863 resultados para set based design


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Planning is an important sub-field of artificial intelligence (AI) focusing on letting intelligent agents deliberate on the most adequate course of action to attain their goals. Thanks to the recent boost in the number of critical domains and systems which exploit planning for their internal procedures, there is an increasing need for planning systems to become more transparent and trustworthy. Along this line, planning systems are now required to produce not only plans but also explanations about those plans, or the way they were attained. To address this issue, a new research area is emerging in the AI panorama: eXplainable AI (XAI), within which explainable planning (XAIP) is a pivotal sub-field. As a recent domain, XAIP is far from mature. No consensus has been reached in the literature about what explanations are, how they should be computed, and what they should explain in the first place. Furthermore, existing contributions are mostly theoretical, and software implementations are rarely more than preliminary. To overcome such issues, in this thesis we design an explainable planning framework bridging the gap between theoretical contributions from literature and software implementations. More precisely, taking inspiration from the state of the art, we develop a formal model for XAIP, and the software tool enabling its practical exploitation. Accordingly, the contribution of this thesis is four-folded. First, we review the state of the art of XAIP, supplying an outline of its most significant contributions from the literature. We then generalise the aforementioned contributions into a unified model for XAIP, aimed at supporting model-based contrastive explanations. Next, we design and implement an algorithm-agnostic library for XAIP based on our model. Finally, we validate our library from a technological perspective, via an extensive testing suite. Furthermore, we assess its performance and usability through a set of benchmarks and end-to-end examples.

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High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

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Garlic is a spice and a medicinal plant; hence, there is an increasing interest in 'developing' new varieties with different culinary properties or with high content of nutraceutical compounds. Phenotypic traits and dominant molecular markers are predominantly used to evaluate the genetic diversity of garlic clones. However, 24 SSR markers (codominant) specific for garlic are available in the literature, fostering germplasm researches. In this study, we genotyped 130 garlic accessions from Brazil and abroad using 17 polymorphic SSR markers to assess the genetic diversity and structure. This is the first attempt to evaluate a large set of accessions maintained by Brazilian institutions. A high level of redundancy was detected in the collection (50 % of the accessions represented eight haplotypes). However, non-redundant accessions presented high genetic diversity. We detected on average five alleles per locus, Shannon index of 1.2, HO of 0.5, and HE of 0.6. A core collection was set with 17 accessions, covering 100 % of the alleles with minimum redundancy. Overall FST and D values indicate a strong genetic structure within accessions. Two major groups identified by both model-based (Bayesian approach) and hierarchical clustering (UPGMA dendrogram) techniques were coherent with the classification of accessions according to maturity time (growth cycle): early-late and midseason accessions. Assessing genetic diversity and structure of garlic collections is the first step towards an efficient management and conservation of accessions in genebanks, as well as to advance future genetic studies and improvement of garlic worldwide.

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Herein we describe the synthesis of a focused library of compounds based on the structure of goniothalamin (1) and the evaluation of the potential antitumor activity of the compounds. N-Acylation of aza-goniothalamin (2) restored the in vitro antiproliferative activity of this family of compounds. 1-(E)-But-2-enoyl-6-styryl-5,6-dihydropyridin-2(1H)-one (18) displayed enhanced antiproliferative activity. Both goniothalamin (1) and derivative 18 led to reactive oxygen species generation in PC-3 cells, which was probably a signal for caspase-dependent apoptosis. Treatment with derivative 18 promoted Annexin V/7-aminoactinomycin D double staining, which indicated apoptosis, and also led to G2 /M cell-cycle arrest. In vivo studies in Ehrlich ascitic and solid tumor models confirmed the antitumor activity of goniothalamin (1), without signs of toxicity. However, derivative 18 exhibited an unexpectedly lower in vivo antitumor activity, despite the treatments being administered at the same site of inoculation. Contrary to its in vitro profile, aza-goniothalamin (2) inhibited Ehrlich tumor growth, both on the ascitic and solid forms. Our findings highlight the importance of in vivo studies in the search for new candidates for cancer treatment.

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To determine the prevalence of the Papanicolaou exam among women aged 20 to 59 years in the city of Campinas (state of São Paulo, Brazil) and to analyze associations between this test and affiliation to private health insurance plans as well as socioeconomic/demographic variables and health-related behavior. To do so, a population-based, cross-sectional study was carried out. Statistical analyses took the study design into account. Despite the significant socioeconomic differences between women with and without private health plans, no differences between these groups were found regarding having been submitted to the Papanicolaou test. In fact no differences were found as to socioeconomic and health variables analyzed. Among all variables analyzed, only marital status was significantly associated with having undergone the test. The Brazilian public health system accounted for 55.7% of the exams. The present findings indicate social equity in the city of Campinas regarding the preventive exam for cervical cancer in the age group studied.

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Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

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Evolving interfaces were initially focused on solutions to scientific problems in Fluid Dynamics. With the advent of the more robust modeling provided by Level Set method, their original boundaries of applicability were extended. Specifically to the Geometric Modeling area, works published until then, relating Level Set to tridimensional surface reconstruction, centered themselves on reconstruction from a data cloud dispersed in space; the approach based on parallel planar slices transversal to the object to be reconstructed is still incipient. Based on this fact, the present work proposes to analyse the feasibility of Level Set to tridimensional reconstruction, offering a methodology that simultaneously integrates the proved efficient ideas already published about such approximation and the proposals to process the inherent limitations of the method not satisfactorily treated yet, in particular the excessive smoothing of fine characteristics of contours evolving under Level Set. In relation to this, the application of the variant Particle Level Set is suggested as a solution, for its intrinsic proved capability to preserve mass of dynamic fronts. At the end, synthetic and real data sets are used to evaluate the presented tridimensional surface reconstruction methodology qualitatively.

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Evolving interfaces were initially focused on solutions to scientific problems in Fluid Dynamics. With the advent of the more robust modeling provided by Level Set method, their original boundaries of applicability were extended. Specifically to the Geometric Modeling area, works published until then, relating Level Set to tridimensional surface reconstruction, centered themselves on reconstruction from a data cloud dispersed in space; the approach based on parallel planar slices transversal to the object to be reconstructed is still incipient. Based on this fact, the present work proposes to analyse the feasibility of Level Set to tridimensional reconstruction, offering a methodology that simultaneously integrates the proved efficient ideas already published about such approximation and the proposals to process the inherent limitations of the method not satisfactorily treated yet, in particular the excessive smoothing of fine characteristics of contours evolving under Level Set. In relation to this, the application of the variant Particle Level Set is suggested as a solution, for its intrinsic proved capability to preserve mass of dynamic fronts. At the end, synthetic and real data sets are used to evaluate the presented tridimensional surface reconstruction methodology qualitatively.

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The enzyme purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) is an attractive molecular target for the treatment of major parasitic infectious diseases, with special emphasis on its role in the discovery of new drugs against schistosomiasis, a tropical disease that affects millions of people worldwide. In the present work, we have determined the inhibitory potency and developed descriptor- and fragment-based quantitative structure-activity relationships (QSAR) for a series of 9-deazaguanine analogs as inhibitors of SmPNP. Significant statistical parameters (descriptor-based model: r² = 0.79, q² = 0.62, r²pred = 0.52; and fragment-based model: r² = 0.95, q² = 0.81, r²pred = 0.80) were obtained, indicating the potential of the models for untested compounds. The fragment-based model was then used to predict the inhibitory potency of a test set of compounds, and the predicted values are in good agreement with the experimental results

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Although the rio Capivari basin is recognized as an area of great importance for the ichthyofauna, it lacks virtually every basic requirement for the definition of appropriate conservation strategies, since not even its species composition is known. The objective of this work is to determine the composition and distribution of fish species in the upper rio Capivari basin, relating them to the local physical features, and to evaluate the effectiveness of proposed conservations units, delimited based on areas of native vegetation remains, on the conservation of local ichthyofauna. During 2007, 50 different watercourses were sampled with gillnets, cast nets and kick nets. A total of 1308 individuals belonging to 41 species were captured. Degree of conservation, altitude and width were the parameters that best explained fish species richness. Considering the recently proposed boundaries for potential conservation units in the region only 15 or 20 out of 41 species would be found in the State Park and Environmental Protection Area respectively. In practice, the proposed conservation units would not be effective tools for fish conservation, since it would be located in mountainous areas of high altitude, of headwaters streams and where few species are found. In such context, the conservation of specific stretches of larger rivers is critical.

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Este artigo apresenta o projeto museográfico da exposição Cartografia de uma história, inaugurada no Museu Paulista da Universidade de São Paulo em março de 2005. O projeto museográfico foi concebido e elaborado a partir do diálogo entre as propostas da equipe de pesquisa e os dados do perfil dos visitantes do Museu, constituindo-se assim um trabalho integrado, que buscava tratar de forma lúdica o ato de descobrir.

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Objective: The biochemical alterations between inflammatory fibrous hyperplasia (IFH) and normal tissues of buccal mucosa were probed by using the FT-Raman spectroscopy technique. The aim was to find the minimal set of Raman bands that would furnish the best discrimination. Background: Raman-based optical biopsy is a widely recognized potential technique for noninvasive real-time diagnosis. However, few studies had been devoted to the discrimination of very common subtle or early pathologic states as inflammatory processes that are always present on, for example, cancer lesion borders. Methods: Seventy spectra of IFH from 14 patients were compared with 30 spectra of normal tissues from six patients. The statistical analysis was performed with principal components analysis and soft independent modeling class analogy cross-validated, leave-one-out methods. Results: Bands close to 574, 1,100, 1,250 to 1,350, and 1,500 cm(-1) (mainly amino acids and collagen bands) showed the main intragroup variations that are due to the acanthosis process in the IFH epithelium. The 1,200 (C-C aromatic/DNA), 1,350 (CH(2) bending/collagen 1), and 1,730 cm(-1) (collagen III) regions presented the main intergroup variations. This finding was interpreted as originating in an extracellular matrix-degeneration process occurring in the inflammatory tissues. The statistical analysis results indicated that the best discrimination capability (sensitivity of 95% and specificity of 100%) was found by using the 530-580 cm(-1) spectral region. Conclusions: The existence of this narrow spectral window enabling normal and inflammatory diagnosis also had useful implications for an in vivo dispersive Raman setup for clinical applications.

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Natural products have widespread biological activities, including inhibition of mitochondrial enzyme systems. Some of these activities, for example cytotoxicity, may be the result of alteration of cellular bioenergetics. Based on previous computer-aided drug design (CADD) studies and considering reported data on structure-activity relationships (SAR), an assumption regarding the mechanism of action of natural products against parasitic infections involves the NADH-oxidase inhibition. In this study, chemometric tools, such as: Principal Component Analysis (PCA), Consensus PCA (CPCA), and partial least squares regression (PLS), were applied to a set of forty natural compounds, acting as NADH-oxidase inhibitors. The calculations were performed using the VolSurf+ program. The formalisms employed generated good exploratory and predictive results. The independent variables or descriptors having a hydrophobic profile were strongly correlated to the biological data.

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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: Silica particles cationized by dioctadecyldimethylammonium bromide (DODAB) bilayer were previously described. This work shows the efficiency of these particulates for antigen adsorption and presentation to the immune system and proves the concept that silica-based cationic bilayers exhibit better performance than alum regarding colloid stability and cellular immune responses for vaccine design. Results: Firstly, the silica/DODAB assembly was characterized at 1 mM NaCl, pH 6.3 or 5 mM Tris. HCl, pH 7.4 and 0.1 mg/ml silica over a range of DODAB concentrations (0.001-1 mM) by means of dynamic light scattering for particle sizing and zeta-potential analysis. 0.05 mM DODAB is enough to produce cationic bilayer-covered particles with good colloid stability. Secondly, conditions for maximal adsorption of bovine serum albumin (BSA) or a recombinant, heat-shock protein from Mycobacterium leprae (18 kDa-hsp) onto DODAB-covered or onto bare silica were determined. At maximal antigen adsorption, cellular immune responses in vivo from delayed-type hypersensitivity reactions determined by foot-pad swelling tests (DTH) and cytokines analysis evidenced the superior performance of the silica/DODAB adjuvant as compared to alum or antigens alone whereas humoral response from IgG in serum was equal to the one elicited by alum as adjuvant. Conclusion: Cationized silica is a biocompatible, inexpensive, easily prepared and possibly general immunoadjuvant for antigen presentation which displays higher colloid stability than alum, better performance regarding cellular immune responses and employs very low, micromolar doses of cationic and toxic synthetic lipid.