User Requirements and User Strategy in the AWARE Project

Abstract AWARE (A tool for monitoring and forecasting Available WAter REsource in mountain environment) is a Project in the VI Framework Programme of European Community. It started in July 2005 and aims at offering methods and tools to monitor and forecast the water resource from Alpine snowmelt by hydrologic models using input data derived from both in situ observations and Earth Observations (EO). In order to reach its objectives, AWARE needs strength collaboration with users. To this purpose activities to raise users' interests, to meet users' expectations and to spread Project achievements are planned. This paper describes the strategy used to collect user requirements within AWARE and illustrates some results of the user requirements analysis

The commitment problem of secured lending

The paper presents a new theory of trade credit in which firms buy inputs on credit from suppliers to restore the benefits of secured bank financing impaired by contract incompleteness. In a setting where investment is endogenous and unobservable to financiers, we show that a bank-secured credit contract is time-inconsistent. Upon being granted credit, the entrepreneur has an incentive to alter the original input combination, jeopardizing the bank’s revenues. Anticipating the entrepreneur’s opportunism, the bank offers an unsecured credit contract, reducing the surplus from the venture. One way for the entrepreneur to commit to the contract terms is to purchase inputs on credit from the supplier. The supplier observes the input investment and acts as a guarantor that inputs will be purchased as contracted, thus facilitating access to secured bank financing. The commitment role of trade credit still holds in a multi-period extension that investigates the impact of bank relationship lending on secured debt and trade credit. Our model provides novel testable predictions on optimal financial contracts in both one-period and repeated lending relationships

Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale

The ERMES agromonitoring system for rice cultivations integrates EO data at different resolutions, crop models, and user-provided in situ data in a unified system, which drives two operational downstream services for rice monitoring. The first is aimed at providing information concerning the behavior of the current season at regional/rice district scale, while the second is dedicated to provide farmers with field-scale data useful to support more efficient and environmentally friendly crop practices. In this contribution, we describe the main characteristics of the system, in terms of overall architecture, technological solutions adopted, characteristics of the developed products, and functionalities provided to end users. Peculiarities of the system reside in its ability to cope with the needs of different stakeholders within a common platform, and in a tight integration between EO data processing and information retrieval, crop modeling, in situ data collection, and information dissemination. The ERMES system has been operationally tested in three European rice-producing countries (Italy, Spain, and Greece) during growing seasons 2015 and 2016, providing a great amount of near-real-time information concerning rice crops. Highlights of significant results are provided, with particular focus on real-world applications of ERMES products and services. Although developed with focus on European rice cultivations, solutions implemented in the ERMES system can be, and are already being, adapted to other crops and/or areas of the world, thus making it a valuable testing bed for the development of advanced, integrated agricultural monitoring systems

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

A FUZZY KNOWLEDGE-BASED SYSTEM FOR BIOMEDICAL IMAGE INTERPRETATION

A general purpose knowledge-based system for biomedical image interpretation is presented. The system acquires knowledge directly from the experts by means of a user friendly dialogue. The knowledge introduced tailors the system to a particular biomedical application. Frame representation technique is used for the representation of descriptive knowledge and a fuzzy reasoning strategy, based on fuzzy production rules, is adopted to manipulate the certain and uncertain knowledge contained into Frame Slots and to deduce interpretations. A detailed description of the application of the system to the analysis of CT images of vertebrae for the quantity evaluation of the bone mineral content is provided

Operational Monitoring of Daily Crop Water Requirements at the Regional Scale with Time Series of Satellite Data

This work presents a simple, cost-effective and operational approach to monitor crop water requirements at the regional scale for water management and monitoring purposes. The recommended FAO-56 methodology calculates crop evapotranspiration using crop-specific coefficients (Kc), which vary according to the crop type, health and phenological stage. This approach, though widely applied for irrigation planning, cannot always match the appropriate crop coefficient with the actual crop phenological stage and health condition, especially in anomalous situations. Previous research demonstrated that crop coefficients and spectral Vegetation Indexes are correlated. Recent studies have used this relationship with high resolution satellite data from different sensors to provide information to irrigation advisory services. However, high resolution data are not feasible for an operational and routine monitoring of water consumption and needs. This paper tests the usefulness of time series of coarse resolution satellite data such as those collected by the MODIS sensor, to monitor crop coefficients temporal and spatial variability and therefore crop water needs at the regional scale taking advantage of the peculiar characteristics offered by MODIS in terms of high temporal resolution and pre-processed products availability. The outlined methodology takes into account the actual growing stage of the crops and nearly real-time vegetation variations, overcoming some limitations of the traditional FAO approach while preserving the maximum operability. The analysis was carried out in the South Milan agricultural area on data referring to 2003 and 2004. The results agreed with those of other studies, and proved to be able to account for the anomalous conditions of the summer in 2003. These results were then compared with those obtained using the traditional FAO crop coefficient curves built with data collected during field campaigns in the same years in rice fields. Constraints, limitations and possible uses are discussed.JRC.H.7-Climate Risk Managemen

Open Access to Historical Information for Landscape Analysis in an SDI Framework

The paper illustrates the potentials of geospatial data to access a historical digital atlas for landscape analysis and territorial government. The experience of a historical geo-portal, the “Atl@nte dei Catasti Storici,” in the management of geo-referenced and non-geo-referenced maps—ancient cadastral and topographic maps of the Lombardy Region—can be considered a case study with common aspects to many European regions with an extensive cartographic heritage. The development of downstream Web-based services enables integration with other data sources (current maps, satellite and Unmanned Aerial Vehicle [UAV] airborne photogrammetry, and multi-spectral images and derived products). This provides new scenarios for retrieving geospatial knowledge in support of more sustainable management and governance of the territory