A new tri-generation system: thermodynamical analysis of a micro compressed air energy storage

There is a growing interest in the electrical energy storage system, especially for matching intermittent sources of renewable energy with customers’ demand. Furthermore, it is possible, with these system, to level the absorption peak of the electric network (peak shaving) and the advantage of separating the production phase from the exertion phase (time shift). CAES (compressed air energy storage systems) are one of the most promising technologies of this field, because they are characterized by a high reliability, low environmental impact and a remarkable energy density. The main disadvantage of big systems is that they depend on geological formations which are necessary to the storage. The micro-CAES system, with a rigid storage vessel, guarantees a high portability of the system and a higher adaptability even with distributed or stand-alone energy productions. This article carries out a thermodynamical and energy analysis of the micro-CAES system, as a result of the mathematical model created in a Matlab/Simulink® environment. New ideas will be discussed, as the one concerning the quasi-isothermal compression/expansion, through the exertion of a biphasic mixture, that will increase the total system efficiency and enable a combined production of electric, thermal and refrigeration energies. The exergy analysis of the results provided by the simulation of the model reports that more than one third of the exergy input to the system is lost. This is something promising for the development of an experimental device

Detecting similarities among distant homologous proteins by comparison of domain flexibilities

Aim of this work is to assess the informativeness of protein dynamics in the detection of similarities among distant homologous proteins. To this end, an approach to perform large-scale comparisons of protein domain flexibilities is proposed. CONCOORD is confirmed as a reliable method for fast conformational sampling. The root mean square fluctuation of alpha carbon positions in the essential dynamics subspace is employed as a measure of local flexibility and a synthetic index of similarity is presented. The dynamics of a large collection of protein domains from ASTRAL/SCOP40 is analyzed and the possibility to identify relationships, at both the family and the superfamily levels, on the basis of the dynamical features is discussed. The obtained picture is in agreement with the SCOP classification, and furthermore suggests the presence of a distinguishable familiar trend in the flexibility profiles. The results support the complementarity of the dynamical and the structural information, suggesting that information from dynamics analysis can arise from functional similarities, often partially hidden by a static comparison. On the basis of this first test, flexibility annotation can be expected to help in automatically detecting functional similarities otherwise unrecoverable. © 2007 The Author(s)

BITS 2015: The annual meeting of the Italian Society of Bioinformatics

This preface introduces the content of the BioMed Central journal Supplements related to the BITS 2015 meeting, held in Milan, Italy, from the 3th to the 5th of June, 2015

Physical Modeling for Programming of TANOS Memories in the Fowler-Nordheim Regime

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Semi-Analytical Model for the Transient Operation of Gate-All-Around Charge-Trap Memories

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Three-Dimensional Simulation of Charge-Trap Memory Programming-Part I: Average Behavior

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Comprehensive Investigation of Statistical Effects in Nitride Memories-Part I: Physics-Based Modeling

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Symptom Dimensions as Predictors of Clinical Outcome, Duration of Hospitalization, and Aggressive Behaviours in Acutely Hospitalized Patients with Psychotic Exacerbation

In the present study we extract clusters of symptoms in acute hospitalized psychotic patients during a re-exacerbation phase, using factor analysis of BPRS-E. We aim to investigate the relative contribution of each symptom dimension in predicting the severity of symptoms at discharge, the length of acute hospitalization, and the occurrence of aggressive behaviours during acute hospitalization. The data are drawn from a prospective, naturalistic, observational study of 183 patients with Psychotic Disorders consecutively admitted to a psychiatric ward, during a re-exacerbation phase. General symptomatology has been measured through BPRS-E at admission and at discharge. Statistical analyses include principal component analysis and multiple linear regression

Vulnerability of European forests to natural disturbances

European forests provide a set of fundamental services that contribute to climate change mitigation and human well-being. At the same time, forests are vulnerable systems because the long life-span of trees limits the possibility of rapid adaptation to drastic environmental changes. Climate-driven disturbances in forests, such as fires, windstorms and insect outbreaks, are expected to rise drastically under global warming. As a result, key forest services, such as carbon sequestration and supply of wood materials, could be seriously affected in the near future. Despite the relevance and urgency of the issue, little is known about the vulnerability of European forests to multiple climate-related hazards and the adaptation benefits of alternative forest management strategies. To fill this knowledge gap we investigated the susceptibility of European forests when exposed to a given natural disturbance under different forest management scenarios. For this purpose, we assessed forest vulnerability by integrating in a data-driven framework satellite observations, national forest inventories, land surface climatic data and records of disturbances over the 2000-2017 period. The integration of these data streams is meant to capture the key drivers of vulnerability and to quantify, for the first time, the vulnerability of European forests to fires, windstorms and insect outbreaks in a systematic and spatially explicit manner. We point out that, the term vulnerability is used in this study to express to what degree a forest ecosystem is affected when exposed to a given disturbance. In order to derive risk estimates, vulnerability estimates should be integrated with hazard and exposure components, according to typical impact assessment frameworks. Results of this analyses show that in average at Europe level forest vulnerability to windstorms appears the disturbance with larger biomass loss both in relative and absolute terms (~38%, ~17 t ha-1) compared to fires (~24%, ~12.5 t ha-1) and insect outbreaks (~21%, ~9 t ha-1). Substantial spatial variations in vulnerability emerge and depict generally higher values in norther and Mediterranean regions. Overall, forest structural properties play a larger control on the vulnerability of European forests to natural disturbances compared to climate and landscape features. However, increases in temperature and changes in precipitation patterns occurred over the last two decades, have contributed substantially to make European forests more vulnerable to natural disturbances. We found that these changes in climate led to a limited increase in vulnerability at Europe for fires and windstorms and to a strong increase for insect outbreaks. However, contrasting regional trends emerging over Europe mask relevant temporal changes in vulnerability occurring at local scale. When analyses of single disturbances are combined together, results show that large part of the European forests are substantially vulnerable to at least one natural disturbance and that many of the areas more vulnerable have been subject to an amplification of vulnerability over the observational period due to changes in climate. Reducing tree age and tree density appear effective forest management strategies to reduce the vulnerability of European forests to climate-driven disturbances. The magnitude of the potential benefits appears strongly dependent on local environmental conditions. Previous assessments of future climate risks to European forests, based on catalogues of disturbances collected at country level, have showed that damage from fires, windstorms and insect outbreaks is likely to increase further in coming decades. Such intensification could offset the impact of land-based strategies aiming to increase the forest carbon sink. However, the country scale approach used in such studies do not allow to explore in detail the underlying physical processes and to elaborate adaptation strategies at appropriate local scales. It is therefore fundamental to elaborate new modelling approaches that address in explicit manner the high spatial and temporal variability of forest disturbances. In this respect, machine learning approaches and the increasing availability of multi-platform satellite observations of land surface in combination with high regional climate model simulations, represent valuable opportunities to appraise the impact of forest disturbances at a spatial and temporal resolution relevant for forest management strategies. This explorative study represents a first step towards such integrated framework.JRC.D.1-Bio-econom