Faithful non-linear imaging from only-amplitude measurements of incident and total fields.

Applicability of inverse scattering based imaging procedures can be broadened by developing new approaches exploiting only amplitude data. As a matter of fact, this can open the way to simpler and less expensive measurement set-ups. In this respect, a two-step based procedure for solving electromagnetic nonlinear inverse scattering problems from only amplitude measurements of the total field has been recently proposed [1,2]. However, in these latter both amplitude and phase of the incident field are still required. In this contribution, we show the possibility of achieving this information from the measured amplitude distribution of the incident field on the observation domain. In particular, a three steps imaging technique which exploits only amplitude measurements of the total and incident fields has been developed. The proposed procedure has been tested against benchmark experimental data available in the literature. The obtained results fully confirm the possibility of achieving faithful reconstructions of unknown targets without performing any phase measurements and any approximation on the scattering equations involved in the inverse scattering problems

Harmonized Landsat 8 and Sentinel-2 Time Series Data to Detect Irrigated Areas: An Application in Southern Italy

Lack of accurate and up-to-date data associated with irrigated areas and related irrigation amounts is hampering the full implementation and compliance of the Water Framework Directive (WFD). In this paper, we describe the framework that we developed and implemented within the DIANA project to map the actual extent of irrigated areas in the Campania region (Southern Italy) during the 2018 irrigation season. For this purpose, we considered 202 images from the Harmonized Landsat Sentinel-2 (HLS) products (57 images from Landsat 8 and 145 images from Sentinel-2). Such data were preprocessed in order to extract a multitemporal Normalized Difference Vegetation Index (NDVI) map, which was then smoothed through a gap-filling algorithm. We further integrated data coming from high-resolution (4 km) global satellite precipitation Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) products. We collected an extensive ground truth in the field represented by 2992 data points coming from three main thematic classes: bare soil and rainfed (class 0), herbaceous (class 1), and tree crop (class 2). This information was exploited to generate irrigated area maps by adopting a machine learning classification approach. We compared six different types of classifiers through a cross-validation approach and found that, in general, random forests, support vector machines, and boosted decision trees exhibited the best performances in terms of classification accuracy and robustness to different tested scenarios. We found an overall accuracy close to 90% in discriminating among the three thematic classes, which highlighted promising capabilities in the detection of irrigated areas from HLS products

Closed Cycle Drying Process to Retrain Industrial Sludge into Construction Products

The article describes a new bio-inspired method for the Advanced Treatment of Industrial Sludge with a Closed Cycle Drying Process. This process represents an innovative way of treating sludge and other shovelable residues deriving from sludge treatment with centrifuges and other industrial processes taking place in large installations, such as refineries, steel mills, chemical plants, glass processing installations, cosmetics manufacturing facilities, pharmaceutical plants. The process is under development within the research project TAFIPACC funded by Horizon 2020. In particular, the process allows retraining Industrial Sludge into construction materials using the new Closed Cycle Drying Process. The study deals with sludge produced by an industrial treatment plant/industrial discharges and civil waste water in the industrial area of Priolo Gargallo (SR) Esso-Erg-Enichem petrochemical plants and by the municipalities of Priolo Gargallo, and Melilli. The plants produce about 30 cubic meters of sludge per day, disposed of 50% in underground dumps and for the other 50% in hazardous and non hazardous waste recovery plants. The difficulty in the treatment is mainly due to the nature of these muds, as pasty and difficult to mix with additives (cement, limestone, H2O, granulometric mix). The presence of bad odours derives from light and heavy hydrocarbons, aromatics, and organic solvents (benzene, toluene, styrene, xylene, etc), causing some problems to operators and inhabitants living in the areas surrounding the plants

Estimation of evapotranspiration and crop coefficients of tendone vineyards using multi-sensor remote sensing data in a mediterranean environment

The sustainable management of water resources plays a key role in Mediterranean viticulture, characterized by scarcity and competition of available water. This study focuses on estimating the evapotranspiration and crop coefficients of table grapes vineyards trained on overhead "tendone" systems in the Apulia region (Italy). Maximum vineyard transpiration was estimated by adopting the "direct" methodology for ETp proposed by the Food and Agriculture Organization in Irrigation and Drainage Paper No. 56, with crop parameters estimated from Landsat 8 and RapidEye satellite data in combination with ground-based meteorological data. The modeling results of two growing seasons (2013 and 2014) indicated that canopy growth, seasonal and 10-day sums evapotranspiration values were strictly related to thermal requirements and rainfall events. The estimated values of mean seasonal daily evapotranspiration ranged between 4.2 and 4.1 mm·d-1, while midseason estimated values of crop coefficients ranged from 0.88 to 0.93 in 2013, and 1.02 to 1.04 in 2014, respectively. The experimental evapotranspiration values calculated represent the maximum value in absence of stress, so the resulting crop coefficients should be used with some caution. It is concluded that the retrieval of crop parameters and evapotranspiration derived from remotely-sensed data could be helpful for downscaling to the field the local weather conditions and agronomic practices and thus may be the basis for supporting grape growers and irrigation managers

Chromosomal bar codes produced by multicolor fluorescence in situ hybridization with multiple YAC clones and whole chromosome painting probes

Colored chromosome staining patterns, termed chromosomal ‘bar codes’ (CBCs), were obtained on human chromosomes by fluorescence in situ hybridization (FISH) with pools of Alu-PCR products from YAC dones containing human DNA inserts ranging from 100 kbp to 1 Mbp. In contrast to conventional G- or R-bands, the chromosomal position, extent, Individual color and relative signal intensity of each ‘bar’ could be modified depending on probe selection and labeling procedures. Alu-PCR amplification products were generated from 31 YAC clones which mapped to 37 different chromosome bands. For multiple color FISH, Alu-PCR amplification products from various clones were either biotinylated or labeled with digoxigenin. Probes from up to twenty YAC clones were used simultaneously to produce CBCs on selected human chromosomes. Evaluation using a cooled CCD camera and digital image analysis confirmed the high reproducibility of the bars from one metaphase spread to another. Combinatorial FISH with mixtures of whole chromosome paint probes was applied to paint seven chromosomes simultaneously in different colors along with a set of YAC clones which map to these chromosomes. We discuss the potential to construct analytical chromosomal bar codes adapted to particular needs of cytogenetic investigations and automated image analysis

DDX11L: a novel transcript family emerging from human subtelomeric regions

BACKGROUND:The subtelomeric regions of human chromosomes exhibit an extraordinary plasticity. To date, due to the high GC content and to the presence of telomeric repeats, the subtelomeric sequences are underrepresented in the genomic libraries and consequently their sequences are incomplete in the finished human genome sequence, and still much remains to be learned about subtelomere organization, evolution and function. Indeed, only in recent years, several studies have disclosed, within human subtelomeres, novel gene family members. RESULTS:During a project aimed to analyze genes located in the telomeric region of the long arm of the human X chromosome, we have identified a novel transcript family, DDX11L, members of which map to 1pter, 2q13/14.1, 2qter, 3qter, 6pter, 9pter/9qter, 11pter, 12pter, 15qter, 16pter, 17pter, 19pter, 20pter/20qter, Xpter/Xqter and Yqter. Furthermore, we partially sequenced the underrepresented subtelomeres of human chromosomes showing a common evolutionary origin.CONCLUSION:Our data indicate that an ancestral gene, originated as a rearranged portion of the primate DDX11 gene, and propagated along many subtelomeric locations, is emerging within subtelomeres of human chromosomes, defining a novel gene family. These findings support the possibility that the high plasticity of these regions, sites of DNA exchange among different chromosomes, could trigger the emergence of new genes

The dire disregard of measurement invariance testing in psychological science

In psychological science, self-report scales are widely used to compare means in targeted latent constructs across time points, groups, or experimental conditions. For these scale mean comparisons (SMC) to be meaningful and unbiased, the scales should be measurement invariant across the compared time points or (experimental) groups. Measurement invariance (MI) testing checks whether the latent constructs are measured equivalently across groups or time points. Since MI is essential for meaningful comparisons, we conducted a systematic review to check whether MI is taken seriously in psychological research. Specifically, we sampled 426 psychology articles with openly available data that involved a total of 918 SMCs to (1) investigate common practices in conducting and reporting of MI testing, (2) check whether reported MI test results can be reproduced, and (3) conduct MI tests for the SMCs that enabled sufficiently powerful MI testing with the shared data. Our results indicate that (1) 4% of the 918 scales underwent MI testing across groups or time and that these tests were generally poorly reported, (2) none of the reported MI tests could be successfully reproduced, and (3) of 161 newly performed MI tests, a mere 46 (29%) reached sufficient MI (scalar invariance), and MI often failed completely (89; 55%). Thus, MI tests were rarely done and poorly reported in psychological studies, and the frequent violations of MI indicate that reported group differences cannot be solely attributed to group differences in the latent constructs. We offer recommendations on reporting MI tests and improving computational reproducibility practices

About the presence of Phlebotomus sergenti Parrot, 1917 (Diptera: Psychodidae) in Eastern Sicily, Italy.

The note reports the data of a three-year sand fly investigation (1997-99) carried out in Eastern Sicily (Italy) with the aim to study the distribution of Phlebotomus sergenti. The survey involved a densely inhabited area at the foot of Mount Etna and the area of Iblei mounts. A total of 9,095 sand flies, of which 63.4 % males, were captured. Five species belonging to the genus Phlebotomus (P. perniciosus, P. perfiliewi, P. neglectus, P. sergenti and P. papatasi) and one to the genus Sergentomyia (S. minuta) were identified. Both the prevalence and distribution of the species were different within the two areas studied. In Mount Etna area, P. perniciosus (77.7 %) was the prevalent species followed by S. minuta (19.8 %), P. sergenti (2.0 %), P. neglectus (0.3 %) and P. papatasi (0.2 %). While in Iblei mounts region S. minuta (84,5 %) showed the highest prevalence, followed by P. perniciosus (14.4 %), P. perfiliewi (0,9 %) and P. neglectus (0,1 %). Here, P. sergenti was a very rare species (‹ 0.02). P. sergenti was mostly associated to domestic habitats of peri-urban and urban zones located between two and 750 m a.s.l. The density values of P. sergenti. expressed as number of specimens/m2 of sticky trap, were between 0.3 and 5.5 with the highest value in the hilly collecting sites. The low observed abundance of P. sergenti does not allow to draw any prediction on the role that the species could play in the transmission of leishmaniasis in Sicily

closed cycle drying process to retrain industrial sludge into construction products

The article describes a new bio-inspired method for the Advanced Treatment of Industrial Sludge with a Closed Cycle Drying Process. This process represents an innovative way of treating sludge and other shovelable residues deriving from sludge treatment with centrifuges and other industrial processes taking place in large installations, such as refineries, steel mills, chemical plants, glass processing installations, cosmetics manufacturing facilities, pharmaceutical plants. The process is under development within the research project TAFIPACC funded by Horizon 2020. In particular, the process allows retraining Industrial Sludge into construction materials using the new Closed Cycle Drying Process. The study deals with sludge produced by an industrial treatment plant/industrial discharges and civil waste water in the industrial area of Priolo Gargallo (SR) Esso-Erg-Enichem petrochemical plants and by the municipalities of Priolo Gargallo, and Melilli. The plants produce about 30 cubic meters of sludge per day, disposed of 50% in underground dumps and for the other 50% in hazardous and non hazardous waste recovery plants. The difficulty in the treatment is mainly due to the nature of these muds, as pasty and difficult to mix with additives (cement, limestone, H2O, granulometric mix). The presence of bad odours derives from light and heavy hydrocarbons, aromatics, and organic solvents (benzene, toluene, styrene, xylene, etc), causing some problems to operators and inhabitants living in the areas surrounding the plants

Capability of Sentinel-2 data for estimating maximum evapotranspiration and irrigation requirements for tomato crop in Central Italy

Abstract The occurrence of water shortages ascribed to projected climate change, especially in the Mediterranean region, fosters the interest in remote sensing (RS) applications to optimize water use in agriculture. Remote sensing evapotranspiration and water demand estimation over large cultivated areas were used to manage irrigation to minimize losses during the crop growing cycle. The research aimed to explore the potential of the MultiSpectral Instrument (MSI) sensor on board Sentinel-2A to estimate crop parameters, mainly surface albedo (α) and Leaf Area Index (LAI) that influence the dynamics of potential evapotranspiration (ETp) and Irrigation Water Requirements (IWR) of processing tomato crop (Solanum lycopersicum L.). Maximum tomato ETp was calculated according to the FAO Penman-Monteith equation (FAO-56 PM) using appropriate values of canopy parameters derived by processing Sentinel-2A data in combination with daily weather information. For comparison, we used the actual crop evapotranspiration (ETa) derived from the soil water balance (SWB) module in the Environmental Policy Integrated Climate (EPIC) model and calibrated with in-situ Root Zone Soil Moisture (RZSM). The experiment was set up in a privately-owned farm located in the Tarquinia irrigation district (Central Italy) during two growing seasons, within the framework of the EU Project FATIMA (FArming Tools for external nutrient Inputs and water Management). The results showed that canopy growth, maximum evapotranspiration (ETp) and IWR were accurately inferred from satellite observations following seasonal rainfall and air temperature patterns. The net estimated IWR from satellite observations for the two-growing seasons was about 272 and 338 mm in 2016 and 2017, respectively. Such estimated requirement was lower compared with the actual amount supplied by the farmer with sprinkler and drip micro-irrigation system in both growing seasons resulting in 364 (276 mm drip micro-irrigation, and 88 mm sprinkler) and 662 (574 mm drip micro-irrigation, and 88 mm sprinkler) mm, respectively. Our findings indicated the suitability of Sentinel-2A to predict tomato water demand at field level, providing useful information for optimizing the irrigation over extended farmland