An automated method for mapping physical soil and water conservation structures on cultivated land using GIS and remote sensing techniques

An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.

Precious earth: From soil and water conservation to sustainable land management

Proceedings of the 9th International Conference of the International Soil conservation Organisation (ISCO-9), from 26-30 August 1996 in Bonn, Germany

Knowledge of exercise recommendations and energy intake from foods and beverages in relation to exercise behaviors within two Hispanic border communities

This research is a secondary analysis of the Qué Sabrosa Vida population-based cross-sectional study of two predominately Mexican American communities located along the Texas-Mexico border in 2000. There were two aims for this research. The first was to determine the relationship between knowledge of exercise and water recommendations, and exercise behavior and water consumption. The second was to determine the relationship between exercise behavior and percentage of energy consumption from beverages. Chi-square analysis revealed the majority of both populations had adequate knowledge about water and exercise recommendations, although significant percentages of the populations (>40%) did not consume water or exercise in adequate amounts. Knowledge was found to be a component of both behaviors, as it was more prevalent in the adults who exercised and consumed water in adequate amounts. Analysis of variance revealed no significant difference between overall beverage calorie percentage and exercise level (all p-values > 0.05); both regions and genders reported ∼18% of total caloric intake from beverages. There was no disproportionate influence of beverage calories on total caloric intake, after controlling for water consumption and independent of exercise behavior. These findings suggest that overall caloric intake, from both foods and beverages, may be the most influential factor to the energy imbalance contributing to the obesity crisis in these Hispanic border populations. ^

Alterations in redox and energy metabolism in Ras-transformed cells: Mechanisms and therapeutic implications

Increasing attention has been given to the connection between metabolism and cancer. Under aerobic conditions, normal cells predominantly use oxidative phosphorylation for ATP generation. In contrast, increase of glycolytic activity has been observed in various tumor cells, which is known as Warburg effect. Cancer cells, compared to normal cells, produce high levels of Reactive Oxygen Species (ROS) and hence are constantly under oxidative stress. Increase of oxidative stress and glycolytic activity in cancer cells represent major biochemical alterations associated with malignant transformation. Despite prevalent upregulation of ROS production and glycolytic activity observed in various cancer cells, underlying mechanisms still remain to be defined. Oncogenic signals including Ras has been linked to regulation of energy metabolism and ROS production. Current study was initiated to investigate the mechanism by which Ras oncogenic signal regulates cellular metabolism and redox status. A doxycycline inducible gene expression system with oncogenic K-ras transfection was constructed to assess the role played by Ras activation in any given studied parameters. Data obtained here reveals that K-ras activation directly caused mitochondrial dysfunction and ROS generation, which appeared to be mechanistically associated with translocation of K-ras to mitochondria and the opening of the mitochondrial permeability transition pore. K-ras induced mitochondrial dysfunction led to upregulation of glycolysis and constitutive activation of ROS-generating NAD(P)H Oxidase (NOX). Increased oxidative stress, upregulation of glycolytic activity, and constitutive activated NOX were also observed in the pancreatic K-ras transformed cancer cells compared to their normal counterparts. Compared to non-transformed cells, the pancreatic K-ras transformed cancer cells with activated NOX exhibited higher sensitivity to capsaicin, a natural compound that appeared to target NOX and cause preferential accumulation of oxidative stress in K-ras transformed cells. Taken together, these findings shed new light on the role played by Ras in the road to cancer in the context of oxidative stress and metabolic alteration. The mechanistic relationship between K-ras oncogenic signals and metabolic alteration in cancer will help to identify potential molecular targets such as NAD(P)H Oxidase and glycolytic pathway for therapeutic intervention of cancer development. ^

Habitat characteristics and energy budget of the ocean quahog (Arctica islandica)

We compared lifetime and population energy budgets of the extraordinary long-lived ocean quahog Arctica islandica from 6 different sites - the Norwegian coast, Kattegat, Kiel Bay, White Sea, German Bight, and off northeast Iceland - covering a temperature and salinity gradient of 4-10°C (annual mean) and 25-34, respectively. Based on von Bertalanffy growth models and size-mass relationships, we computed organic matter production of body (PSB) and of shell (PSS), whereas gonad production (PG) was estimated from the seasonal cycle in mass. Respiration (R) was computed by a model driven by body mass, temperature, and site. A. islandica populations differed distinctly in maximum life span (40 y in Kiel Bay to 197 y in Iceland), but less in growth performance (phi' ranged from 2.41 in the White Sea to 2.65 in Kattegat). Individual lifetime energy throughput, as approximated by assimilation, was highest in Iceland (43,730 kJ) and lowest in the White Sea (313 kJ). Net growth efficiency ranged between 0.251 and 0.348, whereas lifetime energy investment distinctly shifted from somatic to gonad production with increasing life span; PS/PG decreased from 0.362 (Kiel Bay, 40 y) to 0.031 (Iceland, 197 y). Population annual energy budgets were derived from individual budgets and estimates of population mortality rate (0.035/y in Iceland to 0.173/y in Kiel Bay). Relationships between budget ratios were similar on the population level, albeit with more emphasis on somatic production; PS/ PG ranged from 0.196 (Iceland) to 2.728 (White Sea), and P/B ranged from 0.203-0.285/y. Life span is the principal determinant of the relationship between budget parameters, whereas temperature affects net growth efficiency only. In the White Sea population, both growth performance and net growth efficiency of A. islandica were lowest. We presume that low temperature combined with low salinity represent a particularly stressful environment for this species.

Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

Cost and energy efficient reconfigurable embedded platform using Spartan-6 FPGAs

Modern FPGAs with run-time reconfiguration allow the implementation of complex systems offering both the flexibility of software-based solutions combined with the performance of hardware. This combination of characteristics, together with the development of new specific methodologies, make feasible to reach new points of the system design space, and make embedded systems built on these platforms acquire more and more importance. However, the practical exploitation of this technique in fields that traditionally have relied on resource restricted embedded systems, is mainly limited by strict power consumption requirements, the cost and the high dependence of DPR techniques with the specific features of the device technology underneath. In this work, we tackle the previously reported problems, designing a reconfigurable platform based on the low-cost and low-power consuming Spartan-6 FPGA family. The full process to develop the platform will be detailed in the paper from scratch. In addition, the implementation of the reconfiguration mechanism, including two profiles, is reported. The first profile is a low-area and low-speed reconfiguration engine based mainly on software functions running on the embedded processor, while the other one is a hardware version of the same engine, implemented in the FPGA logic. This reconfiguration hardware block has been originally designed to the Virtex-5 family, and its porting process will be also described in this work, facing the interoperability problem among different families.

Risk sharing with Multilateral Financial Institutions in infrastructure and energy project financing : effect on capital relief for commercial banks

(Matsukawa and Habeck, 2007) analyse the main instruments for risk mitigation in infrastructure financing with Multilateral Financial Institutions (MFIs). Their review coincided with the global financial crisis of 2007-08, and is highly relevant in current times considering the sovereign debt crisis, the lack of available capital and the increases in bank regulation in Western economies. The current macroeconomic environment has seen a slowdown in the level of finance for infrastructure projects, as they pose a higher credit risk given their requirements for long term investments. The rationale for this work is to look for innovative solutions that are focused on the credit risk mitigation of infrastructure and energy projects whilst optimizing the economic capital allocation for commercial banks. This objective is achieved through risk-sharing with MFIs and looking for capital relief in project finance transactions. This research finds out the answer to the main question: "What is the impact of risk-sharing with MFIs on project finance transactions to increase their efficiency and viability?", and is developed from the perspective of a commercial bank assessing the economic capital used and analysing the relevant variables for it: Probability of Default, Loss Given Default and Recovery Rates, (Altman, 2010). An overview of project finance for the infrastructure and energy sectors in terms of the volume of transactions worldwide is outlined, along with a summary of risk-sharing financing with MFIs. A review of the current regulatory framework beneath risk-sharing in structured finance with MFIs is also analysed. From here, the impact of risk-sharing and the diversification effect in infrastructure and energy projects is assessed, from the perspective of economic capital allocation for a commercial bank. CreditMetrics (J. P. Morgan, 1997) is applied over an existing well diversified portfolio of project finance infrastructure and energy investments, working with the main risk capital measures: economic capital, RAROC, and EVA. The conclusions of this research show that economic capital allocation on a portfolio of project finance along with risk-sharing with MFIs have a huge impact on capital relief whilst increasing performance profitability for commercial banks. There is an outstanding diversification effect due to the portfolio, which is combined with risk mitigation and an improvement in recovery rates through Partial Credit Guarantees issued by MFIs. A stress test scenario analysis is applied to the current assumptions and credit risk model, considering a downgrade in the rating for the commercial bank (lender) and an increase of default in emerging countries, presenting a direct impact on economic capital, through an increase in expected loss and a decrease in performance profitability. Getting capital relief through risk-sharing makes it more viable for commercial banks to finance infrastructure and energy projects, with the beneficial effect of a direct impact of these investments on GDP growth and employment. The main contribution of this work is to promote a strategic economic capital allocation in infrastructure and energy financing through innovative risk-sharing with MFIs and economic pricing to create economic value added for banks, and to allow the financing of more infrastructure and energy projects. This work suggests several topics for further research in relation to issues analysed. (Matsukawa and Habeck, 2007) analizan los principales instrumentos de mitigación de riesgos en las Instituciones Financieras Multilaterales (IFMs) para la financiación de infraestructuras. Su presentación coincidió con el inicio de la crisis financiera en Agosto de 2007, y sus consecuencias persisten en la actualidad, destacando la deuda soberana en economías desarrolladas y los problemas capitalización de los bancos. Este entorno macroeconómico ha ralentizado la financiación de proyectos de infraestructuras. El actual trabajo de investigación tiene su motivación en la búsqueda de soluciones para la financiación de proyectos de infraestructuras y de energía, mitigando los riesgos inherentes, con el objeto de reducir el consumo de capital económico en los bancos financiadores. Este objetivo se alcanza compartiendo el riesgo de la financiación con IFMs, a través de estructuras de risk-sharing. La investigación responde la pregunta: "Cuál es el impacto de risk-sharing con IFMs, en la financiación de proyectos para aumentar su eficiencia y viabilidad?". El trabajo se desarrolla desde el enfoque de un banco comercial, estimando el consumo de capital económico en la financiación de proyectos y analizando las principales variables del riesgo de crédito, Probability of Default, Loss Given Default and Recovery Rates, (Altman, 2010). La investigación presenta las cifras globales de Project Finance en los sectores de infraestructuras y de energía, y analiza el marco regulatorio internacional en relación al consumo de capital económico en la financiación de proyectos en los que participan IFMs. A continuación, el trabajo modeliza una cartera real, bien diversificada, de Project Finance de infraestructuras y de energía, aplicando la metodología CreditMet- rics (J. P. Morgan, 1997). Su objeto es estimar el consumo de capital económico y la rentabilidad de la cartera de proyectos a través del RAROC y EVA. La modelización permite estimar el efecto diversificación y la liberación de capital económico consecuencia del risk-sharing. Los resultados muestran el enorme impacto del efecto diversificación de la cartera, así como de las garantías parciales de las IFMs que mitigan riesgos, mejoran el recovery rate de los proyectos y reducen el consumo de capital económico para el banco comercial, mientras aumentan la rentabilidad, RAROC, y crean valor económico, EVA. En escenarios económicos de inestabilidad, empeoramiento del rating de los bancos, aumentos de default en los proyectos y de correlación en las carteras, hay un impacto directo en el capital económico y en la pérdida de rentabilidad. La liberación de capital económico, como se plantea en la presente investigación, permitirá financiar más proyectos de infraestructuras y de energía, lo que repercutirá en un mayor crecimiento económico y creación de empleo. La principal contribución de este trabajo es promover la gestión activa del capital económico en la financiación de infraestructuras y de proyectos energéticos, a través de estructuras innovadoras de risk-sharing con IFMs y de creación de valor económico en los bancos comerciales, lo que mejoraría su eficiencia y capitalización. La aportación metodológica del trabajo se convierte por su originalidad en una contribución, que sugiere y facilita nuevas líneas de investigación académica en las principales variables del riesgo de crédito que afectan al capital económico en la financiación de proyectos.

Nonequlibrium particle and energy currents in quantum chains connected to mesoscopic Fermi reservoirs

We propose a model of nonequilibrium quantum transport of particles and energy in a system connected to mesoscopic Fermi reservoirs (mesoreservoir). The mesoreservoirs are in turn thermalized to prescribed temperatures and chemical potentials by a simple dissipative mechanism described by the Lindblad equation. As an example, we study transport in monoatomic and diatomic chains of noninteracting spinless fermions. We show numerically the breakdown of the Onsager reciprocity relation due to the dissipative terms of the model.

Continuous multi-criteria methods for crop and soil conservation planning on La Colacha (Río Cuarto, Province of Cordoba, Argentina)

Agro-areas of Arroyos Menores (La Colacha) west and south of Rand south of R?o Cuarto (Prov. of Cordoba, Argentina) basins are very fertile but have high soil loses. Extreme rain events, inundations and other severe erosions forming gullies demand urgently actions in this area to avoid soil degradation and erosion supporting good levels of agro production. The authors first improved hydrologic data on La Colacha, evaluated the systems of soil uses and actions that could be recommended considering the relevant aspects of the study area and applied decision support systems (DSS) with mathematic tools for planning of defences and uses of soils in these areas. These were conducted here using multi-criteria models, in multi-criteria decision making (MCDM); first of discrete MCDM to chose among global types of use of soils, and then of continuous MCDM to evaluate and optimize combined actions, including repartition of soil use and the necessary levels of works for soil conservation and for hydraulic management to conserve against erosion these basins. Relatively global solutions for La Colacha area have been defined and were optimised by Linear Programming in Goal Programming forms that are presented as Weighted or Lexicographic Goal Programming and as Compromise Programming. The decision methods used are described, indicating algorithms used, and examples for some representative scenarios on La Colacha area are given.