Caloric restriction minimizes aging effects on the femoral medial condyle

This study aimed to analyze the effects of caloric restriction on aged femoral articular cartilage of Wistar rats. Three groups of eight animals each were considered: young (YC) and old (OC) control groups fed with a normal diet and old caloric restriction group (OCR) composed of 18-month-old animals fed with a 31% less caloric diet from 6-months of age. Articular cartilage was studied through morphometry and immunohistochemistry. Body mass was 12% less in the OCR group than in the OC group. The articular cartilage from OC rats show thinner medial condyles, fewer chondrocytes, smaller chondrocytes nuclear volume and, in both condyles, a predominance of collagen type II and less collagen density compared to both YC and OCR groups (p?p?相似文献   

THE FAILURE TO PREDICT THE GREAT RECESSION—A VIEW THROUGH THE ROLE OF CREDIT

Much has been written about why economists failed to predict the latest crisis. Reading the literature, it seems that this crisis was so obvious that economists must have been blind not to see it coming. We approach this failure by looking at one of the key variables in this analysis, the evolution of credit. We compare the conclusions reached in the recent literature with those that could have been drawn from an ex‐ante analysis. We show that the effect of credit on the business cycle cannot be exploited from a policymaker's point of view.     

A non-parametric statistic for testing conditional heteroscedasticity for unobserved component models

When prediction intervals are constructed using unobserved component models (UCM), problems can arise due to the possible existence of components that may or may not be conditionally heteroscedastic. Accurate coverage depends on correctly identifying the source of the heteroscedasticity. Different proposals for testing heteroscedasticity have been applied to UCM; however, in most cases, these procedures are unable to identify the heteroscedastic component correctly. The main issue is that test statistics are affected by the presence of serial correlation, causing the distribution of the statistic under conditional homoscedasticity to remain unknown. We propose a nonparametric statistic for testing heteroscedasticity based on the well-known Wilcoxon''s rank statistic. We study the asymptotic validation of the statistic and examine bootstrap procedures for approximating its finite sample distribution. Simulation results show an improvement in the size of the homoscedasticity tests and a power that is clearly comparable with the best alternative in the literature. We also apply the test on real inflation data. Looking for the presence of a conditionally heteroscedastic effect on the error terms, we arrive at conclusions that almost all cases are different than those given by the alternative test statistics presented in the literature.     

Copula structure analysis

Summary.  We extend the standard approach of correlation structure analysis for dimension reduction of high dimensional statistical data. The classical assumption of a linear model for the distribution of a random vector is replaced by the weaker assumption of a model for the copula. For elliptical copulas a correlation-like structure remains, but different margins and non-existence of moments are possible. After introducing the new concept and deriving some theoretical results we observe in a simulation study the performance of the estimators: the theoretical asymptotic behaviour of the statistics can be observed even for small sample sizes. Finally, we show our method at work for a financial data set and explain differences between our copula-based approach and the classical approach. Our new method yielear models also.     

A copula-based Markov chain model for the analysis of binary longitudinal data

A fully parametric first-order autoregressive (AR(1)) model is proposed to analyse binary longitudinal data. By using a discretized version of a copula, the modelling approach allows one to construct separate models for the marginal response and for the dependence between adjacent responses. In particular, the transition model that is focused on discretizes the Gaussian copula in such a way that the marginal is a Bernoulli distribution. A probit link is used to take into account concomitant information in the behaviour of the underlying marginal distribution. Fixed and time-varying covariates can be included in the model. The method is simple and is a natural extension of the AR(1) model for Gaussian series. Since the approach put forward is likelihood-based, it allows interpretations and inferences to be made that are not possible with semi-parametric approaches such as those based on generalized estimating equations. Data from a study designed to reduce the exposure of children to the sun are used to illustrate the methods.     

<Emphasis Type="BoldItalic">MAD-STEC</Emphasis>: a method for multiple automatic detection of space-time emerging clusters

Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev–Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil.     

The Legacy of Lynching? An Empirical Replication and Conceptual Extension

Research shows enduring impacts of lynching on a variety of modern outcomes. For instance, Messner, Baller, and Zevenbergen found that lynching is associated with contemporary white-on-black homicide. We propose a model describing how events from the past can have effects on events in the present. Essential to our framework is the notion of social forces of “resistance” that can impede or facilitate the temporal transmission of collective memories. We test “indicators of resistance” that influence the transmission of a collective memory supportive of a “legacy of lynching.” Analyses reveal that the positive and significant association between lynching and white-on-black homicide observed by Messner et al. is attenuated and becomes statistically nonsignificant with the inclusion of these indicators. Our results suggest that the temporal transmission of a racist cultural schema manifested through lynching is more likely where resistance is low. These findings have implications for how researchers can study historical legacies.     

Blogging while Black,British and female: a critical study on discursive activism

This study explores Black British women's motivations for divulging racial and ethnic identity in the blogosphere (sometimes referred to as blogging while Black) and their use of blogs for discursive activism. It builds on previous research that gives voice to Black womens marginalized experiences through powerful counter narratives. The blogosphere is often perceived as a racially neutral space where shared interests across geographical and temporal boundaries limit the significance of racial and ethnic identity. However, the constructed narratives of Black British women in this study highlight their experiences of subtle forms of prejudice and discrimination perpetuated through dominant discourses in the mainstream media. The findings demonstrate how they use blogs as a medium for discursive activism to challenge stereotypical raced and gendered representation in the mainstream media. Much of the research on the blogosphere in Britain reflects its use by the White majority population. This study therefore extends understanding of the blogosphere and highlights alternative modes of political communication.     

Multiple tests for the performance of different investment strategies

In the context of modern portfolio theory, we compare the out-of-sample performance of eight investment strategies which are based on statistical methods with the out-of-sample performance of a family of trivial strategies. A?wide range of approaches is considered in this work, including the traditional sample-based approach, several minimum-variance techniques, a shrinkage, and a minimax approach. In contrast to similar studies in the literature, we also consider short-selling constraints and a risk-free asset. We provide a way to extend the concept of minimum-variance strategies in the context of short-selling constraints. A main drawback of most empirical studies on that topic is the use of simple testing procedures which do not account for the effects of multiple testing. For that reason we conduct several hypothesis tests which are proposed in the multiple-testing literature. We test whether it is possible to beat a trivial strategy by at least one of the non-trivial strategies, whether the trivial strategy is better than every non-trivial strategy, and which of the non-trivial strategies is significantly outperformed by naive diversification. The empirical part of our study is conducted using US stock returns from the last four decades, obtained via the CRSP database.