Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Contribution of EMI and GPR proximal sensing data in soil water content assessment by using linear mixed effects models and geostatistical approaches

The estimation of topsoil water content is of primary interest in the framework of precision farming, but, in general, such assessment is costly and complicated by several interfering factors which do not allow an accurate prediction. Proximal sensing can provide suitable technological facilities to support researchers and technicians in this task. GPR and EMI sensors are valuable instruments as they can provide very informative covariates to be used for improving soil water content estimation. In the present work, it was explored the single (EMI or GPR) and the combined (EMI + GPR) contribution of these proximal data sources. Furthermore, geostatistical (Ordinary Kriging and Kriging with external drift) and linear mixed effects models were applied to compare their respective predictive capabilities. As a result, GPR demonstrated to be more effective in estimating topsoil water content with respect to EMI but, combining both the information, an improvement in the prediction accuracy was observed. Moreover, adding more covariates in the models (GPR outcomes or GPR + EMI outcomes) allowed filtering out the structured spatial component of soil water content. Finally, the statistical approaches proved to behave very similarly, with a slight better performance of Kriging with external drift

Spatial variability of soil physical and hydraulic properties in a durum wheat field: An assessment by the BEST-procedure

Spatial variability of soil properties at the field scale can determine the extent of agricultural yields and specific research in this area is needed. The general objective of this study was to investigate the relationships between soil physical and hydraulic properties and wheat yield at the field scale and test the BEST-procedure for the spatialization of soil hydraulic properties. A simplified version of the BEST-procedure, to estimate some capacitive indicators from the soil water retention curve (air capacity, ACe, relative field capacity, RFCe, plant available water capacity, PAWCe), was applied and coupled to estimates of structure stability index (SSI), determinations of soil texture and measurements of bulk density (BD), soil organic carbon (TOC) and saturated hydraulic conductivity (Ks). Variables under study were spatialized to investigate correlations with observed medium-high levels of wheat yields. Soil physical quality assessment and correlations analysis highlighted some inconsistencies (i.e., a negative correlation between PAWCe and crop yield), and only five variables (i.e., clay + silt fraction, BD, TOC, SSI and PAWCe) were spatially structured. Therefore, for the soil–crop system studied, application of the simplified BEST-procedure did not return completely reliable results. Results highlighted that (i) BD was the only variable selected by stepwise analysis as a function of crop yield, (ii) BD showed a spatial distribution in agreement with that detected for crop yield, and (iii) the cross-correlation analysis showed a significant positive relationship between BD and wheat yield up to a distance of approximately 25 m. Such results have implications for Mediterranean agro-environments management. In any case, the reliability of simplified measurement methods for estimating soil hydraulic properties needs to be further verified by adopting denser measurements grids in order to better capture the soil spatial variability. In addition, the temporal stability of observed spatial relationships, i.e., between BD or soil texture and crop yields, needs to be investigated along a larger time interval in order to properly use this information for improving agronomic managemen

Effectiveness of pre- and post-veraison calcium applications to control decay and maintain table grape fruit quality during storage

A two year research was carried out on a table grape vineyard, cv. Italia, to evaluate the effectiveness of pre- and post-veraison calcium applications for controlling postharvest table grape rots and maintaining high fruit quality during cold storage. Two calcium application timings (from fruit set to veraison and from veraison to harvest) were compared to an untreated control. Clusters were sprayed with calcium chloride as Ca EDTA 44%. After each calcium application, bunch samples were collected and Ca 2+ concentration was measured in berry compartments (skin, flesh and seeds). The main mechanical and chemical characteristics were measured on bunch samples at harvesting and during storage. In addition, the incidence of Botrytis cinerea rots, computed as McKinney index, was evaluated in field on natural inoculum and after harvesting on bunches artificially inoculated and maintained at room temperature. The highest Ca 2+ concentrations were detected in skin tissues and after pre-veraison applications. Calcium accumulation in skin and flesh tissues stopped after veraison, whereas it continued up to ripening in seeds since the axial flow, differently from the peripheral, remains functional. In both years, calcium applications to bunches were effective both in maintaining postharvest fruit quality, as shown by flesh firmness and berry breaking force, and in reducing B. cinerea rots during storage. The applications were particularly efficacious if carried out between fruit set and veraison when stomata are functional and the re-translocation of calcium not directly absorbed by the bunches may occur via xylem transport. © 2012 Elsevier B.V

Correction: Castellini, M., et al. Spatial Variability of Soil Physical and Hydraulic Properties in a Durum Wheat Field: An Assessment by the BEST-Procedure. Water 2019, 11, 1434

The authors wish to make the following corrections to this paper [...