Testing spatial cluster occurrence in maps equipped with environmentally defined structures

We propose a novel tool for testing hypotheses concerning the adequacy of environmentally defined factors for local clustering of diseases, through the comparative evaluation of the significance of the most likely clusters detected under maps whose neighborhood structures were modified according to those factors. A multi-objective genetic algorithm scan statistic is employed for finding spatial clusters in a map divided in a finite number of regions, whose adjacency is defined by a graph structure. This cluster finder maximizes two objectives, the spatial scan statistic and the regularity of cluster shape. Instead of specifying locations for the possible clusters a priori, as is currently done for cluster finders based on focused algorithms, we alter the usual adjacency induced by the common geographical boundary between regions. In our approach, the connectivity between regions is reinforced or weakened, according to certain environmental features of interest associated with the map. We build various plausible scenarios, each time modifying the adjacency structure on specific geographic areas in the map, and run the multi-objective genetic algorithm for selecting the best cluster solutions for each one of the selected scenarios. The statistical significances of the most likely clusters are estimated through Monte Carlo simulations. The clusters with the lowest estimated p-values, along with their corresponding maps of enhanced environmental features, are displayed for comparative analysis. Therefore the probability of cluster detection is increased or decreased, according to changes made in the adjacency graph structure, related to the selection of environmental features. The eventual identification of the specific environmental conditions which induce the most significant clusters enables the practitioner to accept or reject different hypotheses concerning the relevance of geographical factors. Numerical simulation studies and an application for malaria clusters in Brazil are presented.     

Impact of calcium and magnesium on growth and morphological acclimations of Nitella: implications for calcification and nutrient dynamics

The impact of calcium (Ca) and magnesium (Mg) on the growth and morphology of a Charophyte, Nitella pseudoflabellata, and the influence of Mg on calcification and phosphorous (P) speciation were studied in laboratory experiments for variable concentrations (≤q120 mg · L^?1) of Ca and Mg. It was clearly identified that Mg aided shoot elongation. An increase in Ca concentrations produced intensified shoot elongation also, but at a lesser rate than the equivalent levels of Mg. Depending on the availability of Ca and Mg, the morphological appearance differed significantly, suggesting significant levels of ecoplasticity. Furthermore, Mg was observed to produce less calcite encrustation. Plant P-speciation suggested a higher Mg concentration corresponding to a more water-soluble and less carbonate-bound P fraction. This indicates that upon senescence and decomposition, a large fraction of P is supplied to the water column; ultimately behaving similar to a typical vascular plant.     

Arsenic speciation in polychaetes (Annelida) and sediments from the intertidal mudflat of Sundarban mangrove wetland, India

This paper documents the concentration of total arsenic and individual arsenic species in four soft-bottom benthic polychaetes (Perenereis cultifera, Ganganereis sootai, Lumbrinereis notocirrata and Dendronereis arborifera) along with host sediments from Sundarban mangrove wetland, India. An additional six sites were considered exclusively for surface sediments for this purpose. Polychaetes were collected along with the host sediments and measured for their total arsenic content using inductively coupled plasma mass spectrometry. Arsenic concentrations in polychaete body tissues varied greatly, suggesting species-specific characteristics and inherent peculiarities in arsenic metabolism. Arsenic was generally present in polychaetes as arsenate (As^V ranges from 0.16 to 0.50 mg kg^?1) or arsenite (As^III ranges from 0.10 to 0.41 mg kg^?1) (30–53 % as inorganic As) and dimethylarsinic acid (DMA^V <1–25 %). Arsenobetaine (AB < 16 %), and PO₄-arsenoriboside (8–48 %) were also detected as minor constituents, whilst monomethylarsonic acid (MA^V) was not detected in any of the polychaetes. The highest total As (14.7 mg kg^?1 dry wt) was observed in the polychaete D. arborifera collected from the vicinity of a sewage outfall in which the majority of As was present as an uncharacterised compound (10.3 mg kg^?1 dry wt) eluted prior to AB. Host sediments ranged from 2.5 to 10.4 mg kg^?1 of total As. This work supports the importance of speciation analysis of As, because of the ubiquitous occurrence of this metalloid in the environment, and its variable toxicity depending on chemical form. It is also the first work to report the composition of As species in polychaetes from the Indian Sundarban wetlands.     

New methodological strategies for detecting bacterial indicators

The development of monitoring strategies for the early warning of seawater pollution, with particular reference to faecal and hydrocarbon contamination, has been the specific goal of research carried out within the Cluster 10-SAM (Advanced Systems for Coastal Marine Monitoring) Project, funded by the Italian Ministry for University and Scientific Research. Advanced analytical approaches have been designed and applied to detect bacterial species that have been selected as potential indicators of pollution in seawater samples. We report the results obtained using the fluorescent antibody and enzymatic assays for the detection of Escherichia coli, and a real-time PCR protocol for monitoring marine areas for hydrocarbon pollution. Immunofluorescence and enzymatic methods revealed the occurrence of different faecal pollution levels, reaching 10⁵ E. coli cells 100 ml^?1 in the Straits of Messina. Real-time PCR results corresponded to the different degree of oil pollution of the analysed samples. The specificity and speed make these methods promising for the detection and evaluation of marine pollution.     

Fume emissions during gas metal arc welding

The control of exposure to welding fumes is of increasing importance in promoting a healthy, safe and productive work environment. This article describes the effects of shielding gas composition on the amount and composition of welding fumes produced during gas metal arc welding (GMAW). The amount of fumes generated during welding was measured for steady current over a range of wire-feed speeds and arc voltages using the standard procedures contained in ANSI/AWS F1.2 [American Welding Society. ANSI/AWS F1.2. Laboratory method for measuring fume generation rates and total fume emission of welding and allied processes. Miami, Florida; 1992]. Results of these measurements show that the fume formation rates (FFRs) increase with CO₂ and O₂ in the shielding gas mixture. The lowest FFRs were obtained with the mixtures of Ar?+?2%CO₂ and Ar?+?3%CO₂?+?1%O₂. The highest FFRs were obtained with the mixtures of Ar?+?18%CO₂ and Ar?+?5%CO₂?+?4%O₂. The welding fumes contains mainly iron, manganese, silicon, titanium and sodium under oxide forms. The fume cluster particles have dimensions between 0.5 and 2?µm. The FFR was found to be governed by the transfer modes of molten metal, i.e. the current intensity and arc voltage, as well as by the shielding gas mixtures composition. Thus these parameters have to be taken into consideration before designing a welding process. Whenever possible, users of GMAW should use the lowest current intensity. However, when this is not possible, due to the constraints of process productivity, welders should use higher currents, but with Ar?+?2%CO₂ and Ar?+?3%CO₂?+?1%O₂ shielding mixtures, which will lead to smaller fume emissions.     

Polychlorinated -dibenzo-p-dioxins/furans and -dioxin-like biphenyls in eggs of common terns from lime island,St. Mary's river,Michigan, USA

Population collapse of common tern (Sterna hirundo) from Lime Island in the St. Mary's River, Michigan, USA were related to the 2,3,7,8-chlorine substituted dioxins, furans, dioxin-like PCBs, and other possible factors using unhatch egg target contaminant analysis. The most toxic congeners, 2,3,7,8-TCDD/DF was found in all samples at noticeable concentrations. Magnitude of sum 2,3,7,8-PCDD/DFs were within the range of 39–93?pg/g wet wt. Dioxin-like PCBs were within the range of 360–1230?ng/g wet wt. Great Toxic Equivalent Quantity (TEQ) contributions by 2,3,7,8-TCDF, 2,3,4,7,8-PeCDF, 2,3,7,8-TCDD, 1,2,3,7,8-PeCDD, and dioxin-like PCBs such as CB-77, CB-126 and CB-105 are considered greatly due to their influence of poor embryo development and consequent damage of embryos of common terns in egg injection studies. However, other organochlorines, heavy metals, and/or synergistic effects also taken in to account. On the whole, TEQs in the tern eggs were greater than the Lowest-Observable-Adverse Effect Level (LOAEL) for bald eagle (Haliaeetus leucocephalus) embryos observed in British Columbia, Canada. Concentrations of dioxin-like PCBs, dioxins, furans in the St. Mary's River food chain are at levels for concern for nesting colonial waterbirds. Eventually, the possible movements of analyzed chemicals downstream from a man-made flood event are discussed.     

Effects of time since fire on birds: how informative are generalized fire response curves for conservation management?

Fire is both a widespread natural disturbance that affects the distribution of species and a tool that can be used to manage habitats for species. Knowledge of temporal changes in the occurrence of species after fire is essential for conservation management in fire-prone environments. Two key issues are: whether postfire responses of species are idiosyncratic or if multiple species show a limited number of similar responses; and whether such responses to time since fire can predict the occurrence of species across broad spatial scales. We examined the response of bird species to time since fire in semiarid shrubland in southeastern Australia using data from surveys at 499 sites representing a 100-year chronosequence. We used nonlinear regression to model the probability of occurrence of 30 species with time since fire in two vegetation types, and compared species' responses with generalized response shapes from the literature. The occurrence of 16 species was significantly influenced by time since fire: they displayed six main responses consistent with generalized response shapes. Of these 16 species, 15 occurred more frequently in mid- or later-successional vegetation (> 20 years since fire), and only one species occurred more often in early succession (< 5 years since fire). The models had reasonable predictive ability for eight species, some predictive ability for seven species, and were little better than random for one species. Bird species displayed a limited range of responses to time since fire; thus a small set of fire ages should allow the provision of habitat for most species. Postfire successional changes extend for decades and management of the age class distribution of vegetation will need to reflect this timescale. Response curves revealed important seral stages for species and highlighted the importance of mid- to late-successional vegetation (> 20 years). Although time since fire clearly influences the distribution of numerous bird species, predictive models of the spatial distribution of species in fire-prone landscapes need to incorporate other factors in addition to time since fire.     

Sustainability measurement of product-service systems: Brazilian case studies about electric car-sharing

Modifying the traditional production system and the culture of consumption is necessary to achieve a sustainable society. The product-service system (PSS) business model allows companies to progressively add services to physical products, thus promoting more pro-sustainable business outcomes. The purpose of this work is to verify how a PSS model can contribute to sustainability by analyzing two electric car-sharing projects using a set of five factors. As a methodological strategy, a Systematic Literature Review and a case study of the two projects (VAMO and EMOTIVE) were performed. Findings show benefits generated by both projects as to environmental aspects, mainly related to gases emission. It was also possible to observe social benefits due to income development and environmental awareness. This paper thus contributes to the discussion of the potential of the PSS models and how they can leverage business models toward a more sustainable society. Although the results are applicable only in this case, this article can motivate new projects and contribute to enriching the debate about sustainable solutions, as the literature in this field still provides few case studies showing these types of applications.     

Government liabilities for disaster risk in industrialized countries: a case study of Australia

This paper explores sovereign risk preferences against direct and indirect natural disasters losses in industrialized countries. Using Australia as a case study, the analysis compares expected disaster losses and government capacity to finance losses. Utilizing a national disaster loss dataset, extreme value theory is applied to estimate an all-hazard annual loss distribution. Unusually but critically, the dataset includes direct as well as indirect losses, allowing for the analysis to consider the oft-ignored issue of indirect losses. Expected annual losses (direct, and direct plus indirect) are overlaid with a risk-layer approach, to distinguish low, medium and extreme loss events. Each risk layer is compared to available fiscal resources for financing losses, grounded in the political reality of Australian disaster financing. When considering direct losses only, we find support for a risk-neutral preference on the part of the Australian government for low and medium loss levels, and a risk-averse preference in regard to extreme losses. When indirect losses are also estimated, we find that even medium loss levels are expected to overwhelm available fiscal resources, thereby violating the available resources assumption underlying arguments for sovereign risk neutrality. Our analysis provides empirical support for the assertion that indirect losses are a major, under-recognised concern for industrialized countries. A risk-averse preference in regard to medium and extreme loss events recommends enhanced investment in both corrective and prospective risk reduction in relation to these risks level, in particular to reduce indirect losses.