Space-time stick-breaking processes for small area disease cluster estimation

We propose a space-time stick-breaking process for the disease cluster estimation. The dependencies for spatial and temporal effects are introduced by using space-time covariate dependent kernel stick-breaking processes. We compared this model with the space-time standard random effect model by checking each model’s ability in terms of cluster detection of various shapes and sizes. This comparison was made for simulated data where the true risks were known. For the simulated data, we have observed that space-time stick-breaking process performs better in detecting medium- and high-risk clusters. For the real data, county specific low birth weight incidences for the state of South Carolina for the years 1997–2007, we have illustrated how the proposed model can be used to find grouping of counties of higher incidence rate.     

Elements of fishing community resilience to climate change in the coastal zone of Bangladesh

Resilience has been conceptualized in various ways by anthropologists, ecologists, systems scientists and engineers; the boundaries of resilience are subjective and context dependent. Consequently, choosing the standards and metrics for assessing resilience remains key challenges for policy makers. In this study, using multicriteria evaluation of 40 basic criteria of human, physical, financial, natural and social assets, we have identified several elements, such as experienced fishermen, natural abundance of hilsa (Tenualosa ilisha), ability to assert decision on fish selling, nets and boats ownership, social harmony and capacity of buying food as essential livelihood assets for the fishermen at Hatiya Island, Bangladesh. These assets may enhance the relative resilience of the fishing community of the island to climate change by as much as 20–40%. The results of this study will improve our understanding of the elements that lead to resilience at the community level.     

Novel Sorbent of Sand Coated with Humic Acid-Iron Oxide Nanoparticles for Elimination of Copper and Cadmium Ions from Contaminated Water

Journal of Polymers and the Environment - Nanoparticles of humic acid and iron oxide were impregnated on the inert sand to produce sorbent for treating groundwater contained of cadmium and copper...     

A quantitative risk management framework for dust and hybrid mixture explosions

Dust and hybrid-mixture explosions continue to occur in industrial processes that handle fine powders and flammable gases. Considerable research is therefore conducted throughout the world with the objective of both preventing the occurrence and mitigating the consequences of such events. In the current work, research has been undertaken to help move the field of dust explosion prevention and mitigation from its current emphasis on hazards (with an accompanying reliance on primarily engineered safety features) to a focus on risk (with an accompanying reliance on hierarchical, risk-based, decision-making tools). Employing the principles of quantitative risk assessment (QRA) of dust and hybrid-mixture explosions, a methodological framework for the management of these risks has been developed.The QRA framework is based on hazard identification via credible accident scenarios for dust explosions, followed by probabilistic fault-tree analysis (using Relex – Reliability Excellence – software) and consequence severity analysis (using DESC – Dust Explosion Simulation Code – software). Identification of risk reduction measures in the framework is accomplished in a hierarchical manner by considering inherent safety measures, passive and active engineered devices, and procedural measures (in that order). An industrial case study is presented to show how inherent safety measures such as dust minimization and dust/process moderation can be helpful in reducing dust and hybrid-mixture explosion consequences in a 400-m³ polyethylene storage silo.     

An optimal level of dust explosion risk management: Framework and application

The current research provides guidance on the prevention and mitigation of dust explosion using a Quantitative Risk Management Framework (QRMF). Using concepts drawn from previous studies, the framework consists of three main steps: (i) a new combined safety management protocol, (ii) the use of DESC (Dust Explosion Simulation Code) and FTA (Fault Tree Analysis) to assess explosion consequences and likelihood, respectively, and (iii) application of the hierarchy of controls (inherent, engineered and procedural safety). QRMF assessment of an industrial case study showed that the original process was at high risk. DESC simulations and Probit equations determined the destructive percentages. FTAs revealed high probabilities of explosion occurrence; in addition, detailed individual and societal risks calculations were made, before and after the framework was applied. Based on the hierarchy of controls technique, the framework showed significant risk reduction to the point where the residual risk was acceptable for the process.     

Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach

A bow-tie diagram combines a fault tree and an event tree to represent the risk control parameters on a common platform for mitigating an accident. Quantitative analysis of a bow-tie is still a major challenge since it follows the traditional assumptions of fault and event tree analyses. The assumptions consider the crisp probabilities and “independent” relationships for the input events. The crisp probabilities for the input events are often missing or hard to come by, which introduces data uncertainty. The assumption of “independence” introduces model uncertainty. Elicitation of expert's knowledge for the missing data may provide an alternative; however, such knowledge incorporates uncertainties and may undermine the credibility of risk analysis.This paper attempts to accommodate the expert's knowledge to overcome missing data and incorporate fuzzy set and evidence theory to assess the uncertainties. Further, dependency coefficient-based fuzzy and evidence theory approaches have been developed to address the model uncertainty for bow-tie analysis. In addition, a method of sensitivity analysis is proposed to predict the most contributing input events in the bow-tie analysis. To demonstrate the utility of the approaches in industrial application, a bow-tie diagram of the BP Texas City accident is developed and analyzed.     

Arsenic,antimony, and other trace element contamination in a mine tailings affected area and uptake by tolerant plant species

The study was conducted to characterize mineralogical and elemental composition of mine tailings in order to evaluate the environmental hazards, and identify the metal accumulation potential of native plant species from São Domingos mine, one of the long-term activity mines of the Iberian Pyrite Belt dating back to pre-Roman times. The mine tailings including soils and different plant species from São Domingos were analyzed for determination of tailings characteristics and chemical element contents in tailings and plants. The large amounts of mining wastes are causing significant adverse environment impacts due to acid mine drainage production and mobilization of potentially toxic metals and metalloids in residential areas, agricultural fields, downstreams, and rivers. The typical mineralogical composition is as follows: quartz, micas, K-feldspar, olivine-group minerals, magnetite, goethite, hematite, jarosite, and sulfides. The mine tailings were highly contaminated by As, Ag, Cr, Hg, Sn, Sb, Fe, and Zn; and among them, As and Sb, main contaminants, attained the highest concentrations except Fe. Arsenic has exhibited very good correlations with Au, Fe, Sb, Se, and W; and Sb with As, Au, Fe, Se, Sn, and W in tailings. Among the all plant species, the higher concentrations of all the metals were noted in Erica andevalensis, Erica australis, Echium plantagium, and Lavandula luisierra. Considering the tolerant behavior and abundant growth, the plant species Erica australis, Erica andevalensis, Lavandula luisierra, Daphne gnidium, Rumex induratus, Ulex eriocladus, Juncus, and Genista hirsutus are of major importance for the rehabilitation and recovery of degraded São Domingos mining area.     

Assessing the Removal Efficiency of Murine Norovirus 1, Hepatitis A Virus,and Human Coronavirus 229E on Dish Surfaces Through General Wash Program of Household Dishwasher

Food and Environmental Virology - The performance of dishwashers in removing live viruses is an important informative value in practical applications. Since foodborne viruses are present in...     

Testing the extraction of 12 mycotoxins from aqueous solutions by insoluble beta-cyclodextrin bead polymer

Environmental Science and Pollution Research - Mycotoxins are toxic metabolites of filamentous fungi; they are common contaminants in numerous foods and beverages. Cyclodextrins are ring-shaped...