Toxics Use Reduction: Pro and Con

With the Massachusetts Toxics Use Reduction Act as an example, important issues related to the goals and effectiveness of TUR are examined. The benefits as claimed by proponents are contrasted with shortcomings outlined by opponents in point-counterpoint style. Ultimately, the authors call for more balanced analysis

Semantic discovery and reuse of business process patterns

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In modern organisations business process modelling has become fundamental due to the increasing rate of organisational change. As a consequence, an organisation needs to continuously redesign its business processes on a regular basis. One major problem associated with the way business process modelling (BPM) is carried out today is the lack of explicit and systematic reuse of previously developed models. Enabling the reuse of previously modelled behaviour can have a beneficial impact on the quality and efficiency of the overall information systems development process and also improve the effectiveness of an organisation’s business processes. In related disciplines, like software engineering, patterns have emerged as a widely accepted architectural mechanism for reusing solutions. In business process modelling the use of patterns is quite limited apart from few sporadic attempts proposed by the literature. Thus, pattern-based BPM is not commonplace. Business process patterns should ideally be discovered from the empirical analysis of organisational processes. Empiricism is currently not the basis for the discovery of patterns for business process modelling and no systematic methodology for collecting and analysing process models of business organisations currently exists. The purpose of the presented research project is to develop a methodological framework for achieving reuse in BPM via the discovery and adoption of patterns. The framework is called Semantic Discovery and Reuse of Business Process Patterns (SDR). SDR provides a systematic method for identifying patterns among organisational data assets representing business behaviour. The framework adopts ontologies (i.e., formalised conceptual models of real-world domains) in order to facilitate such discovery. The research has also produced an ontology of business processes that provides the underlying semantic definitions of processes and their constituent parts. The use of ontologies to model business processes represents a novel approach and combines advances achieved by the Semantic Web and BPM communities. The methodological framework also relates to a new line of research in BPM on declarative business processes in which the models specify what should be done rather than how to ‘prescriptively’ do it. The research follows a design science method for designing and evaluating SDR. Evaluation is carried out using real world sources and reuse scenarios taken from both the financial and educational domains

The Social Value of Zero Balancing

Does Zero Balancing have a social value? Does it in some way contribute to the betterment of society? Does it really have the capacity to make the world a better place? These are questions I started asking myself years ago when I was going through a period of soul searching - investigating my own feelings of powerlessness - feelings of not doing enough in the larger sphere of “making the world a better place”

Big data analytics correlation taxonomy

Big data analytics (BDA) is an increasingly popular research area for both organisations and academia due to its usefulness in facilitating human understanding and communication. In the literature, researchers have focused on classifying big data according to data type, data security or level of difficulty, and many research papers reveal that there is a lack of information on evidence of a real-world link of big data analytics methods and its associated techniques. Thus, many organisations are still struggling to realise the actual value of big data analytic methods and its associated techniques. Therefore, this paper gives a design research account for formulating and proposing a step ahead to understand the relation between the analytical methods and its associated techniques. Furthermore, this paper is an attempt to clarify this uncertainty and identify the difference between analytics methods and techniques by giving clear definitions for each method and its associated techniques to integrate them later in a new correlation taxonomy based on the research approaches. Thus, the primary outcome of this research is to achieve for the first time a correlation taxonomy combining analytic methods used for big data and its recommended techniques that are compatible for various sectors. This investigation was done through studying various descriptive articles of big data analytics methods and its associated techniques in different industries

The Concentration-Response Relation Between PM2.5_{2.5} and Daily Deaths.

Particulate air pollution at commonly occurring concentrations is associated with daily deaths. Recent attention has focused on the shape of the concentration-response curve, particularly at low doses. Several recent articles have reported that particulate matter with aerodynamic diameter $\leq 10 \mu$m PM$_{10}$) was associated with daily deaths with no evidence of a threshold. These reports have used smoothing or spline methods in individual cities and pooled the results across multiple cities to obtain estimates that are more robust. To date, fine particulate matter (aerodynamic diameter $\leq 2.5 \mu$m; PM$_{2.5}$), a component of PM$_{10}$, has not been examined in this regard. We examined this association in a hierarchical model in six U.S. cities. In the first stage, we fit log-linear models including smooth functions of PM$_{2.5}$ in each city, controlling for season, weather, and day of the week. These smooth functions allowed for nonlinearities in the city-specific associations. We combined the estimated curves across cities using a hierarchical model that allows for heterogeneity. We found an essentially linear relationship down to 2 $\mu$g/m$_3$. The same approach was applied to examine the concentration response to traffic particles, controlling for particles from other sources. Once again, the association showed no sign of a threshold. The magnitude of the association suggests that controlling fine particle pollution would result in thousands of fewer early deaths per year

A Bayesian localised conditional auto-regressive model for estimating the health effects of air pollution

Estimation of the long-term health effects of air pollution is a challenging task, especially when modeling spatial small-area disease incidence data in an ecological study design. The challenge comes from the unobserved underlying spatial autocorrelation structure in these data, which is accounted for using random effects modeled by a globally smooth conditional autoregressive model. These smooth random effects confound the effects of air pollution, which are also globally smooth. To avoid this collinearity a Bayesian localized conditional autoregressive model is developed for the random effects. This localized model is flexible spatially, in the sense that it is not only able to model areas of spatial smoothness, but also it is able to capture step changes in the random effects surface. This methodological development allows us to improve the estimation performance of the covariate effects, compared to using traditional conditional auto-regressive models. These results are established using a simulation study, and are then illustrated with our motivating study on air pollution and respiratory ill health in Greater Glasgow, Scotland in 2011. The model shows substantial health effects of particulate matter air pollution and nitrogen dioxide, whose effects have been consistently attenuated by the currently available globally smooth models

Like Other Women: Perspectives of Mothers with Physical Disabilities

This article is based on interviews with ten women, ranging in age from 19 to 45 and living in the Puget Sound area of Washington State. Their disabilities are neurmuscular or musculoskeletal and include spinal cord injury, multiple sclerosis, post-polio and spina bifida. Their children range in age from 11 months to adulthood. The article focuses on specific issues and concerns regarding early childhood ranagement, and includes some discussion of pre-natal and cbstetrical care. Cann misconceptions concerning motherhood and disability are also discussed. men with disabilities also have special concerns as parents. Although their concerns are not addressed in this paper, they are not seen as any less important or deserving of attention. Work on this paper was made possible under Grant #10H53008032 from the Department of Health and Human Services, Bureau of Community Health Services, Family Planning Program, 1980

The Effect of Dose and Timing of Dose on the Association between Airborne Particles and Survival

BACKGROUND: Understanding the shape of the concentration–response curve for particles is important for public health, and lack of such understanding was recently cited by U.S. Environmental Protection Agency (EPA) as a reason for not tightening the standards. Similarly, the delay between changes in exposure and changes in health is also important in public health decision making. We addressed these issues using an extended follow-up of the Harvard Six Cities Study. METHODS: Cox proportional hazards models were fit controlling for smoking, body mass index, and other covariates. Two approaches were used. First, we used penalized splines, which fit a flexible functional form to the concentration response to examine its shape, and chose the degrees of freedom for the curve based on Akaike’s information criterion. Because the uncertainties around the resultant curve do not reflect the uncertainty in model choice, we also used model averaging as an alternative approach, where multiple models are fit explicitly and averaged, weighted by their probability of being correct given the data. We examined the lag relationship by model averaging across a range of unconstrained distributed lag models. RESULTS: We found that the concentration–response curve is linear, clearly continuing below the current U.S. standard of 15 μg/m3, and that the effects of changes in exposure on mortality are seen within two years. CONCLUSIONS: Reduction in particle concentrations below U.S. EPA standards would increase life expectancy

Indirect Resin Composite Restorations Fabricated With Chairside CAD/CAM Systems

Aesthetics has gained significant importance in restorative dentistry besides the potential requirements including the continuity and integrity of tissue and regaining the function and phonation. The demand for esthetic posterior restorations gave way to the use of resin composites in the posterior region as well as the anterior restorations. However, polymerization shrinkage of resin composites limits this application to only with small sized restorations. In order to eliminate the disadvantage of polymerization shrinkage, various methods have been suggested to improve the properties and application methods of resins with the aim of increasing the longevity and function of restorative materials. For this purpose, computer aided design/computer aided manufacturing (CAD/CAM) systems have been used for the past 10 years to fabricate indirect restorations with resin composites as an alternative material in digital system. This review aims to provide an update on the resin composite materials used with indirect restorations and CAD/CAM systems