Concurrent training protocol for men with androgen deficiency in the aging male: a randomized clinical trial

Background: The androgen deficiency in the aging male (ADAM) affects physical, sexual, and psychological aspects with characteristics symptoms of middle-aged men. The practice of regular physical activity and physical exercise can attenuate these symptoms. The aim of this randomized clinical trial is to propose a physical exercise protocol based on concurrent training for middle-aged men with ADAM.

Method: Randomized clinical trial with a 6-month intervention will randomly divided into two groups: experimental group (EG) and control group (CG). Four evaluations will be carried out, (1) pre-intervention; (2) in the first month of intervention; (3) in the third month of intervention; (4) post-intervention, evaluating: physical, psychological, sexual, and hormonal aspects. The intervention protocol with concurrent training will have duration of 6 months; frequency of 3 times weekly, with 60?min per session. The two-way ANOVA test will be used for the inter-group and intra-group comparisons with repeated measurements, and also Sydak’s comparison test.

Conclusion: This protocol was developed with the intent of easing the symptoms of ADAM. In addition, it is believed that the concurrent training protocol could be capable to recover hormonal, physical, psychological, and sexual aspect of middle-aged men with ADAM.     

Geographically Weighted Negative Binomial Regression—incorporating overdispersion

Global regression assumes that a single model adequately describes all parts of a study region. However, the heterogeneity in the data may be sufficiently strong that relationships between variables can not be spatially constant. In addition, the factors involved are often sufficiently complex that it is difficult to identify them in the form of explanatory variables. As a result Geographically Weighted Regression (GWR) was introduced as a tool for the modeling of non-stationary spatial data. Using kernel functions, the GWR methodology allows the model parameters to vary spatially and produces non-parametric surfaces of their estimates. To model count data with overdispersion, it is more appropriate to use a negative binomial distribution instead of a Poisson distribution. Therefore, we propose the Geographically Weighted Negative Binomial Regression (GWNBR) method for the modeling of data with overdispersion. The results obtained using simulated and real data show the superiority of this method for the modeling of non-stationary count data with overdispersion compared with competing models, such as global regressions, e.g., Poisson and negative binomial and Geographically Weighted Poisson Regression (GWPR). Moreover, we illustrate that these competing models are special cases of the more robust model GWNBR.     

Problems with Traditional Science Publishing and Finding a Wider Niche for Post-Publication Peer Review

Science affects multiple basic sectors of society. Therefore, the findings made in science impact what takes place at a commercial level. More specifically, errors in the literature, incorrect findings, fraudulent data, poorly written scientific reports, or studies that cannot be reproduced not only serve as a burden on tax-payers’ money, but they also serve to diminish public trust in science and its findings. Therefore, there is every need to fortify the validity of data that exists in the science literature, not only to build trust among peers, and to sustain that trust, but to reestablish trust in the public and private academic sectors that are witnessing a veritable battle-ground in the world of science publishing, in some ways spurred by the rapid evolution of the open access (OA) movement. Even though many science journals, traditional and OA, claim to be peer reviewed, the truth is that different levels of peer review occur, and in some cases no, insufficient, or pseudo-peer review takes place. This ultimately leads to the erosion of quality and importance of science, allowing essentially anything to become published, provided that an outlet can be found. In some cases, predatory OA journals serve this purpose, allowing papers to be published, often without any peer review or quality control. In the light of an explosion of such cases in predatory OA publishing, and in severe inefficiencies and possible bias in the peer review of even respectable science journals, as evidenced by the increasing attention given to retractions, there is an urgent need to reform the way in which authors, editors, and publishers conduct the first line of quality control, the peer review. One way to address the problem is through post-publication peer review (PPPR), an efficient complement to traditional peer-review that allows for the continuous improvement and strengthening of the quality of science publishing. PPPR may also serve as a way to renew trust in scientific findings by correcting the literature. This article explores what is broadly being said about PPPR in the literature, so as to establish awareness and a possible first-tier prototype for the sciences for which such a system is undeveloped or weak.     

用PowerPoint设计MCAI课件

通过分析各种课件开发工具的特点,介绍了使用PowerPoint制作课件的一般过程.从课件模板、模型的选择和课件内容的设计、创意的实现等四个方面进行了阐述,并具体给出了几个制作技巧.     

工业设计教育建立合理知识结构的探讨

本文讨论了在工业设计专业教育中建立合理知识结构的重要性 ,并对工业设计专业教育课程设置中一些有争议的问题作了分析。     

Urban or rural fragments: which soil use in forest surroundings induces greater litter deposition?

Urban Ecosystems - The soil use in surroundings of forest remnants, as well as, variations in seasonality and rainfall totals from each year might influence the composition, structure, and...     

Zero-inflated proportion data models applied to a biological control assay

Biological control of pests is an important branch of entomology, providing environmentally friendly forms of crop protection. Bioassays are used to find the optimal conditions for the production of parasites and strategies for application in the field. In some of these assays, proportions are measured and, often, these data have an inflated number of zeros. In this work, six models will be applied to data sets obtained from biological control assays for Diatraea saccharalis , a common pest in sugar cane production. A natural choice for modelling proportion data is the binomial model. The second model will be an overdispersed version of the binomial model, estimated by a quasi-likelihood method. This model was initially built to model overdispersion generated by individual variability in the probability of success. When interest is only in the positive proportion data, a model can be based on the truncated binomial distribution and in its overdispersed version. The last two models include the zero proportions and are based on a finite mixture model with the binomial distribution or its overdispersed version for the positive data. Here, we will present the models, discuss their estimation and compare the results.     

A sequence of improved standard errors under heteroskedasticity of unknown form

The linear regression model is commonly used by practitioners to model the relationship between the variable of interest and a set of explanatory variables. The assumption that all error variances are the same (homoskedasticity) is oftentimes violated. Consistent regression standard errors can be computed using the heteroskedasticity-consistent covariance matrix estimator proposed by White (1980). Such standard errors, however, typically display nonnegligible systematic errors in finite samples, especially under leveraged data. Cribari-Neto et al. (2000) improved upon the White estimator by defining a sequence of bias-adjusted estimators with increasing accuracy. In this paper, we improve upon their main result by defining an alternative sequence of adjusted estimators whose biases vanish at a much faster rate. Hypothesis testing inference is also addressed. An empirical illustration is presented.     

Measuring the Cultural Dimension of Migrant Integration and Integration Policy in the European Context: Dilemmas and Discussions1

Migrant integration is usually studied in four dimensions: economic, political, social and cultural. The cultural sphere seems to be the most ambiguous, but also the one that induces various interpretations as it touches upon core norms and values held both by migrants and by the receiving society. This paper aims to reconstruct research approaches to cultural integration and integration policy. Beside the receiving country’s language, that is the obvious differentiating factor of cultural integration, other aspects have been defined: migrants’ religion, knowledge of the receiving country’s symbolic culture, maintenance and transmission of cultural patterns, cultural identity. Furthermore, indicators which appear to adequately measure the effectiveness of integration activities have been assigned to the predefined aspects of cultural integration. They have been confronted with indicators used within integration policies of selected EU states and with expert statements (collected within the Delphi method‐based survey) on given aspects of policies aimed at cultural integration.