Search

OBJECTIVEThe introduction of flow-diverter devices (FDDs) has revolutionized the endovascular treatment of intracranial aneurysms. Here the authors present their Italian multicenter experience using the flow re-direction endoluminal device (FRED) in the treatment of cerebral aneurysms, evaluating both short- and long-term safety and efficacy of this device.METHODSBetween February 2013 and December 2014, 169 consecutive aneurysms treated using FRED in 166 patients were entered into this study across 30 Italian centers. Data collected included patient demographics, aneurysm location and characteristics, baseline angiography, adverse event and serious adverse event information, morbidity and mortality rates, and pre- and posttreatment modified Rankin Scale scores, as well as angiographic and cross-sectional CT/MRI follow-up at 3–6 months and/or 12–24 months per institutional standard of care. All images were reviewed and adjudicated by an independent core lab.RESULTSOf the 169 lesions initially entered into the study, 4 were later determined to be extracranial or nonaneurysmal by the core lab and were excluded, leaving 165 aneurysms in 162 patients treated in 163 procedures. Ninety-one (56.2%) patients were asymptomatic with aneurysms found incidentally. Of the 165 aneurysms, 150 (90.9%) were unruptured. One hundred thirty-four (81.2%) were saccular, 27 (16.4%) were fusiform/dissecting, and the remaining 4 (2.4%) were blister-like. One hundred thirty-seven (83.0%) arose from the anterior circulation.FRED deployment was impossible in 2/163 (1.2%) cases, and in an additional 4 cases (2.5%) the device was misdeployed. Overall mortality and morbidity rates were 4.3% and 7.3%, respectively, with rates of mortality and morbidity potentially related to FRED of up to 2.4% and 6.2%, respectively. Neuroimaging follow-up at 3–6 months showed complete or nearly complete occlusion of the aneurysm in 94% of cases, increasing to 96% at 12–24 months’ follow-up. Aneurysmal sac shrinkage was observed in 78% of assessable aneurysms.CONCLUSIONSThis preliminary experience using FRED for endovascular treatment of complex unruptured and ruptured aneurysms showed a high safety and efficacy profile that is comparable to those of other FDDs currently in use.

Aims: Resting energy expenditure (REE) plays a critical role in the regulation of body weight, with important implications in type 2 diabetes (T2D). However, the relationships between REE and T2D have not been extensively evaluated. We compared REE in persons with diabetes and in persons without diabetes. We also investigated the acute effect of insulin on REE and venous lactate, the latter an indirect measure of neoglucogenetic activity. Methods: REE was measured using indirect calorimetry in 14 newly diagnosed, untreated T2D adults and in 14 non-diabetic age-, gender- and body mass index-matched persons. The REE and lactate venous concentrations were also measured in a subgroup of 5 T2D patients in the hour following an IV insulin bolus. Results: The REE normalized for fat-free mass (FFM) was significantly higher in T2D patients than in the group without diabetes (mean SD: 27.6 1.9 vs. 25.8 1.9 kcal/kg-FFM 24 h; P = 0.02). REE normalized for FFM was correlated with fasting plasma glucose concentration (r = 0.51; P = 0.005). Following the insulin venous bolus REE (00: 2048 242; 100: 1804 228; 200: 1684 230; 300: 1634 212; 450: 1594 179; 600: 1625 197 kcal/24 h; P < 0.001) and both glucose (P < 0.001) and lactate (P < 0.001) concentrations progressively declined in the ensuing hour. Conclusions: Patients with diabetes have a higher energy expenditure, likely a consequence of higher gluconeogenetic activity. This study may contribute to recognizing the nature of body weight reduction that occurs in concomitance with poorly controlled diabetes, and of body weight gain as commonly observed when hypoglycemic treatment is started.

In this paper we discuss classical sufficient conditions to be satisfied from the grid transfer operators in order to obtain optimal two-grid and V-cycle multigrid methods utilizing the theory for Toeplitz matrices. We derive relaxed conditions that allow the construction of special grid transfer operators that are computationally less expensive while preserving optimality. This is particularly useful when the generating symbol of the system matrix has a zero of higher order, like in the case of higher order PDEs. These newly derived conditions allow the use of rank deficient grid transfer operators. In this case the use of a pre-relaxation iteration that is lacking the smoothing property is proposed. Combining these pre-relaxations with the new rank deficient grid transfer operators yields a substantial reduction of the convergence rate and of the computational cost at each iteration compared with the classical choice for Toeplitz matrices. The proposed strategy, i.e. a rank deficient grid transfer operator plus a specific pre-relaxation, is applied to linear systems whose system matrix is a Toeplitz matrix where the generating symbol is a high-order polynomial. The necessity of using high-order polynomials as generating symbols for the grid transfer operators usually destroys the Toeplitz structure on the coarser levels. Therefore, we discuss some effective and computational cheap coarsening strategies found in the literature. In particular, we present numerical results showing near-optimal behavior while keeping the Toeplitz structure on the coarser levels. © 2014, Springer Science+Business Media Dordrecht.

Agroscenari is a multiannual research project, funded and coordinated at the national level, supporting Italian agriculture adaptation to climate change and developing decision-making tools for public administrations and stakeholders. The project was active in six representative areas: Po Valley, Oristano, Benevento, Destra Sele, Faenza and two small basins in the Marche region. Climate change scenarios were created for every area to assess impacts on the main cropping systems and to identify adaptation options. In the last year of the project (2014) a policy brief (PB) for each test area was prepared in order to promote the transfer of scientific results. In addition to summarizing expected climate change, methods and results, PBs contain a SWOT analysis relating strengths and weaknesses internal to the agricultural production systems with the opportunities and threats from climate change, and suggesting adaptation measures for the Italian Rural Development Programme 2014-2020.

A study was carried out on the potential response of soil-borne pathogens causing crop yield losses under a climate change scenario in Europe. A controlled chamber set of experiments was carried out to quantify pathogen response to temperature using pure colonies of three soil-borne fungi, representative of low (Fusarium nivale), medium-high (Athelia rolfsii) and high (Macrophomina phaseolina) temperature requirements. A generic model to simulate fungal growth response to temperature based on these experiments was developed and linked to a soil temperature model component, and to components to simulate soil water content also as resulting from crop water uptake. Pathogens relative growth was simulated over Europe using a IPCC A1B emission scenario derived from the Hadley-CM3 global climate model, available from the European Commission and suitable for use with biophysical models. Two climate scenarios were compared: the baseline, representing a sample of 30 years of daily weather centred on the year 2000, and 2030. The general trend of soil-borne pathogens response to scenario of climate change is a relative increased growth in colder areas of Europe, as a function of their temperature requirements. Projections of F. nivale in the future indicate a relative increase of this winter pathogen of wheat in Northern European countries. A. rolfsii and M. phaseolina, two soil-borne pathogens typical of warmer agricultural areas, could find more favourable conditions in areas of the Central Europe, but they differentiated in Southern Europe where A. rolfsii resulted affected by summer soil temperatures above optimum., JRC.H.4-Monitoring Agricultural Resources

Autres auteurs : G. Bellocchi, J.-E. Bergez, M. Botta, E. Braudeau, S. Bregaglio, L. Carlini, E. Casellas, F. Celette, E. Ceotto, M.-H. Charron-Moirez, R. Confalonieri, M. Corbeels, L. Criscuolo, P. Cruz, A. di Guardo, D. Ditto, C. Dupraz, M. Duru, D. Fiorani, A. Gentile, F. Ewert, C. Gary, E. Habyarimana, C. Jouany, K. Kansou, R. Knapen, G. Lanza Filippi, P.A. Leffelaar, L. Manici, G. Martin, P. Martin, E. Meuter, N. Mugueta, R. Mulia, M. van Noordwijk, R. Oomen, A. Rosenmund, V. Rossi, F. Salinari, A. Serrano, A. Sorce, G. Vincent, J.-P. Theau, O. Thérond, M. Trevisan, P. Trevisiol, F.K. van Evert, D. Wallach, J. Wery et A. Zerourou; International audience; Although existing simulation tools can be used to study the impact of agricultural management on production activities in specific environments, they suffer from several limitations. They are largely specialized for specific production activities: arable crops/cropping systems, grassland, orchards, agro-forestry, livestock etc. Also, they often have a restricted ability to simulate system externalities which may have a negative environmental impact. Furthermore, the structure of such systems neither allows an easy plug-in of modules for other agricultural production activities, nor the use of alternative components for simulating processes. Finally, such systems are proprietary systems of either research groups or projects which inhibits further development by third parties. SEAMLESS aims to provide a tool to integrate analyses of impacts on the key aspects of sustainability and multi-functionality, particularly in Europe. This requires evaluating agricultural production and system externalities for the most important agricultural production systems. It also requires a simulation framework which can be extended and updated by research teams, which allows a manageable transfer of research results to operational tools, and which is transparent with respect to its contents and its functionality. The Agricultural Production and Externalities Simulator (APES) is a modular simulation system aimed at meeting these requirements, and targeted at estimating the biophysical behavior of agricultural production systems in response to the interaction of weather and agro-technical management. APES is a framework which uses components that offer simulation options for different processes of relevance to agricultural production systems. Models are described in the associated help files of components, and a shared ontology is built on the web. Components like these, which are designed to be inherently re-usable, that is not targeted specifically to a given modelling framework, also represent a way to share modelling knowledge with other projects and the scientific community in general. This chapter describes the current state of APES development and presents modelling options in the system, and its software architecture.

International audience; Cropping system models are typically used to simulate crop growth and development at the field scale. Spatial extension of the results to larger scales needs spatially referenced databases using Geographic Information systems (GIS). However, GIS generally lack accuracy and pertinence in the soil characteristics and delineations that are required for this purpose. In addition, most soil parameters used in the soil‐water models are empirical and are estimated without any reference to soil structure, making it difficult to characterize the hydrostructural functionality of spatial soil mapping units in the GIS. The objective of this article is to present an application of a new approach in soil physics for coupling a soil information (mapping and characterization) system based on the soil organization with an agronomic model, CropSyst, to be used for soil and water management purposes. Accordingly, a GIS based on a map of hierarchical natural units in the irrigated area of Cebalat (northern Tunisia) was used to build a geo‐referenced soil information system for the study area. Additional information from the existing GIS of the zone was overlaid to produce “agronomic units,” which result from the spatial superposition of the soil information system, farm map units, and land use. The inputs for the model were different sets of soil, crop, and crop management parameters. Simulations were conducted at the field scale for testing the ability of CropSyst to simulate yield, soil water dynamics, soil salinity, nitrogen leached, and at the regional level, yield. At the field scale, the model accurately, without calibration of soil properties, simulated the soil water content and salinity (RRMSE less than 10%). Simulated soil nitrate concentration was not close to observed values (RRMSE of 54%), but the latter were also associated with large variability. At the regional scale, the model offered an overall good integrated performance in simulating yield in the area under evaluation. For rainfed crops, the regression line between simulated and observed yield was close to 1:1; however, the model slightly underestimated simulated yield for the irrigated crops.

Modern management of environmental resources defines problems from a holistic and integrated perspective, imposing strong requirements to Environmental Decision Support Systems (EDSSs) and Integrated Assessment Tools (IATs), which tend to be increasingly complex in terms of software architecture and computational power in order to cope with the type of problems they must solve. Such systems need to support methodologies and techniques ranging from agent-based modelling to participatory decision-making. Sometimes EDSSs and IATs are built from scratch, often with limited resources, by non-programmers. The disadvantages of this approach, which can quickly become overly expensive in terms of delivery time and resources required, have been addressed by the development of suites of software engineering tools called Environmental Integrated Modelling Frameworks (EIMFs). EIMFs have typically been designed as a response to the increasing complexity of building and delivering EDSSs and IATs. Modelling and simulation tools and frameworks have been adopted at a large scale in the management science and operations research disciplines, and standards for developing and expanding them have been developed. In contrast, no modelling framework has been universally adopted within the environmental modelling domain, and the number of environmental modelling frameworks is still growing. In this book chapter, we strive to address the above issues and clearly identify the essential characteristics of an EIMF. This book chapter also advocates the development of open standards for the exchange and re-use of modelling knowledge, including data sets, models, and procedures in order to facilitate improved communication among the leading EIMFs

Several simulation tools allow studying the impact of agricultural management on production activities in specific environments. Such tools are specialized, to different extents, to specific production activities: arable crops/cropping systems, grassland, orchards, agroforestry, livestock etc. Also, their focus includes to various degrees the estimate of system externalities which may have a negative environmental impact. Furthermore, the structure of such tools does neither allow an easy plug-in of modules for different agricultural production activities, nor the use of different approaches for the simulation of processes via alternate components. Finally, such systems are proprietary systems of either research groups or projects. The SEAMLESS project aims at providing a tool to integrate analyses of impacts on a wide range of aspects of sustainability and multi-functionality of agriculture. This requires evaluating agricultural production and system externalities for most, if not all, types of agricultural production systems. It also requires the availability of a simulation framework which can be extended and updated by research teams with possibly different expertise, which allows a manageable transfer of research results to operational tools, and which is transparent with respect to its contents and its functionality. The Agricultural Production and Externalities Simulator is a modular simulation system targeted at estimating the biophysical behaviour of agricultural production systems in response to the interaction of soil-weather and different options of agro-technical management. APES is currently meant to be used at field scale, simulating 1-D fluxes (future version will also use 2-D fluxes to account for multiple cropping). All modules of this release are first prototypes linked to test the hypothesis on the component based structure and to evaluate consequent modelling and technical issues; outputs should not be analyzed to evaluate model performance at this stage. APES is an application which uses several components being developed to offer simulation options for different processes of relevance in agricultural production systems. Models are described in the associated help files of components, and a shared ontology is being built on specifically to a given modelling framework, are also meant to be a concrete option to share modelling knowledge with other projects and the scientific community. This report presents a description of the current state of development of APES (release 0.3; June 2006).

Metadata only record These proceedings are from the conference, 'Farming Systems Design 2007: An International Symposium on Methodologies on Integrated Analysis on Farm Production Systems - Farm-regional scale design and improvement,' held in Catania (Italy), 10-12 September 2007. The conference sought to promote integration of knowledge across disciplines, compare research methodologies, and identify future research tools and needs in the realm of farm scale design and improvement.