INTEGRATING OPTICAL AND RADAR IMAGERY TO ENHANCE RIVER DROUGHT MONITORING

Drought events are growingly affecting European and Italian territories, hampering local environments and biodiversity, such as the ones relying on rivers for their subsistence. Monitoring of rivers is becoming an important issue to face drought crisis and may be exploited with different tools. Among the most commons, satellite imagery is exploited to map water coverage, basing on optical or radar sources. This work proposes a combination of the two sensors to overcome possible limitations of the single dataset exploitation, reaching a reliable result. The methodology is applied to a stretch of Po River in Lombardy region (Italy). Through Google Earth Engine platform, optical satellite Sentinel-2 and radar satellite Sentinel-1 data are processed. The combination of the radar data and of the optical spectral indices is carried out through a pixel-based supervised classification, with a Random Forest classifier. Maps of water coverage are obtained, numerical outcomes of water surface evaluation are recorded and validated by the mean of reference hydrometric data. A multitemporal analysis is then reported, aiming to prove the efficiency of the procedure. All iterations show reliable accuracies and correlation among water surface estimation and water table measurements in two sections of interest. In perspective, the proposed methodology will be implemented in tools for supporting drought monitoring to be integrated in environmental public administration policies

Precision measurement of Compton scattering in silicon with a skipper CCD for dark matter detection

Experiments aiming to directly detect dark matter through particle recoils can achieve energy thresholds of O(10  eV). In this regime, ionization signals from small-angle Compton scatters of environmental γ rays constitute a significant background. Monte Carlo simulations used to build background models have not been experimentally validated at these low energies. We report a precision measurement of Compton scattering on silicon atomic shell electrons down to 23 eV. A skipper charge-coupled device with single-electron resolution, developed for the DAMIC-M experiment, was exposed to a 241Am γ-ray source over several months. Features associated with the silicon K-, L1-, and L2,3-shells are clearly identified, and scattering on valence electrons is detected for the first time below 100 eV. We find that the relativistic impulse approximation for Compton scattering, which is implemented in Monte Carlo simulations commonly used by direct detection experiments, does not reproduce the measured spectrum below 0.5 keV. The data are in better agreement with ab initio calculations originally developed for x-ray absorption spectroscopy

Towards automation of river water surface detection

European rivers are increasingly impacted by frequent and lasting dry periods, with consequences on jeopardized ecosystems and local economies. Tools for monitoring the evolution of such impacts may be profitable exploited by public administration to assess environmental conditions and draw safeguard policies. This work presents the evolution of a methodology which integrates optical and radar imagery, by Copernicus Sentinel constellations, to map river water surfaces. Despite the base methodology being developed as a man-supervised classification, with necessity for the user to manually define training polygons, the proposed advancements will allow the system to automate training sample extraction. The process is based on the realization of binary masks, originated by processing optical and radar imagery with a BMax Otsu algorithm for image segmentation. The masks are then furtherly refined to obtain a reliable set of classified pixels, from which the training samples are extracted. A sensitivity analysis is performed for assessing the optimal amount of pixels to be considered, with respect to the total area of interest. Furthermore, the performances of several Machine Learning supervised classification algorithms are compared, leading to the selection of the best algorithm to be considered for future developments of the methodology

The reporting of statistics in medical educational studies: an observational study

<p>Abstract</p> <p>Background</p> <p>There is confusion in the medical literature as to whether statistics should be reported in survey studies that query an entire population, as is often done in educational studies. Our objective was to determine how often statistical tests have been reported in such articles in two prominent journals that publish these types of studies.</p> <p>Methods</p> <p>For this observational study, we used electronic searching to identify all survey studies published in <it>Academic Medicine </it>and the <it>Journal of General Internal Medicine </it>in which an entire population was studied. We tallied whether inferential statistics were used and whether p-values were reported.</p> <p>Results</p> <p>Eighty-four articles were found: 62 in <it>Academic Medicine </it>and 22 in the <it>Journal of General Internal Medicine</it>. Overall, 38 (45%) of the articles reported or stated that they calculated statistics: 35% in <it>Academic Medicine </it>and 73% in the <it>Journal of General Internal Medicine</it>.</p> <p>Conclusion</p> <p>Educational enumeration surveys frequently report statistical tests. Until a better case can be made for doing so, a simple rule can be proffered to researchers. When studying an entire population (e.g., all program directors, all deans, and all medical schools) for factual information, do not perform statistical tests. Reporting percentages is sufficient and proper.</p

An index to examine the sexual HIV risk of psychiatric service users based on sexual partners

Numerous studies report higher HIV infection rates among psychiatric patients than in the general population.1 Relative to other HIV-affected populations, they have higher rates of HIV-related risk behaviors in fewer sexual occasions, including multiple partners, partners of unknown or positive HIV status, sex in exchange for money, shelter or goods, and low condom use rates.2 We present a new HIV risk index (RI)3 that takes into account differential risk associated with these factors