If potential morphologically cryptic species, identified based on differentiated mitochondrial DNA, express ecological divergence, this increases support for their treatment as distinct species. However, mitochondrial DNA introgression hampers the correct estimation of ecological divergence. We test the hypothesis that estimated niche divergence differs when considering nuclear DNA composition ...

Regulation of gene expression is central to many biological processes. Although reconstruction of regulatory circuits from genomic data alone is therefore desirable, this remains a major computational challenge. Comparative approaches that examine the conservation and divergence of circuits and their components across strains and species can help reconstruct circuits as well as provide insights...

A method of restriction fragment length polymorphism (RFLP) analysis was used to estimate the amount of genetic divergence between the spontaneously hypertensive rat (SHR) strain and the Wistar-Kyoto (WKY) strain. DNA from each strain was digested with eight restriction endonucleases and hybridized with six single copy gene sequences. The number of hybridization bands in each digestion was used...

The regional and provincial divergence in China’s economic growth has attracted extensive and intensive attention, yet the measurement and research on the sources of the divergence is relatively inadequate. Why there is divergence across provinces? What elements have contributed to the divergence and how? Based on growth regression analysis and “counterfactual econometrics”, this paper construc...

The complex constraints imposed by protein structure and function result in varied rates of sequence and structural divergence in proteins. Analysis of sequence differences between homologous proteins can advance our understanding of structural divergence and some of the constraints that govern the evolution of these molecules. Here, we assess the relationship between amino acid sequence and st...

Estimating word co-occurrence probabilities is a problem underlying many applications in statistical natural language processing. Distance-weighted (or similarityweighted) averaging has been shown to be a promising approach to the analysis of novel co-occurrences. Many measures of distributional similarity have been proposed for use in the distance-weighted averaging framework; here, we empiric...

Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmic design, which is to influence the clustering via weights on the instance points. In this paper, we handle clustering as a constrained minimization of a Bregman divergence. Theoretical results show benefits resembling those of boosting algorithms, and bring new modified weighted versions of cl...

In this research work a large set of the classical numerical functions were taken into account in order to understand both the search capability and the ability to escape from a local optimal of a clonal selection algorithm, called i-CSA. The algorithm was extensively compared against several variants of Differential Evolution (DE) algorithm, and with some typical swarm intelligence algorithms....

This paper examines the ‘cognitive’ and ‘societal’ aspects of the tacit knowledge transfer problem in MNCs. Based on a comparative analysis of the overseas R&D labs of US and Japanese MNCs in the UK, it examines how home-based models of learning influence MNCs’ transnational social spaces for learning and their capabilities to address the tacit knowing problem. It illustrates how the US profess...

Traditional clustering methods deal with a single clustering task on a single data set. However, in some newly emerging applications, multiple similar clustering tasks are involved simultaneously. In this case, we not only desire a partition for each task, but also want to discover the relationship among clusters of different tasks. It’s also expected that the learnt relationship among tasks ca...