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The interaction of magma and wall-rocks is inevitable when magma is moving through Earth's crust. These interactions happen on different timescales and especially the short-term interactions (seconds to days) during the final ascent of the magma can induce changes in eruption dynamics. However, information on this matter is scarce and scattered in different scientific fields. We conducted this review in order to present a full picture of the state of the art for short-timescale magma–wall-rock interactions. According to the three existing studies on short-term magma–carbonate interactions, magma viscosity is the most important controlling factor for carbonate assimilation. Lower viscosity magmas enhance CO 2 -bubble migration away from the reaction site, resulting in a higher carbonate assimilation rate. The released CO 2 plays an important role regarding eruption dynamics since a higher CO 2 release rate would result in accelerated magma ascent and may increase eruption intensity. Despite the importance for hazard assessment, important factors (pressure, magma composition, vapour phase solubilities, carbonate clast properties) for carbonate assimilation in general and CO 2 release rate in particular are not or only poorly constrained. This review presents the present-day knowledge of short-term magma–carbonate interaction that is relevant to establish the basis for future work concerning magma–wall-rock interactions.

Over the last few years, a paradigm shift has emerged towards a circular economy that seeks to return to the process as many material/energy flows as possible to increase the sustainability of products, reducing waste and pollution. The citrus industry is not an exception hence one way to apply this approach is through the re-use of certain outflows to produce bioproducts and bioenergy. The objectives of this work are, first, to present the environmental profile of lemons and derivatives in Argentina through the Life Cycle Assessment methodology, and second, to unveil environmental implications of shifting from traditional industries to biorefineries which apply circular economy principles. To do that, the current production scheme for manufacturing essential oil, concentrated juices and dehydrated peel is studied (baseline), to then consider new products, i.e., ethanol, limonene and biogas, through several scenarios with different degrees of biogas recirculation. We find that for lemon production, agrochemicals represent more than 60% in eleven of the twelve impact categories. For processed products, agriculture contributes with more than 50% in all the categories, followed by natural gas and electricity consumption. It also results that adding value to wastes and implementing circular economy strategies do not ensure a better environmental performance of the system. When comparing the current situation with biorefinery schemes, the most promising scenario is the one in which all the biogas is used to produce electricity, causing the least impact in eight of the twelve categories analyzed.

Strong electric field annihilation by particle-antiparticle pair creation, also known as the Schwinger effect, is a non-perturbative prediction of quantum electrodynamics. Its experimental demonstration remains elusive, as threshold electric fields are extremely strong and beyond current reach. Here, we propose a mesoscopic variant of the Schwinger effect in graphene, which hosts Dirac fermions with an approximate electron-hole symmetry. Using transport measurements, we report on universal 1d-Schwinger conductance at the pinchoff of ballistic graphene transistors. Strong pinchoff electric fields are concentrated within approximately 1 $\mu$m of the transistor's drain, and induce Schwinger electron-hole pair creation at saturation. This effect precedes a collective instability toward an ohmic Zener regime, which is rejected at twice the pinchoff voltage in long devices. These observations advance our understanding of current saturation limits in ballistic graphene and provide a direction for further quantum electrodynamic experiments in the laboratory., Comment: 39 pages, 13 figures, final version with extended discussion of the pinchoff effect in supplementary informations, abstract updated

Background Advanced heart failure is a clinical syndrome characterized by persistent or progressive symptoms of heart failure despite optimal medical therapy. Left ventricular assist device (LVAD) brings survival benefits and improvement in quality of life, compared with conventional medical treatments. Development of Right ventricle failure in patients with LVAD has a direct effect on mortality and hospitalization. Purpose Evaluation of clinical safety and feasibility of echocontrast in patients implanted with 3 different types of LVAD; improvement in the visualization of heart structures; intra and inter-operator agreement of RV assesement with and without contrast. Methods 43 patients were implanted with LVAD, 7 patients (16%) with Jarvik 2000, 31 (72%) with HeartMAte 3, 5 (12%) with (HeartWAre HVAD). Nine patients (21%) had contraindication or refused contrast. In 3 (7%) patients was technically challenging to obtain apical images at all levels. Two (5%) patients lost their follow-up. Our final population was of 29 (67%) patients (mean age 65±7 y; 100% Male). We assessed the reproducibility of these measurements between two different expert blind operators. Results Total 329 (64%) of 516 RV wall segments were available for qualitative analysis without contrast vs 451 (87%) with contrast (p0.86) while it was good for 2D-baseline derived parameters (ICC = 0.74) showing improvement of inter operator reproducibility in the evaluation of regional contractility in the contrast echocardiography modality. Conclusion EC is safe with all the types of LVAD examined. Accurate and reproducible visualization of RV is imperative for reliability of information, a routine use of EC could play a pivotal role in interpreting RV features. EC improves RV morphologic and functional judgment allowing greater accuracy and precision in the assessment of both global and regional RV functions. This finding may have important clinical improvement, especially in the future for analysis focused in RV prognostic role in LVAD patients. Funding Acknowledgement Type of funding sources: None.

This study presents information on the water footprint profile associated with lemon production and its derivatives in the province of Tucuman (Argentina). It follows a life cycle approach considering both water consumption and pollution. Our motivation is the prominent role of this activity in the economy of the region and in the world. The scope of the study covers the agricultural and industrial stages through a “from cradle to gate” approach (from lemon cultivation until production of finished products). The system boundaries include both foreground and background processes involving production and transportation of all material and energy inputs. The functional unit is 1 t of each product considered in the study: fresh fruit, essential oil, concentrated juice, and dehydrated peel. The general system is divided into Agriculture, Preselection, Packing, and Industry. Most of the data used stems from local sources to ensure representativeness. For the impact assessment, water scarcity, ecotoxicity, eutrophication, acidification, and human toxicity midpoint indicators are calculated. The analysis shows that the annual production and processing of lemons have an impact on water scarcity of 1·108 m3 world eq. The results for freshwater ecotoxicity, freshwater eutrophication, freshwater acidification, and human toxicity (non-cancer) are 3.60·106 CTUe, 4.87·t P eq, 5.92·10−1 kg SO2 eq, and 2.05·10−3 CTUh, respectively. For all lemon-based products, the indicator of water scarcity strongly depends on the irrigation water in the orchards. For water degradation, the most influential processes are the use and production of agrochemicals. In all cases, the agricultural stage is crucial in the water footprint profile of the finished products. The processes identified as hotspots through the water footprint profile of the products are as follows: irrigation, use, and production of N fertilizers and pesticides (copper compounds, abamectin and glyphosate), manufacturing of packaging material for fresh fruit, and consumption of natural gas. These should be addressed by lemon growers and manufacturers with preferential attention. Being the first local water footprint profile of Argentine lemons, this work is expected to serve as a baseline to provide diagnostic and improvement opportunities in the citrus sector for public and private stakeholders.

Highlights • EBV reactivation was observed in patients with COVID-19. • NK + and CD8 + T cell reduction was related to the severity of COVID-19 infection. • An increase of B cells in patients with severe symptoms was documented., Objectives The immunologic profile and opportunistic viral DNA increase were monitored in Italian patients with COVID-19 in order to identify markers of disease severity. Methods A total of 104 patients infected with SARS-CoV-2 were evaluated in the study. Of them, 42/104 (40.4%) were hospitalized in an intensive care unit (ICU) and 62/104(59.6%) in a sub-intensive care unit (SICU). Human cytomegalovirus (HCMV) and Epstein-Barr virus (EBV), Parvovirus B19 and Human Herpesvirus 6 virus reactivations were determined by real-time PCR, and lymphocyte subpopulation counts were determined by flow cytometry. Results Among opportunistic viruses, only EBV was consistently detected. EBV DNA was observed in 40/42 (95.2%) of the ICU patients and in 51/61 (83.6%) of the SICU patients. Comparing the two groups of patients, the EBV DNA median level among ICU patients was significantly higher than that observed in SICU patients. In parallel, a significant reduction of CD8 T cell and NK count in ICU patients as compared with SICU patients was observed (p

Background Right ventricular (RV) systolic dysfunction is considered an outcome predictor in various cardiovascular diseases. RV dysfunction, assessed by RV free wall longitudinal strain (RVFWSL) in patients candidate for trans–catheter aortic valve implantation (TAVI), has not been extensively explored as an outcome predictor. Purpose Evaluate the prognostic value of pre intervention RVFWSL in patients undergoing TAVI. Methods: retrospective analysis of 100 patients who underwent transfemoral TAVI in our hospital from 2015 to 2019, with at least a pre and post–TAVI echocardiography. Clinical and echocardiographic data before and after TAVI and follow–up data were collected. We considered the value of [23.3]% the cut–off of normality for RVFWSL. The primary end–point was a composite of death from any cause and hospitalization for heart failure. Results The median age of the patients was 81 years (79–83) with a functional status NYHA II–III (81%) before the intervention. EF was preserved in most of the patients (median 56%, 55–58), while Right ventricle dysfunction assessed with RVFWLS was reduced in half of the patients at baseline. At a median follow–up of 1023 days (630–1387), the univariate analysis demonstrated a predictive value for a reduced RVFWSL ( Conclusions Among patients with severe aortic stenosis undergoing TAVI, a reduced pre–implant RVFWSL is able to predict long–term outcome.

Background Computed tomographic (CT) coronary angiography represents a non–invasive approach to assess plaque characteristics that provides information to change treatment of coronary artery disease (CAD) and to asses risk stratification. Purpose Analyze the differences in plaque composition between patients with different plaque features: soft unstable plaques, hard stable plaques and no plaques; identify whether there is a relationship between the plaque density and the pericoronary fat attenuation index (pFAI). Materials and methods: 372 patients retrospectively analyzed who underwent CTCA for exclusion of CAD. They were divided into three groups: 37 (10%) patients with high attenuated plaques (> 60HU), 137 (37%)with low attenuated plaques ( Results and Discussion Low–attenuated plaques are significantly associated with older age, male sex, dyslipidemia and diabetes mellitus (p Conclusions Coronary plaque analysis showed a good correlation between high–risk plaques and pFAI, supporting the hypothesis that the presence of high–risk plaques can be correlated to inflammatory burden. Furthermore, the presence of high risk plaques predispose to death or hospitalization for coronary intervention.

Background Advanced heart failure is a clinical syndrome characterized by persistent or progressive symptoms of heart failure despite optimal medical therapy. Left ventricular assist device (LVAD) brings survival benefits and improvement in quality of life, compared with conventional medical treatments. Development of Right ventricle failure in patients with LVAD has a direct effect on mortality and hospitalization. Purpose evaluation of clinical safety and feasibility of echocontrast in patients implanted with 3 different types of LVAD; improvement in the visualization of heart structures; intra and inter–operator agreement of RV assesement with and without contrast. Methods 43 patients were implanted with LVAD, 7 patients (16%) with Jarvik 2000, 31 (72%) with HeartMAte 3, 5 (12%) with (HeartWAre HVAD). Nine patients (21%) had contraindication or refused contrast. In 3 (7%) patients was technically challenging to obtain apical images at all levels. Two (5%) patients lost their follow–up. Our final population was of 29 (67%) patients (mean age 65±7 y; 100% Male). We assessed the reproducibility of these measurements between two different expert blind operators Results Total 329 (64%) of 516 RV wall segments were available for qualitative analysis without contrast vs 451 (87%) with contrast (p 0.86) while it was good for 2D–baseline derived parameters (ICC = 0.74) showing improvement of inter operator reproducibility in the evaluation of regional contractility in the contrast echocardiography modality. Conclusion EC is safe with all the types of LVAD examined. Accurate and reproducible visualization of RV is imperative for reliability of information, a routine use of EC could play a pivotal role in interpreting RV features. EC improves RV morphologic and functional judgment allowing greater accuracy and precision in the assessment of both global and regional RV functions. This finding may have important clinical improvement, especially in the future for analysis focused in RV prognostic role in LVAD patients.

Background Although the primary cause of death in COVID–19 infection is respiratory failure, there are evidences that cardiac manifestations may contribute to overall mortality and can even be the primary cause of death. More importantly, it is recognised that COVID–19 is associated with a high incidence of thrombotic complications. Aim of the Study evaluate if CAC score was useful to predict in–hospital mortality and complications in patients with COVID infection Methods Two–hundred–eighty–four patients with proven SARS–CoV2 infection who had a non–contrast Chest CT at our facility were retrospective analysed for coronary artery calcium (CAC) score. Primary endpoint was in–h mortality. Secondary end–points were need for mechanical ventilation and Intensive Care Unit admission. Clinical and radiological data were retrieved. Results Patients with coronary calcium had higher inflammatory burden at admission (D–dimer, CRP, Procalcitonin) and higher high–sensitive Troponin I (HScTnI) at admission and at peak. While there was no association with presence of consolidation and ground glass opacities, patients with coronary calcium had higher incidence of bilateral infiltration and higher in–hospital mortality. The main finding of our research is that CAC alone does not completely identify all the population at risk of events in the setting of COVID 19 patients. Peak HScTnI was associated with higher mortality, intensive care unit admission and mechanical ventilation in both univariable at multivariable analysis. Conclusions Together with the presence of higher inflammation burden CAC may be a useful marker in identifying patients at risk of cardiovascular complications and in hospital mortality.

Funding Acknowledgements Type of funding sources: None. Background In patients with Advanced heart failure (AHF) long-term support with durable mechanical circulatory support (MCS) devices such as left ventricular assist device (LVAD) brings survival benefits and improvement in quality of life, compared with conventional medical treatments. Development of RVF in patients with LVAD has a direct effect on mortality and is associated with prolonged length of stay in intensive care unit and in-hospital stay and with poor quality of life. Purpose: the evaluation of clinical safety and feasibility of echocontrast (EC) in patients implanted with 3 different types of LVAD (HeartWAre HVAD, Jarvik 2000, HeartMate 3); the assessment of the improvement in the visualization of heart structures; the intra and inter-operator agreement of RV measurements (FAC, TAPSE, sPAP, TR, regional wall motion abnormalities) with and without contrast. Methods: Between 2014 and 2019, 43 patients were implanted with LVAD, in particular 7 (16%) patients were implanted with Jarvik 2000, 31 (72%) with HeartMAte 3, 5 (12%) pts with HeartWAre HVAD. Nine patients (21%) either had contraindication or refused contrast injection. In 3 (7%) patients, it was technically challenging to obtain apical images at all levels. Two (5%) patients lost their follow-up. Our final population was of 29 (67%) patients. We also assessed the reproducibility of these measurements between two different expert operators (blind analysis). Results: We observed no allergic reaction to EC. Total 329 (64%) of 516 RV wall segments were available for qualitative analysis without contrast vs 451 (87%) with contrast (p 0.86) while it was good for 2D-baseline derived parameters (ICC = 0.74) showing improvement of inter operator reproducibility in the evaluation of regional contractility in the contrast echocardiography modality. Conclusion: EC is safe with all the types of LVAD we examined. Accurate and reproducible visualization of RV is imperative for reliability of information, a routine use of EC could play a pivotal role in interpreting RV features. EC improves RV morphologic and functional judgment; allowing greater accuracy and precision in the assessment of both global and regional RV functions. This finding may have important clinical improvement, especially in the future for analysis focused in RV prognostic role in LVAD patients

Funding Acknowledgements Type of funding sources: None. Background right ventricular systolic dysfunction is considered an outcome predictor in various cardiac diseases, sometimes stronger than ejection fraction (EF). We assume that right ventricular dysfunction, calculated with echocardiography in patients candidate for trans-catheter aortic valve implantation (TAVI), could be an outcome predictor. Purpose: evaluate the prognostic value of pre-TAVI right ventricular free wall longitudinal strain (RVFWSL) in patients with severe aortic stenosis undergoing TAVI. Methods: retrospective analysis of 100 patient underwent transfemoral TAVI in our hospital from January 2015 to September 2019, with at least a pre-TAVI and post-TAVI echocardiography. For each patients we collected clinical and echo data before and after TAVI and during the follow-up; we measured RVFWSL off-line at the same time. We considered the value of [23.3]% the cut-off of normality for RVFWSL. The primary end-point was a composite of death from any cause and hospitalization for heart failure. Results: the median age of the patients was 81 years (79-83) and EF was preserved in most patients (median 56%, 55-58,28%). At a median follow-up of 1023 days (630-1387), the univariate analysis demonstrated a predictive of a reduced RVFWSL before TAVI (

In view of the extensive use of hexagonal boron nitride (hBN) in 2D material electronics, it becomes important to refine its dielectric characterization in terms of low-field permittivity and high-field strength and conductivity up to the breakdown voltage. The present study aims at filling this gap using DC and RF transport in two Au-hBN-Au capacitor series of variable thickness in the 10--100 nm range, made of large high-pressure, high-temperature (HPHT) crystals and a polymer derivative ceramics (PDC) crystals. We deduce an out-of-plane low field dielectric constant $\epsilon_\parallel=3.4\pm0.2$ consistent with the theoretical prediction of Ohba et al., that narrows down the generally accepted window $\epsilon_\parallel=3$--$4$. The DC-current leakage at high-field is found to obey the Frenkel-Pool law for thermally-activated trap-assisted electron transport with a dynamic dielectric constant $\epsilon_\parallel\simeq3.1$ and a trap energy $\Phi_B\simeq1.3\;\mathrm{eV}$, that is comparable with standard technologically relevant dielectrics., Comment: 10 pages, 2 figures, AM version in Materials Research Express

The main goals of retrofitting strategies are focused on addressing fundamental improvements in energy, environmental, and cost performance. This paper presents a novel formulation model aimed at determining optimal configurations for integrating a multi-energy type system to the process industries. The design and operation tasks are posed in mathematical terms as a bi-criteria mixed-integer linear programming problem (bi-MILP) that seeks to maximize the net present value (NPV) of the process supply chain while minimizing its environmental impact. Hence, the major contribution is the adoption of a mathematical approach to capture the cause-effect relationship between material/energy consumption/demand and the associated environmental impacts. The model capability is validated through a case study based on the Argentinean sugar cane industry and the benefits of integration are demonstrated.

This work comes to fill a knowledge gap regarding the sustainability of the lemon industry. The motivation is the prominent role of the citrus sector in the economy of the northwest of Argentina and in the world: Argentina is the eighth largest producer of fresh citrus fruits, one of the four leading lemon-producing countries and the world's first lemon processor. A water footprint study is conducted to obtain relevant information on the water consumption and degradation associated with citrus production, according to the Water Footprint Network guidelines. A remarkable aspect is that most data used come mainly from actual practices and sources considering daily weather data of seven weather stations from 2012 to 2018. The green, blue and grey water footprints linked to the primary production of lemons are evaluated every year. The water footprint is distributed approximately in 69% (234 m3t−1) green, 8% (30 m3t−1) blue and 23% (82 m3t−1) grey. In addition, the Available Water Remaining (AWARE) indicator is used for outlining the blue water sustainability, resulting in a potential for blue water deprivation of 102 m3 world eq. per tonne of harvested lemons. This work is expected to serve as a baseline to provide diagnostic and improvement opportunities in the lemon sector for public and private stakeholders.

This article contains (i) a set of spreadsheets with data compiled from municipal sanitation or solid waste plans, and (ii) data of the individual and aggregate performance indicators. These indicators have been published in the Journal of Cleaner Production in the article entitled “A municipal solid waste indicator for environmental impact: assessment and identification of best management practices.” The data contained in the spreadsheets are divided as follows: worksheet 1 includes the municipal solid waste generation data from the Brazilian municipalities studied; worksheet 2 presents the individual indicators that form the aggregate indicator; worksheet 3 presents the aggregate indicator and the classification of the municipalities; worksheet 4 provides data correlation; worksheets 5 to 10 depict boxplot graphs of the data; and worksheets 11 to 14 present graphs of individual indicators on a per capita basis and the ranking of municipalities. Fil: Deus, Rafael M.. Universidade Estadual São Paulo; Brasil Fil: Mele, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Universidade Estadual São Paulo; Brasil Fil: Bezerra, Barbara Stolte. Universidade Estadual São Paulo; Brasil Fil: Battistelle, Rosane Aparecida Gomes. Universidade Estadual São Paulo; Brasil

In this work, the effects of multi renewable resource-based energy integration in material supply chains are analysed under stochastic and deterministic conditions. The proposed approach is based on the development of a Multi-objective model to optimize the design and planning decisions of country-size SCs in the existence of conflicting objectives. A multi-scenario mixed-integer linear model is proposed and the capabilities of the approach are examined through a case study from a Sugar cane industry. The integrated energy/material supply chains model shows more economical feasibility than standalone ones and the stochastic solutions in this work demonstrate more robustness in the economic performance of the SC comparing to the deterministic one at any level of the environmental impact. In fact, the stochastic approach optimizes the conflicting objectives as well as improves the whole system robustness compared to the deterministic one and should be therefore the preferred choice in practice.

The sugar-alcohol industry plays a key role in the economics of the province of Tucuman (Argentina). For that reason, the quantification of water volumes consumed during sugarcane growing as well as the water used in the sugar and bioethanol production and in the manufacturing of associated by-products,is highly important for the development of policies that ensure the sugar and alcohol sustainability. The water footprint is the most widespread and up-to-date indicator used to assess water use and consumption associated to a product, activity or watershed. In this work, the green, blue and grey water footprint of the sugarcane production in Tucuman (Argentina), considering different technology levels, has been assessed. All data used in calculations are mostly taken from local sources, from campaigns 2012 to 2016, with the further goal of building a regional water footprint map of such an important cropas sugarcane is. Results are roughly distributed in green water footprint 12% and grey water footprint 88%. Green water footprint exhibits a counterposed behavior with respect to the technology levels. Blue water footprint is very low, under rainfed farming conditions, because it is only associated to dilution and applicationwater for agrochemicals. Grey water footprint exhibits high values for higher technology level due to the use of triazine-based herbicides, which are not present in the agrochemical recipe of the low technology level. This situation raises an interesting trade-off showing that not always higher technology levels would be the more sustainable ones. Fil: Jorrat, María del Milagro. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina Fil: Araujo, Paula Zulema. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Centro de Referencia para Lactobacilos; Argentina Fil: Mele, Fernando Daniel. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina

Multi-objective optimization (MOO) is widely applied in sustainability problems where several objectives must be accounted for in the analysis. Unfortunately, its complexity grows with the number of objectives, which hampers its practical use. In this paper, we simplify MOO problems via their combination with multi-attribute decision-making (MADM) methods. The approach identifies a unique Pareto solution of the MOO problem, which best reflects the decision-makers’ preferences, by using weighting factors generated via four well-known MADM methods: SWING, SMART, AHP and TRADE OFF. The capabilities of this approach are illustrated through its application to the design and planning of a sugar/ethanol supply chain using questionnaires filled in by academic experts in the problem. We find that the weights obtained using MADM algorithms may well differ from the ones given by standard life-cycle assessment methods employed in systems engineering problems. Overall, our approach simplifies the MOO problem by identifying solutions consistent with the decision-makers’ preferences and by providing valuable insight on how these preferences are articulated in practice. Fil: Wheeler, Jonathan. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina Fil: Páez, María Augusta. University of Manchester; Reino Unido Fil: Guillén Gosálbez, Gonzalo. Imperial College London; Reino Unido Fil: Mele, Fernando Daniel. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina

Made available in DSpace on 2020-12-12T02:26:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-01-01 The objective of this study was to develop an aggregate indicator to assess the environmental impact of municipal solid waste management in the small municipalities of the state of São Paulo, Brazil. Additionally, the study aimed at creating a classification of the municipalities considered to identify the best management practices. The study consisted of five phases: Phase 1: Selection of municipalities; Phase 2: Data collection (inputs); Phase 3: Use of the Waste Reduction Model; Phase 4: Analysis of results (outputs) and; Phase 5: Construction of the aggregate indicator and comparison between municipalities to analyze management practices. The results showed that the average waste generation was 223.89 kg (inhabitant−1 year−1), the average carbon dioxide equivalent (CO2e) emissions was 0.166 tons (inhabitant−1 year−1), the average amount of energy savings was 51.37 kWh (inhabitant−1 year−1) and that most municipalities had suitable final waste destinations. After developing the aggregate indicator, which was a geometric mean of the normalized indicators for waste generation, emissions of CO2e, energy consumption and quality of final destination, the municipalities were ranked. Among the ten best-ranked municipalities, six of them disposed of the waste in municipal landfills, and four, in private landfills. Only one municipality is part of a consortium, while seven of them have institutionalized selective collection. One of the critical points for good indicators is the presence of waste pickers. For further improvements in the management of these municipalities, it is suggested that practices involving recycling and the integration of waste pickers with proper technical training are developed and implemented further. It is also recommended fostering greater social inclusion and integrated participation in the management of municipal solid waste. The aggregate indicator developed was regarded as appropriate to assess the environmental impact of municipalities and to classify them, allowing the identification of the best management practices. São Paulo State University (UNESP) School of Engineering, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, CEP Department of Process Engineering and Industrial Management National University of Tucumán (UNT), Av. Independencia 1800, T4002BLR São Paulo State University (UNESP) School of Engineering, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, CEP

Recently, process industries have experienced a significant pressure to shift from centralized energy supplying systems to the in-situ exploitation of renewable resources. Special attention has been paid to multi resource-based energy systems, a particular case of distributed generation where processing nodes include energy generation and can operate either grid-connected or isolated. This work proposes a general model to determine the optimal retrofitting of a supply chain integrating renewable energy sources under uncertain conditions and to analyze the effect of different planning horizons in the solution. The proposed mixed integer linear programming (MILP) formulation allows determining the best combination of available technologies that satisfies the internal energy demand of a given set of scenarios while addressing total expected cost and expected environmental impact minimization. The potential of the approach is illustrated through a case study from the sugar cane industry proposed by Mele et al. (2011).

Non-ST-segment elevation acute coronary syndromes (NSTE-ACSs) are a group of clinical conditions characterized by acute myocardial ischemia. Conventional echocardiography is generally used to evaluate cardiac function using wall motion analysis and left ventricular ejection fraction but may be insufficient to explore all the complex features of NSTE-ACSs, which may vary substantially from patient to patient in terms of severity of ischemia and extent of involved myocardium. In the last years, speckle tracking echocardiography (STE) has become a widely available technique for the non-invasive assessment of cardiac function and has been repeatedly applied in the setting of NSTE-ACSs. In this review we summarize current evidence about the use of STE in patients with NSTE-ACSs, trying to underline advantages and limitations in comparison with conventional echocardiography for: diagnosis of NSTE-ACS, differential diagnosis, identification of high-risk patients, and prediction of outcome.

This article presents a mathematical model to optimize the planning decisions in the Colombian oil palm supply chain (SC). The optimization model consists of a mixed integer linear formulation, aiming at maximizing the expected net present value of the entire SC, including electricity supplied to the national grid by this activity. The model considers different products, types of warehouses, transportation modes, and export options, reflecting as far as possible the current situation of the oil palm industry in Colombia. It sets as free variables the location of the storage and production facilities, their expansion possibilities, and the flows of all feedstock and final products involved in the SC. The model constitutes a quantitative decision-making tool in the area of strategic design and optimal planning of biomass-based SCs. The optimal solution obtained by the model presents a more rational distribution of the production units in comparison with the current situation.

Fil: Araujo, Paula Zulema. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Tucuman. Centro de Referencia para Lactobacilos; Argentina. Universidad Nacional de Tucuman. Facultad de Ciencias Exactas y Tecnologia. Departamento de Ingenieria en Procesos y Gestion Industrial; Argentina

In this work, the effects of waste-based energy closed-loop integration under internal energy demand uncertainty on the multi-objective optimization of supply chains (SC) is analysed and compared. The proposed approach is based on developing a waste-based closed-loop energy integration MOO model to optimize the strategic and tactical decisions of country-size SCs in the presence of conflicting objectives. A stochastic multi-scenario mixed-integer linear program (MILP) is proposed and the capabilities of the approach are illustrated through a case study from a Sugar cane industry reported by Mele, et al.(2011). Additionally, this approach enables to consider and manage the financial risk associated to the different strategic/tactical decisions, resulting in a set of Pareto optimal solutions. It is shown that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact. In fact, the stochastic approach optimizes the conflicting objectives as well as improves the whole system robustness compared to the deterministic one and should be therefore the preferred choice in practice.

Solar power generation has been gaining worldwide increasing interest by virtue of its ability to meet both the growing energy needs and the increasing concerns on the carbon dioxide emissions. One of the most promising Concentrated Solar Power (CSP) technologies under development uses a parabolic dish to concentrate solar power into a focal point, raising thetemperature of a working fluid which is then used in a thermodynamic cycle to generate electricity. In the OMSoP project, funded by the European Commission, it is proposed to use a Brayton cycle in the form of a micro-gas turbine (MGT), which replaces the more conventional Stirling engine,with the aim of increasing the ratio of the electric power generated to the solar energy collected and improving the operability in relation to solar energy short time fluctuations. To achieve these objectives, research and development will be conducted in all aspects of the system leading to a full scale demonstrative plant to be located at the ENEA Casaccia Research Centre.The present work deals with the activities carried out so far by ENEA, which is principally involved in the development and experimental characterization of the dish component, and in the integration of the complete system, both in terms of modelling and realization. © 2015 The Authors. Published by Elsevier Ltd.

Since the advent of the all-volunteer force, one of the foremost personnel challenges of the U.S. Air Force has been recruiting and retaining an adequate number of medical and professional officers in the Air Force's seven medical and professional officer corps: the Biomedical Sciences Corps (BSC), the Chaplain Corps, the Dental Corps, the Judge Advocate General (JAG) Corps (attorneys), the Medical Corps (physicians), the Medical Service Corps (MSC), and the Nurse Corps. For each of these corps, there are highly similar jobs in the private sector, so attracting and retaining these corps' officers is a constant challenge. This article analyzes all seven Air Force medical and professional officer corps and their relative statuses with regard to end strengths, accession levels, promotion flow, and attrition since the late 1970s. The authors find that recent accession and retention trends have been most adverse in the Air Force's Nurse Corps, while the MSC and the JAG Corps appear to have the most stable populations.

Purpose The production of bioethanol in Argentina is based on the sugarcane plantation system, with extensive use of agricultural land, scarce use of fertilizers, pesticides, and artificial irrigation, and burning of sugarcane prior to harvesting. The objective of this paper is to develop a life cycle assessment (LCA) of the fuel ethanol from sugarcane in Tucumán (Argentina), assessing the environmental impact potentials to identify which of them cause the main impacts. Methods Our approach innovatively combined knowledge about the main impact pathways of bioethanol production with LCA which covers the typical emission-related impact categories at the midpoint life cycle impact assessment. Real data from the Argentinean industry subsystems have been used to perform the study: S1—sugarcane production, S2—milling process, S3—sugar production, and S4—ethanol production from molasses, honey, or sugarcane juice. Results and discussion The results are shown in the three alternative pathways to produce bioethanol. Different impact categories are assessed, with global warming potential (GWP) having the highest impact. So, the production of 1 kg of ethanol from molasses emitted 22.5 kg CO2 (pathway 1), 19.2 kg CO2 from honey (pathway 2), and 15.0 kg CO2 from sugarcane juice (pathway 3). Several sensitivity analyses to study the variability of the GWP according to the different cases studied have been performed (changing the agricultural yield, including economic and calorific allocation in sugar production, and modifying the sugar price). Conclusions Agriculture is the subsystem which shows the highest impact in almost all the categories due to fossil fuel consumption. When an economic and calorific allocation is considered to assess the environmental impact, the value is lower than when mass allocation is used because ethanol is relatively cheaper than sugars and it has higher calorific value. Fil: Amores, María José. Universitat Rovira I Virgili; España Fil: Mele, Fernando Daniel. Universidad Nacional de Tucuman. Facultad de Cs.exactas y Tecnologia. Departamento de Ingenieria En Procesos y Gestion Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina Fil: Jiménez, Laureano. Universitat Rovira I Virgili; España Fil: Castells, Francesc. Universitat Rovira I Virgili; España

This paper addresses the strategic planning of bioethanol supply chains (SC) under uncertainty in the demand. The design problem is setting as a reformulation of a multiscenario mixed-integer linear programming (MILP) problem. It consists in the adoption of a simulation-based optimization scheme to accommodate the variables belonging to different management levels. The strategy supports decisions on the capacity expansions of the production and storage facilities of the network over time along with the associated planning decisions (i.e., production rates, sales, etc.). The capability of the approach is demonstrated through a case study based on the Argentinean sugarcane industry. Results include the investment strategy for the optimal SC configuration. Fil: Durand, Guillermo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina Fil: Mele, Fernando Daniel. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Guillén Gosálbez, Gonzalo. Universitat Rovira i Virgili; España Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina

This chapter describes how to optimise energy systems considering their economic and environmental performance simultaneously. To this end, we follow an approach that combines life cycle assessment with multi-objective optimisation. We illustrate how to apply such a framework to the strategic design and planning of biofuel supply chains. The problem is formulated in mathematical terms as a multi-objective mixed-integer linear programme. The aim of the design/planning task is to maximise the net present value while the environmental impact is minimised simultaneously. Eco-indicator 99 is the life cycle assessment methodology incorporated in the model to quantify the environmental damage. The implementation of the algorithm in a case study based on the Argentine industry reveals the conflictive trade-off between economic and environmental objectives. The proposed framework provides valuable insight into the incidence of key operational features in the optimal biofuel supply chain network. Fil: Páez, María Augusta. University of Manchester; Reino Unido Fil: Mele, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina Fil: Guillén Gosálbez, Gonzalo. University of Manchester; Reino Unido

The design of more sustainable bioethanol supply chains (SCs) has recently emerged as an active area of research. Most of the approaches presented so far have somehow a limited scope, as they focus on minimizing the emitted greenhouse gases as unique criterion, neglecting the damage caused in other impact categories. In this work, we address the multiobjective design of bioethanol SCs considering several life cycle assessment impacts. To overcome the numerical difficulties of dealing with several objective functions, we investigate the application of a rigorous mixed-integer linear programming-based dimensionality reduction method that minimizes the error of omitting objectives. The usefulness of this approach is tested through its application to the design of a bioethanol/sugar SC in Argentina, in which five environmental objectives are simultaneously optimized along with the net present value. The proposed method makes it possible to reduce the number of environmental indicators, thereby facilitating the calculation and analysis of the Pareto solutions.

In this paper, we address the strategic planning of integrated bioethanol–sugar supply chains (SC) under uncertainty in the demand. The design task is formulated as a multi-scenario mixed-integer linear programming (MILP) problem that decides on the capacity expansions of the production and storage facilities of the network over time along with the associated planning decisions (i.e., production rates, sales, etc.). The MILP model seeks to optimize the expected performance of the SC under several financial risk mitigation options. This consideration gives a rise to a multi-objective formulation, whose solution is given by a set of network designs that respond in different ways to the actual realization of the demand (the uncertain parameter). The capabilities of our approach are demonstrated through a case study based on the Argentinean sugarcane industry. Results include the investment strategy for the optimal SC configuration along with an analysis of the effect of demand uncertainty on the economic performance of several biofuels SC structures.

In this article, we propose a new method to reduce the computational burden of strategic supply chain (SC) planning models that provide decision support for public policy makers. The method is based on a rolling horizon strategy where some of the integer variables in the mixed-integer programming model are treated as continuous. By comparing with rigorous solutions, we show that the strategy works efficiently. We illustrate the capabilities of the approach presented by its application to a SC design problem related to the sugar cane industry in Argentina. The case study involves determining the number and type of production and storage facilities to be built in each region of the country so that the ethanol and sugar demand is fulfilled and the economic performance is maximized. Fil: Kostin, A. M.. Universitat Rovira I Virgili; España Fil: Guillén Gosálbez, G.. Universitat Rovira I Virgili; España Fil: Mele, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina Fil: Bagajewicz, M. J.. University of Oklahoma; Estados Unidos Fil: Jiménez, L.. Universitat Rovira I Virgili; España

The objective of this work is to present a quantitative tool to support decision-making in the area of optimal design of supply chains (SC) for the combined production of sugar and ethanol. The problem is formulated as a multiobjective mixed-integer linear program that seeks to optimize simultaneously the economic and environmental performance of the production chain. The advantages of the approach presented are illustrated through its application to a case study, in which a trade-off exists between the economic and environmental performance of the network. Our method provides valuable insight into the problem and a guide to adopt more sustainable strategic alternatives in the design of SCs with embedded biorefineries. Fil: Mele, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina Fil: Kostin, Andrew M.. Universitat Rovira I Virgili; España Fil: Guillén Gosálbez, Gonzalo. Universitat Rovira I Virgili; España Fil: Jiménez, Laureano. Universitat Rovira I Virgili; España

We support, with new fitting instruments and the analysis of more recent experimental data, the proposal of a relationship between the mass of a Supermassive Black Hole (SMBH) and the kinetic energy of random motions in the host elliptical galaxy. The first results obtained in a previous paper with 13 elliptical galaxies are now confirmed by the new data and an enlarged sample. We find $M_{BH} \propto (M_{G} \sigma^{2}/c^2)^\beta$ with $0.8 \leq \beta \leq 1$ depending on the different fitting methods and samples used. The meaningful case $\beta = 1$ is carefully analyzed. Furthermore, we test the robustness of our relationship including in the sample also lenticular and spiral galaxies and we show that the result does not change. Finally we find a stronger correlation between the mass of the galaxy and the corresponding velocity dispersion that allows to connect our relationship to the $M_{BH} \propto \sigma^\alpha$ law. With respect to this law, our relationship has the advantage to have a smaller scatter., Comment: 17 pages, 3 figures, accepted for publication in IJMPD

In this work, decisions that have a long lasting effect on the supply chain (SC) such as the design and retrofit of a production/distribution network are considered. The retrofitting tasks are accomplished by using a SC agent-oriented simulation system, which model each entity belonging to the SC as an independent agent. The starting point is a set of possible design options for the existing SC. For each design alternative a performance index is obtained through the agent-based framework by looking for the best value of the operational variables associated to the resulting network. The proposed methodology allows to address the design of complex SCs which are hard to be modelled otherwise, for example by means of standard mathematical programming tools. Specifically, the multi-agent system is suitable for SCs that are either driven by pull strategies or operate under uncertain environments, in which the mathematical programming approaches are likely to be inferior due to the high computational effort required. The advantages of our approach are highlighted through a case study comprising several plants, warehouses and retailers.

To help inform decision making in the event that the Army experiences significant changes to its budget, the U.S. Army Quadrennial Defense Review Office asked the RAND Arroyo Center to provide an empirical understanding of how Army spending affects communities and states. This report presents findings from RAND Arroyo Center research on the economic activity supported by Army spending at the local level.

To help inform decision-making in the event that the Army experiences significant changes to its budget, the U.S. Army Quadrennial Defense Review Office asked the RAND Arroyo Center to provide an empirical understanding of how Army spending affects communities and states. The main report, The Armys Local Economic Effects, presents findings on the economic activity supported by Army spending at the local level. This appendix is an ancillary volume. It provides detailed results of the analysis, organized by state and congressional district. It includes descriptions of the overall economic effects for each state, then delves into more detail by fiscal year, from 2012 through 2014, concluding with a parsing of the data by congressional district, providing maps and calculations. This volume includes Alabama through Minnesota.

This work presents a novel approach that addresses the management of chemical supply chains (SCs) under demand uncertainty. One of the main objectives is to overcome the numerical difficulties associated with solving the underlying large-scale mixed integer nonlinear problem (MINLP). The approach that is proposed relies on a simulation-based optimization strategy that uses a discrete-event system to model the SC. Within this framework, each SC entity is represented as an agent whose activity is described by a collection of states and transitions. The overall system is coupled with an optimization algorithm that is designed to improve its operation. This strategy is a very attractive alternative in the field of decision-making processes under uncertainty, the advantages of which are highlighted with some cases of SC networks that are composed of several plants, warehouses, distribution centers, and retailers.