Development of Grid e-Infrastructure in South-Eastern Europe

Over the period of 6 years and three phases, the SEE-GRID programme has established a strong regional human network in the area of distributed scientific computing and has set up a powerful regional Grid infrastructure. It attracted a number of user communities and applications from diverse fields from countries throughout the South-Eastern Europe. From the infrastructure point view, the first project phase has established a pilot Grid infrastructure with more than 20 resource centers in 11 countries. During the subsequent two phases of the project, the infrastructure has grown to currently 55 resource centers with more than 6600 CPUs and 750 TBs of disk storage, distributed in 16 participating countries. Inclusion of new resource centers to the existing infrastructure, as well as a support to new user communities, has demanded setup of regionally distributed core services, development of new monitoring and operational tools, and close collaboration of all partner institution in managing such a complex infrastructure. In this paper we give an overview of the development and current status of SEE-GRID regional infrastructure and describe its transition to the NGI-based Grid model in EGI, with the strong SEE regional collaboration.Comment: 22 pages, 12 figures, 4 table

SurF: an innovative framework in biosecurity and animal health surveillance evaluation

Surveillance for biosecurity hazards is being conducted by the New Zealand Competent Authority, the Ministry for Primary Industries (MPI) to support New Zealand's biosecurity system. Surveillance evaluation should be an integral part of the surveillance life cycle, as it provides a means to identify and correct problems and to sustain and enhance the existing strengths of a surveillance system. The surveillance evaluation Framework (SurF) presented here was developed to provide a generic framework within which the MPI biosecurity surveillance portfolio, and all of its components, can be consistently assessed. SurF is an innovative, cross‐sectoral effort that aims to provide a common umbrella for surveillance evaluation in the animal, plant, environment and aquatic sectors. It supports the conduct of the following four distinct components of an evaluation project: (i) motivation for the evaluation, (ii) scope of the evaluation, (iii) evaluation design and implementation and (iv) reporting and communication of evaluation outputs. Case studies, prepared by MPI subject matter experts, are included in the framework to guide users in their assessment. Three case studies were used in the development of SurF in order to assure practical utility and to confirm usability of SurF across all included sectors. It is anticipated that the structured approach and information provided by SurF will not only be of benefit to MPI but also to other New Zealand stakeholders. Although SurF was developed for internal use by MPI, it could be applied to any surveillance system in New Zealand or elsewhere

Sea level rise adaptation: emerging lessons for local policy development

Many coastal communities across the United States are beginning to plan for climate-related sea level rise. While impacts and solutions will vary with local conditions, jurisdictions which have begun this process seem to pass through three common stages when developing policy for local sea level rise adaptation: l) building awareness about local sea level rise threats, 2) undertaking analyses of local vulnerabilities, and 3) developing plans and policies to deal with these vulnerabilities. The purpose of this paper is to help advance community dialogue and further inform local decision-makers about key elements and steps for addressing climate-related sea level rise. It summarizes the results of a project the Marine Policy Institute (MPI) undertook during 2011-12 to review experiences from fourteen U.S. coastal jurisdictions representing a variety of city, county, and state efforts with sea level adaptation. There are many more initiatives underway than those reflected in this sample, but the “focus jurisdictions” were selected because of the extensive information publically available on their experiences and lessons being learned that could provide insights for coastal communities, especially in Southwest Florida

Female directorship on boards and corporate sustainability policies: Their effect on sustainable development

We aim to explore whether board gender diversity, specifically women institutional directors, improves the sustainability development and stakeholder engagement of listed firms by affecting corporate social responsibility (CSR) policies. Moreover, within female institutional directors we can differentiate between banks and insurance companies (pressure-sensitive female institutional directors) and mutual funds, investment funds, pension funds and venture capital firms (pressure-resistant female institutional directors). Thus, the effect of these categories of directors on CSR policies is also analysed. Our findings suggest that female institutional, as a whole, have a positive effect on CSR policies, the same behaviour that show pressure-resistant female institutional, while pressure-sensitive institutional do not impact on CSR policies. This research provides a new framework for the role played by certain types of female directors (female institutional directors, female pressure-sensitive directors and female pressure-resistant directors) in CSR policies and, thus, may help policymakers to promote CSR policies, and to take action to promote responsible behaviour among listed firms

Efficiency and productivity of Singapore’s manufacturing sector 2001-2010: An analysis using Simar and Wilson’s (2007) bootstrapped truncated approach

This paper seeks to explain the lagging productivity in Singapore’s manufacturing noted in the statements of the Economic Strategies Committee Report 2010. Two methods are employed: the Malmquist productivity to measure total factor productivity change and Simar and Wilson’s (J Econ, 136:31–64, 2007) bootstrapped truncated regression approach. In the first stage, the nonparametric data envelopment analysis is used to measure technical efficiency. To quantify the economic drivers underlying inefficiencies, the second stage employs a bootstrapped truncated regression whereby bias-corrected efficiency estimates are regressed against explanatory variables. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Most industries were technically inefficient throughout the period except for ‘Pharmaceutical Products’. Sources of efficiency were attributed to quality of worker and flexible work arrangements while incessant use of foreign workers lowered efficiency

Building Near-Real-Time Processing Pipelines with the Spark-MPI Platform

Advances in detectors and computational technologies provide new opportunities for applied research and the fundamental sciences. Concurrently, dramatic increases in the three Vs (Volume, Velocity, and Variety) of experimental data and the scale of computational tasks produced the demand for new real-time processing systems at experimental facilities. Recently, this demand was addressed by the Spark-MPI approach connecting the Spark data-intensive platform with the MPI high-performance framework. In contrast with existing data management and analytics systems, Spark introduced a new middleware based on resilient distributed datasets (RDDs), which decoupled various data sources from high-level processing algorithms. The RDD middleware significantly advanced the scope of data-intensive applications, spreading from SQL queries to machine learning to graph processing. Spark-MPI further extended the Spark ecosystem with the MPI applications using the Process Management Interface. The paper explores this integrated platform within the context of online ptychographic and tomographic reconstruction pipelines.Comment: New York Scientific Data Summit, August 6-9, 201

Water quality evaluation in Mediterranean Lagoons using the Multimetric Phytoplankton Index (MPI): study cases from Sardinia

1 - Water quality in four Sardinian lagoons (western Mediterranean Sea) was assessed using the Multimetric Phytoplankton Index (MPI), which is consistent with the EU Water Framework Directive. The index was developed using data on phytoplankton abundances, species structure and chlorophyll a concentrations in Venice Lagoon, Italy. 2 - The aim of this study was to test the MPI on a larger geographical scale and across a range of lagoon types. Therefore, it was applied to assess water quality in the Cabras, S’Ena Arrubia, Santa Giusta and Calich lagoons in Sardinia. These lagoons are all “choked”, but exhibit a range of sizes and morphometric features. They are directly affected by human activity within the lagoons themselves, such as fisheries, aquaculture and the construction of dams and canals, and are indirectly affected by anthropogenic activities in their catchments, including intensive agriculture, industrial activity and urban development. 3 - The data used in the present study were collected monthly over a period of 4 years (Calich, Santa Giusta and S’Ena Arrubia) to 7 years (Cabras). Samples were collected at three stations at each of the Cabras, Santa Giusta and Calich lagoons, and at two stations at the S’Ena Arrubia Lagoon, providing a total of 220 samples. 4 - The water quality in three of the four lagoons investigated (Cabras, S’Ena Arrubia and Calich) was classified as bad using the MPI. Among these three, water in Cabras Lagoon exhibited the worst condition. Water quality in Santa Giusta Lagoon was classified as poor using the MPI. 5 - Although we present preliminary results that require further verification, the index appears to be a useful tool for assessing the ecological status of typical Mediterranean lagoons

A review of parallel computing for large-scale remote sensing image mosaicking

Interest in image mosaicking has been spurred by a wide variety of research and management needs. However, for large-scale applications, remote sensing image mosaicking usually requires significant computational capabilities. Several studies have attempted to apply parallel computing to improve image mosaicking algorithms and to speed up calculation process. The state of the art of this field has not yet been summarized, which is, however, essential for a better understanding and for further research of image mosaicking parallelism on a large scale. This paper provides a perspective on the current state of image mosaicking parallelization for large scale applications. We firstly introduce the motivation of image mosaicking parallel for large scale application, and analyze the difficulty and problem of parallel image mosaicking at large scale such as scheduling with huge number of dependent tasks, programming with multiple-step procedure, dealing with frequent I/O operation. Then we summarize the existing studies of parallel computing in image mosaicking for large scale applications with respect to problem decomposition and parallel strategy, parallel architecture, task schedule strategy and implementation of image mosaicking parallelization. Finally, the key problems and future potential research directions for image mosaicking are addressed