Non-invasive genetic study and population monitoring of the brown bear (Ursus arctos) (Mammalia: Ursidae) in Kastoria region – Greece

The brown bear (Ursus arctos) in Greece is considered endangered but little is known about the genetic status and the exact size of local populations. Non-invasive genetic sampling was used in this study to investigate the genetic diversity and genetic structure of the brown bear population in the Kastoria region (northwest Macedonia, Greece) and to estimate its population size. Estimation of demographic parameters was based on innovative, well-evaluated methods that can provide estimates from a single sampling session. DNA was extracted from hairs, scat and blood samples and subsequent amplification of 10 microsatellite loci allowed the identification of a minimum number of 75 living bears in the study area while the mark–recapture-based analysis resulted in a point estimation of 219 individuals. Relatively high diversity values, lack of heterozygosity deficiency as well as estimated effective population size, support the Kastoria bear population having good conservation status.     

Backward‐in‐Time Selection of the Order of Dynamic Regression Prediction Model

We investigate the optimal structure of dynamic regression models used in multivariate time series prediction and propose a scheme to form the lagged variable structure called Backward‐in‐Time Selection (BTS), which takes into account feedback and multicollinearity, often present in multivariate time series. We compare BTS to other known methods, also in conjunction with regularization techniques used for the estimation of model parameters, namely principal components, partial least squares and ridge regression estimation. The predictive efficiency of the different models is assessed by means of Monte Carlo simulations for different settings of feedback and multicollinearity. The results show that BTS has consistently good prediction performance, while other popular methods have varying and often inferior performance. The prediction performance of BTS was also found the best when tested on human electroencephalograms of an epileptic seizure, and for the prediction of returns of indices of world financial markets.Copyright © 2013 John Wiley & Sons, Ltd.     

Hierarchical Shrinkage in Time‐Varying Parameter Models

In this paper, we forecast EU area inflation with many predictors using time‐varying parameter models. The facts that time‐varying parameter models are parameter rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time‐varying parameter models. Our approach allows for the coefficient on each predictor to be: (i) time varying; (ii) constant over time; or (iii) shrunk to zero. The econometric methodology decides automatically to which category each coefficient belongs. Our empirical results indicate the benefits of such an approach. Copyright © 2013 John Wiley & Sons, Ltd.     

A Critical Assessment of Project Management Methods with Respect to Electronic Government Implementation Challenges

In taking forward both the Government Modernization and the Civil Service Reform agendas, renewed emphasis is being placed on project management approaches and techniques for achieving objectives more effectively and efficiently. After elaborating on specific electronic government project implementation challenges and giving an overview of state-of-the-art project management approaches, the paper examines the weaknesses of three commonly used methods in the light of the e-Government project challenges. The analysis identifies gaps in the methods, contributing to a better understanding of the factors that lead to success or failure. The resolution of such methodological limitations could lead to the enhancement of project management methods when applied to future projects.     

基于l_1正则化RanBoost的人脸表情识别及程度估计(英文)

鉴于之前的大多数工作仅仅局限于人脸的表情识别,在本文中,我们提出了一种基于排序模型的创新性人脸表情识别方法。与之前的方法不同的是,我们提出的方法不但能够做表情识别,而且能够估计表情的程度,而表情程度估计则对于理解人的情绪变化有很大的帮助。虽然精确标注表情的程度很困难,但是表情随时间变化的有序信息提供了相对的度量。基于这种观察,我们将表情程度估计问题转化为一个排序问题,并且用Rankboost建立排序模型。排序模型的输出可以直接用于程度估计,而且我们也可以将排序模型用于表情识别。为了进一步提高我们提出的方法的性能,我们将l1正则化引入到Rankboost中。在Cohn-Kanade数据库上进行实验,实验结果表明我们提出的方法与当前的方法比较,有着明显的优势。     

Testing for Granger (non‐)causality in a time‐varying coefficient VAR model

In this paper we propose Granger (non‐)causality tests based on a VAR model allowing for time‐varying coefficients. The functional form of the time‐varying coefficients is a logistic smooth transition autoregressive (LSTAR) model using time as the transition variable. The model allows for testing Granger non‐causality when the VAR is subject to a smooth break in the coefficients of the Granger causal variables. The proposed test then is applied to the money–output relationship using quarterly US data for the period 1952:2–2002:4. We find that causality from money to output becomes stronger after 1978:4 and the model is shown to have a good out‐of‐sample forecasting performance for output relative to a linear VAR model. Copyright © 2008 John Wiley & Sons, Ltd.     

Oncogene-induced senescence is part of the tumorigenesis barrier imposed by DNA damage checkpoints

Recent studies have indicated the existence of tumorigenesis barriers that slow or inhibit the progression of preneoplastic lesions to neoplasia. One such barrier involves DNA replication stress, which leads to activation of the DNA damage checkpoint and thereby to apoptosis or cell cycle arrest, whereas a second barrier is mediated by oncogene-induced senescence. The relationship between these two barriers, if any, has not been elucidated. Here we show that oncogene-induced senescence is associated with signs of DNA replication stress, including prematurely terminated DNA replication forks and DNA double-strand breaks. Inhibiting the DNA double-strand break response kinase ataxia telangiectasia mutated (ATM) suppressed the induction of senescence and in a mouse model led to increased tumour size and invasiveness. Analysis of human precancerous lesions further indicated that DNA damage and senescence markers cosegregate closely. Thus, senescence in human preneoplastic lesions is a manifestation of oncogene-induced DNA replication stress and, together with apoptosis, provides a barrier to malignant progression.     

Activation of the DNA damage checkpoint and genomic instability in human precancerous lesions

DNA damage checkpoint genes, such as p53, are frequently mutated in human cancer, but the selective pressure for their inactivation remains elusive. We analysed a panel of human lung hyperplasias, all of which retained wild-type p53 genes and had no signs of gross chromosomal instability, and found signs of a DNA damage response, including histone H2AX and Chk2 phosphorylation, p53 accumulation, focal staining of p53 binding protein 1 (53BP1) and apoptosis. Progression to carcinoma was associated with p53 or 53BP1 inactivation and decreased apoptosis. A DNA damage response was also observed in dysplastic nevi and in human skin xenografts, in which hyperplasia was induced by overexpression of growth factors. Both lung and experimentally-induced skin hyperplasias showed allelic imbalance at loci that are prone to DNA double-strand break formation when DNA replication is compromised (common fragile sites). We propose that, from its earliest stages, cancer development is associated with DNA replication stress, which leads to DNA double-strand breaks, genomic instability and selective pressure for p53 mutations.