“Law on Transboundary Movement of Hazardous Substances through Sea

This study pertain to legal control of pollution from transboundary movement of hazardous substances through sea. It is an emerging area in international maritime law. There is growing environmental awareness that oceans are no longer an inexhaustible resource. This has resulted in a complex system of integrated ocean policies and international legal frame work in this regard. Considering the peculiar nature of hazardous substances, the development of law in this regard has been haphazard. The legal framework in this area is not comprehensive and lacks coherence. India is geo-strategically located in the central part of Indian Ocean through which many international sea routes lie. India is also fast emerging as a maritime hub. Indian legal framework in this respect also suffers from serious pitfalls. In this backdrop, this study makes a sincere attempt to identify and analyse the legal intricacies in this area, in order to evolve a better regime for control of pollution pursuant to transboundary movement of hazardous substances through sea

An Integrated Framework To Improve The Concept Of Resource Specialisation.

Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.

Pressure of massless hot scalar theory in the boundary effective theory framework

We use the boundary effective theory approach to thermal field theory in order to calculate the pressure of a system of massless scalar fields with quartic interaction. The method naturally separates the infrared physics, and is essentially nonperturbative. To lowest order, the main ingredient is the solution of the free Euler-Lagrange equation with nontrivial (time) boundary conditions. We derive a resummed pressure, which is in good agreement with recent calculations found in the literature, following a very direct and compact procedure.

Building a Open Source Framework for Virtual Medical Training

This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.

Process oriented framework to support PLM implementation

Product lifecycle management (PLM) innovates as it defines both the product as a central element to aggregate enterprise information and the lifecycle as a new time dimension for information integration and analysis. Because of its potential benefits to shorten innovation lead-times and to reduce costs, PLM has attracted a lot of attention at industry and at research. However, the current PLM implementation stage at most organisations still does not apply the lifecycle management concepts thoroughly. In order to close the existing realisation gap, this article presents a process oriented framework to support effective PLM implementation. The framework central point consists of a set of lifecycle oriented business process reference models which links the necessary fundamental concepts, enterprise knowledge and software solutions to effectively deploy PLM. (c) 2007 Elsevier B.V. All rights reserved.

Reducing Urban Transport Energy Dependence: A New Urban Development Framework and GIS-Based Tool

High urban transport energy consumption is directly influenced by transport energy dependence. Dramatic reductions in urban transport energy dependence or consumption are not yet being widely observed despite the variety of urban planning tools currently available. A new urban development framework is presented to tackle this issue that makes use of a recently developed and successfully trialed GIS-based tool, the Transport Energy Specification (TES). The TES was simulated on a neighborhood in Sao Carlos, Brazil. In the simulation, energy dependence was reduced by a factor of 8 through activity location or infrastructure modifications to the built environment.

A Computational Framework for Institutional Agency

This paper provides a computational framework, based on Defeasible Logic, to capture some aspects of institutional agency. Our background is Kanger-Lindahl-P\"orn account of organised interaction, which describes this interaction within a multi-modal logical setting. This work focuses in particular on the notions of counts-as link and on those of attempt and of personal and direct action to realise states of affairs. We show how standard Defeasible Logic can be extended to represent these concepts: the resulting system preserves some basic properties commonly attributed to them. In addition, the framework enjoys nice computational properties, as it turns out that the extension of any theory can be computed in time linear to the size of the theory itself.

A Logic Framework of Normative-based Contract Management

We explore of the feasibility of the computationally oriented institutional agency framework proposed by Governatori and Rotolo testing it against an industrial strength scenario. In particular we show how to encode in defeasible logic the dispute resolution policy described in Article 67 of FIDIC.

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

A framework for selecting appropriate remotely sensed data dimensions for environmental monitoring and management

Two major factors are likely to impact the utilisation of remotely sensed data in the near future: (1)an increase in the number and availability of commercial and non-commercial image data sets with a range of spatial, spectral and temporal dimensions, and (2) increased access to image display and analysis software through GIS. A framework was developed to provide an objective approach to selecting remotely sensed data sets for specific environmental monitoring problems. Preliminary applications of the framework have provided successful approaches for monitoring disturbed and restored wetlands in southern California.

A framework to monitor sustainability in the grains industry

Community awareness of the sustainable use of land, water and vegetation resources is increasing. The sustainable use of these resources is pivotal to sustainable farming systems. However, techniques for monitoring the sustainable management of these resources are poorly understood and untested. We propose a framework to benchmark and monitor resources in the grains industry. Eight steps are listed below to achieve these objectives: (i) define industry issues; (ii) identify the issues through growers, stakeholder and community consultation; (iii) identify indicators (measurable attributes, properties or characteristics) of sustainability through consultation with growers, stakeholders, experts and community members, relating to: crop productivity; resource maintenance/enhancement; biodiversity; economic viability; community viability; and institutional structure; (iv) develop and use selection criteria to select indicators that consider: responsiveness to change; ease of capture; community acceptance and involvement; interpretation; measurement error; stability, frequency and cost of measurement; spatial scale issues; and mapping capability in space and through time. The appropriateness of indicators can be evaluated using a decision making system such as a multiobjective decision support system (MO-DSS, a method to assist in decision making from multiple and conflicting objectives); (v) involve stakeholders and the community in the definition of goals and setting benchmarking and monitoring targets for sustainable farming; (vi) take preventive and corrective/remedial action; (vii) evaluate effectiveness of actions taken; and (viii) revise indicators as part of a continual improvement principle designed to achieve best management practice for sustainable farming systems. The major recommendations are to: (i) implement the framework for resources (land, water and vegetation, economic, community and institution) benchmarking and monitoring, and integrate this process with current activities so that awareness, implementation and evolution of sustainable resource management practices become normal practice in the grains industry; (ii) empower the grains industry to take the lead by using relevant sustainability indicators to benchmark and monitor resources; (iii) adopt a collaborative approach by involving various industry, community, catchment management and government agency groups to minimise implementation time. Monitoring programs such as Waterwatch, Soilcheck, Grasscheck and Topcrop should be utilised; (iv) encourage the adoption of a decision making system by growers and industry representatives as a participatory decision and evaluation process. Widespread use of sustainability indicators would assist in validating and refining these indicators and evaluating sustainable farming systems. The indicators could also assist in evaluating best management practices for the grains industry.

Developing a framework for assessment of the environmental determinants of walking and cycling

The focus for interventions and research on physical activity has moved away from vigorous activity to moderate-intensity activities, such as walking. In addition, a social ecological approach to physical activity research and practice is recommended. This approach considers the influence of the environment and policies on physical activity. Although there is limited empirical published evidence related to the features of the physical environment that influence physical activity, urban planning and transport agencies have developed policies and strategies that have the potential to influence whether people walk or cycle in their neighbourhood. This paper presents the development of a framework of the potential environmental influences on walking and cycling based on published evidence and policy literature, interviews with experts and a Delphi study. The framework includes four features: functional, safety, aesthetic and destination; as well as the hypothesised factors that contribute to each of these features of the environment. In addition, the Delphi experts determined the perceived relative importance of these factors. Based on these factors, a data collection tool will be developed and the frameworks will be tested through the collection of environmental information on neighbourhoods, where data on the walking and cycling patterns have been collected previously. Identifying the environmental factors that influence walking and cycling will allow the inclusion of a public health perspective as well as those of urban planning and transport in the design of built environments. (C) 2002 Elsevier Science Ltd., All rights reserved.

RFID adoption: framework and survey in large Brazilian companies

Purpose - The purpose of this paper is to provide a framework for radio frequency identification (RFID) technology adoption considering company size and five dimensions of analysis: RFID applications, expected benefits business drivers or motivations barriers and inhibitors, and organizational factors. Design/methodology/approach - A framework for RFID adoption derived from literature and the practical experience on the subject is developed. This framework provides a conceptual basis for analyzing a survey conducted with 114 companies in Brazil. Findings - Many companies have been developing RFID initiatives in order to identify potential applications and map benefits associated with their implementation. The survey highlights the importance business drivers in the RFID implementation stage, and that companies implement RFID focusing on a few specific applications. However, there is a weak association between expected benefits and business challenges with the current level of RFID technology adoption in Brazil. Research limitations/implications - The paper is not exhaustive, since RFID adoption in Brazil is at early stages during the survey timeline. Originality/value - The main contribution of the paper is that it yields a framework for analyzing RFID technology adoption. The authors use this framework to analyze RFID adoption in Brazil, which proved to be a useful one for identifying key issues for technology adoption. The paper is useful to any researchers or practitioners who are focused on technology adoption, in particular, RFID technology.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.