Influence of thermal parameters on the dendritic arm spacing and the microhardness of Al-5.5wt.%Sn alloy directionally solidified

As ligas Al-Sn são amplamente utilizados em aplicações tribológicas. Nesse estudo, análises térmica, microestrutural e dureza (HV) foram realizadas ao longo de um lingote da liga Al-5,5%Sn, obtido por solidificação direcional horizontal transitória. Os principais parâmetros analisados incluem a velocidade de deslocamento da isoterma liquidus (V_L) e a taxa de resfriamento (T_R). Esses parâmetros térmicos desempenham um papel fundamental na formação da microestrutura. A microestrutura dendrítica foi caracterizada através dos espaçamentos dentríticos primários (λ₁), os quais foram determinados, experimentalmente, e correlacionados com V_L, e T_R. O comportamento apresentado pela liga Al- 5,5% Sn, durante a solidificação,é semelhante ao de outras ligas de alumínio, isto é, observa-se rede dendrítica mais grosseira com a diminuição da taxa de resfriamento, indicando que a imiscibilidade entre o alumínio e estanho não tem um efeito significativo sobre o relação entre o espaçamento dendrítico primário e taxa de resfriamento. A dependência da microdureza em V_L, T_R e no λ₁ foi também analisada. Verificaram-se menores valores de HV para maiores T_R. Por outro lado, os valores HV aumentam com valores crescentes de λ₁.

Service Utilization Patterns of Homeless Youth

Few studies exist on the types of characteristics associated with service utilization (e.g., shelters, food programs) among homeless youth in the U.S. Services are important, however, because without food and shelter, numerous homeless youth resort to trading sex in order to meet their daily survival needs. Access to physical and mental health services gives homeless youth more of an opportunity to integrate into mainstream society than they would otherwise have. To address this gap in our understanding, my study examines what traits (e.g. age, race, abuse history) correlate with the use of shelters, food programs, street outreach, counseling, STD/STI testing, and HIV testing among homeless youth. The Theory of Reasoned Action is used as an ideological framework in conjunction with theoretical constructs of risk, need, and prior service exposure. Data were obtained from the Social Network and Homeless Youth Project (SNHYP), a sample of 249 Midwestern homeless youth ages 14 to 21, which used trained interviewers to conduct structured interviews with youth. Respondents were interviewed in both shelters and on the street over a period of approximately one year. My findings revealed that homeless youth’s service usage varied across gender, sexual orientation, age, having recently held a job, and having ever been physically or sexually abused, in addition to other characteristics. Conversely, service use was not associated with social network size or subjective norms (i.e. attitudes of peers, such as acceptance of condom use) of youths’ social networks. By examining these areas, my study builds on previous research on homeless youth and lays the framework for future research on service utilization by homeless youth.

Information Acceptance and ICT Resistance: Promoting the Role of Information in Rural Community Development

Rural community development is a major issue for developing countries. Much attention has been given Information and Communication Technology (ICT) projects to connect rural communities with the global network. However, ICT resistance is a deterring factor in addressing the digital divide in developing countries. It is postulated that reversing the resistance to to ICT can be strategizedthrough "information acceptance." ICT can be accepted by rural communities by creating demand for information. The paper calls for the refocusing on the role of information in rural community development and ICT as a tool for change agent. Initiatives for rural community development must emphasize the importance of information in rural communities.

Predicting epidemic outbreak from individual features of the spreaders

Knowing which individuals can be more efficient in spreading a pathogen throughout a determinate environment is a fundamental question in disease control. Indeed, over recent years the spread of epidemic diseases and its relationship with the topology of the involved system have been a recurrent topic in complex network theory, taking into account both network models and real-world data. In this paper we explore possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible-infected-recovered (SIR) model, and several attributes of the originating vertices, considering Erdos-Renyi (ER), Barabasi-Albert (BA) and random geometric graphs (RGG), as well as a real case study, the US air transportation network, which comprises the 500 busiest airports in the US along with inter-connections. Initially, the heterogeneity of the spreading is achieved by considering the RGG networks, in which we analytically derive an expression for the distribution of the spreading rates among the established contacts, by assuming that such rates decay exponentially with the distance that separates the individuals. Such a distribution is also considered for the ER and BA models, where we observe topological effects on the correlations. In the case of the airport network, the spreading rates are empirically defined, assumed to be directly proportional to the seat availability. Among both the theoretical and real networks considered, we observe a high correlation between the total epidemic prevalence and the degree, as well as the strength and the accessibility of the epidemic sources. For attributes such as the betweenness centrality and the k-shell index, however, the correlation depends on the topology considered.

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

JOB SATISFACTION: A QUALITY INDICATOR IN NURSING HUMAN RESOURCE MANAGEMENT

This descriptive study addresses the job satisfaction of nurse managers and clinical nurses working at the Hematology and Hemotherapy Services of a public hospital in Sao Paulo. The study objectives were to identify the factors that caused job satisfaction among nurse managers and clinical nurses, and support the results in the development of indicators to evaluate the quality of nursing human resource management. The components of the study were: autonomy, interaction, professional status, job requirements, organizational norms and remuneration. Participants were 44 nurses. Data were collected using a Job Satisfaction Index (JSI) questionnaire. In conclusion, this study permitted the identification of the clinical nurse group, which was the most satisfied, with a JSI of 10.5; the managerial group scored 10.0. Regarding the satisfaction levels in regards to the current activity, 88.9% of the nurse managers reported feeling satisfied, as did 90.9% of clinical nurses. For both groups, autonomy was the component with the highest level of professional satisfaction.

THE CONQUEST OF CENTRAL BRAZIL: FRONTIERS AND FRONTS PIONEERING IN THE NINETEENTH CENTURY

The process of territorial formation in Brazil is examined in this paper in order to establish, through a study that favors more interior region of Portuguese America, a suitable analytical arsenal geohistorica an interpretation of the built legacy of colonial Lusitanian action on American soil. Thus, it is expected to recover some aspects not yet addressed conclusively by the specialized literature, the importance of colonial territorial nexus in the construction and maintenance of the substrate material on which the new politically independent state would claim jurisdiction after 1822. Through the examination of so-called western border, articulated through the contacts held between the cities network of Goias and the strong, prisons, villages and towns planned in Mato Grosso, outline an interpretation of regional dynamics in the moments preceding the running of the Brazilian political emancipation.

RHEOLOGICAL EVALUATION OF THE STRUCTURE OF ICE CREAM MIXES VARYING FAT BASE

This paper discusses the influence of fat type in the structure of ice cream, during its production by means of rheo-optical analysis. Fat plays an important part in the ice cream structure formation. It's responsible for the air stabilization, flavor release, texture and melting properties. The objective of this study was to use a rheological method to predict the fat network formation in ice cream with three types of fats (hydrogenated, low trans and palm fat). The three formulations were produced using the same methodology and ratio of ingredients. Rheo-optical measurements were taken before and after the ageing process, and the maximum compression force, overrun and melting profile were calculated in the finished product. The rheological analysis showed a better response from the ageing process from the hydrogenated fat, followed by the low trans fat. The formulation with palm fat showed greater differences between the three, where through the rheological tests a weaker destabilization of the fat globule membrane by the emulsifier was suggested. The overrun, texture measurements and meltdown profile has shown the distinction on the structure formation by the hydrogenated fat from the other fats.

Homophobic discourse in blogs: Weaving of violence and network

This article aims at analyzing the effects of meaning installed in the discursive space of a blog, especially a formulation of discriminatory nature which was posted in November, 2011 and considerably discussed in other discursive spaces on the Internet. By means of French Discourse Analysis, we sought to track the memory networks and the ideological effects that are at play in the discourse on homosexuals posted by browsers-subjects and how they update the meanings already there in order to install effects of prejudice and hatred. Our interest is also to catch the meanings of violence inscribed in the electronic network and analyze the functioning of the language in motion in this space bordered by the imaginary in which it is possible to say anything. Hence, by means of the analyses performed in this study, we observed these effects of the subject's full freedom when he/she subscribes to the electronic network without fear of any punishment of any order. The discourses of intolerance and hatred posted on the blog by the subject give voice to a discursive confrontation observed by marks of agreement or indignation, supported by the discursive memory. Thus, we observed the interruption of regularities that break up with a supposed linearity in the discourse, putting the contradiction and the heterogeneous nature of the sayings on the net in motion.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Unveiling the relationship between complex networks metrics and word senses

The automatic disambiguation of word senses (i.e., the identification of which of the meanings is used in a given context for a word that has multiple meanings) is essential for such applications as machine translation and information retrieval, and represents a key step for developing the so-called Semantic Web. Humans disambiguate words in a straightforward fashion, but this does not apply to computers. In this paper we address the problem of Word Sense Disambiguation (WSD) by treating texts as complex networks, and show that word senses can be distinguished upon characterizing the local structure around ambiguous words. Our goal was not to obtain the best possible disambiguation system, but we nevertheless found that in half of the cases our approach outperforms traditional shallow methods. We show that the hierarchical connectivity and clustering of words are usually the most relevant features for WSD. The results reported here shed light on the relationship between semantic and structural parameters of complex networks. They also indicate that when combined with traditional techniques the complex network approach may be useful to enhance the discrimination of senses in large texts. Copyright (C) EPLA, 2012

Hydrochemical variability at the Upper Paraguay Basin and Pantanal wetland

Compartmentalization is a prerequisite to understand large wetlands that receive water from several sources. However, it faces the heterogeneity in space and time, resulting from physical, chemical and biological processes that are specific to wetlands. The Pantanal is a vast seasonally flooded continental wetland located in the centre of South America. The chemical composition of the waters that supply the Pantanal (70 rivers) has been studied in order to establish a compartmentalization of the wetland based on soil-water interactions. A PCA-based EMMA (End-Members Mixing Analysis) procedure shows that the chemistry of the rivers can be viewed as a mixture of 3 end-members, influenced by lithology and land use, and delimiting large regions. Although the chemical composition of the end-members changed between dry and wet seasons, their spatial distribution was maintained. The results were extended to the floodplain by simple tributary mixing calculation according to the hydrographical network and to the areas of influence for each river when in overflow conditions. The resulting map highlights areas of high geochemical contrast on either side of the river Cuiaba in the north, and of the rivers Aquidauana and Abobral in the south. The PCA-based treatment on a sampling conducted in the Nhecolandia, a large sub region of the Pantanal, allowed the identification and ordering of the processes that control the geochemical variability of the surface waters. Despite an enormous variability in electrical conductivity and pH, all data collected were in agreement with an evaporation process of the Taquari River water, which supplies the region. Evaporation and associated saline precipitations (Mg-calcite, Mg-silicates K-silicates) explained more than 77% of the total variability in the chemistry of the regional surface water sampling.

Relating network rigidity, time scale hierarchies, and expression noise in gene networks

Fluctuation-dissipation theorems can be used to predict characteristics of noise from characteristics of the macroscopic response of a system. In the case of gene networks, feedback control determines the "network rigidity," defined as resistance to slow external changes. We propose an effective Fokker-Planck equation that relates gene expression noise to topology and to time scales of the gene network. We distinguish between two situations referred to as normal and inverted time hierarchies. The noise can be buffered by network feedback in the first situation, whereas it can be topology independent in the latter.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Effect of the Type of Emulsifying Salt on Microstructure and Rheological Properties of "Requeijao Cremoso" Processed Cheese Spreads

The role of different types of emulsifying saltssodium citrate (TSC), sodium hexametaphosphate (SHMP), sodium tripolyphosphate (STPP) and tetrasodium pyrophosphate (TSPP)on microstructure and rheology of requeijao cremoso processed cheese was determined. The cheeses manufactured with TSC, TSPP, and STPP behaved like concentrated solutions, while the cheese manufactured with SHMP exhibited weak gel behavior and the lowest values for the phase angle (G/G). This means that SHMP cheese had the protein network with the largest amount of molecular interactions, which can be explained by its highest degree of fat emulsification. Rotational viscometry indicated that all the spreadable cheeses behaved like pseudoplastic fluids. The cheeses made with SHMP and TSPP presented low values for the flow behavior index, meaning that viscosity was more dependent on shear rate. Regarding the consistency index, TSPP cheese showed the highest value, which could be attributed to the combined effect of its high pH and homogeneous fat particle size distribution.