Predictive response-relevant clustering of expression data provides insights into disease processes

This article describes and illustrates a novel method of microarray data analysis that couples model-based clustering and binary classification to form clusters of ;response-relevant' genes; that is, genes that are informative when discriminating between the different values of the response. Predictions are subsequently made using an appropriate statistical summary of each gene cluster, which we call the ;meta-covariate' representation of the cluster, in a probit regression model. We first illustrate this method by analysing a leukaemia expression dataset, before focusing closely on the meta-covariate analysis of a renal gene expression dataset in a rat model of salt-sensitive hypertension. We explore the biological insights provided by our analysis of these data. In particular, we identify a highly influential cluster of 13 genes-including three transcription factors (Arntl, Bhlhe41 and Npas2)-that is implicated as being protective against hypertension in response to increased dietary sodium. Functional and canonical pathway analysis of this cluster using Ingenuity Pathway Analysis implicated transcriptional activation and circadian rhythm signalling, respectively. Although we illustrate our method using only expression data, the method is applicable to any high-dimensional datasets

A Survey of Social Network Analysis Techniques and their Applications to Socially Aware Networking

Socially aware networking is an emerging research field that aims to improve the current networking technologies and realize novel network services by applying social network analysis (SNA) techniques. Conducting socially aware networking studies requires knowledge of both SNA and communication networking, but it is not easy for communication networking researchers who are unfamiliar with SNA to obtain comprehensive knowledge of SNA due to its interdisciplinary nature. This paper therefore aims to fill the knowledge gap for networking researchers who are interested in socially aware networking but are not familiar with SNA. This paper surveys three types of important SNA techniques for socially aware networking: identification of influential nodes, link prediction, and community detection. Then, this paper introduces how SNA techniques are used in socially aware networking and discusses research trends in socially aware networking

Fog Computing: A Taxonomy, Survey and Future Directions

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

Aligning Key Success Factors to ERP Implementation Strategy: Learning from a Case Study

CAHIER DE RECHERCHE n°2012-08 E5These last years, we can observe that most of companies implemented an ERP system but many of them fail. Much of research that has been conducted in this field, focus on KSFs. We have noticed that confronting those KSFs to ERP implementation strategies seems quiet fecund. So provide in this article a brief overview of the literature dealing with key success factors related to an ERP implementation project to better cope with the field, then come out with a framework analyzing these KSFs depending on implementation strategies. Then we study a case of an ERP implementation project in a company operating in the automotive industry, with a quail-metric methodology, to better understand the reasons of ERP implementation projects success or failure

Aligning Key Success Factors to ERP Implementation Strategy: Learning from a Case Study

CAHIER DE RECHERCHE n°2012-08 E5These last years, we can observe that most of companies implemented an ERP system but many of them fail. Much of research that has been conducted in this field, focus on KSFs. We have noticed that confronting those KSFs to ERP implementation strategies seems quiet fecund. So provide in this article a brief overview of the literature dealing with key success factors related to an ERP implementation project to better cope with the field, then come out with a framework analyzing these KSFs depending on implementation strategies. Then we study a case of an ERP implementation project in a company operating in the automotive industry, with a quail-metric methodology, to better understand the reasons of ERP implementation projects success or failure

Growth rings in tropical trees : role of functional traits, environment, and phylogeny

Acknowledgments Financial support of the Centre National de la Recherche Scientifique (USR 3330), France, and from the Rufford Small Grants Foundation (UK) is acknowledged. We thank the private farmers and coffee plantation companies of Kodagu for providing permissions and logistical support for this project. We are grateful to N. Barathan for assistance with slide preparation and data entry, S. Aravajy for botanical assistance, S. Prasad and G. Orukaimoni for technical inputs, and A. Prathap, S. Shiva, B. Saravana, and P. Shiva for field assistance. The corresponding editor and three anonymous reviewers provided insightful comments that improved the manuscript.Peer reviewedPostprin

Short course on principles and applications of beach nourishment

Covers the engineering aspects of beach nourishment. (Document is 192 pages

The effects of social norms among peer groups on risk behavior: A multilevel approach to differentiate perceived and collective norms

Social norms have been found to be an important factor in individuals’ health and risk behaviors. Past research has typically addressed which social norms individuals perceive in their social environments (e.g., in their peer group). The present article explores normative social influences beyond such perceptions by applying a multilevel approach and differentiating between perceived norms at the individual level and collective norms at the group level. Data on norms and three road traffic risk behaviors (speeding, driving after drinking, and texting while driving) were obtained from a representative survey among young German car drivers (N = 311 anchor respondents) and their peer groups (overall N = 1,244). Multilevel modeling (MLM) revealed that beyond individual normative perceptions of peers’ behavior and approval, actual collective norms (peers’ actual risk behavior and attitudes) affect individuals’ risk behaviors. Findings are discussed with regard to theorizing normative influences on risk behavior and practical implications