SITUACIÓN ACTUAL DE LA SOBERANÍA Y SEGURIDAD ALIMENTARIA Y NUTRICIONAL EN ONCE COMUNIDADES DEL MUNICIPIO EL SAUCE, DEPARTAMENTO DE LEÓN, NICARAGUA EN EL PERIODO 2015-2016

RESUMEN El presente proyecto de investigación da a conocer resultados de trabajo de campo y sus principales funciones se dirigieron al fortalecimiento institucional para promover un proceso de gobernanza de la Soberanía, Seguridad Alimentaria y Nutricional a nivel local. Las comunidades asignadas fueron Los Panales (caseríos Nueva Esperanza, Nueva España), Los Loros (todos los caseríos), Santa Bárbara, (caseríos Agua Fría), Guacucal (caseríos Santa Lucía), Sálales (caseríos Lasla y las Cigarreras), Valle San Antonio (caseríos El Tempisque), Los Altos de Ocotal (caseríos Buena Vista, Guayabo, Las Minitas y Cerro Colorado); todos los caseríos de Las Mercedes, Sábana Grande, Los Tololos y San Ramón; en la mayor parte de los caseríos de La Palma, Santa Lucía, y se brindó seguimiento parcial a las comunidades del municipio El Sauce, departamento de León. Los principales resultados de la investigación estuvieron basados en el eje de “Articulación interinstitucional al implementar un mecanismo que ayude a reducir la desnutrición y forjar la Soberanía, Seguridad Alimentaria y Nutricional a nivel local en once comunidades del municipio El Sauce”, estos fueron: Fortalecimiento de la gobernanza municipal en Soberanía, Seguridad Alimentaria y Nutricional como resultados de acciones interinstitucionales que se promueven a nivel local. Fortalecimiento institucional sobre el uso de herramientas básicas y mecanismos de gestión a nivel local en pro de la Soberanía, Seguridad Alimentaria y Nutricional. Acompañamiento de los procesos ejecutados en pro del bienestar de las familias, su calidad de vida y un desarrollo humano sostenible

Relationships between Remotely Sensed Data and Biomass Components in a Big Sagebrush (Artemisia tridentata) Dominated Area in Yellowstone National Park

Abstract: The predictive power of a hyperspectral imagery for estimating woody and herbaceous biomass were examined for a big sagebrush (Artemisia tridentata) dominated area in Yellowstone National Park, Wyoming, United States of America. The normalized difference vegetation (NDV) and structure insensitive pigment (SIP) indices were used to investigate the relationships between biomass components and reflectance spectra. Ground data were collected in 13 sample plots 1 m 2 in size by clipping all herbaceous vegetation to ground level and stripping green leaves from big sagebrush plants. Strong relationships (R 2 from 0.83 to 0.96) were found between the hyperspectral data and biomass components. The results indicate that fine resolution hyperspectral imagery is capable of estimating various biomass components in big sagebrush dominated areas

GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures

© 2019, The Author(s). Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N ≥ 28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N = 13,608 – 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is with rs11614913[T] in the microRNA MIR196A2 gene that associates with lumbar spine area (P = 2.3 × 10−42, β = −0.090) and confers risk of hip fracture (P = 1.0 × 10−8, OR = 1.11). We demonstrate that the risk allele is less efficient in repressing miR-196a-5p target genes. We also show that the DXA area measure contributes to the risk of hip fracture independent of bone density

The public health benefits of insulation retrofits in existing housing in the United States

BACKGROUND: Methodological limitations make it difficult to quantify the public health benefits of energy efficiency programs. To address this issue, we developed a risk-based model to estimate the health benefits associated with marginal energy usage reductions and applied the model to a hypothetical case study of insulation retrofits in single-family homes in the United States. METHODS: We modeled energy savings with a regression model that extrapolated findings from an energy simulation program. Reductions of fine particulate matter (PM(2.5)) emissions and particle precursors (SO(2 )and NOx) were quantified using fuel-specific emission factors and marginal electricity analyses. Estimates of population exposure per unit emissions, varying by location and source type, were extrapolated from past dispersion model runs. Concentration-response functions for morbidity and mortality from PM(2.5 )were derived from the epidemiological literature, and economic values were assigned to health outcomes based on willingness to pay studies. RESULTS: In total, the insulation retrofits would save 800 TBTU (8 × 10(14 )British Thermal Units) per year across 46 million homes, resulting in 3,100 fewer tons of PM(2.5), 100,000 fewer tons of NOx, and 190,000 fewer tons of SO(2 )per year. These emission reductions are associated with outcomes including 240 fewer deaths, 6,500 fewer asthma attacks, and 110,000 fewer restricted activity days per year. At a state level, the health benefits per unit energy savings vary by an order of magnitude, illustrating that multiple factors (including population patterns and energy sources) influence health benefit estimates. The health benefits correspond to $1.3 billion per year in externalities averted, compared with$5.9 billion per year in economic savings. CONCLUSION: In spite of significant uncertainties related to the interpretation of PM(2.5 )health effects and other dimensions of the model, our analysis demonstrates that a risk-based methodology is viable for national-level energy efficiency programs

Taxonomic and Environmental Variability in the Elemental Composition and Stoichiometry of Individual Dinoflagellate and Diatom Cells from the NW Mediterranean Sea

Here we present, for the first time, the elemental concentration, including C, N and O, of single phytoplankton cells collected from the sea. Plankton elemental concentration and stoichiometry are key variables in phytoplankton ecophysiology and ocean biogeochemistry, and are used to link cells and ecosystems. However, most field studies rely on bulk techniques that overestimate carbon and nitrogen because the samples include organic matter other than plankton organisms. Here we used X-ray microanalysis (XRMA), a technique that, unlike bulk analyses, gives simultaneous quotas of C, N, O, Mg, Si, P, and S, in single-cell organisms that can be collected directly from the sea. We analysed the elemental composition of dinoflagellates and diatoms (largely Chaetoceros spp.) collected from different sites of the Catalan coast (NW Mediterranean Sea). As expected, a lower C content is found in our cells compared to historical values of cultured cells. Our results indicate that, except for Si and O in diatoms, the mass of all elements is not a constant fraction of cell volume but rather decreases with increasing cell volume. Also, diatoms are significantly less dense in all the measured elements, except Si, compared to dinoflagellates. The N:P ratio of both groups is higher than the Redfield ratio, as it is the N:P nutrient ratio in deep NW Mediterranean Sea waters (N:P = 20–23). The results suggest that the P requirement is highest for bacterioplankton, followed by dinoflagellates, and lowest for diatoms, giving them a clear ecological advantage in P-limited environments like the Mediterranean Sea. Finally, the P concentration of cells of the same genera but growing under different nutrient conditions was the same, suggesting that the P quota of these cells is at a critical level. Our results indicate that XRMA is an accurate technique to determine single cell elemental quotas and derived conversion factors used to understand and model ocean biogeochemical cycles

The sequences of 150,119 genomes in the UK Biobank

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data(1,2). Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank(3). This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation