Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

Abstract. The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008–2013. The results showed that including soil moisture observations in the event rainfall–runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha−1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process

A neuro-fuzzy model to predict the inflow to the guardialfiera multipurpose dam (Southern Italy) at medium-long time scales

Intelligent computing tools based on fuzzy logic and artificial neural networks have been successfully applied in various problems with superior performances. A new approach of combining these two powerful tools, known as neuro-fuzzy systems, has increasingly attracted scientists in different fields. Few studies have been undertaken to evaluate their performances in hydrologic modeling. Specifically are available rainfall-runoff modeling typically at very short time scales (hourly, daily or event for the real-time forecasting of floods) with in input precipitation and past runoff (i.e. inflow rate) and in few cases models for the prediction of the monthly inflows to a dam using the past inflows as input. This study presents an application of an Adaptive Network-based Fuzzy Inference System (ANFIS), as a neuro-fuzzy-computational technique, in the forecasting of the inflow to the Guardialfiera multipurpose dam (CB, Italy) at the weekly and monthly time scale. The latter has been performed both directly at monthly scale (monthly input data) and iterating the weekly model. Twenty-nine years of rainfall, temperature, water level in the reservoir and releases to the different uses were available. In all simulations meteorological input data were used and in some cases also the past inflows. The performance of the defined ANFIS models were established by different efficiency and correlation indices. The results at the weekly time scale can be considered good, with a Nash- Sutcliffe efficiency index E = 0.724 in the testing phase. At the monthly time scale, satisfactory results were obtained with the iteration of the weekly model for the prediction of the incoming volume up to 3 weeks ahead (E = 0.574), while the direct simulation of monthly inflows gave barely satisfactory results (E = 0.502). The greatest difficulties encountered in the analysis were related to the reliability of the available data. The results of this study demonstrate the promising potential of ANFIS in the forecasting of the short term inflows to a reservoir and in the simulation of different scenarios for the water resources management in the longer term

Biofeedback and Feedforward in Telerobotics Control

Biofeedback and Feedforward in Telerobotics Contro

Human Control Performance in Telemanipulation Experiences

Human Control Performance in Telemanipulation Experience

Movimento e controllo nella telerobotica: feedback e feedforward

Movimento e controllo nella telerobotica: feedback e feedforwar

IMPIEGO DEL CONTENUTO IDRICO DEL SUOLO E DEL DEFLUSSO SUPERFICIALE PER LA STIMA DELLA PERDITA DI SUOLO PARCELLARE A SCALA DI EVENTO

Nel presente lavoro viene valutata la potenzialità di accoppiare la USLE con il contenuto d’acqua del suolo pre-evento o il deflusso stimato, per migliorare l’accuratezza della stima della perdita di suolo a scala di singolo evento erosivo. A tale scopo sono stati utilizzati due approcci per i quali la perdita di suolo e il fattore di erosività sono legati da una legge di potenza. Il primo è il modello USLE-MM con deflusso stimato da un modello afflussi deflussi, SCRRM, che importa dati di contenuto d’acqua. Il secondo approccio è quello del modello SM4E che utilizza i dati di contenuto d’acqua pre-evento per correggere il fattore di erosività della pioggia. I due modelli sono stati testati usando le misure effettuate sulle parcelle di 22 m realizzate alle stazioni sperimentali di Masse e Sparacia. I risultati mostrano che la USLE-MM, che impiega misure di deflusso, conduce alle migliori stime della perdita di suolo. In atto, la simulazione del deflusso o l’uso del contenuto idrico del suolo conducono a una performance del modello peggiore di quella riscontrabile con la USLE originaria. Ulteriori indagini dovranno essere effettuate per migliorare la previsione del deflusso a scala di parcella, facendo anche ricorso a un database di misure più esteso

Anomaly detection in plant growth in a controlled environment using 3D scanning techniques and deep learning

This paper presents a comparison of different methodologies for monitoring the plants growth in a greenhouse. A 2D measurement based on Computer Vision algorithms and 3D shape measurements techniques (Structured light, LIDAR and photogrammetry) are compared. From the joined 2D and 3D data, an analysis was performed considering health plant indicators. The methodologies are compared among each other. The acquired data are then fed into Deep Learning algorithms in order to detect anomalies in plant growth. The final aim is to give an assessment on the image acquisition methodologies, selecting the most suitable to be used to create the Deep Learning model inputs saving time and resources

Hepatitis C virus clearance after direct-acting antivirals in cirrhotic patients by stages of liver impairment: the ITAL-C network study

Background and Aims: HCV-infected patients with decompensated cirrhosis, and in particular those Child-Pugh-Turcotte (CPT) class C, are usually excluded from studies investigating the sustained virological response (SVR12) to new direct-acting antivirals (DAAs). A more refined classification of cirrhotic patients has been provided by D’Amico et al. In this system stage 1 includes patients without portal hypertension, stage 2 those with esophageal varices, stage 3 patients who bled from varices, stage 4 patients with a single episode of decompensation events, and stage 5 those with multiple decompensation events. To assess the SVR12 after therapy in patients with advanced fibrosis and cirrhosis stratified according to the D’Amico” system. To evaluate the functional outcome during the follow up after treatment. Methods:We investigated a cohort of 2612 patients, from a network of 24 Italian centers, with chronic HCV infection and advanced fibrosis (no. = 575) or cirrhosis (no. = 2037). Different DAAs schedules were administered at the physicians’ choice, in accordance with national and international guidelines. All patients have completed 3 months of follow-up post treatment. Results: At exception of bilirubin levels, numbers of patients with normal albumin and INR values increased significantly in respect to baseline. Circulating platelets and creatinine levels increased significantly in respect to baseline. A remarkable increase in the numbers of CPT class A patients became apparent, whose frequency increased from 35.9% to 80.3% (p < 0.001). During the 3 month post-treatment follow up, no decompensation events were detected in patients with advanced hepatic fibrosis; a single patient developed HCC, and one patient died for acute leukemia. Of the 1739 stage 1 and 2 cirrhotics, 33 patients (1.9%) manifested events of decompensation or a HCC, and 1 of them died for uncontrolled esophageal bleed. Among the 277 decompensated cirrhotics (stage 3 to 5), 25 subjects (9.0%) experienced single or multiple events or a HCC, 4 were transplanted being HCVRNA negative at the time of the OLT,1 died for acute hepatic failure and 1 for diabetic complications. Results are shown in the Table. Conclusions: Our findings support the safety and the efficacy of DAAs treatment even in patients with portal hypertension and decompensated liver disease (stages 3–5 or CPT class C)

Safety and efficacy of ombitasvir/paritaprevir/ritonavir/dasabuvir plus ribavirin in patients over 65 years with HCV genotype 1 cirrhosis

Purpose: To analyse safety and efficacy of treatment based on ombitasvir/paritaprevir/ritonavir/dasabuvir plus ribavirin in the sub-group of GT1 patients older than 65\ua0years. Methods: We collected data extracted from the ABACUS compassionate-use nationwide Italian programme, in patients with cirrhosis due to hepatitis C virus (HCV) Genotype-1 (GT1) or 4 and at high risk of decompensation. GT1-HCV-infected patients received once-daily ombitasvir/paritaprevir, with the pharmacokinetic enhancer ritonavir (25/150/100\ua0mg) and twice-daily dasabuvir (250\ua0mg) plus Ribavirin (RBV) (OBV/PTV/r + DSV + RBV) for 12 (GT1b) or 24 (GT1a) weeks. Endpoints were to evaluate safety and efficacy, the latter defined as HCV RNA negative 12\ua0weeks after the end of treatment (SVR12). Results: Patients who suffered any adverse event (AE) were 74/240 (30.8%); 13/240 (5.4%) discontinued the treatment. A multivariate analysis found albumin < 3.5\ua0g/dL (OR 2.04: 95% CI 1.0\u20134.2, p < 0.05) and hypertension (OR 4.6: 95% CI 2.3\u20139.2, p < 0.001) as variables independently associated with AE occurrence. The SVR12 was 95% (228/240). Multivariate analysis identified baseline bilirubin < 2\ua0mg/dL (OR 4.9: 95% CI 1.17\u201320.71, p = 0.029) as the only variable independently associated with SVR12. Conclusion: Our findings suggest that OBV/PTV/r + DSV + RBV is safe and effective in real-life use in patients with compensated cirrhosis, HCV-GT1 infection, and age over 65