungs from mice recovering from infection presented prominent lymphoid aggregates in peribronchial and perivascular areas, consistent with the location of bronchus-associated lymphoid tissue (BALT). BALT areas contained proliferating B and T cells, germinal centers, T cell infiltrates, dendritic cells (DCs). We also observed local production of antibody generating cells and homeostatic chemokines in BALT areas. Conclusions: These data indicate that PorB might be an optimal adjuvant candidate for improving the protective effect of F. tularensis antigens. The presence of BALT induced after intranasal challenge in vaccinated mice might play a role in regulation of local immunity and long-term protection, but more work is needed to elucidate mechanisms that lead to its formation.

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Baccharis dracunculifolia DC (Asteraceae) is a Brazilian medicinal plant popularly used for its antiulcer and anti-inflammatory properties. This plant is the main botanical source of Brazilian green propolis, a natural product incorporated into food and beverages to improve health. The present study aimed to investigate the chemical profile and intestinal anti-inflammatory activity of B. dracunculifolia extract on experimental ulcerative colitis induced by trinitrobenzenosulfonic acid (TNBS). Colonic damage was evaluated macroscopically and biochemically through its evaluation of glutathione content and its myeloperoxidase (MPO) and alkaline phosphatase activities. Additional in vitro experiments were performed in order to test the antioxidant activity by inhibition of induced lipid peroxidation in the rat brain membrane. Phytochemical analysis was performed by HPLC using authentic standards. The administration of plant extract (5 and 50 mgkg(-1)) significantly attenuated the colonic damage induced by TNBS as evidenced both macroscopically and biochemically. This beneficial effect can be associated with an improvement in the colonic oxidative status, since plant extract prevented glutathione depletion, inhibited lipid peroxidation and reduced MPO activity. Caffeic acid, p-coumaric acid, aromadendrin-4-O-methyl ether, 3-prenyl-p-coumaric acid, 3,5-diprenyl-p-coumaric acid and baccharin were detected in the plant extract.

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Background: Since successful treatment of superficial bladder cancer with BCG requires proper induction of Th1 immunity, we have developed a rBCG-S1PT strain that induced a stronger cellular immune response than BCG. This preclinical study was designed to compare the modulatory effects of BCG and rBCG-S1PT on bladder TNF-alpha and IL-10 expression and to evaluate antitumour activity. Methods: For Experiment I, the MB49 bladder cancer cell line was used in C57BL/6 mice. Chemical cauterization of the bladder was performed to promote intravesical tumor implantation. Mice were treated by intravesical instillation with BCG, rBCG-S1PT or PBS once a week for four weeks. After 35 days the bladders were removed and weighed. TNF-

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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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Background Tuberculosis clusters in families may be due to increased household exposure, shared genetic factors, or both. Household contact studies are useful to control exposure because socioeconomic and environmental conditions are similar to all subjects, allowing the evaluation of the contribution of relatedness to disease development. Methods In this study, the familial aggregation of tuberculosis using relatedness and a specific inherited marker (HLA-DRB1) was evaluated. Fifty families, which had at least two cases of tuberculosis diagnosed within the past 5 years, were selected from a cohort of tuberculosis carried out in Recife, Brazil. The first case diagnosed was considered to be a primary case. The secondary attack rate of tuberculosis in household contacts was estimated according to the degree of relatedness. The relative risk of having tuberculosis based on the degree of relatedness household and the population attributable fraction to relatedness were also estimated. HLA-DRB1 typing and attributable etiologic/preventive fractions were calculated among sick and healthy household contacts. Results Compared to unrelated contacts, the relative risk for tuberculosis adjusted for age was 1.38 (95% CI 0.86 to 2.21). Relatedness contributed 23% to the development of tuberculosis at the population levels. The HLA-DRB1*04 allele group (OR = 2.44; p =0.0324; etiologic fraction =0.15) was overrepresented and the DRB1*15 allele group (OR=0.48; p=0.0488; protective fraction=0.19) was underrepresented among household contacts exhibiting tuberculosis. The presence of DRB1 shared alleles between primary cases and their contacts was a risk factor for tuberculosis (p=0.0281). Conclusion This household contact model together with the utilisation of two genetic variables permitted the evaluation of genetic factors contributing towards tuberculosis development.

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Ion channels are pores formed by proteins and responsible for carrying ion fluxes through cellular membranes. The ion channels can assume conformational states thereby controlling ion flow. Physically, the conformational transitions from one state to another are associated with energy barriers between them and are dependent on stimulus, such as, electrical field, ligands, second messengers, etc. Several models have been proposed to describe the kinetics of ion channels. The classical Markovian model assumes that a future transition is independent of the time that the ion channel stayed in a previous state. Others models as the fractal and the chaotic assume that the rate of transitions between the states depend on the time that the ionic channel stayed in a previous state. For the calcium activated potassium channels of Leydig cells the R/S Hurst analysis has indicated that the channels are long-term correlated with a Hurst coefficient H around 0.7, showing a persistent memory in this kinetic. Here, we applied the R/S analysis to the opening and closing dwell time series obtained from simulated data from a chaotic model proposed by L. Liebovitch and T. Toth [J. Theor. Biol. 148, 243 (1991)] and we show that this chaotic model or any model that treats the set of channel openings and closings as independent events is inadequate to describe the long-term correlation (memory) already described for the experimental data. (C) 2008 American Institute of Physics.