Phylogeny and micro-habitats utilized by lizards determine the composition of their endoparasites in the semiarid Caatinga of Northeast Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudo da tecnologia de acesso Wi-Fie suas aplicações em ambientes indoor e outdoor

Wireless communications is a feature that has become indispensable for many people in the whole world. Through this feature, communication process can become much more efficient, allowing people to access information much more quickly wherever they are. The constant evolution of communication technologies allows the development of new unthinkable applications and services. This new range of possibilities brings greater mobility and efficiency for final users and also helps service providers and carriers to improve the quality of services offered by them. This study presents the principles of wireless communication and the Wi-Fi technology as well as its most modern applications, covering from the basics of computer networks to the procedures of planning a wireless network, concepts of radio frequency, antennas, patterns, regulatory agencies, network equipment, protocols and network monitoring

Um direcionamento às novas tecnologias na arquitetura: habitação de um futuro presente, em um espaço para a vida

This paper tries, across research, books, magazines and charts that relate to the architecture of today, establishing a direction as to the technological advances that may be involved in the architecture project. Such that the configuration space has flexibility to meet the basic architectural principles and the wishes of the user, who should participate as a key character of the decisions of spatialization - interface. Both the personal point of view of their social relations within the housing, and the functional environments equipped and qualified to meet expectations during its use. Respecting the power of free choice of human beings, not to put yourself to the detriment by excessive use of technology. And still look for ways to integrate the individual to society connected to your network - home. Keywords: interface, information, technology, space flexibility

Segurança em redes sem fio: estudo sobre o desenvolvimento de conjuntos de dados para comparação de IDS

Pós-graduação em Engenharia Elétrica - FEIS

Correlação e visualização de alertas de segurança em redes de computadores

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Tecnologia da informação, discurso e poder: análise de domínio a partir do conceito de exclusão digital na perspectiva da teoria centro-periferia

Pós-graduação em Ciência da Informação - FFC

L3-arpsec - módulo seguro para controle e proteção do protocolo de resolução de endereços em redes definidas por software

Pós-graduação em Engenharia Elétrica - FEIS

Relação entre risco de erosão e distância de camalhões em estradas florestais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geração de simuladores de filas para diferentes contextos com estudo de casos para redes de computadores

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Assessing Needs for Computer Pest Management Software in Nebraska Agriculture

A mail survey was conducted to assess current computer hardware use and perceived needs of potential users for software related to crop pest management in Nebraska. Surveys were sent to University of Nebraska-Lincoln agricultural extension agents, agribusiness personnel (including independent crop consultants), and crop producers identified by extension agents as computer users. There were no differences between the groups in several aspects of computer hardware use (percentage computer use, percentage IBM-compatible computer, amount of RAM memory, percentage with hard drive, hard drive size, or monitor graphics capability). Responses were similar among the three groups in several areas that are important to crop pest management (pest identification, pest biology, treatment decision making, control options, and pesticide selection), and a majority of each group expressed the need for additional sources of such information about insects, diseases, and weeds. However, agents mentioned vertebrate pest management information as a need more often than the other two groups. Also, majorities of each group expressed an interest in using computer software, if available, to obtain information in these areas. Appropriate software to address these needs should find an audience among all three groups.

Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

A novel strategy for building interoperable MPI environment in heterogeneous high performance systems

Breakthrough advances in microprocessor technology and efficient power management have altered the course of development of processors with the emergence of multi-core processor technology, in order to bring higher level of processing. The utilization of many-core technology has boosted computing power provided by cluster of workstations or SMPs, providing large computational power at an affordable cost using solely commodity components. Different implementations of message-passing libraries and system softwares (including Operating Systems) are installed in such cluster and multi-cluster computing systems. In order to guarantee correct execution of message-passing parallel applications in a computing environment other than that originally the parallel application was developed, review of the application code is needed. In this paper, a hybrid communication interfacing strategy is proposed, to execute a parallel application in a group of computing nodes belonging to different clusters or multi-clusters (computing systems may be running different operating systems and MPI implementations), interconnected with public or private IP addresses, and responding interchangeably to user execution requests. Experimental results demonstrate the feasibility of this proposed strategy and its effectiveness, through the execution of benchmarking parallel applications.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.