Do not only connect: a model of infiltration-excess overland flow based on simulation

The paper focusses on connectivity in the context of infiltration-excess overland flow and its integrated response as slope-base overland flow hydrographs. Overland flow is simulated on a sloping surface with some minor topographic expression and spatially differing infiltration rates. In each cell of a 128 × 128 grid, water from upslope is combined with incident rainfall to generate local overland flow, which is stochastically routed downslope, partitioning the flow between downslope neighbours. Simulations show the evolution of connectivity during simple storms. As a first approximation, total storm runoff is similar everywhere, discharge increasing proportionally with drainage area. Moderate differences in plan topography appear to have only a second-order impact on hydrograph form and runoff amount. Total storm response is expressed as total runoff, runoff coefficient or total volume infiltrated; each plotted against total storm rainfall, and allowing variations in average gradient, overland flow roughness, infiltration rate and storm duration. A one-parameter algebraic expression is proposed that fits simulation results for total runoff, has appropriate asymptotic behaviour and responds rationally to the variables tested. Slope length is seen to influence connectivity, expressed as a scale distance that increases with storm magnitude and can be explicitly incorporated into the expression to indicate runoff response to simple events as a function of storm size, storm duration, slope length and gradient. The model has also been applied to a 10-year rainfall record, using both hourly and daily time steps, and the implications explored for coarser scale models. Initial trails incorporating erosion continuously update topography and suggest that successive storms produce an initial increase in erosion as rilling develops, while runoff totals are only slightly modified. Other factors not yet considered include the dynamics of soil crusting and vegetation growth

Food industry by-products valorization and new ingredients: cases of study

The concern about food and beverages is gaining importance for the general public in terms of health and more environmentally sustainable food products. Healthy foods imply the awareness on their safety, nutritional characteristics, and the potential inclusion of nutritive complements such as antioxidants, vitamins, and proteins, which promote a benefit to the consumer's health. Also, organic foods, with less added chemicals such as pesticides, are more demanded recently. The environmentally sustainable food production has to reconsider the wastes as by-products that can be transformed to provide valuable compounds (antioxidants, fiber, fuels, etc.) that could be used as new products or raw materials in the food industry or even applied in other sectors such as pharmaceutical, polymer, and energy industries. In this chapter, selected successful case studies in which food wastes are transformed into new products by using different separation and purification technologies will be shown. Furthermore, the use of different wild vegetables from natural environments as a source of valuable compounds and new ingredients will be described.info:eu-repo/semantics/publishedVersio

Neighborhood disparities in stroke and myocardial infarction mortality: a GIS and spatial scan statistics approach

<p>Abstract</p> <p>Background</p> <p>Stroke and myocardial infarction (MI) are serious public health burdens in the US. These burdens vary by geographic location with the highest mortality risks reported in the southeastern US. While these disparities have been investigated at state and county levels, little is known regarding disparities in risk at lower levels of geography, such as neighborhoods. Therefore, the objective of this study was to investigate spatial patterns of stroke and MI mortality risks in the East Tennessee Appalachian Region so as to identify neighborhoods with the highest risks.</p> <p>Methods</p> <p>Stroke and MI mortality data for the period 1999-2007, obtained free of charge upon request from the Tennessee Department of Health, were aggregated to the census tract (neighborhood) level. Mortality risks were age-standardized by the direct method. To adjust for spatial autocorrelation, population heterogeneity, and variance instability, standardized risks were smoothed using Spatial Empirical Bayesian technique. Spatial clusters of high risks were identified using spatial scan statistics, with a discrete Poisson model adjusted for age and using a 5% scanning window. Significance testing was performed using 999 Monte Carlo permutations. Logistic models were used to investigate neighborhood level socioeconomic and demographic predictors of the identified spatial clusters.</p> <p>Results</p> <p>There were 3,824 stroke deaths and 5,018 MI deaths. Neighborhoods with significantly high mortality risks were identified. Annual stroke mortality risks ranged from 0 to 182 per 100,000 population (median: 55.6), while annual MI mortality risks ranged from 0 to 243 per 100,000 population (median: 65.5). Stroke and MI mortality risks exceeded the state risks of 67.5 and 85.5 in 28% and 32% of the neighborhoods, respectively. Six and ten significant (p < 0.001) spatial clusters of high risk of stroke and MI mortality were identified, respectively. Neighborhoods belonging to high risk clusters of stroke and MI mortality tended to have high proportions of the population with low education attainment.</p> <p>Conclusions</p> <p>These methods for identifying disparities in mortality risks across neighborhoods are useful for identifying high risk communities and for guiding population health programs aimed at addressing health disparities and improving population health.</p

What makes a great journal great in economics?: The singer not the song

This paper analyses what makes a great journal great in economics. Alternative research assessment measures (RAM) are discussed, with an emphasis on the Thomson Reuters Institute for Scientific Information (ISI) Web of Science database. ISI RAM that are calculated annually or updated daily are defined, including the classic 2-year impact factor (2YIF), 5-year impact factor (5YIF), immediacy (zero-year impact factor (0YIF)), eigenfactor score, article influence, citation performance per paper online, h-index, Zinfluence, PI-BETA (papers ignored - by even the authors) and two new RAM measures, self-citation threshold approval rating and impact factor inflation. The data are analysed for the most highly cited journals in economics, management, business and business-finance on the basis of 2YIF. In addition to evaluating research in the most highly cited journals in economics, management, business and business-finance, the paper evaluates alternative RAM, highlights similarities and differences in RAM criteria, finds that several RAM capture similar performance characteristics, and finds that immediacy and PI-BETA are not highly correlated with other RAM. Harmonic mean rankings of the 12 RAM criteria are also presented. Emphasizing 2YIF to the exclusion of other useful RAM criteria can lead to a distorted evaluation of journal performance and influence. © 2010 Blackwell Publishing Ltd