Effective Node Clustering and Data Dissemination In Large-Scale Wireless Sensor Networks

The denseness and random distribution of large-scale WSNs makes it quite difficult to replace or recharge nodes. Energy efficiency and management is a major design goal in these networks. In addition, reliability and scalability are two other major goals that have been identified by researchers as necessary in order to further expand the deployment of such networks for their use in various applications. This thesis aims to provide an energy efficient and effective node clustering and data dissemination algorithm in large-scale wireless sensor networks. In the area of clustering, the proposed research prolongs the lifetime of the network by saving energy through the use of node ranking to elect cluster heads, contrary to other existing cluster-based work that selects a random node or the node with the highest energy at a particular time instance as the new cluster head. Moreover, a global knowledge strategy is used to maintain a level of universal awareness of existing nodes in the subject area and to avoid the problem of disconnected or forgotten nodes. In the area of data dissemination, the aim of this research is to effectively manage the data collection by developing an efficient data collection scheme using a ferry node and applying a selective duty cycle strategy to the sensor nodes. Depending on the application, mobile ferries can be used for collecting data in a WSN, especially those that are large in scale, with delay tolerant applications. Unlike data collection via multi-hop forwarding among the sensing nodes, ferries travel across the sensing field to collect data. A ferry-based approach thus eliminates, or minimizes, the need for the multi-hop forwarding of data, and as a result, energy consumption at the nodes will be significantly reduced. This is especially true for nodes that are near the base station as they are used by other nodes to forward data to the base station. MATLAB is used to design, simulate and evaluate the proposed work against the work that has already been done by others by using various performance criteria

PRIVATE SECTOR EMIRATIZATION: EVALUATING THE POLICIES AND PRACTICES DESIGNED TO ACHIEVE ABU DHABI\u27S STRATEGIC HRM GOAL

The purpose of this study is two-fold: firstly, to gauge the job satisfaction levels of UAE nationals employed in the private sector and secondly to consider the HRM policies and procedures most likely to attract and retain such individuals. The issue is of contemporary importance because the UAE has a fast-growing population, and already overstaffed public sector and, a labor nationalization program that has yet to have a significant impact on the ratio of nationals employed in the private sector visa- vis the classic public sector. Using a combination of employee survey and expert interview feedback this study provides a policy-orientated analysis of the current state of private sector Emiratizations and makes a significant contribution to the emerging Arab Middle East HR Model by suggesting ways in which UAE HR policies and strategies may be enhanced. If the compensation and benefits disparity between the two influence the employment decision include Salary and Fringe Benefits, opportunities for growth along with training and development, a friendly and professional working environment that offers job security, and finally the social perceptions. This research can be helpful in understanding what incentives and measures can be useful and effective for the operational implementation of the Emiratizations process. The analysis can help in the identification and prioritization of issues that are impacting the pace of implementation of the Emiratizations process. This study finds a number of statistically significant relationships between the dependent variable of “continuance intentions” and various predictor variables: β .399 for pay and benefits; β .163 for professional development opportunities; β .072 for the nature of the job; the impact of sociocultural influences was found to have a significant and negative relationship, β -.423. The study concludes by making a number of policy-relevant recommendations focusing on HRD at the macro level and HRM policies and procedures at the company leve

Private Sector Emiratisation: Evaluating The Policies and Practices Designed To Achieve Abu Dhabi\u27s Strategic HRM Goal

The purpose of this study is two-fold: firstly, to gauge the job satisfaction levels of UAE nationals employed in the private sector and secondly to consider the HRM policies and procedures most likely to attract and retain such individuals. The issue is of contemporary importance because the UAE has a fast growing population, an already overstaffed public sector and, a labour nationalisation program that has yet to have a significant impact on the ratio of nationals employed in the private sector visà- vis the classic public sector. Using a combination of employee survey and expert interview feedback this study provides a policy-orientated analysis of the current state of private sector Emiratisation and makes a significant contribution to the emerging Arab Middle East HR Model by suggesting ways in which UAE HR policies and strategies may be enhanced. If the compensation and benefits disparity between the two sectors be minimised, the majority of Emiratis would be willing to work in the private sector. The factors that can influence the employment decision include Salary and Fringe Benefits, opportunities for growth along with training and development, a friendly and professional working environment that offers job security and finally the social perceptions. This research can be helpful in understanding what incentives and measures can be useful and effective for the operational implementation of the Emiratisation process. The analysis can help in identification and prioritisation of issues that are impacting the pace of implementation of Emiratisation process. This study finds a number of statistically significant relationships between the dependent variable of “continuance intentions” and various predictor variables: β .399 for pay and benefits; β .163 for professional development opportunities; β .072 for the nature of the job; the impact of sociocultural influences was found to have a significant and negative relationship, β -.423. The study concludes by making a number of policyrelevant recommendations focusing on HRD at the macro level and HRM policies and procedures at the company lev

Frequency of Abo, Rhesus Phenotypes and Most Probable Genotypes and the Type of RHD Negative Variants among UAE Nationals in Al Ain District

Knowledge of the frequencies and the phenotypes of ABO and rhesus system is very important for blood bank and transfusion services policies. The objective of this study was to determine the frequency of ABO, Rhesus phenotype and most probable genotypes in Al Ain area (UAE). The studied group consisted of 500 locals of both gender from different age groups (17-58 years old). ABO and Rh-hr phenotype reactivity were determined using conventional tube method and gel technology, molecular techniques were also applied. Our study shows the distribution of ABO phenotypes was as follows: 0= 56%, A= 26.2%, B= 14.2% and AB= 3.6%. The distribution of Rh antigens was as follows: D= 90.4 %, C= 76.2%, E= 27.2%, c= 71.6% and e= 97.8%. And the distribution of most probable genotypes was as follows: Rl r= 29.8%, R l R l = 28.4%, R l R2= 16.8%, rr= 8.4%, R2 r= 8.2%, R o 1\u27=5%, R2 R2= 2.2%, and r\u27r= 1.2%. Our study showed that the most frequent antigen amongst five major antigens of Rh system was RhD while the least common was E antigen. We developed an innovative method that combines molecular analysis and serological testing of Rh genes to be applied in blood bank environment as it is considered as a first study done in the area. This approach could improve patient care and transfusion outcomes by reducing alloimmunization. The challenge lies in integrating such testing into blood bank environment, standardizing methods, obtaining Food and Drug Administration approval for labeling donor units, and enhancing information systems to incorporate and use this new information effectively

Subchronic Exposure to TCDD, PeCDF, PCB126, and PCB153: Effect on Hepatic Gene Expression

We employed DNA microarray to identify unique hepatic gene expression patterns associated with subchronic exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other halogenated aromatic hydrocarbons (HAHs). Female Harlan Sprague-Dawley rats were exposed for 13 weeks to toxicologically equivalent doses of four different HAHs based on the toxic equivalency factor of each chemical: TCDD (100 ng/kg/day), 2,3,4,7,8-pentachlorodibenzofuran (PeCDF; 200 ng/kg/day), 3,3′,4,4′,5-pentachlorobiphenyl (PCB126; 1,000 ng/kg/day), or 2,2′,4,4′,5,5′-hexachlorobiphenyl (PCB153; 1,000 μg/kg/day). Global gene expression profiles for each exposure, which account for 8,799 gene probe sets contained on Affymetrix RGU34A GeneChips, were compared by principal components analysis. The aryl hydrocarbon receptor (AhR) ligands TCDD, PeCDF, and PCB126 produced very similar global gene expression profiles that were unique from the nonAhR ligand PCB153, underscoring the extensive impact of AhR activation and/or the resulting hepatic injury on global gene expression in female rat liver. Many genes were co-expressed during the 13-week TCDD, PeCDF, or PCB126 exposures, including classical AhR-regulated genes and some genes not previously characterized as being AhR regulated, such as carcinoembryonic-cell adhesion molecule 4 (C-CAM4) and adenylate cyclase-associated protein 2 (CAP2). Real-time reverse-transcriptase polymerase chain reaction confirmed the increased expression of these genes in TCDD-, PeCDF-, and PCB126-exposed rats as well as the up- or down-regulation of several other novel dioxin-responsive genes. In summary, DNA microarray successfully identified dioxin-responsive genes expressed after exposure to AhR ligands (TCDD, PeCDF, PCB126) but not after exposure to the non-AhR ligand PCB153. Together, these findings may help to elucidate some of the fundamental features of dioxin toxicity and may further clarify the biologic role of the AhR signaling pathway

μ-CS: An extension of the TM4 platform to manage Affymetrix binary data

<p>Abstract</p> <p>Background</p> <p>A main goal in understanding cell mechanisms is to explain the relationship among genes and related molecular processes through the combined use of technological platforms and bioinformatics analysis. High throughput platforms, such as microarrays, enable the investigation of the whole genome in a single experiment. There exist different kind of microarray platforms, that produce different types of binary data (images and raw data). Moreover, also considering a single vendor, different chips are available. The analysis of microarray data requires an initial preprocessing phase (i.e. normalization and summarization) of raw data that makes them suitable for use on existing platforms, such as the TIGR M4 Suite. Nevertheless, the annotations of data with additional information such as gene function, is needed to perform more powerful analysis. Raw data preprocessing and annotation is often performed in a manual and error prone way. Moreover, many available preprocessing tools do not support annotation. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of microarray data are needed.</p> <p>Results</p> <p>The paper presents <it>μ</it>-CS (Microarray Cel file Summarizer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix binary data. <it>μ</it>-CS is based on a client-server architecture. The <it>μ</it>-CS client is provided both as a plug-in of the TIGR M4 platform and as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data, avoiding the manual invocation of external tools (e.g. the Affymetrix Power Tools), the manual loading of preprocessing libraries, and the management of intermediate files. The <it>μ</it>-CS server automatically updates the references to the summarization and annotation libraries that are provided to the <it>μ</it>-CS client before the preprocessing. The <it>μ</it>-CS server is based on the web services technology and can be easily extended to support more microarray vendors (e.g. Illumina).</p> <p>Conclusions</p> <p>Thus <it>μ</it>-CS users can directly manage binary data without worrying about locating and invoking the proper preprocessing tools and chip-specific libraries. Moreover, users of the <it>μ</it>-CS plugin for TM4 can manage Affymetrix binary files without using external tools, such as APT (Affymetrix Power Tools) and related libraries. Consequently, <it>μ</it>-CS offers four main advantages: (i) it avoids to waste time for searching the correct libraries, (ii) it reduces possible errors in the preprocessing and further analysis phases, e.g. due to the incorrect choice of parameters or the use of old libraries, (iii) it implements the annotation of preprocessed data, and finally, (iv) it may enhance the quality of further analysis since it provides the most updated annotation libraries. The <it>μ</it>-CS client is freely available as a plugin of the TM4 platform as well as a standalone application at the project web site (<url>http://bioingegneria.unicz.it/M-CS</url>).</p

Generation of mouse ES cell lines engineered for the forced induction of transcription factors

Here we report the generation and characterization of 84 mouse ES cell lines with doxycycline-controllable transcription factors (TFs) which, together with the previous 53 lines, cover 7–10% of all TFs encoded in the mouse genome. Global gene expression profiles of all 137 lines after the induction of TFs for 48 hrs can associate each TF with the direction of ES cell differentiation, regulatory pathways, and mouse phenotypes. These cell lines and microarray data provide building blocks for a variety of future biomedical research applications as a community resource

Seeded Bayesian Networks: Constructing genetic networks from microarray data

<p>Abstract</p> <p>Background</p> <p>DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results.</p> <p>Results</p> <p>Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data.</p> <p>Conclusion</p> <p>The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.</p

Genomotyping of Coxiella burnetii Using Microarrays Reveals a Conserved Genomotype for Hard Tick Isolates

C. burnetii is a Gram-negative intracellular Y-proteobacteria that causes the zoonotic disease Q fever. Q fever can manifest as an acute or chronic illness. Different typing methods have been previously developed to classify C. burnetii isolates to explore its pathogenicity. Here, we report a comprehensive genomotyping method based on the presence or absence of genes using microarrays. The genomotyping method was then tested in 52 isolates obtained from different geographic areas, different hosts and patients with different clinical manifestations. The analysis revealed the presence of 10 genomotypes organized into 3 groups, with a topology congruent with that obtained through multi-spacer typing. We also found that only 4 genomotypes were specifically associated with acute Q fever, whereas all of the genomotypes could be associated to chronic human infection. Serendipitously, the genomotyping results revealed that all hard tick isolates, including the Nine Mile strain, belong to the same genomotype