408 research outputs found

    The effect of particulate matter on paper degradation

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    Background: In this work we explore the chemical effects of particulate matter on paper. We exposed paper made of pure cellulose to the environment in different locations in central London, outdoors (in sheltered conditions) and indoors, for a period of up to 6 months. We monitored particulate matter (PM) deposition by counting the particles deposited every month with a scanning electron microscope. We analysed elemental composition of the deposited particles using inductively coupled plasma mass spectrometry. After accelerated degradation of the exposed samples, we determined the degree of polymerisation using viscometry. Results: We observed higher deposition rates and higher metal concentration outdoors than indoors. Elemental analysis of the deposited particles revealed the presence of some transition metals (Fe, Cu, Cr) that can contribute to the degradation of cellulose fibres through the Fenton reaction. By comparing the degree of polymerisation of pro‑ tected, unprotected and unexposed samples we could determine the relative contribution of PM deposition on the increase of the degradation rate. We found that the surface concentration of iron correlates with the reduction in the degree of polymerisation of the exposed paper. Conclusions: The results suggest that the presence of Fenton metals in PM has a significant effect on the accelera‑ tion of the degradation of cellulose. However, we estimate that this will unlikely occur at the levels of area coverage by PM that are typically avoided in indoor heritage through preventive maintenance and cleaning

    Fire risk modeling: an integrated and data-driven approach applied to Sicily

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    Wildfires are key not only to landscape transformation and vegetation succession, but also to socio-ecological values loss. Fire risk mapping can help to manage the most vulnerable and relevant ecosystems impacted by wildfires. However, few studies provide accessible daily dynamic results at different spatio-temporal scales. We develop a fire risk model for Sicily (Italy), an iconic case of the Mediterranean Basin, integrating a fire hazard model with an exposure and vulnerability analysis under present and future conditions. The integrated model is data-driven but can run dynamically at a daily time step, providing spatially and temporally explicit results through the k.LAB (Knowledge Laboratory) software. This software provides an environment for input data integration, combining methods and data such as geographic information systems, remote sensing and Bayesian network algorithms. All data and models are semantically annotated, open and downloadable in agreement with the FAIR principles (findable, accessible, interoperable and reusable). The fire risk analysis reveals that 45 % of vulnerable areas of Sicily have a high probability of fire occurrence in 2050. The risk model outputs also include qualitative risk indexes, which can make the results more understandable for non-technical stakeholders. We argue that this approach is well suited to aiding in landscape and fire risk management, under both current and climate change conditions.</p

    Are protected areas covering important biodiversity sites? An assessment of the nature protection network in Sicily (Italy)

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    GIS spatial analysis of three indicators (vegetation value, faunal richness and landscape heterogeneity) was used to detect and map High-Value Biodiversity Areas (HVBAs), estimate the coverage of biodiversity in the Sicilian protected areas network, and identify new priority areas that could improve long-term biodiversity conservation outcomes. Findings indicated that only 32% of HVBAs are currently covered by the protected areas network. Hotspot analysis revealed that a modest expansion (less than 1%) in the current extent of protected areas would include a disproportionate amount (56%) of biodiversity hotspots, and identified prioritized candidates HVBAs for designation of new protected areas. © 2018 Elsevier Lt

    Adult weight gain and diabetes among African American and White adults in southeastern US communities

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    To examine associations between adult weight gain and diabetes among African Americans and whites

    Individual and neighborhood-level socioeconomic characteristics in relation to smoking prevalence among black and white adults in the Southeastern United States: a cross-sectional study

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    <p>Abstract</p> <p>Background</p> <p>Low individual-level socioeconomic status (SES) is associated with higher prevalence of cigarette smoking. Recent work has examined whether neighborhood-level SES may affect smoking behavior independently from individual-level measures. However, few comparisons of neighborhood-level effects on smoking by race and gender are available.</p> <p>Methods</p> <p>Cross-sectional data from adults age 40-79 enrolled in the Southern Community Cohort Study from 2002-2009 (19, 561 black males; 27, 412 black females; 6, 231 white males; 11, 756 white females) were used in Robust Poisson regression models to estimate prevalence ratios (PRs) and 95% confidence intervals (CI) for current smoking in relation to individual-level SES characteristics obtained via interview and neighborhood-level SES characteristics represented by demographic measures from US Census block groups matched to participant home addresses.</p> <p>Results</p> <p>Several neighborhood-level SES characteristics were modestly associated with increased smoking after adjustment for individual-level factors including lower percentage of adults with a college education and lower percentage of owner-occupied households among blacks but not whites; lower percentage of households with interest, dividends, or net rental income among white males; and lower percentage of employed adults among black females.</p> <p>Conclusions</p> <p>Lower neighborhood-level SES is associated with increased smoking suggesting that cessation programs may benefit from targeting higher-risk neighborhoods as well as individuals.</p

    Epidemiology and pattern of resistance of gram-negative bacteria isolated from blood samples in hospitalized patients: A single center retrospective analysis from southern italy

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    Background: Blood culturing remains the mainstream tool to inform an appropriate treatment in hospital-acquired bloodstream infections and to diagnose any bacteremia. Methods: A retrospective investigation on the prevalence of Gram-negative bacteria (GNB) and their resistance in hospitalized patients by age, sex, and units from blood cultures (BCs) was conducted from January 2018 to April 2020 at Sant’Elia hospital, Caltanissetta, southern Italy. We divided the patient age range into four equal intervals. Results: Multivariate demographic and microbiological variables did not show an association between bacteria distributions and gender and age. The distribution by units showed a higher prevalence of Klebsiella pneumoniae and Acinetobacter baumannii in the intensive care unit (ICU) and Escherichia coli in the non-intensive care units (non-ICUs). The analysis of antibiotic resistance showed that E. coli was susceptible to a large class of antibiotics such as carbapenem and trimethoprim-sulfamethoxazole. K. pneumoniae showed a significant susceptibility to colistin, tigecycline, and trimethoprim-sulfamethoxazole. From the survival analysis, patients with E. coli had a higher survival rate. Conclusions: The authors stress the importance of the implementation of large community-level programs to prevent E. coli bacteremia. K. pneumoniae and E. coli susceptibility patterns to antibiotics, including in the prescription patterns of general practitioners, suggest that the local surveillance and implementation of educational programs remain essential measures to slow down the spread of resistance and, consequently, increase the antibiotic lifespan
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