The effect of particulate matter on paper degradation

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

A focus group study for the design of a web-based tool for improving problem-solving in older adults

The development of easily accessible and usable social and cognitive enhancement trainings is becoming a priority to reduce the impact of aging on quality of life. Since most activities of daily living (e.g., making a meal) require problem-solving skills, problem-solving interventions could be used to improve and/or maintain functional abilities in aging to prolong independence. To design an effective problem-solving training and increase older adults' adherence to the training, this study examined older adults' perceptions of their challenges in activities of daily living, their skills and difficulties in using information technology (IT), and their motivations and expectations for participating in a web-based problem-solving training activity. Four focus groups (two in Italy and two in the Netherlands) were conducted with older adults aged between 65 and 84 years, a total of 27 participants. The data were analyzed using the Atlas.ti 8 software for the thematic analysis. The analysis identified five thematic areas: interests and activities, difficulties and concerns, experiences and motivations for training, expertise and resources, suggestions for the design of the new training. The results were used to develop a first prototype of a Shared, Web-based, Intelligent Flexible Thinking Training (SWIFT), adapted to future user needs. The participation of older adults in this design phase was critical to understanding their needs, motivations, and expectations regarding the implementation and use of a cognitive enhancement training.</p

Sedentary and Physically Active Behavior Patterns Among Low-Income African-American and White Adults Living in the Southeastern United States

Increased sedentary behavior and lack of physical activity are associated with increased risk for many chronic diseases. Differences in leisure-time physical activity between African American and white adults have been suggested to partially explain racial disparities in chronic disease outcomes, but expanding the definition of physical activity to include household and occupational activities may reduce or even eliminate racial differences in total physical activity. The objective of this study was to describe patterns of active and sedentary behaviors in black and white adults and to examine these behaviors across demographic measures. Sedentary and physically active behaviors were obtained from a validated physical activity questionnaire in 23,021 black men, 9,899 white men, 32,214 black women, and 15,425 white women (age 40–79) at enrollment into the Southern Community Cohort Study. Descriptive statistics for sedentary time; light, moderate, and vigorous household/occupational activity; sports/exercise; total activity; and meeting current physical activity recommendations via sports/exercise were examined for each race-sex group. Adjusted means were calculated using multiple linear regression models across demographic measures. Study participants spent approximately 60% of waking time in sedentary behaviors. Blacks reported more television viewing time than whites (45 minutes for females, 15 minutes for males), but when sitting time was expressed as a proportion of overall awake time, minimal racial differences were found. Patterns of light, moderate, and vigorous household/occupational activity were similar in all race/sex groups. 2008 Physical Activity Guidelines for Americans were followed by 16% of women and 25% of men independent of race. Overall, black and white men and women in this study spent the majority of their daily time in sedentary behaviors and less than one-fourth followed current guidelines for physical activity. These results indicate that public health campaigns should focus on both reducing sedentary behavior and increasing physical activity in all adult US populations

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

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)

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

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

<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