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Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

Today, many public organizations adopt training programs to develop the productivity and performance of employees. While most previous studies have examined the direct influence of training programs on the productivity of employees, there is a lack of empirical evidence on the indirect effect of training evaluation on employee productivity through job performance. Accordingly, the aim of this study is to examine the mediation role of job performance on the relationship between training evaluation and employee productivity in the General Directorate of Residency and Foreigners Affairs in the UAE (GDRFA). To achieve the objectives and answer research questions, this study used quantitative methods, Structural Equation Modeling methods were applied to validate the conceptual framework and hypotheses. The questionnaire a is data collection tool. The population is the workforce inside GDRFA. The data analysis was conducted on 387 valid questionnaires with a response rate 86%. The findings indicate that training has a significant effect on the employee productivity, while job performance partially mediates this relationship. Based on this outcome, the leaders in GDRFA should foster job performance by developing task and contextual performance. The adoption of training evaluation must be conducted after the competition of training programs in public organizations and based on modern approaches such as the Kirkpatrick model in order to enhance the productivity of employees.

Grid computing provides a robust paradigm for aggregating disparate resources in a secure and controlled environment. The emerging grid infrastructure gives rise to a class of scientific applications and services in support of collaborative and distributed resource-sharing requirements, as part of teleimmersion, visualization and simulation services. Because such applications operate in a collaborative mode, data must be stored, processed and delivered in a timely manner. Such classes of applications have collaborative and distributed resource-sharing requirements, and have stringent real-time constraints and quality-of-service (QoS) requirements. A QoS management approach is therefore essential to orchestrate and guarantee the interaction among such applications in a distributed computing environment. Grid architectures require an underpinning of QoS support to manage complex computation-intensive and data-intensive applications, as current grid middleware solutions lack QoS provision. QoS guarantees in the grid context have, however, not been given the importance they merit. To enhance its functionality, a computational grid must be overlaid with an advanced QoS architecture to best execute those applications with real-time constraints. This thesis reports on the design and implementation of a software framework, called Grid QoS Management (G-QoSm). G-QoSm incorporates a new QoS management model and provides a service-oriented QoS management approach that supports the Open Grid Service Architecture. Its novel features include grid-service discovery based on QoS attributes, immediate and advance resource reservation, service execution with QoS constraints, and techniques for QoS adaptation to compensate for resource degradation, and to optimise resource allocation while maintaining a service level agreement. The benefits of G-QoSm are demonstrated by prototype test-beds that integrate scientific grid applications and simulate grid data-transfer applications. Result

The Grid approach provides the ability to access and use distributed resources as part of virtual organizations. The emerging Grid infrastructure gives rise to a class of scientific applications and services to support collaborative and distributed resource-sharing requirements as part of teleimmersion, visualization, and simulation services. Because such applications operate in a collaborative mode, data must be stored and delivered in timely manner to meet deadlines. Hence, this class of applications has stringent real-time constraints and quality-of-service (QoS) requirements. A QoS management approach is required to orchestrate and guarantee the interaction between such applications and services. In this paper we discuss the design and prototype implementation of a QoS system and show how we enable Grid applications to become QoS compliant. We validate this approach through a case study of nanomaterials. Our approach enhances the current Open Grid Services Architecture. We demonstrate the usefulness of the approach on a nanomaterials application.

Grid computing provides a robust paradigm for aggregating disparate resources in a secure and controlled environment. The emerging grid infrastructure gives rise to a class of scientific applications and services in support of collaborative and distributed resource-sharing requirements, as part of teleimmersion, visualization and simulation services. Because such applications operate in a collaborative mode, data must be stored, processed and delivered in a timely manner. Such classes of applications have collaborative and distributed resource-sharing requirements, and have stringent real-time constraints and quality-of-service (QoS) requirements. A QoS management approach is therefore essential to orchestrate and guarantee the interaction among such applications in a distributed computing environment. Grid architectures require an underpinning of QoS support to manage complex computation-intensive and data-intensive applications, as current grid middleware solutions lack QoS provision. QoS guarantees in the grid context have, however, not been given the importance they merit. To enhance its functionality, a computational grid must be overlaid with an advanced QoS architecture to best execute those applications with real-time constraints. This thesis reports on the design and implementation of a software framework, called Grid QoS Management (G-QoSm). G-QoSm incorporates a new QoS management model and provides a service-oriented QoS management approach that supports the Open Grid Service Architecture. Its novel features include grid-service discovery based on QoS attributes, immediate and advance resource reservation, service execution with QoS constraints, and techniques for QoS adaptation to compensate for resource degradation, and to optimise resource allocation while maintaining a service level agreement. The benefits of G-QoSm are demonstrated by prototype test-beds that integrate scientific grid applications and simulate grid data-transfer applications. Result