The Use of Landsat 8 and Sentinel-2 Data and Meterological Observations for Winter Wheat Yield Assessment

This study focuses on winter wheat yield assessment from NASA's Harmonized Landsat Sentinel-2 (HLS) product and meteorological observations through phenological fitting. Vegetation indices (VIs), namely difference vegetation index (DVI), normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI2), extracted from satellite optical data, are fitted per pixel against accumulated growing degree days (AGDD) using a quadratic function. Accumulated VIs are correlated against winter wheat yields. Results show a better performance from DVI compared to NDVI and EVI2

Riesgo cardiovascular y metabolismo de la glucosa: acuerdos y discrepancias entre las clasificaciones OMS-85 y ADA-97

ObjetivoConocer las diferencias entre el riesgo coronario de los sujetos con glucemia basal alterada (GBA), intolerancia oral a la glucosa (ITG) y diabetes mellitus tipo 2 según las clasificaciones diagnósticas de la OMS-85 y ADA-97 en una población adulta con un riesgo alto de presentar diabetes mellitus.DiseñoEstudio descriptivo, transversal, multicéntrico.EmplazamientoAtención primaria, 7 centros de salud.PacientesUn total de 970 sujetos considerados población de riesgo para diabetes mellitus tipo 2.MedicionesSe clasificaron los sujetos según los criterios OMS-85 (normales, ITG, diabetes) y según la ADA-97 (normales, GBA y diabetes). Se recogieron las siguientes variables: edad, sexo, consumo de tabaco, índice de masa corporal, tensión arterial sistólica, tensión arterial diastólica, glucemia basal, glucemia a las 2 horas de la PTOG, HbA1c, microalbuminuria, colesterol total, cHDL, cLDL, triglicéridos y se estimó el cálculo del riesgo coronario mediante la tabla de Wilson et al de 1998, basada en el estudio Framingham.ResultadosSe evaluó a 970 sujetos con una edad media de 58,6 ± 12,4 años, 453 varones (46,7%) y 517 mujeres (53,3%). En el análisis de la presencia de factores de riesgo cardiovascular se observa que éstos son menos frecuentes en los sujetos normales y que su prevalencia es más elevada en los diabéticos (OMS y ADA). No existen diferencias significativas entre el riesgo coronario y los diversos factores de riesgo cuando se analizan grupos homónimos OMS–ADA (normales, ITG-GBA o diabéticos). Según la clasificación de la OMS-85, el riesgo coronario en los distintos tipos de alteraciones del metabolismo de la glucosa fue un 11,3% en sujetos normales, un 14% en ITG y un 27,3% en diabéticos, y según la ADA-97 un 11,4% en sujetos normales, un 15,7% en GBA y un 29,5% en diabéticos.ConclusionesA mayor grado de patología hidrocarbonada, mayor coexistencia de factores de riesgo y mayor estimación del riesgo coronario. No hay diferencias importantes entre los estadios de las clasificaciones OMS y ADA ni en la presencia de factores de riesgo cardiovascular ni en relación al riesgo coronario.AimTo identify the differences between coronary heart disease risk in patients with altered basal glucemia (ABG), oral glucose intolerance (OGI) and type II diabetes mellitus according to the WHO-85 and ADA-97 diagnostic classifications, in an adult population at high risk for diabetes mellitus.DesignDescriptive, cross-sectional, multicenter study.SettingSeven primary health care centers in Spain.Patient970 persons considered the population at risk for type II diabetes mellitus.MeasuresParticipants were classified according to the criteria of the WHO-85 (normal, OGI, diabetes) and the ADA-97 system (normal, ABG, diabetes). The following variables were recorded: age, sex, smoking habit, body mass index, systolic blood pressure, diastolic blood pressure, basal glucemia, glucemia 2 h after an oral glucose tolerance test, HbA1c, microalbmuniuria, total cholesterol, HDL, LDL and triglycerides. Coronary heart disease risk was calculated with the 1998 table developed by Wilson et al. on the basis of the Framingham study.ResultsA total of 970 participants were studied. Mean age was 58.6 #+ 12.4 years; 453 were men (46.7%) and 517 were women (53.3%). Our analysis showed that cardiovascular disease risk factors were less frequent in normal subjects, and that their prevalence was higher in persons with diabetes (according to both WHO and ADA classifications). There were no significant differences in coronary heart disease risk or different risk factors between analogous groups in the two classification systems (normal, OGI/ABG or diabetes). Coronary heart disease risk in persons with different types of alterations in glucose metabolism was 11.3% in normal subjects, 14% in persons with OGI and 27.3% in persons with diabetes according to the WHO-85 system, and 11.4% in normal subjects, 15.7% in persons with ABG and 29.5% in persons with diabetes according to the ADA-97 system.ConclusionsThe greater the alteration in carbohydrate metabolism, the greater the coexistence of risk factors and the estimated risk of coronary heart disease. There were no significant differences in the presence of cardiovascular risk factors, or in the relationship between carbohydrate metabolism and coronary heart disease risk, between analogous stages identified with one classification system or the other

Photometric type Ia supernova surveys in narrow band filters

We study the characteristics of a narrow band type Ia supernova survey through simulations based on the upcoming Javalambre Physics of the accelerating universe Astrophysical Survey (J-PAS). This unique survey has the capabilities of obtaining distances, redshifts, and the SN type from a single experiment thereby circumventing the challenges faced by the resource-intensive spectroscopic follow-up observations. We analyse the flux measurements signal-to-noise ratio and bias, the supernova typing performance, the ability to recover light curve parameters given by the SALT2 model, the photometric redshift precision from type Ia supernova light curves and the effects of systematic errors on the data. We show that such a survey is not only feasible but may yield large type Ia supernova samples (up to 250 supernovae at $z<0.5$ per month of search) with low core collapse contamination ($\sim 1.5$ per cent), good precision on the SALT2 parameters (average $\sigma_{m_B}=0.063$, $\sigma_{x_1}=0.47$ and $\sigma_c=0.040$) and on the distance modulus (average $\sigma_{\mu}=0.16$, assuming an intrinsic scatter $\sigma_{\mathrm{int}}=0.14$), with identified systematic uncertainties $\sigma_{\mathrm{sys}}\lesssim 0.10 \sigma_{\mathrm{stat}}$. Moreover, the filters are narrow enough to detect most spectral features and obtain excellent photometric redshift precision of $\sigma_z=0.005$, apart from $\sim$ 2 per cent of outliers. We also present a few strategies for optimising the survey's outcome. Together with the detailed host galaxy information, narrow band surveys can be very valuable for the study of supernova rates, spectral feature relations, intrinsic colour variations and correlations between supernova and host galaxy properties, all of which are important information for supernova cosmological applications.Comment: 20 pages, 12 tables and 26 figures. Version accepted by MNRAS, with results slightly different from previous on

Evaluation of the MODIS Albedo Product over a Heterogeneous Agricultural Area

In this article, the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF)/Albedo product (MCD43) is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction (EODIX) project campaign, which was developed in Barrax (Spain) in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal (RTLSR) (which corresponds to the MODIS BRDF algorithm) and the RossThick-Maignan-LiSparse-Reciprocal (RTLSR-HS), were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor. During the campaign, airborne images were retrieved with different view zenith angles along the principal and orthogonal planes. Comparing the results of applying the models to the airborne data with ground measurements, we obtained a root mean square error (RMSE) of 0.018 with both RTLSR and RTLSR-HS models. The evaluation of the MODIS BRDF/Albedo product (MCD43) was performed by comparing satellite images with AHS estimations. The results reported an RMSE of 0.04 with both models. Additionally, taking advantage of a homogeneous barley pixel, we compared in situ albedo data to satellite albedo data. In this case, the MODIS albedo estimation was (0.210 +/- 0.003), while the in situ measurement was (0.204 +/- 0.003). This result shows good agreement in regard to a homogeneous pixel

The influence of the C+N+O abundances on the determination of the relative ages of Globular Clusters: the case of NGC 1851 and NGC 6121 (M4)

The color magnitude diagram (CMD) of NGC 1851 presents two subgiant branches (SGB), probably due the presence of two populations differing in total CNO content. We test the idea that a difference in total CNO may simulate an age difference when comparing the CMD of clusters to derive relative ages. We compare NGC 1851 with NGC 6121 (M4), a cluster of very similar [Fe/H]. We find that, with a suitable shift of the CMDs that brings the two red horizontal branches at the same magnitude level, the unevolved main sequence and red giant branch match, but the SGB of NGC 6121 and its red giant branch "bump" are fainter than in NGC 1851. In particular, the SGB of NGC 6121 is even slightly fainter than the the faint SGB in NGC 1851. Both these features can be explained if the total CNO in NGC 6121 is larger than that in NGC 1851, even if the two clusters are coeval. We conclude by warning that different initial C+N+O abundances between two clusters, otherwise similar in metallicity and age, may lead to differences in the turnoff morphology that can be easily attributed to an age difference.Comment: accepted for publication in MNRA

Differential clinical efficacy of anti-CD4 monoclonal antibodies in rat adjuvant arthritis is paralleled by differential influence on NF-κB binding activity and TNF-α secretion of T cells

The aim of this study was to analyze the differential effects of three anti-CD4 monoclonal antibodies (mAbs) (with distinct epitope specifities) in the treatment of rat adjuvant arthritis (AA) and on T-cell function and signal transduction. Rat AA was preventively treated by intraperitoneal injection of the anti-CD4 mAbs W3/25, OX35, and RIB5/2 (on days -1, 0, 3, and 6, i.e. 1 day before AA induction, on the day of induction [day 0], and thereafter). The effects on T-cell reactivity in vivo (delayed-type hypersensitivity), ex vivo (ConA-induced proliferation), and in vitro (mixed lymphocyte culture) were assessed. The in vitro effects of anti-CD4 preincubation on T-cell receptor (TCR)/CD3-induced cytokine production and signal transduction were also analyzed. While preventive treatment with OX35 and W3/25 significantly ameliorated AA from the onset, treatment with RIB5/2 even accelerated the onset of AA by approximately 2 days (day 10), and ameliorated the arthritis only in the late phase (day 27). Differential clinical effects at the onset of AA were paralleled by a differential influence of the mAbs on T-cell functions, i.e. in comparison with OX35 and W3/25, the 'accelerating' mAb RIB5/2 failed to increase the delayed-type hypersentivity (DTH) to Mycobacterium tuberculosis, increased the in vitro tumor necrosis factor (TNF)-α secretion, and more strongly induced NF-κB binding activity after anti-CD4 preincubation and subsequent TCR/CD3-stimulation. Depending on their epitope specificity, different anti-CD4 mAbs differentially influence individual proinflammatory functions of T cells. This fine regulation may explain the differential efficacy in the treatment of AA and may contribute to the understanding of such treatments in other immunopathologies

Enhancing Remote Sensing Based Yield Forecasting: Application to Winter Wheat in United States

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. In Becker-Reshef et al. (2010) and Franch et al. (2015) we developed an empirical generalized model for forecasting winter wheat yield. In this study we present a new model based on the extrapolation of the pure wheat signal (100 percent of wheat within the pixel) from MODIS (Moderate-resolution Imaging Spectroradiometer) data at 1-kilometer resolution and using the Difference Vegetation Index (DVI). The model has been applied to monitor the national and state level yield of winter wheat in the United States from 2001 to 2016

The ACS Survey of Galactic Globular Clusters. III. The Double Subgiant Branch of NGC 1851

Photometry with HST's ACS reveals that the subgiant branch (SGB) of the globular cluster NGC 1851 splits into two well-defined branches. If the split is due only to an age effect, the two SGBs would imply two star formation episodes separated by $\sim$ 1 Gyr. We discuss other anomalies in NGC 1851 which could be interpreted in terms of a double stellar population. Finally, we compare the case of NGC 1851 with the other two globulars known to host multiple stellar populations, and show that all three clusters differ in several important respects.Comment: 22 pages, 7 figures, accepted for pubblication on Ap

Evaluation of Near-Surface Air Temperature from Reanalysis over the United States and Ukraine: Application to Winter Wheat Yield Forecasting

In this work we evaluate the near-surface air temperature datasets from the ERA-Interim, JRA55, MERRA2, NCEP1, and NCEP2 reanalysis projects. Reanalysis data were first compared to observations from weather stations located on wheat areas of the United States and Ukraine, and then evaluated in the context of a winter wheat yield forecast model. Results from the comparison with weather station data showed that all datasets performed well (r2>0.95) and that more modern reanalysis such as ERAI had lower errors (RMSD ~ 0.9) than the older, lower resolution datasets like NCEP1 (RMSD ~ 2.4). We also analyze the impact of using surface air temperature data from different reanalysis products on the estimations made by a winter wheat yield forecast model. The forecast model uses information of the accumulated Growing Degree Day (GDD) during the growing season to estimate the peak NDVI signal. When the temperature data from the different reanalysis projects were used in the yield model to compute the accumulated GDD and forecast the winter wheat yield, the results showed smaller variations between obtained values, with differences in yield forecast error of around 2% in the most extreme case. These results suggest that the impact of temperature discrepancies between datasets in the yield forecast model get diminished as the values are accumulated through the growing season