766 resultados para clustering users in social network


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To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.

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Praticas na midia social se refere a vista ou a percepcao de uma marca nao so com base em suas ofertas e servicos, mas tambem sobre seus valores e cultura como percebido principalmente pelos consumidores. As organizacoes podem utilizer a imagem que é interessante e aceitavel para os clients. Nos ultimos anos, uma das formas que as organizacoes de forma consistente comercializar ou publicitar a sua marca envolve midias sociais. O ojetivo deste estudo é explorer quais sao as praticas de midia social no negocio de educacao de viagens. Para obter os dados, a pesquisadora entrevistou pessoas de seis empresas de educacao de viagens e cotejadas informacoes sobre o tema a partir de fonts primarias e secundarias existentes. O pesquisador conduziu a pesquisa para determiner praticas de marketing de midia social em que se aplicam nos sectores do turismo e educacao. Com base nos dados obtidos pelo pesquisador, as praticas de marketing de midia social incluem a utilizacao de plataformas de midia social com um alcance internacional generalizada tipo Facebook, Twitter, Instagram e YouTube. Outra estratégia é para postar constantemente as atualizações que não são apenas interessante, mas também informativo sobre os produtos e serviços oferecidos por uma marca ou organização. As empresas ou organizações devem também interagir com os clientes ou clientes on-line, a fim de manter os interesses deste último em ofertas e serviços da ex. O envolvimento do cliente é uma das razões por que os clientes optam por seguir as empresas on-line através da mídia social. A pesquisa também revela outras vantagens e benefícios da mídia social que constituem as melhores práticas, tais como a conversão de não-clientes para os clientes, o aumento da presença da mídia para aumentar a popularidade, a comunicação eficaz das metas e objetivos organizacionais, bem como a formação de um bom relacionamento com os clientes. As organizações também podem usar turístico criado conteúdo (TCC) e outros tipos de conteúdo para orientar a tomada de decisão no desenvolvimento do produto gerado pelo usuário.

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The musculature that sustains the stinging organ was studied in three species of social wasps using scanning electron microscopy technique. It were observed some differences among species in which sting autotomy occurs and in which it does not. These differences were related to the diameter,length and position of insertion of these muscles.

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Recent results from our laboratory have shown that 30-bites social conflict in mice produces a high-intensity, short-term analgesia which is attenuated by systemically injected 5-HT1A receptor agonists, such as BAY R 1531 (6-methoxy-4-(di-n-propylamino)-1,3,4,5-tetrahydrobenz(c,d)indole hydrochloride) and gepirone. The present study investigated the effects of these drugs, as well as the 5-HT1A receptor antagonist WAY 100135 (N-tert-butyl-3-(4-(2-methoxyphenyl)piperazine-1-yl)-2-phenylpropanamide) injected into the midbrain periaqueductal gray matter of mice on 30-bites analgesia. Four to five days after guide-cannula implantation, each mouse received microinjection of gepirone (30 nmol/0.2 mu l), BAY R 1531 (10 nmol/0.2 mu l), WAY 100135 (10 nmol/0.2 mu l), saline (0.9% NaCl) or vehicle (saline + 4% Tween 80) 5 min before either an aggressive (30 bites) or a non-aggressive interaction. Nociception was assessed by the tail-flick test made before as well as 1, 5, 10 and 20 min after social interaction. The full 5-HT1A receptor agonist BAY R 1531 blocked, whereas, WAY 100135 and gepirone intensified 30-bites analgesia, Neither non-aggressive interaction, per se, nor the three compounds given after this type of social interaction significantly changed nociception. These results indicate that 5-HT1A receptors in the periaqueductal gray inhibit analgesia induced by social conflict in mice. (C) 1998 Elsevier B.V. B.V.

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The aim of this study is to describe the degree of yeast-colonization in diabetic and hemodialysed-users of dental prostheses. Individuals (306) were examined using an oral rinse technique in order to evaluate the incidence of yeast-carriage, and genotype of C. albicans. Yeasts were isolated from 68.4% (91/133) individual's dental prostheses users. Dental prostheses were found to be a significant factor for the yeast colonization (P < 0.05). Overall, the intensity of carriage was higher in diabetic patients as compared with health and hemodialysed individuals (P < 0.05). The isolation rates were: C. albicans (51.7%), C. parapsilosis (20.9%), C. tropicalis (14.3%), C. glabrata (6.6%), C. krusei (3.3%), C. rugosa (1.1%), and Pichia (Pichia ohmeri, 2.2%). Ready-To-Go RAPD Analysis Beads were used and primer OPJ 6 distinguished the C. albicans isolates found in prostheses users. All the isolates were grouped into 11 RAPD profiles in four main clusters and, the average S (AB) for the entire collection of 47 C. albicans isolates were 0.779 +/- 0.178. Over 85% of isolates had a similarity level higher than or equal to 0.8 reinforcing the idea that the use of dental prostheses, independently of the host's clinical condition, probably provides the necessary conditions for these strains to gain a growth-specific advantage over others.

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This article presents a well-known interior point method (IPM) used to solve problems of linear programming that appear as sub-problems in the solution of the long-term transmission network expansion planning problem. The linear programming problem appears when the transportation model is used, and when there is the intention to solve the planning problem using a constructive heuristic algorithm (CHA), ora branch-and-bound algorithm. This paper shows the application of the IPM in a CHA. A good performance of the IPM was obtained, and then it can be used as tool inside algorithm, used to solve the planning problem. Illustrative tests are shown, using electrical systems known in the specialized literature. (C) 2005 Elsevier B.V. All rights reserved.

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Objective: To evaluate perinatal factors associated with early neonatal death in preterm infants with birth weights (BW) of 400-1,500 g.Methods: A multicenter prospective cohort study of all infants with BW of 400-1,500 g and 23-33 weeks of gestational age (GA), without malformations, who were born alive at eight public university tertiary hospitals in Brazil between June of 2004 and May of 2005. Infants who died within their first 6 days of life were compared with those who did not regarding maternal and neonatal characteristics and morbidity during the first 72 hours of life. Variables associated with the early deaths were identified by stepwise logistic regression.Results: A total of 579 live births met the inclusion criteria. Early deaths occurred in 92 (16%) cases, varying between centers from 5 to 31%, and these differences persisted after controlling for newborn illness severity and mortality risk score (SNAPPE-II). According to the multivariate analysis, the following factors were associated with early intrahospital neonatal deaths: gestational age of 23-27 weeks (odds ratio - OR = 5.0; 95%CI 2.7-9.4), absence of maternal hypertension (OR = 1.9; 95%CI 1.0-3.7), 5th minute Apgar 0-6 (OR = 2.8; 95%CI 1.4-5.4), presence of respiratory distress syndrome (OR = 3.1; 95%CI 1.4-6.6), and network center of birth.Conclusion: Important perinatal factors that are associated with early neonatal deaths in very low birth weight preterm infants can be modified by interventions such as improving fetal vitality at birth and reducing the incidence and severity of respiratory distress syndrome. The heterogeneity of early neonatal rates across the different centers studied indicates that best clinical practices should be identified and disseminated throughout the country.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.