Prevalência de tuberculose em transplantados renais: revisão sistemática e meta-análise

INTRODUÇÃO: A prevalência de tuberculose entre transplantados renais (TB-TXR) é maior do que na população geral. Assim, objetivamos realizar uma revisão sistemática e meta-análise da prevalência de TB-TXR. MÉTODOS: Após buscas eletrônicas e revisão de referências, estimou-se a prevalência agrupada de TB-TXR e realizou-se meta-regressão. Como referência para comparações, utilizou-se a prevalência de TB na população geral (0,18%; 95% IC = 0,16-0,20). RESULTADOS: Foram triados 253 estudos e 41 incluídos. A prevalência agrupada de TB-TXR foi 2,51% (95% IC = 2,17-2,85). Na meta-regressão, amostra > 2501 e alta prevalência de TB na população geral (p < 0,05) permaneceram associadas com a prevalência de TB-TXR. CONCLUSÃO: A prevalência agrupada de TB-TXR encontrada foi 14 vezes maior do que a prevalência de TB na população geral e, dessa forma, destacamos a necessidade de que o planejamento de medidas de prevenção e controle da TB específicas para este grupo de indivíduos seja pauta nas discussões do setor saúde.

Polimorfismo nulo dos genes GSTM1 e GSTT1 na suscetibilidade do câncer renal: evidências baseadas em meta-análise

ResumoIntroduçãoO câncer renal é uma doença oncourológica complexa e multifatorial.Objetivo:Realizar uma meta-análise para investigar a associação do polimorfismo nulo dos genes GSTM1 e GSTT1 no contexto do câncer renal.Método:Estudos em seres humanos, do tipo caso-controle, publicados no período de 1999 a 2013, que investigavam a associação do polimorfismo nulo dos genes GSTM1 e GSTT1 no câncer renal, foram agrupados para a confecção da presente meta-análise.Resultados:Foram selecionados 10 artigos sobre o tema proposto. Não foram encontradas associações entre o polimorfismo nulo dos genes GSTM1 (OR = 1,015; IC95% = 0,897-1,147) e GSTT1 (OR = 1,081; IC95% = 0,791- 1,479) e o câncer renal.Conclusões:Conclui-se que os polimorfismos nulos de GSTM1 e GSTT1 não estão associados ao risco do desenvolvimento de câncer renal, pois apresentam papel limitado, se é que existe alguma contribuição efetiva, no desenvolvimento dos tumores renais.

A software engineering approach to distributed systems for composite modeling

The goal of this thesis is to define and validate a software engineering approach for the development of a distributed system for the modeling of composite materials, based on the analysis of various existing software development methods. We reviewed the main features of: (1) software engineering methodologies; (2) distributed system characteristics and their effect on software development; (3) composite materials modeling activities and the requirements for the software development. Using the design science as a research methodology, the distributed system for creating models of composite materials is created and evaluated. Empirical experiments which we conducted showed good convergence of modeled and real processes. During the study, we paid attention to the matter of complexity and importance of distributed system and a deep understanding of modern software engineering methods and tools.

Distributed energy resources in an electricity retailer’s short-term profit optimization

Liberalization of electricity markets has resulted in a competed Nordic electricity market, in which electricity retailers play a key role as electricity suppliers, market intermediaries, and service providers. Although these roles may remain unchanged in the near future, the retailers’ operation may change fundamentally as a result of the emerging smart grid environment. Especially the increasing amount of distributed energy resources (DER), and improving opportunities for their control, are reshaping the operating environment of the retailers. This requires that the retailers’ operation models are developed to match the operating environment, in which the active use of DER plays a major role. Electricity retailers have a clientele, and they operate actively in the electricity markets, which makes them a natural market party to offer new services for end-users aiming at an efficient and market-based use of DER. From the retailer’s point of view, the active use of DER can provide means to adapt the operation to meet the challenges posed by the smart grid environment, and to pursue the ultimate objective of the retailer, which is to maximize the profit of operation. This doctoral dissertation introduces a methodology for the comprehensive use of DER in an electricity retailer’s short-term profit optimization that covers operation in a variety of marketplaces including day-ahead, intra-day, and reserve markets. The analysis results provide data of the key profit-making opportunities and the risks associated with different types of DER use. Therefore, the methodology may serve as an efficient tool for an experienced operator in the planning of the optimal market-based DER use. The key contributions of this doctoral dissertation lie in the analysis and development of the model that allows the retailer to benefit from profit-making opportunities brought by the use of DER in different marketplaces, but also to manage the major risks involved in the active use of DER. In addition, the dissertation introduces an analysis of the economic potential of DER control actions in different marketplaces including the day-ahead Elspot market, balancing power market, and the hourly market of Frequency Containment Reserve for Disturbances (FCR-D).

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Chronic macro-economic and financial imbalances in the world economy: a meta-economic view

Global finance, combining offshore banking and universal banks to drive a broader globalization process, has transformed the modus operandi of the world economy. This requires a new "meta-economic" framework in which short-term portfolio-investment flows are treated as the dominant phenomenon they have become. Organized by global finance, these layered bi-directional flows between center and periphery manage a tension between financial concentration and monetary fragmentation. The resulting imbalances express the asymmetries built into that tension and render the exchange rate a more strategic policy variable than ever.

Social physique anxiety across physical activity settings : a meta-analytical review

The purpose of this meta-analytic investigation was to review the empirical evidence specific to the effect of physical activity context on social physique anxiety (SP A). English language studies were located from computer and manual literature searches. A total of 146 initial studies were coded. Studies included in the meta-analysis presented at least one empirical effect for SPA between physical activity participants (i.e., athletes or exercisers) and non-physical activity participants. The final sample included thirteen studies, yielding 14 effect sizes, with a total sample size of 2846. Studies were coded for mean SPA between physical activity participants and non-physical activity participants. Moderator variables related to demographic and study characteristics were also coded. Using Hunter and Schmidt's (2004) protocol, statistical artifacts were corrected. Results indicate that, practically speaking, those who were physically active reported lower levels of SPA than the comparison group (dcorr = -.12; SDeorr.-=-;22). Consideration of the magnitude of the ES, the SDeorr, and confidence interval suggests that this effect is not statistically significant. While most moderator analyses reiterated this trend, some differences were worth noting. Previous research has identified SPA to be especially salient for females compared to males, however, in the current investigation, the magnitude of the ES' s comparing physical activity participants to the comparison group was similar (deorr = -.24 for females and deorr = -.23 for males). Also, the type of physical activity was investigated, and results showed that athletes reported lower levels of SP A than the comparison group (deorr = -.19, SDeorr = .08), whereas exercisers reported higher levels of SPA than the comparison group (deorr = .13, SDeorr = .22). Results demonstrate support for the dispositional nature of SP A. Consideration of practical significance suggests that those who are involved in physical activity may experience slightly lower levels of SPA than those not reporting physical activity participation. Results potentially offer support for the bi-directionality of the relationship between physical activity and SP A; however, a causality may not be inferred. More information about the type of physical activity (i.e., frequency/nature of exercise behaviour, sport classificationllevel of athletes) may help clarify the role of physical activity contexts on SPA.

Perceptions of intergroup bias : the roles of social projection and meta-stereotypes

Underlying intergroup perceptions include processes of social projection (perceiving personal traitslbeliefs in others, see Krueger 1998) and meta-stereotyping (thinking about other groups' perceptions of one's own group, see Vorauer et aI., 1998). Two studies were conducted to investigate social projection and meta-stereotypes in the domain of White-Black racial relations. Study 1, a correlational study, examined the social projection of prejudice and 'prejudiced' meta-stereotypes among Whites. Results revealed that (a) Whites socially projected their intergroup attitudes onto other Whites (and Blacks) [i.e., Whites higher in prejudice against Blacks believed a large percentage of Whites (Blacks) are prejudiced against Blacks (Whites), whereas Whites low in prejudice believed a smaller percentage of Whites (Blacks) are prejudiced]; (b) Whites held the meta:..stereotype that their group (Whites) is viewed by Blacks to be prejudiced; and (c) prejudiced meta-stereotypes may be formed through the social projection of intergroup attitudes (result of path-model tests). Further, several correlates of social projection and meta-stereotypes were identified, including the finding that feeling negatively stereotyped by an outgroup predicted outgroup avoidance through heightened intergroup anxiety. Study 2 replicated and extended these findings, investigating the social projection of ingroup favouritism and meta- and other-stereotypes about ingroup favouritism. These processes were examined experimentally using an anticipated intergroup contact paradigm. The goal was to understand the experimental conditions under which people would display the strongest social projection of intergroup attitudes, and when experimentally induced meta-stereotypes (vs. other-stereotypes; beliefs about the group 11 preferences of one's outgroup) would be most damaging to intergroup contact. White participants were randomly assigned to one of six conditions and received (alleged) feedback from a previously completed computer-based test. Depending on condition, this information suggested that: (a) the participant favoured Whites over Blacks; (b) previous White participants favoured Whites over Blacks; (c) the participant's Black partner favoured Blacks over Whites; (d) previous Black participants favoured Blacks over Whites; (e) the participant's Black partner viewed the participant to favour Whites over Blacks; or (£) Black participants previously participating viewed Whites to favour Whites over Blacks. In a defensive reaction, Whites exhibited enhanced social projection of personal intergroup attitudes onto their ingroup under experimental manipulations characterized by self-concept threat (i.e., when the computer revealed that the participant favoured the ingroup or was viewed to favour the ingroup). Manipulated meta- and otherstereotype information that introduced intergroup contact threat, on the other hand, each exerted a strong negative impact on intergroup contact expectations (e.g., anxiety). Personal meta-stereotype manipulations (i.e., when the participant was informed that her/ his partner thinks s/he favours the ingroup) exerted an especially negative impact on intergroup behaviour, evidenced by increased avoidance of the upcoming interracial interaction. In contrast, personal self-stereotype manipulations (i.e., computer revealed that one favoured the ingroup) ironically improved upcoming intergroup contact expectations and intentions, likely due to an attempt to reduce the discomfort of holding negative intergroup attitudes. Implications and directions for future research are considered.

The practical application of a meta-analysis of deinstitutionalization : adaptive behaviour outcomes and the piloting of a transitional questionnaire for adults with intellectual disabilities

This investigation examined the effects of de institutionalization on the adaptive behaviour and adjustment of adults with intellectual disabilities (ID). In study 1, a meta-analysis was conducted with 23 studies on deinstitutionalization adaptive behaviour outcomes. Deinstitutionalization was associated with modest improvements in adaptive behaviour however outcomes varied across adaptive behaviour domains and other substantive variables. Clinical and service implications of these results were explicated. Noting the trends from the meta-analysis, study 2 used this information in refining and piloting an Agency Transition Survey used to evaluate community transitions for persons with ID. Information derived from the survey was found to be valuable and adequate for the effective evaluation of transitional success. Potential applications of the survey and meta-analysis results were illustrated.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

The Implementation of Jenkins’s 21st-Century Skills in the Curriculum: A Cross-National Policy Analysis

This meta-analytic study sought to determine if cross-national curricula are aligned with burgeoning digital learning environments in order to help policy makers develop curriculum that incorporates 21st-century skills instruction. The study juxtaposed cross- national curricula in Ontario (Canada), Australia, and Finland against Jenkins’s (2009) framework of 11 crucial 21st-century skills that include: play, performance, simulation, appropriation, multitasking, distributed cognition, collective intelligence, judgment, transmedia navigation, networking, and negotiation. Results from qualitative data collection and analysis revealed that Finland implements all of Jenkins’s 21st-century skills. Recommendations are made to implement sound 21st-century skills in other jurisdictions.

La calidad como meta de la organización por Rafael Sanmiguel Flores

Tesis (Maestría en Ciencias de la Administración con Especialidad en Investigación de Operaciones) U.A.N.L.

La calidad como meta de la organización por Maricela E. Covarrubias Ortiz

Tesis (Maestría en Ciencias de la Administración con Especialidad en Relaciones Industriales) U.A.N.L.

Analysis of multiple change-points in normally distributed series.

Tesis (Maestría en Ciencias con Orientación en Matemáticas) UANL, 2013.