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Com o objetivo de analisar a comunidade de Informática da Educação e suas contribuições e colaborações no cenário nacional, o presente trabalho traz os resultados que foram obtidos a partir de três acervos de grande relevância na área: da RBIE, da RENOTE e do SBIE. A base de dados que foi tomada como ponto de partida contempla 119 edições e 4.497 artigos publicados por 14.680 autores. Para organizar, consolidar e extrair informações relevantes, a partir dessa base, foi utilizado um método de descoberta de conhecimento em bases de dados. Adicionalmente, conceitos de Teoria dos Grafos foram necessários para identificar autores influentes, conforme suas posições estruturais nos grafos obtidos através dos dados das coautorias relatadas nos artigos. A partir das meta-análises consideradas, das estatísticas gerais fornecidas e das análises das redes de colaboração, foram produzidas informações sólidas, que podem ser utilizadas em trabalhos futuros e em diversas vertentes de pesquisa.

This paper introduces two heuristic algorithms for the Maximum-Diameter Clustering Problem (MDCP), based on the Biased Random-Key Genetic Algorithm (BRKGA) and the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristics. This problem consists of finding k clusters that minimize the largest within-cluster distance (diameter) among all clusters. The MDCP is classified as NP-hard and presents increased difficulty when attempting to determine the optimal solution for any instance. The results obtained in the experiments using 50 well-known instances indicate a good performance of proposed heuristics, that outperformed both three algorithms and an integer programming model from the literature.

The problem of finding an optimal sample stratification has been extensively studied in the literature. In this paper, we propose a heuristic optimization method for solving the univariate optimum stratification problem to minimize the sample size for a given precision level. The method is based on the variable neighborhood search metaheuristic, which was combined with an exact method. Numerical experiments were performed over a dataset of 24 instances, and the results of the proposed algorithm were compared with two very well-known methods from the literature. Our results outperformed 94% of the considered cases. Besides, we developed an enumeration algorithm to find the optimal global solution in some populations and scenarios, which enabled us to validate our metaheuristic method. Furthermore, we find that our algorithm obtained the optimal global solutions for the vast majority of the cases.

Com o objetivo de conhecer novas perspectivas em relação ao acervo da Revista TEIAS, em destaque pela alta qualidade de seus trabalhos e de excelência confirmada pelo sistema de avaliação Qualis da CAPES, o trabalho analisa sua comunidade por meio das redes de colaborações e contribuições. Criada no ano 2000 com foco na área de conhecimento Educação, em seu 21º ano de atuação superou a marca de 1.000 artigos publicados por mais de 1.300 autores. Para a realização das meta-análises foi considerado o processo de Descoberta de Conhecimento em Bases de Dados e conceitos de Teoria dos Grafos. Os resultados obtidos possuem estatísticas gerais, análises das redes de colaboração, termos em destaque ao passar dos anos e autores considerados influentes com base em sua frequência de publicação na revista, pela quantidade de autores com quem colaboram bem como por meio do uso da medida de centralidade por intermediação. Assim, o presente trabalho fornece informações e análises importantes, que podem ser consideradas em outras pesquisas e apoiam interpretações, perspectivas e contribuições deste importante acervo.

The dissemination of microdata by public institutions, especially National Statistical Offices (NSOs), and data sharing between public and private organizations and the academia are of undeniable importance today. However, very important ethical and legal aspects related to privacy protection, whether for an individual or a company, often restrict this cooperation. In this sense, the methods of Statistical Disclosure Control (SDC), or, more specifically, microaggregation techniques, offer an alternative to enable the dissemination and sharing of microdata through the control of disclosure risk. In this article, we propose a new heuristic method that adopts concepts from Biased Random Key Genetic Algorithm (BRKGA) metaheuristic and present a comparative study with well-known microaggregation methods. Computational simulations show that the proposed method consistently outperforms other methods in terms of simultaneously reducing information loss and disclosure risk. In addition, the proposed method allows the adopting or even combining of any information loss and disclosure risk metrics. This feature delivers great flexibility and much more control to the privacy protection process.

Para a realização de meta-análises do acervo da Revista Produção Online foram considerados o processo de Descoberta de Conhecimento em Bases de Dados e conceitos de Teoria dos Grafos. Os resultados obtidos possuem estatísticas gerais, análises das redes de colaboração, termos em destaque por meio do uso de mineração de texto e a identificação de autores considerados influentes, com base em frequência de publicação, e nas medidas de centralidade em grafos. O objetivo do trabalho é apresentar um panorama geral e de contribuições da revista, de maneira impessoal, apolítica e restrita a dados públicos. Os resultados obtidos apoiam interpretações, perspectivas e saberes deste importante acervo.

Heuristics denote a powerful concept, covering a wide range of computational, economic, and psychological sciences, as the ability to handle challenging problems with minimal resources. From a computational perspective, heuristics are commonly used in decision making - when vast amounts of information are available in complex environments - or even when dealing with intractable problems. Through shortcuts and tricks, they can produce acceptable solutions even with few resources compared to exhaustive approaches. Although found on many practical applications, their rich interdisciplinary history is not commonly explored in literature. This paper presents a recent and comprehensive literature review on the topic of heuristics. We present historical data that emphasizing the growth of this concept in several research fields, since the 1950s, and the authors' perspective on future directions. This history is told with a timeline as background, highlighting from the bounded rationality to computational intractability.

Over the last decades, many researchers have studied and proposed new methods for the solution of the multivariate optimal allocation problem, which can be performed by choosing one of the followin...

Os sistemas de apoio à decisão beneficiam-se de padrões ocultos (semi-)extraídos automaticamente de grandes bases de dados. No domínio específico da caracterização de gastrópodes, dados e medidas morfológicas podem apoiar os biólogos na identificação de caramujos terrestres. Embora lesmas e caramujos possam ser facilmente identificados por seus sistemas excretório e reprodutivo, o corpo do molusco é comumente inacessível por causa da deterioração do material macio ou da fossilização da concha. O presente artigo tem, como objetivo, investigar a performance de um classificador baseado em instâncias, quando aplicado sobre um conjunto de dados com características morfológicas de conchas de caracóis terrestres. Avaliações experimentais indicam que um método proposto alcançou acurácia superior a 99% na identificação de espécies de caramujos.

O Pensamento Computacional já é considerado uma das habilidades intelectuais básicas do humano, sendo comparado à leitura e capacidade de realizar operações aritméticas, e a influência do “mundo digital” no cotidiano já está presente na Lei de Diretrizes e Bases da Educação Nacional (LDB). Nesse sentido, o uso de ferramentas educacionais, como Objetos de Aprendizagem (OA), que promovam desenvolvimento cognitivo necessário à construção desse conhecimento e suas associações, são de suma importância. O presente trabalho apresenta uma revisão da literatura sobre OA relacionados à Computabilidade, tendo por base a análise de mais de 15,5 mil artigos de acervos importantes relacionados. Nesta revisão foram identificadas lacunas no cenário nacional quanto à temática, em especial para a Educação Básica.

Cluster Analysis is a multivariate method to handle real problems associated with several fields. This area combines several methods of unsupervised classification, which can be applied in order to identify groups in a data set. The Clustering Problems are classified as NP-Hard and, in order to obtain such classification, the number of groups k may be fixed or, in the Automatic approach, the ideal k must be identified upon evaluation of some validation index. In this paper the Silhouette Index was considered and a new proposed Hybrid Heuristic Algorithm (HHA) operates to identify the ideal number of groups. The HHA consider two heuristic algorithms based on metaheuristics: an algorithm based on Iterated Local Search (ILS) that considers a density-based approach and a literature Evolutionary Algorithm (EA). Besides, the HHA have a heuristic algorithm that verify clustering tendency, considering the Hopkins Statistic. Basically, according with the clustering tendency level, the HHA use a specific heuristic (ILS or EA). The computational experiments used three literature data sets with eighty-two instances, and all of them were considered and reported by different researchers. The effectiveness and the efficiency of the proposed heuristic are reflected in substantially lower computational time and in the solutions quality, that are competitive when compared with the best results reported in the literature.

The Sonic Hedgehog signaling (Shh) pathway has been implicated in both proliferation of myoblast cells and terminal differentiation of muscle fibers, and contradictory results of these effects have been described. To clarify the role of Shh during myogenesis, we decided to study the effects of recombinant Shh and the distribution of Gli-1 during in vitro and in situ embryonic chick skeletal muscle differentiation at later stages of development. Gli-1 was found in small aggregates near the nucleus in mononucleated myoblasts and in multinucleated myotubes both in vitro and in situ chick muscle cells. Some Gli-1 aggregates colocalized with gamma-tubulin positive-centrosomes. Gli-1 was also found in striations and at the subsarcolemmal membrane in muscle fibers in situ. Recombinant Shh added to in vitro grown muscle cells induced the nuclear translocation of Gli-1, as well as an increase in the number of myoblasts and in the number of nuclei within myotubes. We suggest that Gli-1 aggregates observed in chick muscle cells near the nuclei of myoblasts and myotubes could be a storage site for the rapid cellular redistribution of Gli-1 upon specific signals during muscle differentiation.

O presente trabalho apresenta um panorama geral das contribuições e das redesde colaboração criadas por esta importante revista na área de educação e informática, em comemoração à sua 40ª edição, publicada em 2019. Para tanto, foram considerados os processos de descoberta de conhecimento em bases de dados, a tarefa de mineração de textos, métodos de análises de dados e conceitos de teoria de grafos. A base de dados utilizada possui informações referentes a todos os dados bibliográficos da RENOTE (17 anos), e é formada por 1.866 artigos, 3.052 autores e a colaboração entre seus pares. Tratase de uma apresentação neutra, restrita aos dados disponíveis, que visa fomentar a importância do tema no cenário acadêmico.

The lymphatic system associated with the central nervous system (CNS) includes the lymphatic vasculature that spins around the brain, the spinal cord, and its associated LNs. The CNS-associated lymphatic system is involved in the drainage of CSF macromolecules and meningeal immune cells toward CNS-draining LNs, thereby regulating waste clearance and immune surveillance within CNS tissues. Presented is a novel approach to obtain three-dimensional (3D) and cellular resolution images of CNS-associated lymphatics while preserving the integrity of their circuits within surrounding tissues. The iDISCO+ protocol is used to immunolabel lymphatic vessels in decalcified and cleared whole mount preparations of the vertebral column that are subsequently imaged with light sheet fluorescence microscopy (LSFM). The technique reveals the 3D structure of the lymphatic network connecting the meningeal and epidural spaces around the spinal cord to extravertebral lymphatic vessels. Provided are 3D images of the drainage circuits of molecular tracers previously injected into either the CSF via the cisterna magna or the thoracolumbar spinal parenchyma. The iDISCO+/LSFM approach brings unprecedented opportunities to explore the structure and function of the CNS-associated lymphatic system in neurovascular biology, neuroimmunology, brain and vertebral cancer, or vertebral bone and joint biology.

Lysosomes and acidic compartments are involved in breaking down of macromolecules, membrane recycling, and regulation of signaling pathways. Here, we analyzed the role of acidic compartments during muscle differentiation and the involvement of the Wnt/beta-catenin pathway in lysosomal function during myogenesis. Acridine orange was used to localize and quantify acidic cellular compartments in primary cultures of embryonic muscle cells from Gallus gallus. Our results show an increase in acidic compartment size and area, as well as changes in their positioning during the initial steps of myogenesis. The inhibition of lysosomal function by either the chloroquine Lys05 or the downregulation of LAMP-2 with siRNA impaired chick myogenesis, by inhibiting myoblast fusion. Two activators of the Wnt/beta-catenin pathway, BIO and Wnt3a, were able to rescue the inhibitory effects of Lys05 in myogenesis. These results suggest a new role for the Wnt/beta-catenin pathway in the regulation of acidic compartment size, positioning, and function in muscle cells.

A new optimization algorithm is presented to solve the stratification problem. Assuming the number L of strata and the total sample size n are fixed, we obtain strata boundaries by using an objective function associated with the variance. In this problem, strata boundaries must be determined so that the elements in each stratum are more homogeneous among themselves. To produce more homogeneous strata, this paper proposes a new algorithm that uses the Greedy Randomized Adaptive Search Procedure (GRASP) methodology. Computational results are presented for a set of problems, with the application of the new algorithm and some algorithms from literature.

This article presents a new algorithm to optimize the multivariate optimal allocation problem. Many researchers have studied and proposed new methods for the solution this problem, which can be performed by choosing one of the following goals: (i) minimizing the weighted combination of relative variances, considering the sample size fixed or (ii) minimizing the sample size in a way that the coefficients of variation are lower or equal to the previously fixed coefficients of variation. The proposed algorithm is based on a nonlinear optimization method denoted hyperbolic penalty. Results obtained for real populations show that the algorithm is a good alternative to solve this problem.

Human adipose-derived stromal cells (hADSC) are a heterogeneous cell population that contains adult multipotent stem cells. Although it is well established that hADSC have skeletal potential in vivo in adult organisms, in vitro assays suggest further differentiation capacity, such as into glia. Thus, we propose that grafting hADSC into the embryo can provide them with a much more instructive microenvironment, allowing the human cells to adopt diverse fates or niches. Here, hADSC spheroids were grafted into either the presumptive presomitic mesoderm or the first branchial arch (BA1) regions of chick embryos. Cells were identified without previous manipulations via human-specific Alu probes, which allows efficient long-term tracing of heterogeneous primary cultures. When grafted into the trunk, in contrast to previous studies, hADSC were not found in chondrogenic or osteogenic territories up to E8. Surprisingly, 82.5% of the hADSC were associated with HNK1+ tissues, such as peripheral nerves. Human skin fibroblasts showed a smaller tropism for nerves. In line with other studies, hADSC also adopted perivascular locations. When grafted into the presumptive BA1, 74.6% of the cells were in the outflow tract, the final goal of cardiac neural crest cells, and were also associated with peripheral nerves. This is the first study showing that hADSC could adopt a perineural niche in vivo and were able to recognize cues for neural crest cell migration of the host. Therefore, we propose that xenografts of human cells into chick embryos can reveal novel behaviors of heterogeneous cell populations, such as response to migration cues.

We propose algorithmic frameworks based on the iterated local search (ILS) metaheuristic to obtain good-quality solutions for the Euclidean Steiner tree problem (ESTP) in n dimensions. This problem consists in finding a tree with minimal total length that spans p points given in an n-dimensional Euclidean space and, eventually, also some additional points whose insertion contributes to reduce the total length of the tree. These ILS approaches make use of both the tree enumeration structure, called topology-describing vector, and the exact minimization step of a well-known branch-and-bound method for the ESTP. Computational results are provided.

Tiki1 is a Wnt protease and antagonist specifically expressed in the Spemann-Mangold Organizer and is required for head formation in Xenopus embryos. Here we report neighbor-joining phylogenetic analysis of vertebrate Tiki genes and their mRNA expression patterns in chick, mouse, and rabbit embryos. Tiki1 and Tiki2 orthologues are highly conserved, and exhibit similar but also different developmental expression patterns among the vertebrate/mammalian species analyzed. The Tiki1 gene is noticeably absent in the rodent lineage, but is present in lagomorphs and all other vertebrate/mammalian species examined. Expression in Hensen's node, the equivalent of the Xenopus Organizer, was observed for Chick Tiki2 and Rabbit Tiki1 and Tiki2. Mouse Tiki2 was detected at low levels at gastrulation and head fold stages, but not in the node. Mouse Tiki2 and chick Tiki1 display similar expression in the dorsal spinal cord. Chick Tiki1 expression was also detected in the surface ectoderm and maxillary bud, while chick Tiki2 was found in the anterior intestinal portal, head mesenchyme and primitive atrium. Our expression analyses provide evidence that Tiki1 and Tiki2 are evolutionarily conserved among vertebrate species and their expression in the Organizer and other regions suggests contributions of these Wnt inhibitors to embryonic patterning, as well as organogenesis. Our analyses further reveal mis-regulation of TIKI1 and TIKI2 in human cancer and diseases.

O presente trabalho traz um estudo do problema de detecção de comunidades associadas às redes complexas, ou seja, redes formadas por elementos do mundo real. De forma a realizar esse estudo, as redes foram representadas por uma estrutura matemática denominada grafo. E de forma a detectar as comunidades nessas redes, aplicou-se um algoritmo de detecção de comunidades no grafo associado. Em particular, neste trabalho, optou-se pela utilização de um algoritmo de detecção de comunidades, denominado FastGreedy. Uma vez definida a comunidade, em uma segunda fase do estudo, foi aplicado um algoritmo de agrupamento (K-means) em cada um dos grafos, considerando o número de grupos igual ao número de comunidades. A comunidade definida e os agrupamentos construídos foram avaliados a posteriori mediante o cálculo da modularidade e do coeficiente de silhueta. Ao final desse trabalho, são apresentados alguns resultados computacionais concernentes à aplicação desses algoritmos, disponíveis no software livre R, considerando três bases reais. This paper presents a study of the problem of detecting communities associated with complex networks, this is, networks comprising elements of the real world. In order to perform this study, networks were represented by a mathematical structure called graph. And, in order to detect the communities these networks was applied to an algorithm for detecting communities in associated graph. In particular, in this work, we opted for the use of a community detection algorithm, called FastGreedy. Once defined the community, in a second phase of the study, we applied a clustering algorithm (K-means) in each of the graphs, groups considering the number equal to the number of communities. The community defined and constructed clusters were evaluated retrospectively by calculating the coefficient of modularity and silhouette. At the end of this work are presented some results concerning the application of these computational algorithms available in the free software R, considering three real bases.Keywords: Graphs; Communities; Algorithms.

Stratified sampling is a technique that consists in separating the elements of a population into nonoverlapping groups, called strata. This paper describes a new algorithm to solve the one-dimensional case, which reduces the stratification problem to just determining strata boundaries. Assuming that the number L of strata and the total sample size n are predetermined, we obtain the strata boundaries by taking into consideration an objective function associated with the variance. In order to solve this problem, we have implemented an algorithm based on the iterative local search metaheuristic. Computational results obtained from a real data set are presented and discussed.

We report a new optimal resolution for the statistical stratification problem under proportional sampling allocation among strata. Consider a finite population of N units, a random sample of n units selected from this population and a number L of strata. Thus, we have to define which units belong to each stratum so as to minimize the variance of a total estimator for one desired variable of interest in each stratum, and consequently reduce the overall variance for such quantity. In order to solve this problem, an optimal algorithm based on the concept of minimal path in a graph is proposed and assessed. Computational results using real data from IBGE (Brazilian Central Statistical Office) are provided.

We characterized cerebral Oil Red O-positive lipid-laden cells (LLC) of aging mice evaluating their distribution, morphology, density, functional activities and inflammatory phenotype. We identified LLC in meningeal, cortical and neurogenic brain regions. The density of cerebral LLC increased with age. LLC presenting small lipid droplets were visualized adjacent to blood vessels or deeper in the brain cortical and striatal parenchyma of aging mice. LLC with larger droplets were asymmetrically distributed in the cerebral ventricle walls, mainly located in the lateral wall. We also found that LLC in the subventricular region co-expressed beclin-1 or LC3, markers for autophagosome or autophagolysosome formation and perilipin (PLIN), a lipid droplet-associated protein, suggesting lipophagic activity. Some cerebral LLC exhibited β galactosidase activity indicating a senescence phenotype. Moreover, we detected production of the pro-inflammatory cytokine TNF-α in cortical PLIN+ LLC. Some cortical NeuN+ neurons, GFAP+ glia limitans astrocytes, Iba-1+ microglia and S100β+ ependymal cells expressed PLIN in the aging brain. Our findings suggest that cerebral LLC exhibit distinct cellular phenotypes and may participate in the age-associated neuroinflammatory processes.

We present an exact method for integer linear programming problems that combines branch and bound with column generation at each node of the search tree. For the case of models involving binary column vectors only, we propose the use of so-called geometrical cuts to be added to the subproblem in order to eliminate previously generated columns. This scheme could be applied to general integer problems without specific structure. We report computational results on a successful application of this approach to a telecommunications network planning problem.

The cluster analysis has several methods that aim to identify groups within a dataset. This paper presents a new method for the automatic clustering problem based on both Density and Grid methodologies. The goal of the new method is identify the ideal number of clusters given a dataset by the maximization of Silhouette Index. According the computational experiments, the use of this method is a new promising way to solve the problem.

Galectin-3 is a β-galactoside-binding protein with an inhibitory role in B cell differentiation into plasma cells in distinct lymphoid tissues. We use a model of chronic schistosomiasis, a well-characterized experimental disease hallmarked by polyclonal B cell activation, in order to investigate the role of galectin-3 in controlling IgA production through peritoneal B1 cells. Chronically infected, galectin-3-deficient mice (Lgals3 −/−) display peritoneal fluid hypercellularity, increased numbers of atypical peritoneal IgM+/IgA+ B1a and B1b lymphocytes and histological disturbances in plasma cell niches when compared with Lgals3 +/+ mice. Similar to our infection model, peritoneal B1 cells from uninfected Lgals3 −/− mice show enhanced switching to IgA after in vitro treatment with interleukin-5 plus transforming growth factor-β (IL-5 + TGF-β1). A higher number of IgA+ B1a lymphocytes was found in the peritoneal cavity of Lgals3 −/−-uninfected mice at 1 week after i.p. injection of IL-5 + TGF-β1; this correlates with the increased levels of secreted IgA detected in the peritoneal fluid of these mice after cytokine treatment. Interestingly, a higher number of degranulated mast cells is present in the peritoneal cavity of uninfected and Schistosoma mansoni-infected Lgals3 −/− mice, indicating that, at least in part, mast cells account for the enhanced differentiation of B1 into IgA-producing B cells found in the absence of galectin-3. Thus, a novel role is revealed for galectin-3 in controlling the expression of surface IgA by peritoneal B1 lymphocytes; this might have important implications for manipulating the mucosal immune response.

Mast cell hyperplasia can be causally related with chronic inflammation and liver fibrosis. Their survival and proliferation is dependent upon locally produced growth factors, the major one being the stem cell factor (SCF). Glucocorticoids can decrease mastocytosis, down-regulating the mast cell production of pro-inflammatory factors or inhibiting the expression of SCF in stroma. We compared dexamethasone effect on SCF expression in co-cultures of mast cells with NIH/3T3 fibroblasts or with primary cultures of activated hepatic stellate cells. Dexamethasone abrogated the NIH/3T3 stroma capacity to sustain mast cell proliferation, but not of hepatic stellate cells, at the post-transcriptional level. Mast cells reverted completely dexamethasone effect on hepatic stellate cells, increasing their SCF synthesis and transport. In both models, dexamethasone inhibited the mast cell spreading on the stroma, which was thus not required for mast cell survival and proliferation. Liver pathologies associated with mast cell hyperplasia are not expected to be sensitive to glucocorticoid treatments.

Glioblastoma (GBM) is one of the most aggressive human cancers. Despite current advances in multimodality therapies, such as surgery, radiotherapy and chemotherapy, the outcome for patients with high grade glioma remains fatal. The knowledge of how glioma cells develop and depend on the tumor environment might open opportunities for new therapies. There is now a growing awareness that the main limitations in understanding and successfully treating GBM might be bypassed by the identification of a distinct cell type that has defining properties of somatic stem cells, as well as cancer-initiating capacity - brain tumor stem cells, which could represent a therapeutic target. In addition, experimental studies have demonstrated that the combination of antiangiogenic therapy, based on the disruption of tumor blood vessels, with conventional chemotherapy generates encouraging results. Emerging reports have also shown that microglial cells can be used as therapeutic vectors to transport genes and/or substances to the tumor site, which opens up new perspectives for the development of GBM therapies targeting microglial cells. Finally, recent studies have shown that natural toxins can be conjugated to drugs that bind to overexpressed receptors in cancer cells, generating targeted-toxins to selectively kill cancer cells. These targeted-toxins are highly effective against radiation- and chemotherapy-resistant cancer cells, making them good candidates for clinical trials in GBM patients. In this review, we discuss recent studies that reveal new possibilities of GBM treatment taking into account cancer stem cells, angiogenesis, microglial cells and drug delivery in the development of new targeted-therapies.