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The pioneering objective of a permanent outpost on the lunar surface requires the development of technologies for in situ resource utilisation. Consolidation of lunar soil into products is imperative to avoid unaffordable transportation burdens. The paper addresses the feasibility of the Local Microwave Heating effect as a promising technology for sintering lunar regolith based on microwave radiation, with a simple solid-state generator requiring a relatively modest amount of energy. Experiments were conducted using terrestrial simulants with physical and chemical properties similar to those of lunar regolith. Laboratory equipment with a purpose-built microwave actuator was designed and manufactured with "Design for Embarking" in mind. Experiments have demonstrated the feasibility of the proposed technology with a reasonable degree of confidence. Solid artefacts were obtained with proper setting of microwave parameters and appropriate scanning strategy, proving the feasibility of regolith sintering with a localised microwave source A roadmap for future development of the technology has been established. • Preliminary study on Localized Microwave Sintering of Lunar Regolith: Highlights. • Localized Microwave Heating is effective to consolidate lunar regolith simulants. • A solid-state generator with an open-end antenna is a promising lightweight low-energy system for ISRU. • Microwave heating of regolith is feasible regardless of the simulant's ilmenite content. • The technique can be used to produce 3D parts using an additive approach. [ABSTRACT FROM AUTHOR]

The present investigation elaborates on the level of game theory application for the applied and theoretical analyses of climate change and development studies. This editorial shows that the common good character of global climate alongside the increasing internalization of environmental externalities through national regulations and international environmental treaties jointly result in the increasing congruence between the context of climate change problems and the game theoretical method. Furthermore, the adoption of the Paris Accord by the overwhelming majority of developing countries as well as the disproportionate vulnerability of the Global South have led to an increasing shift in focus with regard to international development cooperation, from poverty alleviation and economic growth to green growth and circular economy solutions, within developing countries. The underutilization of game theory in the context of development studies is not satisfactory. This paper underlines the importance of implementing an impetus to researchers for scholarly discussions and applications of game theory in a discourse on the following topics: 1. economic growth; 2. climate change mitigation and adaptation; and 3. a broader socioeconomic development. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is a novel production process, that allows the creation of lightweight and customizable devices. Such capacity requires a high grade of reliability under the action of service loads, especially under fatigue loads. One of the high-performance steels adopted for selective laser melting (SLM) is the AISI 316L. However, SLM is severally affected by laser beam power and scanning velocity. Mechanical properties must be investigated to provide reliability of final products, but this requires a huge amount of time. On the other hand, energy methods, such as the Risitano's thermographic method and the novel static thermographic method, by performing stepwise fatigue tests and static tensile tests, can assess the material's performance by monitoring the energy release. In this work, failure analysis has been performed, showing the differences between the traditional and AM manufacturing process, giving an insight to understand and improve the quality of the AM production process. [ABSTRACT FROM AUTHOR]

On the wave of the success of the participatory budgeting (PB) implemented in Porto Alegre, Brazil, a number of administrations around the world jumpstarted new forms of nonfinancial balance reporting. This trend was supported by an increasing consensus from the international community. PB aims to enhance mutual trust between the different social stakeholders and foster public administrations transparency. For this reason, PB is recognized as an effective tool for facilitating good governance, sustainability, and development. Previous field research does not highlight local voting and corruption figures. To shed light on these variables throughout a case study, this article makes use of original mixed methods techniques to analyze the PB experience of a municipality in Southern Italy. The combination of data regarding census, voting shares, and projects' features is a methodological innovation, used here for the first time. Fieldwork has been conducted to collect both quantitative and qualitative data. These data were employed along with official demographics statistics to inspect existing public management and development dynamics. Four distinct data sources, intersecting population and voting data through the PB tool were examined. After mainstreaming PB, referring to the world's benchmark of Porto Alegre, this article investigates the good practice of Casamarciano, Campania. Evidence shows compelling features from the local experience and encouraging involvement of the community, rating the poll participation even greater than Porto Alegre engagement. The qualitative data pinpoints the local administration's management choices—noteworthy, the town's PB model—and the innovation behind the public management strategies. These outcomes may help to better understand PB dynamics, yielding improved local development and sustainability indications for public affairs governance. [ABSTRACT FROM AUTHOR]

Commons governance theory is central to identifying and managing conflicts arising from natural and cultural resources traps. Scholars – using game theory and economic analysis of law – have proposed alternative models, consisting of a set of mitigated scenarios, multiple players, and new equilibria in commons governance. Likewise, novel legal innovations of the commons have also been designed. Reinterpreting the commons in light of political economy, ecology, and pluralistic approaches, a critical review of existing scholarship, economic analysis of law, and case study investigations are performed. Examining an array of views – including governance of water in Ecuador, Bolivia, and Italy – a research and policy agenda is put forward to offer original interpretations and novel holistic perspectives. Germane environmental policy implications deriving from SDGs, resilient governance, and polycentric perspectives are thus extrapolated. Finally, pluralistic frameworks drafted by mitigation and adaptation are measured by improved sustainable development performance in commons, resource, and water governance. [ABSTRACT FROM AUTHOR]

The present inquiry addresses the nexus between the development of electronic government and corruption in the provision of public sector services in developing and transition economies. The study analyzes the potential contribution of electronic government in combating petty corruption within the framework of two superimposed principal-agent model and show that electronic government could potentially limit bureaucratic corruption. To address the research question empirically, the study applies random tobit and linear random effects panel estimators to a dataset made of 121 countries, which covers the time period between 2008 and 2018. Estimations reveal that the adoption of electronic government in the delivery of public sector services has been the central factor that contributed to the reduction of petty corruption in developing and transition economies. The level of per capita income, political rights, civil liberties and share of natural resources in gross exports also correspond with less bribery in the public sector service delivery. Furthermore, the study finds that a lower level of socio-economic development corresponds with a greater level of petty corruption. Hence, e-government presents one of the utmost opportunities for socio-economic development and offers solutions for the improvement of the efficiency and effectiveness of public administration. [ABSTRACT FROM AUTHOR]

Since December 2019, the novel coronavirus disease (COVID-19) has had a considerable impact on the health and socio-economic fabric of Italy. The effective reproduction number Rt is one of the most representative indicators of the contagion status as it reports the number of new infections caused by an infected subject in a partially immunized population. The task of predicting Rt values forward in time is challenging and, historically, it has been addressed by exploiting compartmental models or statistical frameworks. The present study proposes an Artificial Neural Networks-based approach to predict the Rt temporal trend at a daily resolution. For each Italian region and autonomous province, 21 daily COVID-19 indicators were exploited for the 7-day ahead prediction of the Rt trend by means of different neural network architectures, i.e., Feed Forward, Mono-Dimensional Convolutional, and Long Short-Term Memory. Focusing on Lombardy, which is one of the most affected regions, the predictions proved to be very accurate, with a minimum Root Mean Squared Error (RMSE) ranging from 0.035 at day t + 1 to 0.106 at day t + 7. Overall, the results show that it is possible to obtain accurate forecasts in Italy at a daily temporal resolution instead of the weekly resolution characterizing the official Rt data. [ABSTRACT FROM AUTHOR]

Environmental, energy, business and development dynamics have received strong research interest. However, previous studies have mainly explored these topics separately. Conversely, we study these aspects jointly, constructing a composite indicator and assessing resulting impact on several SDGs domains. The aim of the analysis is to discover the importance of latent aspects in explaning the environmental, energy and business efficiency for specific countries. Estimating this multidimensional efficiency is relevant for the identification of the conditions for the achievement of CO 2 containment and sustainable development progress. We make use of the World Bank's World Development Indicators (WB WDI) for selected emerging countries from the Asia-Pacific region ranging from lower-middle-income to upper-middle-income economies, following the WB Group country classifications by income level. We build a composite indicator for eliciting diverse dimensions related to the environment, energy policy and economic factors. The first steps of the indicators analysis are achieved by the combination of the DEA and Tobit analyses. Therefore, we examine the environmental, energy and business efficiency according to the economic development stage of the analysed countries, making use of an entropy index. The index' robustness is tested at both stages – first, exploring the Tobit analysis, therefore, by inspecting an additional Asia-Pacific country having a different income with respect to the benchmark. The results suggest the creation of country clusters. Above all, China outstands in terms of environmental efficiency and R&D, as a result of a broader energy development strategic plan in the last few decades. • Environmental, energy, business and development dynamics are analysed jointly for the first time • A composite indicator on selected SDGs components is built • The World Bank's World Development Indicators are used for Asia-Pacific emerging countries • DEA, Tobit, entropy and robustness analyses explore the effect of environmental efficiency on CO 2 emissions • We observe different clusters for all sub-regions for the evaluation of efficiency and R&D intensity [ABSTRACT FROM AUTHOR]

This article reviews and launches perspectives on the progress of nuclear fusion research and development. To this end, the current state of nuclear fusion technology, the recent breakthroughs in nuclear fusion research occurred in the US, Japan, and China, the role of private companies and investments in nuclear fusion research and development are investigated for both advanced and emerging economies. The survey draws upon academic sources and media contributions from experts in the field of nuclear fusion. While nuclear fusion has reached the break-even point in the generation of nuclear fusion electricity, there are still serious challenges that will obviate the market alignment of nuclear fusion energy until the early 2030s – and more realistically the mid-2050s. Nonetheless, never in history, the level of public support and private engagement for nuclear fusion energy research and development has been as high as now. Furthermore, the study shows that there is a steadily increasing accumulation of scholarly knowledge on nuclear fusion and a broad consensus among the leading experts that nuclear fusion is the "holy grail" of the transition toward a post-resource, and hence, fully circular energy system. • Nuclear fusion is the "holy grail" of transition to an emission-free energy system. • Since 1983 the energy gain factor of nuclear fusion energy has been steadily growing. • The breakthrough of 2022 gave an impetus to further commercial interest in nuclear fusion energy research. • There are increasing public subsidization schemes, more engagement of established private enterprises, and a growing number of start-ups worldwide. • The earliest 2030 and latest 2050 nuclear fusion will be more competitive than conventional energy sources. • In the long run, nuclear fusion energy will crowd out conventional fossil fuels and other renewables. [ABSTRACT FROM AUTHOR]

The ongoing invasion of Russia of Ukraine and energy crises have sparked concern about economic and geopolitical stability all over the world. In Europe, the war has destabilized and endangered the energy cooperation and transition between European countries within and outside of the EU. This emergency has shown once more the importance of energy resilience policies to offset the vulnerability of energy systems and energy insecurity at the national and regional levels. Consilience has been reached on the necessity of enhancing EU energy security as an adaptation strategy. This work contributes to the existing scholarship on renewable energy transition and citizens' perception, focusing on European Union member states. Key characteristics of the renewable energy transition in the EU prior to the energy crisis and the war in Ukraine are examined. To this end, we analyze selected economic, environmental, social, policy and political variables on energy sorting from the Eurobarometer studying European citizens' perceptions. The exercise makes use of spatially-clustered regression to explore spatial heterogeneity and to elicit determinant information on specific regional groups. We learn that southern Europeans attribute less importance to energy infrastructure to facilitate the renewable energy transition and repute the EU solidity not a requirement for energy security access. Conversely, northern European citizens tend not to associate the responsibility of the EU in guiding competitiveness and policy toward green energy sources transformation. Robustness tests confirm our hypothesis. Regardless of regional differences, the EU energy and ecological transition will thrive with industrial and political cohesion. This process will pass through increased trust in institutions and dedicated energy policy action which will smooth the risks and disruptions coming from current and future shocks. • Eurobarometer variables European citizens' perceptions of renewable energy transition are analyzed. • Spatial heterogeneity statistics builds regional clusters southern Europeans ex-ante analysis of the Ukraine war and energy crisis. • Southern Europeans attribute less importance to energy infrastructure for renewable energy transition • Southern Europeans repute EU solidity not a requirement for energy security access. • Northern European citizens do not associate EU competitiveness with green energy sources transformation. [ABSTRACT FROM AUTHOR]

The present paper reviews the green hydrogen uptake policies in the United States and the European Union. While the EU has a rather broad public support strategy that envisages the entire hydrogen value chain, the U.S. policies are more focused on hydrogen research hubs and subsidies having electric vehicle applications. From the experience of the solar and wind power rollout of the past three decades, we know that the subsidization schemes of the end product play an important role in the transition to renewables. These kinds of subsidization schemes are still lacking for clean hydrogen both in the EU and the U.S. This paper provides a brief overview of selected subsidization schemes from other renewables markets, which are then applied to define an exemplary subsidization path to empower large-scale growth in a market for green hydrogen. Here is proposed a long-term subsidization scheme – deemed as an adequate strategy for the expansion of clean hydrogen in an electricity mix. The suggested exemplary subsidization path recommends shifting from feed-in tariffs to direct marketing with market premiums once a certain threshold is reached, while both can be flanked by the issuance of a Guarantee of Origin for green hydrogen so that there is one market for hydrogen and another market for the certificates. • -A long-term subsidization scheme for the rollout of green hydrogen in the electricity mixes is proposed. • -An exemplary subsidization path to empower large-scale growth in a market for green hydrogen is drafted. • -U.S. and EU are used as case studies to capture lessons for subsidization of green hydrogen economy uptake. • -The U.S. has more centralized green hydrogen rollout policies, whereas the EU has a wider policy toolkit. • -Shifting from FIT to direct marketing with market premiums is key once a certain pre-defined threshold is reached. [ABSTRACT FROM AUTHOR]

Seasonal hunger is the most common food insecurity experience for millions of small dryland farmers. This study tests the relationships between food insecurity, farm forests, and biomass poverty using a longitudinal dataset from the Amhara region of Ethiopia. These data form part of the Ethiopia Socioeconomic Survey, which collected panel data over three survey rounds from 530 households between 2011 and 2016. This dataset represents a collection of unique socioeconomic, wellbeing, and micro-land use measures, including farm forests. Hierarchical mixed effect regression models assessed the relationship between food insecurity and farm forests as well as the conditional effects of biomass poverty among the poorest farmers and women-headed households. Over a six-year study period, farmers reported increased stress from smaller land holdings, higher prices, and climate-related shocks. A clear trend towards spontaneous dispersed afforestation is observed by both researchers and satellite remote sensing. Model results indicate, dedicating approximately 10% of farm area to forest reduces months of food insecurity by half. The greatest reductions in food insecurity from farm forests are reported by ultra-poor and crop residue-burning households, suggesting that biomass poverty may be a major constraint to resilient food security on these farms. This research provides novel quantitative evidence of induced intensification and food security impacts of farm management preserving and building stores of biomass value as green assets. The results reported here have important implications for nature-based solutions as a major strategy to achieve sustainable development in some contexts. [ABSTRACT FROM AUTHOR]

Energy recovery is a viable option for waste management to integrate prevention, reuse and recycling when those strategies are not feasible. As such, efficient management of energy from waste can facilitate the circular economy (CE) transition. Efficient waste and energy management can assist sustainable development by curbing environmental degradation and resource depletion, improving energy security and health and safety conditions and creating new jobs and income. European countries have put substantial efforts and investments to improve their management efficiency of energy from waste and align to CE. To this end, this study develops a robust composite indicator to clarify and quantify this nexus, calculating European countries' achievements and filling a literature gap. A set of statistical techniques is employed to analyze a large panel dataset of 17 countries and 14 energy efficiency variables for 15 years. One may observe that Denmark, the Netherlands, Austria, the UK and Germany get positive outcomes. Conversely, the remaining 12 European countries get negative performances at the global level. Results vary across the different sub-indexes. 5 sensitivity and robustness analyses corroborate the results and confirm the hypothesis. The findings can assist the CE transition and may be used for research, management and policy purposes. This work's rationale. [Display omitted] [ABSTRACT FROM AUTHOR]

The present study investigates the nexus between electrification of the mountainous rural areas and selected indicators of socioeconomic development, such as household income, learning hours, and fuel choices in cooking behavior. The empirical investigation is based on the field survey in the recently electrified Yapshor and non-electrified Deh villages of the Rushan district of the Gorno-Badakhshan Autonomous Region of Tajikistan. The study reveals a strong positive impact of electrification of these villages on the level of household income and daily learning hours of school-age children. Getting electricity access leads to a 34–48% increase in household income and to 71–95 min of additional daily learning hours for school-age children. Furthermore, electricity access also strongly contributes to the substitution of firewood, coal, or animal manure with clean electricity for cooking. Due to individual taste preferences there is, however, still a substantial percentage of village dwellers who have not shifted to clean electricity for cooking. [ABSTRACT FROM AUTHOR]

Circular economy proposes paradigm shifts from linear production patterns. Entrepreneurs can highly benefit from fresh models driven by industrial symbiosis. In this setting, renewable energy is a prime asset for fostering circular economy and sustainable development. Equity crowdfunding can assist this transition, proposing an array of possibilities for supporting green entrepreneurship. The inquiry at hand is the first exercise linking circular economy, renewable energy and equity crowdfunding. This work tests whether the deal value of an equity-based crowdfunding campaign is higher in countries with renewable energy orientation. It is made use of probit model estimations. One may observe that being a firm from a country consuming large proportions of renewable energy is positively associated with higher crowdfunding performance. Conversely, when a company is located in a country which has large shares/ratios of renewable electricity production, it usually gets modest results when compared to its international competitors. Lower deal values are also attributed to firms situated in countries relying on biomass use. The solidity of the analyses is ensured by robustness tests. The outcomes may elicit policy and research formulation on environmental sustainability and business success at micro/macro levels – of primary importance to illuminate energy, circular economy and ecological transitions. Renewable energy-Equity crowdfunding-Circular economy interplay. [Display omitted] • Circular economy, renewable energy and equity crowdfunding are analysed for the first time. • The deal value of an equity-based crowdfunding campaign is higher in countries with renewable energy orientation. • Countries consuming large proportions of renewable energy are positively associated with a higher crowdfunding performance. • Companies from a country which has large shares of renewable electricity production, get modest results. • Lower deal values are attributed to firms situated in countries relying on biomass use. [ABSTRACT FROM AUTHOR]

The role of civic participation in issues directly or indirectly related to environmental quality is reputed to be on the rise globally. Bottom-up grassroots movements can be conducive to powering socially acceptable, smooth, and hence, more efficient transitions toward low-carbon energy futures. This factor can also unlock the potential of communities, improving the adaptation and social acceptability towards major changes and providing possible policy instruments. On contrary, bottom-up grassroots movements are unfavorable to the extension of renewable energy capacities, especially in the case of wind energy, if this causes costs for the local communities, which outweigh the corresponding benefits. Determining these dynamics is pivotal for addressing public ecological concerns and calls for quantitative regional studies. This paper addresses the nexus between civic engagement and energy transition in 11 countries of the Nordic-Baltic Sea Region. The study detects a strong positive relationship between civic engagement within environmental organizations and the share of renewable energy sources in the domestic electricity mixes of the countries of the Nordic-Baltic Sea Region. Nonparametric panel estimator with fixed effects reveals that the impact of civic engagement has been continuously rising – i.e. the significance of civic engagement as a factor in the energy transition has risen. Nevertheless, the study also finds that the magnitude of civic engagement over the years has been relatively stable in most countries of the region since 1981. In a few of them, civic engagement has been declining. The work argues that this decline could be attributed to the fact that politics, especially since 2005, deemed environmental issues as an important aspect of public policy – a factor that contributed to mainstreaming the phenomenon. • Civic engagement and energy transition are analyzed for 11 Nordic-Baltic Sea Region countries. • Civic engagement in environmental NGOs has a strong positive relationship with renewables share. • Civic engagement significance as a factor of energy transition is on the rise. • The magnitude of civic engagement has been stable in most countries. • Especially since 2005, politics deemed environmental issues as important in public policy. [ABSTRACT FROM AUTHOR]

Energy poverty is a significant development issue that is not univocally interpreted. In many parts of the world, people do not have access to modern and reliable energy, which can be a big problem, particularly for vulnerable and developing countries. When vulnerable people do not have access to energy, they will often not be able to get the power they need to improve their lives. In addition, they may not be able to get proper food, education, health, sanitation, or basic needs for daily living. We use interval-based composite indicators and triplex representations of intervals to measure and assess access to electricity in 54 developing countries as a concept approximating relevant aspects of energy poverty. The proposed composite metric is innovative because it accurately quantifies how much electricity is available to people and how resilient and vulnerable people in developing countries are when they lose access to energy. After comparing the different representations, we found that one group of developing countries is more vulnerable to national and international events than the other. However, other countries are more resilient to electricity access problems. Conflicts and wars can impact the index used to measure energy poverty. However, as measured by the index, these factors contribute to poor performance. • Developing countries' electricity access as a proxy of energy poverty are measured and assessed. • Interval-based composite indicators and triplex representations as a sensitivity analysis are built. • Robust measures of electricity access and energy resilience in developing nations are provided. • A subset of developing countries shows higher vulnerability, while other displays higher electricity access resilience. [ABSTRACT FROM AUTHOR]

A specific technical expertise is required to machine metal–matrix composites (MMCs). It is well known, from the literature data, that MMCs cutting involves high costs and high machining times due to excessive tool wear and possible subsurface damage. In recent years, the emphasis of research has focused on understanding the mechanics and mechanisms that are responsible for the behaviour of MMCs during the material removal process. These kinds of studies would be the most effective way of understanding the machining characteristics and deformation behaviour of the material. This work is a contribution to understanding the effects of two antagonistic phenomena that determine MMCs behaviour during the cutting process, such as the thermal softening of the matrix and the matrix hardening due to strain. To this end, a simplified model that describes the behaviour of the reinforcements beneath the machined surface is proposed and experimentally validated. [ABSTRACT FROM AUTHOR]

Currently the biodiesel chain is promoted by the European energy policy. For the Italian scenario the sunflower is one of the most important crop to be considered for biodiesel production but the chain is not fully profitable. This problem could be solved with the increase of farm incomes through a proper valorization of by-products. From this point of view the oilseed crop is not considered only for oil production but also for producing multiple products with the same economic value. This is the main inspiring concept of the Extravalore project. The sub-project “Raw Materials” investigated about the possible influence of different agro-technics performed in three distinct geographical environments (Northern, Central and Southern Italy) on the characteristics of by-products obtained from sunflower crop. A national net of experimental tests was set during the 2010–2013 period in order to evaluate the adaptability and the potential production of high oleic sunflower hybrids. 7 seed companies supplied the 20 genotypes assessed in total (18 high oleic hybrids and 2 as control), 11 of them were evaluated all the three years. Achene yields of tested high oleic hybrids were extremely variable: from 2.05 t ha −1 to 4.04 t ha −1 in Northern Italy, from 2.50 t ha −1 to 4.24 t ha −1 in Central Italy and from 2.09 t ha −1 to 2.68 t ha −1 in Southern Italy. For this reason, it was necessary a precise characterization of varieties before their cultivation. The cultivar screening showed general difficulty for high oleic hybrids to reach the performances of achene and oil yields of the conventional ones. In particular, LG55.57HO and PR64H31 resulted the best high oleic cultivars for Northern Italy; many of the high oleic tested cultivars performed well for Central Italy and also for Southern Italy but with a higher variability. The highest potential production was registered in Central Italy; Northern Italy gave decreased but similar results, despite the different latitude; in Southern Italy the productions were 20–30% lower, even with the irrigation support. All high oleic tested cultivars showed oleic acid content in lipid fraction always above the 84% in Central Italy, meaning a stability of the character, very important for the biodiesel production. [ABSTRACT FROM AUTHOR]

The Extravalore project aims to give added value to oilseed crops, considering them also for producing multiple products with the same economic value and being interesting for the market thanks to their various utilizations. An evaluation of the main cultivars of Brassica napus subsp. oleifera and Brassica carinata has been performed within the project, analyzing them in three Italian locations with different climatic conditions (Palazzolo dello Stella – North Italy, Osimo – Central Italy, Cassibile – South Italy) to assay their adaptability and production potential. During the 2010–2013 period, 43 varieties of rapeseed were evaluated, but only 13 of them for all the period considered; moreover, also 4 varieties of B. carinata were tested. The seed yields of tested cultivars of rapeseed varied a lot among locations, depending also by the seasonal trend. Central Italy was the less disadvantaged by climatic conditions: on average, it was reached a seed yield of 4 t ha −1 , a theoretical oil production of 1.63 t ha −1 and more than 8 t ha −1 of crop residues. In Northern and Southern Italy, if compared with Central Italy values, the seed yields were both lower than 30% and theoretical oil productions lower than 60%; moreover, crop residues in Northern Italy were 12% lower than in Central Italy while in Southern Italy 65% lower. The agronomic behavior of varieties differed a lot among the three experimental areas: DK Expower was the best at North; Albatros, Artoga, Exagone and Excalibur in Central Italy; Excalibur, Zoom and PR46W14 at South Italy but none of them reached a seed yield of 2 t ha −1 . Concerning B. carinata , the cultivars did not give good productions in any of the experimental areas, mainly because of the low oil content in the seeds. Even in Central Italy, where the best results were registered, the seed yield was on average 28% lower than in rapeseed and oil production 10% lower; the crop residues were double than rapeseed. In any case, the valorization of the crop residues is important with a wide range of possible utilization from the direct energetic use to the biochemicals extraction with consequent environmental advantages due to the substitution of dedicated or fossil feedstock with crop residues. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to report an interdisciplinary, cooperative-learning project in a second-year course within the “Enzo Ferrari” Master of Science Degree in Mechanical Engineering. The work aims to raise awareness of the educational impact of additive manufacturing and reverse engineering. Design/methodology/approach – Students are asked to develop, concurrently, the design and the manufacturing solution for an eye-tracker head mount. A digital head model is reverse engineered from an anatomical mannequin and used as an ergonomic mock-up. The project includes prototype testing and cost analysis. The device is produced using additive manufacturing techniques for hands-on evaluation by the students. Findings – Results of the presented case study substantiate the authors’ belief in the tremendous potential of interdisciplinary project-based learning, relying on innovative technologies to encourage collaboration, motivation and dynamism. Originality/value – The paper confirms a spreading conviction that the soon-to-be engineers will need new practice-oriented capabilities to cope with new competitive scenarios. Engineering education must adapt to the social, rather than industrial, revolution that is being brought about by additive fabrication. [ABSTRACT FROM AUTHOR]

Back in December 2019, the novel coronavirus disease 2019 (Covid-19) started rapidly spreading worldwide, especially in Italy that was among the most affected countries. The geographical distribution of air pollution and Covid-19 mortality in Italy suggested atmospheric pollution as a worsening factor of severe Covid-19 health outcomes. The present nationwide ecological study focused on all 107 Italian territorial areas, aiming to assess the potential association between Particulate Matter concentration, less than 2.5 μm in diameter (exposure), and Covid-19 mortality rate (outcome) throughout 2020, by looking at 28 potential confounders. A potential positive association between exposure and outcome was observed when performing a multivariate regression analysis with a Negative Binomial model, suggesting that an increase of 1 μg/m3 in the exposure is associated with an increase of 9.0% (95% CI: 6.5%–11.6%) in the average Covid-19 mortality rate, conditional on all 28 potential confounders. A sensitivity analysis, based on the E-value, shows that a hypothetical unmeasured confounder would have to be associated with both PM 2.5 concentration and Covid-19 mortality rate by a rate ratio of at least 1.40-fold each to explain away the exposure-outcome association, conditional on all 28 covariates included in the main analysis model. Moreover, the Observed Covariate E-value (OCE) was reported to provide a contextualization of the E-value on the observed covariates included in the study. The OCE sensitivity analysis shows that a set of unknown confounders similar in size and magnitude to the set of the considered climatic factors could potentially explain away the estimated exposure-outcome association. Consequently, the role of climatic factors in the Covid-19 pandemic is worth of further investigation. [ABSTRACT FROM AUTHOR]

The long-accepted thermoelectric model for electro-discharge machining is being brought into question. Several experimental facts prompt the proposal of a new theory based on the effect of gap pollution on the ignition of discharges. The first experimental proof comes from the recently reported observation of debris chains and clusters. In this view, each step of the process depends on the previous ones through a deterministic relation, even if the overall evolution is unpredictable. The paper establishes mathematical grounds for the abovementioned intuitions by setting up and solving a recursive equation for the machining energy employed at each discharge event. By means of numerical and algebraic tools, the above equation is studied and shows a chaotic evolution similar to that of the logistic map. Results reconcile the apparent paradox between deterministic nature and stochastic localization of the discharges and introduce a description of the chaotic dynamics of electro-discharge processes. [ABSTRACT FROM AUTHOR]

The present study elaborates on the perspectives of fuel cell electric buses in German public transportation from a purely economic point of view and formulates recommendations for policies in public transportation in Germany. To this end, the study proposes nine valid scenarios and embeds diesel and fuel-cell bus operations into them. The total cost of ownership-based scenario analysis shows that beginning from 2035 fuel cell electric buses will be economically more attractive than diesel buses. The study identifies carbon pricing and subsidization of solar and wind power generation as the central drivers of fuel cell-based public transportation. • Scaling-up of green hydrogen will lead to substantial price reductions. • Full commercialization of the hydrogen FC buses will be achieved latest by 2035. • Hydrogen FC buses will be up to 17% cheaper than that of diesel buses by 2035. [ABSTRACT FROM AUTHOR]

Abstract: Electro-discharge (ED) processes depend on the contemporaneous effect of many factors, which complicates process control/predictability and induced many authors in the last 60 years to work on explicative models. Studies split into two main approaches: theoretical and empirical. Theoretical works are based on the thermo-electrical theory and try to describe process phenomena by a physical model, with unavoidable assumptions and simplifications that cause a move away from veracity. On the contrary, experimentalists establish empirical models based on statistical analysis of results and optimization methods, but the findings are limited to domain-specific applications. In addition, numerous papers focus on single-spark analysis, failing in considering the interaction between successive discharges, or of transient phenomena as the presence of bubbles and debris in the gap. At present the scientific debate involves the ignition model, with two different points of view regarding the discharge-driving phenomenon: the debris bridge effect (pollutants in the dielectric drive the performances), and the dielectric strength effect (properties of the dielectric drive the performances). The paper addresses this dispute by investigating the debris formed during small-hole ED drilling of a 72wt% Al2O3–28wt% TiC composite. Particles are found to hollow out and pack within the gap, joining by necks. The first experimental evidence is given of the presence of chains and clusters of debris, towards a new model for electro-discharge processes that goes beyond the thermoelectric theory. [Copyright &y& Elsevier]

Cobalt-base alloys are generally adopted in applications that require wear, corrosion, and heat resistance. In particular, cobalt-chromium-molybdenum (Co-Cr-Mo) alloy is currently being used in the aerospace and medical field. Both applications require product personalization and take advantage by parts manufacturing through additive technologies, such as direct metal laser sintering (DMLS). This technology still has limitations for the manufacture of small cavities, such as holes with diameters below 0.6 mm and high aspect ratio, which require drilling of the additive manufactured part. This research aims at investigating the effects of electrodischarge drilling (EDD) on surface and subsurface features of CoCrMo samples built by DMLS. High aspect ratio holes are produced with diameter of 0.6 mm and depth 15 times higher. Due to the absence of physical contact between tool and workpiece in EDD, machining forces are negligible and microfeatures can be produced with a high accuracy irrespective of the material hardness and strength. In this study, peak current, pulse-on-time, and duty ratio are adopted as control factors using the Taguchi method. Material removal rate, Electrode wear rate (EW), and surface roughness are measured as responses. S/ N ratios and analysis of variance analysis lead to identify the significant process parameters and the optimal combination level of machining parameters. From the responses can be determined which ensures high productivity and smooth surface finish, even if tool wear is medium high. All the analyses are supported by the study of material removal mechanisms and surface morphology in the microscale, to account for the macroscopic trends. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to verify the feasibility and evaluate the dimensional accuracy of two rapid casting (RC) solutions based on 3D printing technology: investment casting starting from 3D-printed starch patterns and the ZCast process for the production of cavities for light-alloys castings. Design/methodology/approach – Starting from the identification and design of a benchmark, technological prototypes were produced with the two RC processes. Measurements on a coordinate measuring machine allowed calculating the dimensional tolerances of the proposed technological chains. The predictive performances of computer aided engineering (CAE) software were verified when applied to the ZCast process modelling. Findings – The research proved that both the investigated RC solutions are effective in obtaining cast technological prototypes in short times and with low costs, with dimensional tolerances that are completely consistent with metal casting processes. Practical implications – The research assessed the feasibility and dimensional performances of two RC solutions, providing data that are extremely useful for the industrial application of the considered technologies. Originality/value – The paper deals with experimental work on innovative techniques on which data are still lacking in literature. In particular, an original contribution to the determination of dimensional tolerances and the investigation on the predictive performances of commercial CAE software is provided. [ABSTRACT FROM AUTHOR]

The present inquiry lays a groundwork for the analysis of the net greenhouse gas (GHG) footprint of oil in the oil-abundant settings. To address the research question, the study puts forward a three-sector decision model, which provides a common ground for the assessment of the interaction of the structuralist and institutional factors influencing environmental pollution in the oil-reliant economies. The study shows that fossil-fuel abundance triggers forces, which induce diametrically opposed effects concerning atmospheric pollution. These are the rising carbon-intensive oil extraction and processing and fossil-fueled power generation versus shrinkage of the carbon-intensive manufacturing and growth of the low-carbon tertiarization. The theoretical analysis enables compartmentalization of the essential factors, which determine GHG emissions in the respective countries. To assess the significance of the proposed theoretical framework, the study employs multivariate panel co-integration techniques and two-stage fixed effects estimations for a dataset of 38 oil-producing countries for the time period between 1960 and 2018. In contrast to the existing literature, this study drives apart from the black box approaches that employ just one omnibus variable, per capita income. • The study combines two strands of literature – the Resource Curse and the environmental Kuznets curve hypotheses • A novel three-sector model, which provides a common ground for structuralist, institutional and purely economic analyses of carbon footprint, is put forward. • The inquiry disentangles the environmentally relevant forces triggered by oil abundance on the theoretical level. • Compartmentalization of the factors, induced by fossil fuel abundance and their empirical analysis, provides a basis for environmental policies in oil-producing countries. • The 'black box' parametric estimators establish a monotonically increasing relationship between oil rents and the quantity of greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

• Sunflower is an important oilseed crop affected by environmental and geopolitical threats. • Sunflower can be managed with advanced agriculture techniques thanks to its high mechanizability. • Remote sensing is widespread in the agricultural sector, but it is not so for sunflowers. • Most of the studies on the application of remote sensing do not involve the world's major producers. • The evaluated topics are: vegetation indices, forecasting and growth models, abiotic stresses. Sunflower is an annual species of the Asteraceae family, and it occupies a relevant position in the world market business as one of the most important oilseed crops. Given the current geopolitical situation and climate change, the agri-food supply chain of sunflower is in crisis. In this context, precision agriculture, especially remote sensing, can address demands for more production and greater sustainability. The aim of the present systematic review is to evaluate the available scientific literature on precision agriculture applied to sunflower crop, specifically the use of hyperspectral data to calculate vegetation indices or create crop growth models. The systematic review follows specific guidelines and a well-described review protocol. A total of 104 studies were included in the review, starting from raw search in different data sources (Scopus, Web of Science, Springer Link, and Science Direct) and following with the application of inclusion criteria. Results focused on the following main topics: crop management (i.e., management zones, yield prediction, vegetation indices correlations), sunflower crop growth monitoring (i.e., identify different growth stages and vegetation parameters), weed management, and industrial applications. The role of hyperspectral sensors has been thoroughly investigated to help choose ideal wavelengths related to vegetation indices. Future research should prioritise water stress management, time-saving evaluation of new sunflower hybrids, and crop growth models. [ABSTRACT FROM AUTHOR]

Resilience is a hot topic within the international development agenda and Sustainable Development Goals. Nowadays, resilience plays a crucial role in improving the quality of life of vulnerable categories and is designed as a major strategy to face the diverse dimensions and dynamics of vulnerability. Energy results among the most relevant fields of applications of resilience policies, especially when it comes to electricity. As a multidimensional concept, energy resilience policies must relate to the dimensions of sustainability – here considered as the interplay between the economic, social, environmental and governance dimensions. Due to the complexity of the phenomenon, energy resilience can be effectively outlined making use of composite indicators techniques. This paper presents the following new results: i) energy resilience is defined and ranked, strengthening a composite indicator for both OECD and non-OECD countries; the determinants of energy resilience are investigated; ii) an innovation on the construction of the World Bank's Regulatory Indicators on Sustainable Energy is operated. Our exercise makes use of an approach based on interval data to assess the sensitivity of the measure from different specifications. For the same scope, the robustness of the ranks obtained is analyzed through an uncertainty analysis. These choices aim to enhance the soundness and the validity of the composite indicator. The methodology provides a more reliable baseline to validate the results and the conceptual assumptions undertaken. It is found that, according to the diverse theoretical frameworks and methodologies applied, some countries vary considerably both in the pillars that aggregate the variables and within the minima, the centers, and the maxima of the intervals. • Energy and resilience are compelling development policy, regulatory, and scientific quests. • Energy resilience is measured by an interval data composite indicator. • Interval data is a robust method for measuring energy resilience. • GDP is related to energy resilience. • Results vary with respect to linear methods in that they allow to better represent uncertainty. [ABSTRACT FROM AUTHOR]

Vulnerability has garnered an increasing attention from academia, international community and industry. Nonetheless, formal definition, mainstreaming, and measurement of vulnerability are still flawed in the economic literature. Energy vulnerability, intended as the exposure of an energy system to adverse events and change, often overlaps with other energy policy concepts such as resilience, security, poverty, justice, and sustainability. This paper improves understanding of vulnerability in economics, energy, and sustainability studies by: i) constructing a dataset on energy vulnerability made of 180.000 observations; ii) formally defining energy vulnerability, while considering the regulatory framework and development agenda; iii) building a composite indicator on energy vulnerability; iv) analyzing and ranking the energy vulnerability of a vast number of OECD and non-OECD countries; v) testing for robustness checks. The analysis suggests that GDP is not necessarily a leading driver for energy vulnerability, whilst resource embedment is, since fossil and renewable energy producers are less vulnerable. Eventually, the paper validates that green countries are less vulnerable, differently from cold, heavily-industrialized, and highly-consuming countries. • GDP is not a strong driver for energy vulnerability. • Green, scarcely consuming, warm, non-industrial countries perform better. • Resource endowment and electricity access matter. • Fossil and renewable energy exporters display a lower vulnerability. • Rankings for the single energy vulnerability pillars vary widely. [ABSTRACT FROM AUTHOR]

Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, machine learning can be applied to agriculture. Better crop management, plant health assessment, and early disease detection are some of the main challenges facing the agricultural sector. Plant phenotyping can play a key role in addressing these challenges, especially when combined with machine learning techniques. Therefore, this study reviews available scientific literature on the applications of machine learning algorithms in plant phenotyping with a specific focus on sunflowers. The most common algorithms in the agricultural field are described to emphasise possible uses. Subsequently, the overview highlights machine learning application on phenotyping in three primaries areas: crop management (i.e., yield prediction, biomass estimation, and growth stage monitoring), plant health (i.e., nutritional status and water stress), and disease detection. Finally, we focus on the adoption of machine learning techniques in sunflower phenotyping. The role of machine learning in plant phenotyping has been thoroughly investigated. Artificial neural networks and stacked models seems to be the best way to analyse data. [ABSTRACT FROM AUTHOR]

The growing interest in advancing microfluidic devices for manipulating fluids within micrometer-scale channels has prompted a shift in manufacturing practices, moving from single-component production to medium-size batches. This transition arises due to the impracticality of lab-scale manufacturing methods in accommodating the increased demand. This experimental study focuses on the design of master benchmarks 1–5, taking into consideration critical parameters such as rib width, height, and the relative width-to-height ratio. Notably, benchmarks 4 and 5 featured ribs that were strategically connected to the inlet, outlet, and reaction chamber of the master, enhancing their utility for subsequent replica production. Vat photopolymerization was employed for the fabrication of benchmarks 1–5, while replicas of benchmarks 4 and 5 were generated through polydimethylsiloxane casting. Dimensional investigations of the ribs and channels in both the master benchmarks and replicas were conducted using an optical technique validated through readability analysis based on the Michelson global contrast index. The primary goal was to evaluate the potential applicability of vat photopolymerization technology for efficiently producing microfluidic devices through a streamlined production process. Results indicate that the combination of vat photopolymerization followed by replication is well suited for achieving a minimum rib size of 25 µm in width and an aspect ratio of 1:12 for the master benchmark. [ABSTRACT FROM AUTHOR]

The author reflects on new editorial team assembled by the International Social Science Journal (ISSJ) in January 2023 to cooperatively strive for excellence in publishing outstanding works and advance its scholarly and inter-disciplinary knowledge.

This work introduces a revised version of the Food Sustainability Index , proposed by the Economist Intelligence Unit and the Barilla Center for Food and Nutrition in 2016. Our Adjusted Food Sustainability Index features two important advantages: 1) it employs the Mazziotta-Pareto method to compute weights, hence granting an objective aggregation criterion and 2) it does not take policy variables into account, thus focusing on the status quo . The policy variables are aggregated into the Policy Index , measuring the quality of the food sustainability policies. We compute the two indices for 25 countries worldwide, then we use the Data Envelopment Analysis to evaluate policy efficiency. Our results show that country-level variation in policy efficiency is wide and policies affect food sustainability significantly, especially when they target nutritional challenges. [ABSTRACT FROM AUTHOR]

The attachment or entrapment of microbial cells and enzymes are promising solutions for various industrial applications. When the traps are beads, they are dispersed in a fluidized bed in a vessel where a pump guarantees fresh liquid inflow and waste outflow without washing out the cells. Scientific papers report numerous types of cell entrapment, but most of their applications remain at the laboratory level. In the present research, rigid polymer beads were manufactured by two different additive manufacturing (AM) techniques in order to verify the economy, reusability, and stability of the traps, with a view toward a straightforward industrial application. The proposed solutions allowed for overcoming some of the drawbacks of traditional manufacturing solutions, such as the limited mechanical stability of gel traps, and they guaranteed the possibility of producing parts of constant quality with purposely designed exchange surfaces, which are unfeasible when using conventional processes. AM proved to be a viable manufacturing solution for beads with complex shapes of two different size ranges. A deep insight into the production and characteristics of beads manufactured by AM is provided. The paper provides biotechnologists with a manufacturing perspective, and the results can be directly applied to transit from the laboratory to the industrial scale. [ABSTRACT FROM AUTHOR]

Electro-discharge machining (EDM) of thin deep features widens processing opportunities of difficult-to-cut materials, such as Ni-based alloys, towards attractive industrial applications. Conversely, the complex interaction between electrical, thermal, and chemical phenomena in EDM thwarts process modeling and prediction. As a matter of fact, recent experimental discoveries encourage setting forth a new theory of discharge ignition in the gap, based on the role of debris, which lays foundations for a recursive mathematical model showing a chaotic evolution. The paper reports on electro-discharge drilling of small deep holes in Inconel 718. Process performances are measured with varying electrode size and geometry, attesting a pivotal effect of gap pollution on productivity and on the onset of a secondary detrimental removal of material by intergranular corrosion. All findings support the emerging model for discharge ignition via debris bridges, and, most notably, debris chains are documented for the first time in the field of metals, second only to a previous case for a ceramic composite. On the whole, the paper provides conclusive validation of the role of debris in the ignition of discharges. [ABSTRACT FROM AUTHOR]

Food system resilience has multiple dimensions. We draw on food system and resilience concepts and review resilience framings of different communities. We present four questions to frame food system resilience (Resilience of what? Resilience to what? Resilience from whose perspective? Resilience for how long?) and three approaches to enhancing resilience (robustness, recovery, and reorientation—the three "Rs"). We focus on enhancing resilience of food system outcomes and argue this will require food system actors adapting their activities, noting that activities do not change spontaneously but in response to a change in drivers: an opportunity or a threat. However, operationalizing resilience enhancement involves normative choices and will result in decisions having to be negotiated about trade-offs among food system outcomes for different stakeholders. New approaches to including different food system actors' perceptions and goals are needed to build food systems that are better positioned to address challenges of the future. [ABSTRACT FROM AUTHOR]

Green innovation (GI) is widely accepted as a driver of carbon neutrality and sustainable development. Human resource is the executor of green innovation, both higher education (HE) and scientific research (SR) are vital to green innovation. This study explores the impact of HE and SR on GI in 285 prefecture-level cities in China from 2003 to 2019. The results show that both HE and SR contribute significantly to GI. Researcher density, regional innovation, and entrepreneurship capacity were introduced as mediating variables, and the results appear to be all significant mediating effects. Finally, corresponding recommendations were made: the government should strengthen the coordination of education and science and technology resources, promote interactive enterprises and universities' development, and strengthen GI in western China. • Impact of higher education and scientific research on green innovation is explored. • Both contribute significantly to green innovation. • Coordination of education and science and technology resources should be strengthened. • Interactive development of enterprises and universities should be promoted. • Green innovation in western China should be strengthened. [ABSTRACT FROM AUTHOR]

One of the most important open challenges in climate science is downscaling. It is a procedure that allows making predictions at local scales, starting from climatic field information available at large scale. Recent advances in deep learning provide new insights and modeling solutions to tackle downscaling-related tasks by automatically learning the coarse-to-fine grained resolution mapping. In particular, deep learning models designed for super-resolution problems in computer vision can be exploited because of the similarity between images and climatic fields maps. For this reason, a new architecture tailored for statistical downscaling (SD), named MSG-GAN-SD, has been developed, allowing interpretability and good stability during training, due to multi-scale gradient information. The proposed architecture, based on a Generative Adversarial Network (GAN), was applied to downscale ERA-Interim 2-m temperature fields, from 83.25 to 13.87 km resolution, covering the EURO-CORDEX domain within the 1979--2018 period. The training process involves seasonal and monthly dataset arrangements, in addition to different training strategies, leading to several models. Furthermore, a model selection framework is introduced in order to mathematically select the best models during the training. The selected models were then tested on the 2015-2018 period using several metrics to identify the best training strategy and dataset arrangement, which finally produced several evaluation maps. This work is the first attempt to use the MSG-GAN architecture for statistical downscaling. The achieved results demonstrate that the models trained on seasonal datasets performed better than those trained on monthly datasets. This study presents an accurate and cost-effective solution that is able to perform downscaling of 2 m temperature climatic maps. [ABSTRACT FROM AUTHOR]

Laser Powder Bed Fusion (LPBF) technology was used to produce samples based on the Ti–6Al–4V alloy for biomedical applications. Solid-state phase transformations induced by thermal treatments were studied by neutron diffraction (ND), X-ray diffraction (XRD), scanning transmission electron microscopy (STEM) and energy-dispersive spectroscopy (EDS). Although, ND analysis is rather uncommon in such studies, this technique allowed evidencing the presence of retained β in α' martensite of the as-produced (#AP) sample. The retained β was not detectable by XRD analysis, nor by STEM observations. Martensite contains a high number of defects, mainly dislocations, that anneal during the thermal treatment. Element diffusion and partitioning are the main mechanisms in the α ↔ β transformation that causes lattice expansion during heating and determines the final shape and size of phases. The retained β phase plays a key role in the α' → β transformation kinetics. [ABSTRACT FROM AUTHOR]

Metal additive manufacturing is now taking the lead over traditional manufacturing techniques in applications such as aerospace and biomedicine, which are characterized by low production volumes and high levels of customization. While fulfilling these requirements is the strength of metal additive manufacturing, respecting the tight tolerances typical of the mentioned applications is a harder task to accomplish. Powder bed fusion (PBF) is a class of additive manufacturing in which layers of metal powder are fused on top of each other by a high-energy beam (laser or electron beam) according to a computer-aided design (CAD) model. The quality of raw powders for PBF affects the mechanical properties of additively manufactured parts strongly, and therefore it is crucial to avoid the presence of any source of contamination, particularly cross-contamination. In this study, the identification and quantification of cross-contamination in powders of Ti-6Al-4V and maraging steel was performed using scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) techniques. Experimental results showed an overall good reliability of the developed method, opening the way for applications in machine learning environments. [ABSTRACT FROM AUTHOR]

• Indigenous giant banana relative enset unique traits add agrifood system resilience. • Novel mature enset area measure improves three food security indicator models' fit. • Perineal enset's overlapping generations a 'moving average' food insecurity metric. • Mature enset area indicates both buffering and adaptive contributions to stability. • Indigenous agrifood systems' living assets and green storage require more study. Enset-based food systems are unique to southern Ethiopia where they serve as a staple food for millions of households. Enset, a banana relative of which the entire pseudostem and corm are edible, possesses a highly unusual combination of crop traits including perenniality, highly flexible planting and harvest times, and tolerance of a very wide range of environmental conditions, which together earn it the local name of "the tree against hunger." Previous studies have identified the strategic food security value of mature enset stands for household food security, but a multisector panel data set makes identifying wider enset food security associations tractable for the first time. We assess whether household data on area of mature enset is associated with four indicators of food security together with demographic, asset, and consumption covariates. We find that area of mature enset significantly improves estimates for three of four food security indicators, thus improving our understanding of the role of understudied indigenous crops. Consistent and reliable food security indicators are needed to improve monitoring, particularly with regard to stability. Variance components of multilevel longitudinal models indicate that exposure to both idiosyncratic and covariate disturbance affects food security stability in a way that is consistent with reports of enset acting as both a food security buffer and an active adaptation strategy in the face of shocks or change. Here we show that living assets comprising culturally relevant indigenous crops such as enset can improve accuracy of food insecurity assessments, which may encourage wider investigation of other agrifood system-specific asset-like natural stores of value associated with food security and resilience. [ABSTRACT FROM AUTHOR]

We present three-dimensional radiation-hydrodynamical simulations of the impact of stellar winds, photoelectric heating, photodissociating and photoionizing radiation, and supernovae on the chemical composition and star formation in a stratified disc model. This is followed by a sink-based model for star clusters with populations of individual massive stars. Stellar winds and ionizing radiation regulate the star formation rate at a factor of ~10 below the simulation with only supernova feedback due to their immediate impact on the ambient interstellar medium after star formation. Ionizing radiation (with winds and supernovae) significantly reduces the ambient densities for most supernova explosions to ρ < 10-25 g cm-3, compared to 10-23g cm-3 for the model with only winds and supernovae. Radiation from massive stars reduces the amount of molecular hydrogen and increases the neutral hydrogen mass and volume filling fraction. Only this model results in a molecular gas depletion time-scale of 2 Gyr and shows the best agreement with observations. In the radiative models, the Hα emission is dominated by radiative recombination as opposed to collisional excitation (the dominant emission in non-radiative models), which only contributes ~1-10 per cent to the total Hα emission. Individual massive stars (M ≥ 30M☉) with short lifetimes are responsible for significant fluctuations in the Hα luminosities. The corresponding inferred star formation rates can underestimate the true instantaneous star formation rate by a factor of ~10. [ABSTRACT FROM AUTHOR]

We present three-dimensional radiation-hydrodynamical simulations of the impact of stellar winds, photoelectric heating, photodissociating and photoionizing radiation, and supernovae on the chemical composition and star formation in a stratified disc model. This is followed by a sink-based model for star clusters with populations of individual massive stars. Stellar winds and ionizing radiation regulate the star formation rate at a factor of ~10 below the simulation with only supernova feedback due to their immediate impact on the ambient interstellar medium after star formation. Ionizing radiation (with winds and supernovae) significantly reduces the ambient densities for most supernova explosions to ρ < 10-25 g cm-3, compared to 10-23g cm-3 for the model with only winds and supernovae. Radiation from massive stars reduces the amount of molecular hydrogen and increases the neutral hydrogen mass and volume filling fraction. Only this model results in a molecular gas depletion time-scale of 2 Gyr and shows the best agreement with observations. In the radiative models, the Hα emission is dominated by radiative recombination as opposed to collisional excitation (the dominant emission in non-radiative models), which only contributes ~1-10 per cent to the total Hα emission. Individual massive stars (M ≥ 30M☉) with short lifetimes are responsible for significant fluctuations in the Hα luminosities. The corresponding inferred star formation rates can underestimate the true instantaneous star formation rate by a factor of ~10. [ABSTRACT FROM AUTHOR]

We present three-dimensional radiation-hydrodynamical simulations of the impact of stellar winds, photoelectric heating, photodissociating and photoionizing radiation, and supernovae on the chemical composition and star formation in a stratified disc model. This is followed by a sink-based model for star clusters with populations of individual massive stars. Stellar winds and ionizing radiation regulate the star formation rate at a factor of ∼10 below the simulation with only supernova feedback due to their immediate impact on the ambient interstellar medium after star formation. Ionizing radiation (with winds and supernovae) significantly reduces the ambient densities for most supernova explosions to ρ < 10-25 g cm-3, compared to 10-23g cm-3 for the model with only winds and supernovae. Radiation from massive stars reduces the amount of molecular hydrogen and increases the neutral hydrogen mass and volume filling fraction. Only this model results in a molecular gas depletion time-scale of 2 Gyr and shows the best agreement with observations. In the radiative models, the Hα emission is dominated by radiative recombination as opposed to collisional excitation (the dominant emission in non-radiative models), which only contributes ∼1-10 per cent to the total Hα emission. Individual massive stars (M ≥ 30M☉) with short lifetimes are responsible for significant fluctuations in the Hα luminosities. The corresponding inferred star formation rates can underestimate the true instantaneous star formation rate by a factor of ∼10. [ABSTRACT FROM AUTHOR]