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The electrification-based literature reports a limited knowledge about the mechanisms of evolution of electricity demand in off-grid settings, especially in remote contexts of developing countries, due to the lack of robust and appropriate modelling frameworks. Such lack of understanding and modelling endeavour contributes to an inefficient allocation of resources for electrification projects and inappropriate off-grid sizing processes. As a first step towards the development of a more appropriate electricity demand model, we present a comparative study of two approaches for modelling different diffusion mechanisms of electricity connections: system-dynamics and agent-based models. The latter includes the modelling of social network archetypes in the simulation of diffusion processes. We model different scenarios of diffusion and we use them for evaluating the impact on the sizing process of an off-grid hydroelectric system. The results suggest that the structure of the social network can represent a crucial parameter that can impact on timing needed to complete the diffusion of electricity access – from few months to even >10 years. This affects the sizing process and the long-term sustainability of the power system, leading to variation of the hydroelectric capacity and the battery size up to around 55% and 100%, respectively. Our results indicate that the agent-based approach allows a more diversified representation of diffusion processes, but the limitations and scarcity of data can be an obstacle to their prompt application for energy application in unelectrified areas. On the contrary, system-dynamics can represent a more appropriate method since it requires less quantitative data and it provides a more structural and holistic modelling framework for conceptualising and formulating in a the determinants and complexities affecting the evolution of electricity demand in unelectrified areas.

This paper deals with an economic aspect of distributed generation systems which rural energy cooperatives may mainly support, since they can effectively coordinate the different stakeholders within an energy access initiative. Members of a rural energy cooperative would share the costs of deploying a distributed generation system, so that each of them can benefit from it. To minimise the overall investment cost, such a cooperative must consider both technical sizing and cost allocation among its members. For the latter, an important issue to take into account is the so-called willingness-to-pay. For obtaining the design of the distributed generation system we propose to use facility location covering (FALCO) models. The solution of the FALCO model provides both the structure of the distributed generation system and the investment cost to be covered by the members of the cooperative. We take advantage of the structure of the primal and dual optimal solutions of the FALCO model to endogenously determine the minimum and maximum willingness-to-pay of the cooperative members and then to apply rationing techniques to obtain the final allocation of costs to each member. Thus, our approach optimises the generator locations and minimises the total system cost, while assigning to each member at least her minimum willingness-to-pay. From our point of view, this method may help the beneficiaries to accept the investment cost allocation. Finally, a case study based on real data from a rural village in Maharashtra, where a group of farmers wanting to buy and share an energy system to pump water for irrigating their fields, is used to illustrate the working of the proposed cost allocation methodology.

© 2019 Elsevier Ltd Energy access projects in remote off-grid areas would benefit from the adoption of a multi-energy system perspective, addressing all energy needs – not only lighting and power appliances, but also water-heating and cooking – by means of a mix of energy vectors. However, multi-energy analyses in remote areas are hindered by a lack of models allowing for the generation of multi-energy load profiles based on interview-based information characterised by high uncertainty. This study proposes a novel open-source bottom-up stochastic model specifically conceived for the generation of multi-energy loads for systems located in remote areas. The model is tested and validated against data obtained from a real system, showing a very good approximation of measured profiles, with percentage errors consistently below 2% for all the selected indicators, and an improved accuracy compared to existing approaches. In particular, some innovative features – such as the possibility to define and modulate throughout the day appliances’ duty cycles – seem to be determinant in marking a difference with previous approaches. This might arguably be even more beneficial for case studies characterised by a larger penetration of appliances that are subject to complex and unpredictable duty cycle behaviour. ispartof: Energy vol:177 pages:433-444 status: published

Electric cooking (or e-cooking) based on renewable sources and highly-efficient cooking devices could represent a sustainable and reliable option to achieve the universal access to clean cooking facilities by 2030. Still, the techno-economic feasibility of e-cooking has never been evaluated through (i) a high-resolution assessment of the electric and cooking load profiles, coupled with (ii) a least-cost energy system optimisation for the related electricity supply. Hence, the present study aims at accurately investigating the techno-economic potential of a fully-renewable solar micro-grid, ensuring an integrated access to electricity and clean cooking, based on two representative case studies in Tanzania, namely: (i) a residential case study, and (ii) a community-service case study. Bottom-up stochastic load profiles are generated for the two contexts by expanding the existing LoadProGen model with a novel complementary algorithm for the computation of high-resolution cooking loads. The cost-optimised results prove the cost-competitiveness of e-cooking, especially for the community-service case, where it would require only an additional 17% capital investment due to the pre-existence of other energy-intensive activities. Moreover, the range of Levelised Cost for Cooking a Meal (LCCM) obtained for e-cooking considering the different scenarios lies within 0.16 ÷ 0.70 USD/meal, a range that is comparable with that of all other cooking options – including firewood –, and even more cost-competitive than LPG.

The mass-scale integration of electric vehicles into the power system is a key pillar of the European energy transition agenda. Yet, the extent to which such integration would represent a burden for the power system of each member country is still an unanswered question. This is mainly due to a lack of accurate and context-specific representations of aggregate mobility and charging patterns for large electric vehicle fleets. Here, we develop and validate against empirical data an open-source model that simulates such patterns at high (1-min) temporal resolution, based on easy-to-gather, openly accessible data. We hence apply the model – which we name RAMP-mobility – to 28 European countries, showing for the first time the existence of marked differences in mobility and charging patterns across those, due to a combination of weather and socio-economic factors. We hence quantify the impact that fully-electric car fleets would have on the demand to be met by each country's power system: an uncontrolled deployment of electric vehicles would increase peak demand in the range 35–51%, whilst a plausible share of adoption of smart charging strategies could limit the increase to 30–41%. On the contrary, plausible technology (battery density) and infrastructure (charging power) developments would not provide substantial benefits. Efforts for electric vehicles integration should hence primarily focus on mechanisms to support smart vehicle-to-grid interaction. The approach is applicable generally beyond Europe and can provide policy makers with quantitatively reliable insights about electric vehicles impact on the power system.

According to IEA projections, the penetration of electric vehicles in the world transportation sector is expected to increase in the next decades to comply with the future GHG emissions policy targets. The change in transport technology mix will cause a change the environmental and economic impacts of the transportation sector, switching it from flows to funds, that is, from the production and use of the fuel to the production of the fuel pathway and powertrain infrastructures. Therefore, due to their comprehensiveness, the use of Life Cycle Assessment models will be increasingly important with respect to Well-to-Wheels ones in assessing the impact of future transport technologies. In this paper, the Hybrid Input-Output analysis is proposed as the appropriate framework to assess the impact due to a change in transport technology mix from a LCA perspective. First, LCA and WTW approaches are theoretically compared. Secondly, the LCA model is applied for the analysis of the economic and environmental impact caused by the prospected penetration of Fuel Cell Electric Vehicles (FCEV) based on Proton Exchange Membrane Fuel Cell (PEMFC) for Germany in 2050. In addition to the production of the vehicles, the LCA model includes the infrastructures for hydrogen production and distribution and the prospected change in the national electricity production mix. Significant discrepancies have been found by comparing results of LCA with the ones obtained by well-established WTW models already available in the literature. It is found that the impact caused by infrastructures and production of vehicles could significantly offset the expected reduction in CO2 emissions and primary non-renewable energy consumptions.

Sphingosine 1-phosphate (S1P) is a potent bioactive sphingolipid binding to specific G protein-coupled receptors expressed in several organs. The relevance of S1P-S1P receptor axis in the pathophysiology of immune and nervous systems has encouraged the development of S1P receptor modulators for the treatment of neurological, autoimmune and/or inflammatory disorders. Currently, four S1P receptor modulators are approved drugs for multiple sclerosis (MS), an inflammatory disorder of the central nervous system. As main pharmacologic effect, these treatments induce lymphopenia due to the loss of responsiveness to S1P gradients guiding lymphocyte egress from lymphoid organs into the bloodstream. Recent data point to immunological effects of the S1P modulators beyond the inhibition of lymphocyte trafficking. Further, these drugs may cross the blood-brain barrier and directly target CNS resident cells expressing S1P receptors. Here we review the role of S1P signalling in neuroimmunology at the light of the evidences generated from the study of the mechanism of action of S1P receptor modulators in MS and integrate this information with findings derived from neuroinflammatory animal models and in vitro observations. These insights can direct the application of therapeutic approaches targeting S1P receptors in other disease areas.

Faults and malfunctions occurring in engineering systems may cause additional resources consumptions and economic expenditures, thus their detection and isolation is of great practical significance. The procedure to discover faults is known as diagnosis, and it can be based on different techniques, depending on the purpose of the analysis: to predict the failure time of the component, or to quantify the inefficiencies of the system due to the anomaly. Among the existing approaches adopted to diagnose the energy systems, Thermoeconomic diagnosis provides useful information to detect the anomalies and to quantify its negative impacts. However, this method does not allow to identify possible strategies useful to reduce the inefficiencies caused by anomalies, which could be a crucial need for the system operator. To face this issue, this article proposes a method to perform Thermoeconomic diagnosis of energy systems that enables the analyst to understand the interdependencies between the components, and decomposing the main indicator resulting from Thermoeconomic diagnosis, known as malfunction. The method provides useful information for the system operators to define practical strategies to reduce the negative effects of malfunctions. This approach is also formalized and applied to the CGAM benchmark to highlight the practical achievements of this approach with numerical values. It is found that the proposed approach provides useful insight about the effects of malfunctions, and it may be helpful for system operators to reduce the negative impacts of the anomaly by pinpointing the component with higher contribution in total inefficiency of the system. In this specific case, proper intervention on the pinpointed component mitigated the total inefficiency of the system by almost 40%, and recovered the reference efficiency of the system.

Laboratory protocols based on water heating procedures represent the most widespread tool for the evaluation of Improved Cooking Stoves (ICSs) thermal performance. Nevertheless, the performance of the cooking system can vary substantially when the boundary conditions – ambient conditions, burn sequence – differ from those experienced in a specific lab. Consequently, we developed and experimentally validated a Cooking Stoves Thermal Performance Simulator (Cook-STePS), based on a 1-D heat and mass transfer model and implemented in an Excel® and VBA environment, in order to provide additional information about how the performance of a cooking system would change, in selected conditions, as compared to the baseline laboratory performance. The study shows how the tool can be effectively applied to a generic cooking system through a two-steps procedure, based on (i) a preliminary set of experimental tests in controlled conditions and (ii) the simulation of performance in the desired conditions.

In the world, the number of forcibly displaced people is arising. These people have several needs, especially in terms of food security. The humanitarian response usually focuses on food availability and access, while food processing is often neglected. In this framework, cooking technologies play an essential role. Many scientific studies and international reports address the issue of clean cooking technologies dissemination in developing countries. Less information is instead available in the literature for the specific case of humanitarian contexts, such as refugee and Internally Displaced Persons (IDP) camps, or informal humanitarian settlements. Unsustainable and inefficient cooking technologies or practices can have direct impact on food preparation, and indirect effects on local biomass resources overexploitation, health of local people, and social conflicts between hosted and hosting communities. This study aims at presenting a systematic review of both scientific and grey literature on cooking technologies and related practices, including a selection of experiences from the implementation of cooking devices in humanitarian projects and programmes. The Authors conclude that the attention to the problem is arising, but still very few information is available, in terms of scientific research.

Supply chain analysis is an expression used to refer to the process of investigating and studying the role and contribution of each economic agent along the supply chain (actors such as producers, traders and consumers, as well as legal entities such as businesses, authorities and development organizations) that contributes directly to the generation of a final product or service. It involves the evaluation of every stage of the supply chain starting from the raw material or intermediate product acquisition and finishes downstream, after several stages of transformation or increase in value and the final delivery of the product to the costumer. The rise of globalization caused global trading to become more common, increasing the role and importance of supply chain management. Global supply chains usually extend between industrialized and developing countries, in which the variation of economy, regulations, legalisation and standards pose difficulties in managing the supply chain. Usually developing countries play the role of raw material suppliers or manufacturers to industrialized countries. However, they face problems affecting the performance of the supply chain, which include instability of governments and policies, corruption, labour intensive industries, deteriorated infrastructures, limited use of new technologies, underemployment, child labour, and low education level of the population. This report provides a set of simple and easy to follow tools for analysing supply chains in developing countries.

Production activities of modern economies are ultimately sustained by depletion of non-renewable fossil fuels. In the perspective of non-renewables displacement, an accurate evaluation of energy embodied in goods and services is crucial in order to select among alternative products or policies. Economic-based Input-Output models are widely used for this purpose: however, due to the increasing amount of international trades of products, definition of appropriate methods to account for the energy embodied in trades is nowadays crucial. In this paper, international trades treatment methods in Input-Output analysis are comprehensively formalized and applied to a case study based on the World Input-Output Database (WIOD). Energy embodied in final demand and in detailed products of key national energy sectors have been evaluated for the WIOD countries according to Single-Region and Multi-Regional models. It is found that an inappropriate use of international trades treatment models may produce very inaccurate estimations of numerical values of embodied energy. Three country groups has been identified, characterized by different ranges of fractions of imported/exported primary fossil fuels: Single-Region method A returns best results for countries of Group 1, with high values of fossil exports and low values of fossil imports; Multi-Regional method C is to be preferred for countries of Group 2, with high values of fossil imports and low values of fossil exports; finally, Single-Region method B returns lower deviations compared to other methods for countries of group 3, with low values of fossil imports and exports. This paper aims at supporting researchers in the field of Life Cycle Assessment in the application of Environmentally extended Input-Output analysis, finding the best trade-off between the efforts due to data collection and the accuracy of results.

The fixed dome digester design is the most deployed small scale biogas technology in sub-Sahara Africa (SSA). This design is deployed on mono-feedstock-wet anaerobic digestion (WAD) principle. Little or nothing has been reported in the literature on the sustainability in terms of the actual field operation and performance of this design within the SSA context. This study aims at bridging this gap and bringing additional insights to the scientific literature by investigating the sustainability of the Nepali–type fixed dome digester within the context of rural Cameroon. The investigations were evaluated in terms of operating parameters, biogas production, production rate and productivity of the digester. In addition the local investment cost of the design was analyzed. The design was operated on multiple-locally-available feedstock mixed with water at an average of 3:1 ratio resulting in a higher than design TS of 16%. The design, thus was operated towards the dry anaerobic digestion principle, highlighting insufficient mono-feedstock and water scarcity for a sustainable operation of the design within the context of rural SSA. The average biogas production was 1.2 m 3 biogas /day, giving average volumetric production rate of 0.16 m 3 biogas /m 3 digester day −1 and yields of 0.18 m 3 biogas /kg VS respectively. This low performance compared with the potential mesophilic biogas production rate of 0.27 m 3 biogas /m 3 digester day −1 could be linked to insufficient mixing of digester content and low operating temperatures. Gas storage facility (dome), skilled labour and cement made significant contributions to the investment cost of the digester. The Levelized cost of Energy from the digester was less than 1 € cents/MJ.

In this paper, thermodynamic performances of a Waste-to-Energy power plant are evaluated by means of Exergy Life Cycle Assessment (ELCA). Environmentally Extended Input-Output Analysis is proposed as the computational structure of ELCA, allowing to account for the embodied exergy of electricity production and for the Exergy Return on (non-renewable Exergy) Investment (ExROI). Results of the analysis reveal that non-renewable resources requirement of the WtE plant is not negligible. Nonetheless, the plant is able to produce a net amount of electricity that pays back such resources requirements about a hundred times.

The performance indicators of Improved Cook Stoves (ICSs) for Developing Countries are commonly evaluated and compared using the arithmetic average of replicated tests performed using a standardized laboratory-based test, commonly the Water Boiling Test (WBT). Possibility theory is here employed to examine energy data retrieved from the WBT-based literature regarding the results of laboratory tests on ICSs and traditional Three-Stone Fire (TSF) stoves; fifty-seven comparisons of stoves are analysed. Chebyshev and uniform possibility distributions are employed to represent energy data affected by epistemic uncertainty. The extension principle of fuzzy set theory is applied to obtain possibility distributions of the saving of fuel use parameter for each comparison of cookstoves. The results indicate that at 90%, 95% and 99% degree of confidence, only 22.22%, 15.00% and 15.00% of all the supposed “improved” stoves emerged respectively as real ICSs at most, while the percentage of “improved” stoves obtained by considering the mean values of the WBT is among 3 and 6 times higher than the percentage resulted by taking into account the epistemic uncertainties. The work suggests how neglecting intrinsic uncertainties of tests’ results might lead to misinterpret and report non-comprehensive information about ICSs’ thermal energy performance, and to reveal some concerns about their effective improvements over traditional devices.

One of the most controversial topics in energy analysis consists in the internalization of the effects of human labor in the embodied energy requirements of goods and services. In this paper, the Bioeconomic Input-Output model is proposed to address such issue: it consists in a partially closed Hybrid Input-Output model in which the production of human labor is internalized within the economy as a new productive sector. The human labor sector absorbs a portion of the national final demand, while it produces working hours in order to sustain the national economic activities. The Bioeconomic model causes a reallocation of the total energy embodied in the production of goods and services due to two overlapping effects: a change in the national production technology due to the definition of the human labor sector, and a reduction in the available final demand for the consumptions of the households. The Bioeconomic and the standard Input-Output models are comparatively applied for the analysis of (1) the energy embodied in goods and services produced by the Italian economy in 2010, and (2) the primary energy requirements of alternative dishwashing solutions in Italy. Specific embodied energy in Italian products increases by less than 5% for mining and energy industries, by 5–15% for manufacturing industries and by 15–70% for tertiary sectors. On the other hand, the energy embodied in total production from each sector may be lower or greater (from −20% to +50%) with respect to results of the standard Input-Output model. Moreover, it is found that the energy embodied in dishwashing by hand and by dishwasher in Italy increases respectively by 62% and by 35% if the Bioeconomic model is adopted. Based on these results, Authors argue that human labor should methodically be included alongside the supply chain of goods and services in both embodied energy analysis and life-cycle assessment.

In developing countries, energy is recognized to be essential for promoting equitable growth, fostering social inclusion and preserving the environment. Nevertheless, the current state of the energy sectors of developing countries still represents a major hindrance to the fulfillment of this goal. In this frame, electrical energy storage may allow a cost-effective exploitation of renewable sources in order to cope with the improvement of the power supply service via local national grids, but mainly it may become a building block of rural electrification through integration within off-grid systems. This paper focuses on electrical energy storage in sub-Saharan Africa providing an overview of the main aspects of this theme. Indeed, the specific features of the power sector in sub-Saharan Africa are analyzed about the framework of application of electrical energy storage. The typical technologies implemented in this context and the status of the market as well as of the economic models to support the diffusion of storage together with renewable energy technologies are highlighted. Moreover, an overview of technical aspects such as storage capacity sizing and interface converters for integration with renewables are described. Finally, an experimental application of a hybrid micro-grid in rural Tanzania is presented. With this paper, our aim is to provide an overall view, within the main technical and non-technical aspects, of electrical energy storage in a context – sub-Saharan Africa – which has a huge potential, both in market terms, but also with regards to the possibility to develop and implement alternative technical solutions which may be integrated in the power systems of high income countries as well. © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ available 1 november 2018

Astrocytes are crucial regulators of innate and adaptive immune responses in the injured central nervous system. Depending on timing and context, astrocyte activity may exacerbate inflammatory reactions and tissue damage, or promote immunosuppression and tissue repair. Recent literature has unveiled key factors and intracellular signaling pathways that govern astrocyte behavior during neuroinflammation. Here we have re-visited in vivo studies on astrocyte signaling in neuroinflammatory models focusing on evidences obtained from the analysis of transgenic mice where distinct genes involved in ligand binding, transcriptional regulation and cell communication have been manipulated in astrocytes. The integration of in vivo observations with in vitro data clarifies precise signaling steps, highlights the crosstalk among pathways and identifies shared effector mechanisms in neuroinflammation.

The impact of energy production, transformation and use on the environmental resources encourage to understand the mechanisms of resource degradation and to develop proper analyses to reduce the impact of the energy systems on the environment. At the technical level, most attempts for reducing the environmental impact of energy systems focus on the improvement of process efficiency. One way toward an integrated approach is that of adopting exergy analysis for assessing efficiency and test improving design and operation solutions. The paper presents an exergy based analysis for improving efficiency and safety of energy systems, named Thermorisk analysis. The purpose of the Thermorisk analysis is to supply information to control, and eventually reduce, the risk of the systems (i.e. risk of accidents) by acting on the thermodynamic parameters and safety characteristics in the same frame. The proper combination of exergy and risk analysis allows monitoring the effects of efficiency improvement on the safety of the systems analyzed. A case study is presented, showing the potential of the analysis to identify the relation between the exergy efficiency and the risk of the system analyzed, and the contribution of inefficiencies on the safety of the process. Possible modifications in the process are indicated to improve the safety of the system.

This paper proposes an exergy-based well-to-wheels analysis to compare different passenger vehicles, based on three key indicators: petroleum energy use, CO 2 emissions, and economic cost. A set of fuel pathways, including petroleum-based fuels, compressed natural gas, biofuels, and electricity are considered in five representative national energy mixes, namely Brazil, China, France, Italy, and the United States of America. Results show no fundamental difference in the fossil fuel pathways among the five scenarios considered. Compressed natural gas vehicles and electric vehicles can completely displace oil consumption in the personal transportation sector. Compressed natural gas vehicles also reduce CO 2 emissions by over 20% compared to gasoline vehicles. Emissions from electric vehicles greatly vary depending on the electricity mix. In low-carbon electricity mixes electric vehicles reach almost-zero CO 2 emissions, while the use of biofuels leads to the lowest CO 2 emissions in carbon-intensive electricity generation mixes, where vehicles running on E85 could reduce CO 2 emission by over 50% compared to gasoline vehicles. Hybrid electric vehicles show the lowest overall economic cost, due to improved efficiency and low cost of petroleum-based fuels. Vehicles running on electricity are characterized by significantly higher capital cost and lower operating costs. Thus, different electricity generation costs impact minimally the overall cost. These results can be used to inform decision-makers regarding the multi-dimensional impact of passenger vehicles, including environmental impact, economic cost, and depletion of primary energy resources, with particular focus on petroleum.

In this paper, we describe the development, implementation and application of a novel mathematical procedure devoted to formulating the daily load profiles of off-grid consumers in rural areas. The procedure aims at providing such profiles as input data for the design process of off-grid systems for rural electrification. Indeed, daily load profiles represent an essential input for off-grid systems capacity planning methods based on steady-state energy simulation and lifetime techno-economic analyses, and for the analysis of the logics to control the energy fluxes among the different system components. Nevertheless, no particular attention has been devoted so far in the scientific literature as regards specific approaches for daily load profiles estimates for rural consumers. In order to contribute to covering this gap, we developed a new mathematical procedure taking into consideration the specific features of rural areas. The procedure is based on a set of data that can be surveyed and/or assumed in rural areas, and it relies on a stochastic bottom-up approach with correlations between the different load profile parameters (i.e. load factor, coincidence factor and number of consumers) in order to build up the coincidence behavior of the electrical appliances. We have implemented the procedure in a software tool (LoadProGen) which can eventually support the off-grid systems design process for rural electrification. Finally, we have applied the procedure to a case study in order to clarify the proposed approach.

In this research, a novel integration is presented to develop a hydrogen-based strategy solution for 600 kW electrical power production. The proposed system consists of solid oxide fuel cell (SOFC), gas turbine, organic Rankine cycle (as the Waste-to-Energy technology), and a proton exchange membrane (PEME). PEME utilizing as a hydrogen production unit in order to cover a portion of SOFC fuel consumption rate and utilizing a waste-to-energy technology to provide more electricity generation are the distinguishing feature of proposed integration. The parametric analysis explores the effects of significant variables (such as the fuel cell current density, compressor pressure ratio, and organic Rankine cycle turbine inlet temperature on the system performance. The corresponding analysis provides such important following results: (1) increasing the SOFC's current density over a range of 2000–8000 (A/m2) decreases the energy and exergy efficiencies respectively from 17.92% to 12.74% and from 54.98% to 30.26%, (2) Although high overall exergy efficiency is achieved by reducing the compressor pressure ratio. By considering specific thermodynamic conditions which are obtained by parametric analysis, exergy and exergo-economic results reveal that the after-burner is identified as the component with maximum exergy destruction rate (21.44% of total) and it has the lowest value of the exergo-economic factor (0.006%) due to high thermodynamic inefficiencies, while the organic turbine has the highest exergo-economic factor 90.34% due to its high investment cost. Also, the net exergy efficiency results as 45% and levelized cost of electricity (LCOE) results as 0.102 $/kWh.

Integrated systems modelling has provided insights on pathways for the sustainable use of energy, land and water resources. Among the existing modelling tools, some have been widely used to engage policy makers, due to their open source and basic structure. Yet, in the attempt of simplifying the representation of integrated systems, essential features significantly influencing the dynamics between systems may have been left aside. This study proposes an improved formulation of the Open Source Energy Modelling System (OSeMOSYS), for a better representation of energy and resource storage processes. In particular, the focus of this work is the storage losses introduction for both dams for hydropower generation and batteries for electricity storage. The modifications were applied to a case study representing key features of both a developed and developing country. The results highlight that, with low additional computational effort, a much more accurate representation of the storage technologies can be achieved. Despite the introduction of losses, renewable energy technologies tend to have a high penetration in the future energy mix thanks to storage applications that remedy their unpredictability and seasonality.

Introduction Acute Myeloid Leukaemia (AML) is a heterogeneous and multi-step disease. The serial acquisition of mutations and the environmental pressure allow one or more clones to expand and contribute to the disease. In particular, 6% of AMLs are characterised by an initial mutation in the DNMT3a gene, followed by mutations in NPM (NPMc) and FLT3 loci (FLT3-ITD). We previously shown that NPMc can drive AML development in mouse model and highly cooperates with FLT3-ITD. Moreover, it has been reported that normal Hematopoietic Stem Cells (HSCs) of elderly people may bear some somatic early AML mutations and this correlate with an increased risk of hematologic diseases suggesting that mutations can shape pre-leukemic HSCs to be more prone to the acquisition of further mutations giving rise to Leukaemia Initiating Cells (LIC). While the ability of FLT3-ITD to drive HSC compartment exhaustion has been already shown, the impact of NPMc on HSCs remains unclear. Material and methods Taking advantage of the extended pre-leukemic phase of our inducible NPMc mouse model, we elucidate the role of NPMc in HSCs by functional and transcriptional analysis. Moreover, to investigate the basis of NPMc and FLT3-ITD cooperation we generate mice carrying both the conditional NPMc transgene and the FLT3-ITD constitutive mutation and, before AML onset, we analyse double mutant HSCs behaviour. Results and discussions We have found that NPMc expression lead to the expansion of the HSC compartment through the enforcement of a stem-cell transcriptional program that increases self-renewal by promoting quiescence. We then investigated how the NPMc dependent quiescence program is linked to its oncogenic function. The expression of NPMc +in the FLT3-ITD background prevents the HSCs exhaustion imposed by FLT3-ITD and restores their repopulating capacity. Accordingly, gene expression analysis revealed a strong dominance of NPMc +with the restoration of the same transcriptional program observed in the NPMc HSCs. These data strongly suggest that NPMc imposes a HSC-specific program that, in combination with the oncogenic signal provided by FLT3-ITD, allows the selection of the LIC and the occurrence of AML. Conclusion In conclusion, enforcement of quiescence might be a critical function for the maintenance of the transformed clone during both the pre-leukemic and the leukemic phase. As consequence, interfering with quiescence key determinants may eradicate the reservoir of quiescent cells responsible for disease recurrence.

Efforts towards ensuring clean and affordable electricity for all have been progressing slowly in rural, off grid areas of developing countries. In this context, hybrid microgrids may offer reliable and potentially clean electricity for isolated locations. Nevertheless, the process of planning and operation of these systems faces several challenges, often due to the uncertainties related to the renewable resources and to the stochastic nature of electricity consumption in rural contexts. This paper tackles this problem and contributes to the literature in bridging the gap between field practices and two-stage stochastic modeling approaches by identifying an open-source modeling framework which is then applied to real local data. As reference case-study, we consider a microgrid built in 2015 in Bolivia. Overall, the optimal system results from a compromise between the Net Present Cost, the peak capacity installed and the flexibility (to balance variable generation). Different approaches to size isolated microgrids are tested, with the conclusion that methods accounting for the uncertainty in both demand and renewable generation may lead to a more robust configuration with little impacts on the final cost for the community.

For the acceptability of energy systems, environmental impacts are becoming more and more important. One primary way for reducing impacts related to processes is by improving efficiency of plants. A key instrument currently used to verify such improvements is exergy analysis, extended to include also the environmental externalities generated by systems. Through exergy-based analyses, it is possible indeed to evaluate the overall amount of resources consumed along all the phases of the life cycle of a system, from construction to dismantling. However, resource consumption is a dimension of the impact of a system at global level, while it may not be considered a measure of its local impact. In the paper a complementary approach named Combined Risk and Exergy Analysis (CRExA) to assess impacts from major accidents in energy systems is proposed, based on the combination of classical exergy analysis and quantitative risk analysis (QRA). Impacts considered are focused on effects on human health. The approach leads to the identification of solutions to minimize damages of major accidents by acting on the energy system design.

Introduction AML is hierarchically organised with at the apex Leukaemia Stem Cells (LSCs), a rare cell population able to initiate and sustain the tumour growth. LSCs share many functional properties with normal Hematopoietic Stem Cells (HSCs) including self-renewal capacity and quiescence. Quiescent LSCs can survive to radiation and chemotherapy acting as a reservoir for leukaemia relapse, the major cause of death for AML patients. Therefore, LSCs quiescence is critical for leukaemia maintenance and few evidences suggest that quiescence regulation in pre-leukemic phase plays a pivotal role for leukemogenic process as well. Material and methods We analysed the transcriptional deregulations induced by the expression of different leukemic oncogenes in HSCs and we examined the contribution of representative quiescence related genes in AML growth by in vivo RNA interference screening. Results and discussions The transcriptional profile of oncogene-expressing HSCs is enriched in a quiescent stem cell gene signature, compared to normal HSCs. Therefore, we hypothesised that enhancement of the quiescent phenotype in HSCs could be a shared mechanism for leukaemia development and maintenance. The in vivo shRNA screening allowed the identification of genes whose silencing in AML blasts was sufficient to significantly decrease in vitro self-renewal and delay leukaemia growth in vivo . Conclusion We identified quiescence-related genes, commonly deregulated by leukemic oncogenes at pre-leukemic level, which may offer new therapeutic targets in a wide group of AML patients.

The present work is focused on a new procedure for the determination of NO x emission from combustion processes, which allow using very detailed and comprehensive reaction schemes, on the basis of the results obtained from CFD computations. This procedure is validated in the case of high swirled confined natural gas diffusion flames. The experimental data refer to the work developed within the German TECFLAM cooperation concerning a swirl burner ( 0.6 S 1.4 ) fed with natural gas characterized by 150 kW thermal load and 0.8 equivalence ratio (TECFLAM webpage, www.tu-darmstadt.de/fb/mb/ekt/tecflam ; Schmittel et al., Proceedings of the Combustion Institute 28 (2000) 303–309). The CFD analysis represents a useful technology to provide the flow and temperature fields. The high swirling configuration makes the solution an interesting and difficult task for commercial codes. In particular, previous attempts of predicting the flow and temperature fields with the FLUENT code failed (Meier et al., Applied Physics B 71 (2000a) 725–731). Only a careful attention to the boundary conditions and converging strategy allows to reach a satisfactory modeling of the main characteristics of the flame. The numerical calculation was performed using the commercial code FLUENT6.0. NO x formation is a chemical process whose time-scale is of the same order of mixing fluid dynamics. For this reason, comprehensive modeling of NO x reaction processes in combustion systems requires simulation of both the turbulent fluid dynamics and chemical kinetics in the system being modeled. Hundreds of elementary reactions are required to provide a detailed description of the formation and depletion of oxides of nitrogen in combustion systems. However, it is not currently feasible to use such detailed reaction mechanisms to model a turbulent reacting system in which large reaction kinetics schemes are coupled with the turbulent fluid dynamics. Consequently, the difficulties in coupling detailed chemistry and detailed fluid dynamics force to adopt proper simplifications. The prediction of NO x formation is then obtained by postprocessing the flow and temperature fields, as predicted by CFD, and lumping together computational cells similar in terms of NO x formation. The resulting macrocells are assumed to be a network of ideal reactors, which are simulated adopting a detailed kinetics. The characteristics and operating conditions of each reactor are defined by a procedure already developed for furnaces and named SFIRN (Faravelli et al., Computers and Chemical Engineering 25 (2001) 613–618). The predictions have been tested on flames at different swirl numbers. Both the CFD and the chemical analysis show a satisfactory agreement with the measured data.

Simvastatin has been reported to improve endotheliumdependent vascular relaxation in patients with hypercholesterolemia. The consequent decrease in arterial stiffness might be associated with a decrease in blood pressure (BP).The aim of this study was to determine whether simvastatin 20 and 40 mg/d have an effect on systolic and diastolic blood pressure (SBP and DBP, respectively) in patients with hypercholesterolemia, and, if so, whether the effect is dose dependent and/or is related to the changes in the serum lipid profile.This 6-month, open-label study was conducted at the Lipid Clinics of the Department of Internal Medicine, University of Milan, Maggiore Hospital IRCCS, and of the Department of Internal Medicine 1, G. Salvini Hospital, Garbagnate Milanese (Milan, Italy). Patients aged 18 to 80 years with primary hypercholesterolemia who were following a low-fat, low-cholesterol diet for2 months before the study were enrolled. Patients at high risk for cardiovascular disease (CVD), according to the National Cholesterol Education Program Adult Treatment Panel II guidelines, were given simvastatin 20 mg (tablet) QD for 3 months, and those at low risk for CVD continued with diet only for 3 months (controls). Efficacy variables included body weight, SBP, DBP, and serum lipid levels (total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], high density lipoprotein cholesterol [HDL-C], and triglycerides [TG]). At 3 months, patients in the simvastatin + diet group who reached their therapeutic goal continued to receive simvastatin 20 mg/d for 3 additional months. In simvastatintreated patients who were normotensive at baseline or who became normotensive at 3 months but who did not reach the therapeutic goal, the simvastatin dosage was increased to 40 mg/d. Patients in both groups who remained hypertensive at 3 months were switched to hypotensive therapy. In the diet-only group, patients who were formerly normotensive or who became normotensive at 3 months but who did not reach their therapeutic goal continued with diet only or started lipid-lowering therapy. All other patients in the diet-only group continued to be treated with diet only, for 3 additional months. Efficacy variables were measured again at 6 months. Tolerability of simvastatin was assessed at each visit using patient interview and measurement of serum aminotransferase and creatine phosphokinase levels.The study population comprised 222 patients (132 women, 90 men; mean [SEM] age, 53.9 [0.95] years [range, 23-76 years]); 115 high-risk patients (57 with untreated stage 1 hypertension) were assigned to the simvastatin + diet group, and 107 low-risk patients (29 with untreated stage 1 hypertension) were assigned to the diet-only group. In the simvastatin group, after 3 months of therapy, mean SBP was decreased by 3.9 (1.49) mm Hg (change, -2.9%), mean DBP decreased by 3.0 (0.87) mm Hg (change, -3.7%), mean TC decreased by 90.6 (3.98) mg/dL (change, -27.0%), mean LDL-C decreased by 88.9 (3.88) mg/dL (change, -35.6%), and mean TG decreased by 26.3 (7.34) mg/dL (change, -15.8%) (all, P0.001). Mean HDL-C increased by 3.6 (1.16) mg/dL (change, 6.9%; P0.001). The BP-lowering effect was found only in patients with hypertension at baseline (n = 57); in these patients, mean SBP decreased by 7.2 (2.44) mm Hg (change, -4.8%; P0.005 vs baseline) and DBP decreased by 4.8 (1.29) mm Hg (change, -5.6%; P0.001 vs baseline). Also in the simvastatin group, 26 patients (22.6%) achieved their target SBP/DBP. In patients with normotension at baseline (n = 58), neither SBP nor DBP was changed significantly (changes, -0.8 [1.65] and -1.4 [1.15] mm Hg, respectively [-0.6% and -1.8%, respectively]). The changes in serum lipid levels were similar between hypertensive and normotensive patients in the simvastatin group. Forty-one patients (18 hypertensive and 23 normotensive at baseline) were treated with simvastatin 40 mg/d plus diet between months 3 and 6. At 6 months, no further significant decrease was observed in mean BP. In contrast, the expected dose-dependent response was observed for TC and LDL-C levels. In the diet-only group, no significant changes occurred in BP or serum lipid levels. Changes in BP, TC, LDL-C, TG, and HDL-C were significantly greater in the simvastatin + diet group than in the diet-only group (all, P0.001). Body weight did not change significantly in either group.In this group of patients with hypercholesterolemia, the starting dosage of simvastatin (20 mg/d) was associated with reductions in SBP and DBP within 3 months of treatment in patients with hypertension, and this effect was independent of the lipid-lowering properties of the drug. Although the decrease in BP was modest, it is likely clinically relevant. Further studies on this topic are advisable.

The neurotrophin receptor p75NTR is a marker for human differentiation-prone muscle satellite cells and regulates myogenesis. Here, we wondered whether inflammation could modify p75NTR expression on muscle precursor cells in vitro and in vivo. In vitro experiments on human primary skeletal myoblasts demonstrated that exposure to IFN-γ or IL-1α decreased transcript and protein levels of p75NTR. Furthermore, histological investigations showed a reduction in the pool of p75NTR expressing satellite cells in inflammatory myopathy biopsies. These data suggest a link between muscle inflammation and reduction of p75NTR expression on precursor cells.

This article aims at assessing whether multinational enterprises play a role in the reduction of energy poverty, while not causing environment degradation or inefficient usage of energy resources. Sub-Saharan Africa has been identified as an ideal test-field for this study. Using a panel of more than 1500 home-host country pairs observed from 2005 and 2011, we study the effect of foreign direct investment on the access to electricity, energy intensity and carbon factor, based on the level of economic and institutional development of home and host countries. Results reveal that institutions and income play a different role. In countries with weak institutions, foreign direct investment increases access to electricity, especially if from other institutionally backward contexts, and transfers cleaner technologies. On the contrary, in poor countries, investment from multinational enterprise increases environmental degradation without bringing any benefit to the local energy sector.

Simvastatin 40 to 80 mg/d has been found to increase high-density lipoprotein cholesterol (HDL-C) levels significantly more than atorvastatin at equipotent doses (ie, 20-80 mg/d). Data on the effects of lower doses of the 2 drugs on HDL-C levels are conflicting.The purpose of this study was to investigate the effects of simvastatin 20 mg/d and atorvastatin 10 mg/d on HDL-C levels in patients with hypercholesterolemia.Patients with primary hypercholesterolemia (total cholesterol [TC]250 mg/dL) who were not taking any lipid-lowering agents and who were following a low-fat diet were randomized to receive 1 of 2 treatments: simvastatin 20 mg/d or atorvastatin 10 mg/d. Serum TC, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and HDL-C levels were measured using standard methods after 2 months of therapy. In a secondary analysis, lipids and lipoprotein cholesterol were measured after 1 year in patients who continued treatment.Of the 240 patients enrolled (108 men and 132 women; age range, 23-77 years, mean [SEM] 56.7 [0.69]), 235 completed the study. After 2 months of therapy, TC, LDL-C, and serum TG levels decreased significantly versus baseline in both groups (P0.001), with no significant differences between treatment groups. HDL-C levels increased by 9.0% (P0.001 vs baseline) in the simvastatin group and by 4.3% (P0.02) in the atorvastatin group. The difference between the 2 groups in the percentage increase in HDL-C was statistically significant (P0.05). In 113 patients who continued treatment, HDL-C levels at 1 year were still significantly higher than baseline levels in the simvastatin group (6.3%, P = 0.034), but not in the atorvastatin group (2.8%, P = 0.587).The findings from this study suggest that the HDL-C-increasing effect of simvastatin 20 mg is significantly greater than that of atorvastatin 10 mg. Since increasing HDL-C levels is thought to lower the risk for atherosclerosis and coronary heart disease, these results warrant further investigation.

Transaldolase (TAL) is a key enzyme of the reversible nonoxidative branch of the pentose phosphate pathway (PPP) that is responsible for the generation of NADPH to maintain glutathione at a reduced state (GSH) and, thus, to protect cellular integrity from reactive oxygen intermediates (ROIs). Formation of ROIs have been implicated in certain types of apoptotic cell death. To evaluate the role of TAL in this process, Jurkat human T cells were permanently transfected with TAL expression vectors oriented in the sense or antisense direction. Overexpression of TAL resulted in a decrease in glucose 6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase activities and NADPH and GSH levels and rendered these cells highly susceptible to apoptosis induced by serum deprivation, hydrogen peroxide, nitric oxide, tumor necrosis factor-alpha, and anti-Fas monoclonal antibody. In addition, reduced levels of TAL resulted in increased glucose 6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase activities and increased GSH levels with inhibition of apoptosis in all five model systems. The effect of TAL expression on susceptibility to apoptosis through regulating the PPP and GSH production is consistent with an involvement of ROIs in each pathway tested. Production of ROIs in Fas-mediated cell death was further substantiated by measurement of intracellular ROI production with oxidation-sensitive fluorescent probes, by the protective effects of GSH precursor, N-acetyl cysteine, free radical spin traps 5,5-dimethyl-1-pyrroline-1-oxide and 3,3,5,5-tetramethyl-1-pyrroline-1-oxide, the antioxidants desferrioxamine, nordihydroguaiaretic acid, and Amytal, and by the enhancing effects of GSH depletion with buthionine sulfoximine. The results provide definitive evidence that TAL has a role in regulating the balance between the two branches of PPP and its overall output as measured by GSH production and thus influences sensitivity to cell death signals.