1,721,124 research outputs found
Modelling and Performance Analysis of an Integrated Plasma Gasification Combined Cycle (IPGCC) Power Plant
No full textThe waste management is become a very crucial issue in many countries, due to the ever-increasing amount of waste material, both domiciliary and industrial, generated. The main strategies for the waste management are the increase of material recovery (MR) which can reduce the landfill disposal, the improvement of energy recovery (ER) from waste and the minimization of the environmental impact.
Recent studies have focused on an innovative technology, the plasma gasification, that has been dem- onstrated as one of the most effective and environmentally friendly methods for solid waste treatment and energy utilization.
In this paper, a plasma gasification process based on plasma torch technology has been investigated by developing a thermochemical model (EPJ, EquiPlasmaJet) able to estimate both the syngas composition and the energy required for the gasification reactions. The EPJ model has been employed to predict the syngas composition and the energy balance of a RDF (refuse derived fuel) plasma arc gasification reactor using air as plasma gas, and, in order to define the optimal operating conditions three different configu- rations have been investigated.
Results show that, in the better plant solution, the plasma gasification efficiency is 69.1% (LHV) and the lower heating value of the syngas generated is about 9 MJ/kg. Furthermore in order to evaluate the suit- ability of this technology for energy recovery from solid wastes, the integration of the optimum plasma gasification system (PGS) with a gas turbine combined cycle (GTCC) has been analysed and the perfor- mance of the resulting integrated plasma gasification combined cycle (IPGCC) has been evaluated. The system efficiency (31% LHV) is very high in comparison with the efficiency of conventional technologies based on waste incineration (20%)
Is immunotherapy with fungal vaccines effective?
No full textPurpose of review Although allergen immunotherapy (AIT) for fungi has been performed for many years, evidence clearly demonstrating its clinical benefit are still lacking. Here, we reviewed the available studies assessing efficacy and safety of AIT for molds. Recent findings Studies on AIT for fungi were performed only for the two predominating mold species in the external environment, namely Cladosporium and Alternaria. There is no evidence for other mold species. Recent finding in the literature are lacking; the 2 most recent studies on AIT for molds were published in 2011. Overall, 13 studies were identified (the first was published in 1986), but only nine of these compared AIT to placebo. The studies are small (median study sample size, 27 patients) and of low quality, owing to several defects leading to moderate-to-high risk of bias. Symptoms improvement and medication use reduction, which are the main outcome measures of the studies, were inconsistently demonstrated. There are some concerns about safety with Cladosporium extracts, whereas vaccines with Alternaria extracts seem to be safe and well tolerated. Summary Low strength evidence suggests that mold AIT is efficacious for the treatment of respiratory allergies. High-quality studies with an adequate sample size are needed
The impact of antiviral treatments on the course of chronic hepatitis C: an evidence-based approach
No full textHepatitis C virus chronic infection is currently the most common cause of end-stage liver disease. The benefit of antiviral therapy on liver histology and its impact on the long-term course of the disease has been extensively studied. However, the results are still equivocal and the overall assessment of treatment effect remains difficult to evaluate. Although the conclusions of the last National Institute of Health Consensus Development Conferences on Hepatitis C have recently been published, several important issues still remain unanswered. We review the available data by an evidence-based approach and conclude that: 1) peginterferon alfa is more effective than conventional interferon in improving liver histology; 2) monotherapy with PEG-interferon induces a marked reduction in staging in virological sustained responders and to a lesser degree in relapsers, but provides no benefit to nonresponders after 24-48 weeks of treatment; 3) maintenance therapy aiming to improve histology in virological nonresponders should be considered experimental and of unproven benefit; 4) although the reduction in the number of events in sustained responders suggests a long-term benefit of IFN therapy, available evidence is still insufficient to confirm that IFN prolongs life in HCV infected patients. Data of the long-term benefit of subjects treated with IFN plus ribavirin are still not available; 5) pooling of published data suggests a slight preventive effect of IFN on HCC development in patients with HCV-related cirrhosis. The magnitude of this effect is low and the observed benefit might be due to spurious associations. The preventive effect is more evident among sustained responders to interferon
New experimental VLE data for the binary mixture of carbon dioxide + perfluorohexane (CO2 + C6F14) from 273 K to 333 K
No full textMixtures of carbon dioxide and perfluorocarbons are more frequently used in different fields: in energy conversion systems, in the electronic industry, in chemical plants and for medical applications. Among all perfluorocarbons, perfluorohexane has interesting properties (e.g. high thermal stability and high carbon dioxide solubility) to be used in mixture, as a working fluid in power and refrigeration cycles. The study of these systems relies on the availability of accurate thermodynamic models of the fluid mixture, which usually require to be calibrated on experimental data. Experimental data on the carbon dioxide and perfluorohexane mixture are scarcely available in literature and limited to a very narrow temperature range. This work aims to enrich the available literature data on VLE measurements of carbon dioxide and perfluorohexane mixture. On the basis of the implemented static-analytical method, high-pressure phase equilibrium data have been collected. Isothermal measurements have been performed within the temperature range of 273 K-333 K and at pressures up to 8.5 MPa. Particular attention to calibration procedures of the measuring devices (temperature and pressure probes and gas chromatograph) and to uncertainty calculation has been devoted. Finally, measurements show a good agreement with the data available in literature. (C) 2019 Elsevier B.V. All rights reserved
An interpretable cluster-based logistic regression model, with application to the characterization of response to therapy in severe eosinophilic asthma
No full textAsthma is a disease characterized by chronic airway hyperresponsiveness and inflammation, with signs of variable airflow limitation and impaired lung function leading to respiratory symptoms such as shortness of breath, chest tightness and cough. Eosinophilic asthma is a distinct phenotype that affects more than half of patients diagnosed with severe asthma. It can be effectively treated with monoclonal antibodies targeting specific immunological signaling pathways that fuel the inflammation underlying the disease, particularly Interleukin-5 (IL-5), a cytokine that plays a crucial role in asthma. In this study, we propose a data analysis pipeline aimed at identifying subphenotypes of severe eosinophilic asthma in relation to response to therapy at follow-up, which could have great potential for use in routine clinical practice. Once an optimal partition of patients into subphenotypes has been determined, the labels indicating the group to which each patient has been assigned are used in a novel way. For each input variable in a specialized logistic regression model, a clusterwise effect on response to therapy is determined by an appropriate interaction term between the input variable under consideration and the cluster label. We show that the clusterwise odds ratios can be meaningfully interpreted conditional on the cluster label. In this way, we can define an effect measure for the response variable for each input variable in each of the groups identified by the clustering algorithm, which is not possible in standard logistic regression because the effect of the reference class is aliased with the overall intercept. The interpretability of the model is enforced by promoting sparsity, a goal achieved by learning interactions in a hierarchical manner using a special group-Lasso technique. In addition, valid expressions are provided for computing odds ratios in the unusual parameterization used by the sparsity-promoting algorithm. We show how to apply the proposed data analysis pipeline to the problem of sub-phenotyping asthma patients also in terms of quality of response to therapy with monoclonal antibodies
Optimization Methodology for the Climb Trajectory of a SSTO Lifting-Body Reusable Launcer
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