Preferred Scenario Research Articles

Anticipating prosperity: a systemic analysis of long-term economic trajectories

PurposeThis study introduces an innovative approach to long-term economic forecasting by integrating anticipatory governance (AG) and causal layered analysis methodologies. Focussing on emerging economies, with Vietnam as a case study, we explore potential economic trajectories to 2050.Design/methodology/approachThe research employs a mixed-method approach, combining quantitative economic projections with qualitative scenario building and analysis.FindingsOur findings reveal four distinct future scenarios, ranging from low growth to transformative change. The preferred scenario, characterized by adaptive change, projects a Gross National Income (GNI) per capita of $30,684 by 2050, with significant reductions in agricultural labour and improvements in human development indicators.Originality/valueThis study contributes to theoretical and practical domains by demonstrating the value of integrated foresight methodologies in economic planning. It offers policymakers a comprehensive framework for navigating complex, long-term economic challenges and opportunities. This research underscores the importance of adaptive governance and systemic thinking in achieving sustainable, inclusive economic growth in an increasingly uncertain global environment.

Improving Grade Nine Students’ English Language Speaking Skill of Polite Requests: Misrak Chora Secondary School

Most commonly it is agreed that politeness is reflected in the pragmatic use of language. Although the politeness phenomenon is universal, with many expressional similarities, each language possesses norms and ways of expressing politeness within a given cultural context. Politeness has connection with everyday life such as with greeting, inviting, helping, apologizing, opinions, advice, questioning and suggesting information etc. English speaker tourists most frequently visit and resident in Hawassa City-Ethiopia and have cultural and communication exposure. However, many Ethiopian students are observed incompetent in this regard. Thus, the current study was intended to improve EFL learners’ polite requesting skills in some selected situations both in classroom contexts and outside contexts. For this purpose, the pre-experimental research design was employed to the study, and twenty students (10 females and 10 males) were randomly selected by lottery system from the 9<sup>th</sup> B classroom. This makes 22.2% of the population in the class. Six politeness genres were selected from the students’ English textbook for explicit lesson intervention. Based on Written Discourse Completion Test (WDCT) instrument prepared from these contents, both pretest and posttest conditions were administered to the selected students. Also cooperative learning strategies such as role play, pair work, group discussion, extemporaneous speeches on situations, cooperative jigsaw, interactive discourse, timed interview, Think-Pair-Share (TPS) were utilized during the lesson sessions. Then, frequencies, means, standard deviations, variances and percentages were used to obtain the main findings. On pretest, students have scored the overall 27.16% (mean, 8.15) regarding all polite request situations. However, it was found that the posttest scores showed great difference about 78.3% (mean, 23.5) in all situations. The study has also sought which request contexts grade nine students improve best as a result of the explicit instruction. Although students have improved performance in all tested situations, they had showed very significant change on request for apology followed by for help. In apology situation the students have achieved 90% and the least in preference scenario which is 65%. Thus, it is recommended that learners have to be explicitly taught in context of these language genres to develop learners' communicative abilities in the area. Teachers should devote time to instruct on this language content [polite request] as it is everyday encounter in one's life. Syllabus designers also should allot much time and tasks on the area so that school teachers give attention to areas.

Augmented ɛ‐constraint‐based matheuristic methodology for Bi‐objective production scheduling problems

AbstractMatheuristic is an optimisation methodology that integrates mathematical approaches and heuristics to address intractable combinatorial optimisation problems, where a common framework is to insert mixed integer linear programming (MILP) models as local search functions for evolutionary algorithms. However, since a mathematical programming formulation only tries to find the solution with the best objective value, matheuristics are rarely adopted to multi‐objective scenarios asking for a set of Pareto optimal solutions, for example, vehicle routing problems and production scheduling problems. In this situation, the ɛ‐constraint, which transforms multi‐objective problems into single‐objective formulations by considering selected objectives as constraints, seems to be a promising approach. First, an augmented ɛ‐constraint‐based matheuristic methodology (ɛ‐MH) is proposed to apply the idea of ɛ‐constraint to embedded MILP models, so that Pareto fronts obtained by meta‐heuristics can be further improved by solving a set of MILP models. Afterwards, four speed‐up strategies are developed to alleviate the computational burden resulting from repeatedly solving mathematical formulations, which also imply preferable scenarios for taking advantages of the ɛ‐MH. Finally, several real‐world bi‐objective scheduling problems are discussed to present potential applications for the proposed methodology.

Response and prediction of ecosystem service values to land use change resulting from underground coal mining in high groundwater table areas: A case study of Jining City, China

Ecosystem services are crucial for human survival and development. Changes in land use can lead to alterations in ecosystem service functions. However, the mechanism of how land use changes resulting from underground coal mining affect ecosystem service remains unclear, especially in areas with high groundwater levels. To address this issue, we studied the spatiotemporal in land use change in Jining City from 2000 to 2020 and employed Markov-PIM (probability integration method)-PLUS (Patch-generate Land Use Simulation) model to simulate land use change and ecosystem service values (ESV) in Jining City by 2030 under four different scenarios. The results indicate that from 2000 to 2020, the area of ecological space increased by 169.99 km2, and the area of living space expanded by 775.28 km2, while the area of production space decreased by 945.27 km2, conversely. These changes led to a 3 million yuan increase in total ESV. From 2020 to 2030, there was a marked decline in ESV under both natural development (ND) and living space preference (LSP) scenarios, with decreases of 0.59 billion yuan and 1.38 billion yuan, respectively. In contrast, in production space preference (PSP) and ecological space preference (ESP) scenarios, ESV increase by 0.22 billion yuan and 0.34 billion yuan. The ESP scenario is an effective strategy to strengthen environmental protection, significantly improve the ESV level of Jining City and meet the development goals of Jining City. Finally, the study concludes with recommendations like comprehensive management, industrial upgrading, and collaborative development for optimizing Jining City's future land use and enhance ESV for urban development.

Decarbonising waste-to-energy: A life cycle assessment study

With Waste-to-Energy (WtE) plants expected to play an expanding role in managing municipal solid waste (MSW), it is critical that the sector decarbonises if climate targets are to be met. Here we investigate the climate and environmental performance of capturing and sequestering (CCS) carbon emissions from WtE via process modelling and Life Cycle Assessment (LCA), exploring multiple scenarios, including e.g. carbon capture rates and MSW composition, to identify trades-offs and preferable scenarios. The LCA results show that, despite associated energy penalties, carbon capture significantly lowers climate change impacts, with WtE qualifying as a Carbon Dioxide Removal technology for capture rates above 50 %. We also find that CCS increases impacts in all other environmental categories and that the waste composition plays a key role in determining the environmental performance. Overall, we argue that economics is the chief deployment challenge, particularly because of additional transportation costs due to dispersed nature of waste.

Social life cycle hotspot analysis of future hydrogen use in the EU

Abstract Purpose The widespread use of hydrogen in the EU aimed at reducing greenhouse gas emissions may involve complex value chains (e.g. importation from third countries) with potential effects (positive or negative) on the different sectors of society. Achieving sustainable hydrogen deployment must be motivated not only by environmental and economic aspects but also by social responsibility and the search for human well-being. Given this, and the scarcity of studies currently available on prospective social impacts of hydrogen production, the present purpose of this article is to unveil and assess the main social impacts linked to the future hydrogen value chains. Methods The methodological approach adopted in this article encompasses the following steps: (i) analysis of two potential value chains for hydrogen use in EU: an on-site option, where hydrogen is produced and used in the same European country, and an off-site option, where hydrogen is produced in a European country different from its usage involving more unit processes, in terms of storage and transport activities, and working time to deliver the same quantity of hydrogen. This framework will include (i) scenario analysis and a forward-looking perspective taking into account the critical raw materials employed across the entire value chain, (ii) identification of a list of relevant social impact categories and indicators through a systematic procedure, (iii) social hotspot analysis using Product Social Impact Life Cycle Assessment (PSILCA) to assess the selected representative value chains, and (iv) conducting scenario analysis and subsequently interpreting of results. Results and discussion The off-site value chain shows a relatively worse social performance (6 to 72 times) than the on-site value chain across most selected indicators due to the more complex value chain. Although the identification of social hotspots depends on the specific social indicator under evaluation, the power source components (wind and solar PV) manufacturing processes and the relatively increased complexity of the off-site option highly conditioned the social performance of the hydrogen value chains in most of the indicators considered. A scenario analysis was carried out comparing both value chains with two additional locations for hydrogen production: Northern Africa and Western Asia. The findings indicate that the on-site value chain presents the lowest impact scores. For the off-site option, the production of hydrogen in a European country is the most preferable scenario in terms of the social indicators evaluated. Conclusions According to findings, producing hydrogen in a different location than where it is consumed increases the social impacts of its deployment. Measures at mid and long term should be considered for improving the social impact of hydrogen deployment in Europe. This includes increasing reuse and recycling, responsibly sourcing raw materials, and creating regulatory frameworks ensuring safe working conditions across global value chains. Furthermore, this article highlights the crucial role of the S-LCA methodology in evaluating social aspects as a support for targeted policy interventions, and the need to adapt this to the specific case study. At the same time, it acknowledges that other relevant social aspects that can influence the social sustainability of the hydrogen technology are not captured with this methodology (in particular social acceptance, affordability and energy security). Improvements in selecting indicators and refined geographical and temporal representations of the value chains to better represent hydrogen technologies and future size market are research gaps filled in the present scientific work.

Cost-Effectiveness of Plasma Microbial Cell-Free DNA Sequencing When Added to Usual Care Diagnostic Testing for Immunocompromised Host Pneumonia.

Immunocompromised host pneumonia (ICHP) is an important cause of morbidity and mortality, yet usual care (UC) diagnostic tests often fail to identify an infectious etiology. A US-based, multicenter study (PICKUP) among ICHP patients with hematological malignancies, including hematological cell transplant recipients, showed that plasma microbial cell-free DNA (mcfDNA) sequencing provided significant additive diagnostic value. The objective of this study was to perform a cost-effectiveness analysis (CEA) of adding mcfDNA sequencing to UC diagnostic testing for hospitalized ICHP patients. A semi-Markov model was utilized from the US third-party payer's perspective such that only direct costs were included, using a lifetime time horizon with discount rates of 3% for costs and benefits. Three comparators were considered: (1) All UC, which included non-invasive (NI) and invasive testing and early bronchoscopy; (2) All UC & mcfDNA; and (3) NI UC & mcfDNA & conditional UC Bronch (later bronchoscopy if the initial tests are negative). The model considered whether a probable causative infectious etiology was identified and if the patient received appropriate antimicrobial treatment through expert adjudication, and if the patient died in-hospital. The primary endpoints were total costs, life-years (LYs), equal value life-years (evLYs), quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio per QALY. Extensive scenario and probabilistic sensitivity analyses (PSA) were conducted. At a price of $2000 (2023 USD) for the plasma mcfDNA, All UC & mcfDNA was more costly ($165,247 vs $153,642) but more effective (13.39 vs 12.47 LYs gained; 10.20 vs 9.42 evLYs gained; 10.11 vs 9.42 QALYs gained) compared to All UC alone, giving a cost/QALY of $16,761. NI UC & mcfDNA & conditional UC Bronch was also more costly ($162,655 vs $153,642) and more effective (13.19 vs 12.47 LYs gained; 9.96 vs 9.42 evLYs gained; 9.96 vs 9.42 QALYs gained) compared to All UC alone, with a cost/QALY of $16,729. The PSA showed that above a willingness-to-pay threshold of $50,000/QALY, All UC & mcfDNA was the preferred scenario on cost-effectiveness grounds (as it provides the most QALYs gained). Further scenario analyses found that All UC & mcfDNA always improved patient outcomes but was not cost saving, even when the price of mcfDNA was set to $0. Based on the evidence available at the time of this analysis, this CEA suggests that mcfDNA may be cost-effective when added to All UC, as well as in a scenario using conditional bronchoscopy when NI testing fails to identify a probable infectious etiology for ICHP. Adding mcfDNA testing to UC diagnostic testing should allow more patients to receive appropriate therapy earlier and improve patient outcomes.

Integration of preferences in multimodal multi-objective optimization

Various existing multimodal multi-objective evolutionary algorithms (MMEAs) efficiently search for an approximation to the Pareto optimal front (PF), which consists of multiple equivalent Pareto optimal sets (PSs), when tackling multimodal multi-objective optimization problems (MMOPs). However, in practical applications, the Decision-maker (DM) often seeks specific portions of the PF, known as the Region of Interest (ROI), corresponding to particular instances rather than the whole PF. Existing MMEAs only focus on the whole PF and lack exploration of the ROI. Consequently, we propose an innovative MMEA that incorporates the DM’s preferences and local convergence quality (MMEA-PLC). The proposed algorithm integrates the DM’s preferences into the traditional Pareto-dominance relationship, enabling the search for multiple equivalent Pareto optimal set subsets (PSSs) within the ROI. Due to the influence of local PFs, accurately representing the ROI can be challenging when expressed across different PFs. Therefore, we design a preference-based Pareto-dominance relationship to accurately convey the preferences on different PFs by mapping solutions onto a hyperplane in the objective space. Then, we further develop a scheme for assessing local convergence quality (LCQ) to ensure that the algorithm can identify multiple equivalent PSSs within the same ROI. To verify the effectiveness of the proposed algorithm, MMEA-PLC was experimentally compared with eight state-of-the-art MMEAs on 28 benchmark functions and a real-life application problem. Experimental results show that MMEA-PLC has significant competitive advantages in different preference scenarios.

Consequences of omitting non-lethal wildlife impacts from stated preference scenarios

Stated preference (SP) research on willingness to pay (WTP) for improvements to wildlife populations focuses almost universally on measures related to whether organisms live or die. Preferences for changes in non-lethal harm to wildlife are generally overlooked. To evaluate the consequences, this article develops a theoretical model and corresponding discrete choice experiment (DCE) to evaluate whether and how the omission of information on non-lethal wildlife harm influences WTP estimation, grounded in a case study of marine plastic reductions in the North Atlantic. The theoretical model suggests that when environmental programs have both lethal and non-lethal impacts on wild species, DCEs that omit information on the latter may not produce valid welfare measures. Empirical results show that the omission of this information has multiple impacts on welfare estimates, largely consistent with theoretical predictions. Results suggest that welfare estimates for wildlife improvements can be confounded by the omission of information on non-lethal harm from SP scenarios. Results also demonstrate the hazards of excluding potentially welfare-relevant information from SP scenarios when respondents might assume relationships between omitted information and other material included in the questionnaire.

Exploring equality and sustainability trade-offs of energy transition outcomes in the United States in 2050

With increasing focus on equitable and just energy transition, it is critical to understand the trade-offs of different decarbonization outcomes across economic, environmental, and social sustainability criteria. In this analysis, we use a multi-criteria decision analysis to quantify sustainability outcomes across 32 decarbonization outcomes in 2050 in the U.S. The economic sustainability criteria we use are system cost, national average retail rate, and electricity system employment. The environmental sustainability criteria we use are life cycle greenhouse gas emissions, life cycle water depletion, life cycle land transformation, and air pollution fatalities. The social sustainability (distributional impacts) criteria we use are retail rate equality across states, electricity employment equality across low-income households, and air pollution disparities across census tracts. We evaluate performance across these criteria under eleven different stakeholder preference scenarios. We find that decarbonization policies with indefinitely extended tax credits have the highest sustainability score under equal criteria weighting, with greater investments in renewable energy technologies, and result in better environmental, system cost, job, and air pollution disparities compared to mid-case scenarios, that only include current policies and CO2 reduction targets. We also see that our multi-criteria decision analysis identifies decarbonization outcomes that would not have been identified as optimal under a single objective, which highlights the importance of trade-off analyses to understand decarbonization outcomes more holistically.

Abstract PO4-03-11: Discerning the impact of ctDNA detection on patient decisions in early-stage breast cancer

Abstract Background: Detection of circulating tumor DNA (ctDNA) after neoadjuvant therapy for triple negative breast cancer (TNBC) is associated with increased risk of recurrence. Ongoing trials aim to determine whether knowledge of specific genomic mutations in ctDNA can inform targeted adjuvant therapy to improve prognosis. The impact of knowledge of ctDNA status on patient treatment decisions weighing benefit and toxicity is unknown. Methods: 401 women were recruited via the Research Advocacy Network from Young Survivors’ Coalition, Living Beyond Breast Cancer, and Pink-4-Ever Ending Disparities. Participants had to self-report a history of non-metastatic breast cancer and have received chemotherapy in the prior 6 months to 10 years to be eligible. Participants completed a 27 question Qualtrics survey detailing demographics and experience with prior chemotherapy. Based on estimations from prior data, participants were presented with scenarios mimicking residual TNBC and unknown, negative, or positive ctDNA status with corresponding risk of recurrence of 40%, 20%, or 55% respectively. Participants were then presented with 12 scenarios (in random order) combining various degrees of absolute risk reduction (5%, 15%, 35%) with established toxicity profiles of four possible post-neoadjuvant therapies (capecitabine, immunotherapy, PARP inhibitor, and PI3K inhibitor). Participants rated scenarios in terms of acceptability from 0-100. A general linear model with repeated measures (3 × 4) was used to determine the contributions of risk reduction and toxicity to acceptability. Models were also run with the addition of between subject factors: age group (< 40; >40), stage of cancer (Stage 1; Stage 2/3), and previous experience with toxicity (Yes; No), to examine whether any of these factors moderated the effects of risk reduction and toxicity. Effect sizes were determined by partial h2. Results: 286 eligible respondents completed the survey with evaluable responses. Average age was 41.2 (range 27-75). When the hypothetical risk of recurrence decreased from 40% (ctDNA-unknown) to 20% (ctDNA-negative), significantly less participants preferred adjuvant capecitabine vs. no therapy (95.1% versus 63.3%, p< 0.001). Across the 12 scenarios, both benefit (F=448.5, p< 0.001; preference for greater benefit) and toxicity (F=33.64, p< 0.001; preference for lower toxicity) significantly influenced acceptability, but benefit had a much larger effect size than toxicity (h2=0.76 and 0.26, respectively). There was no significant interaction effect, and the pattern of results was not moderated by age, stage of cancer, or prior experience with chemotherapy toxicity. The most preferred scenario (greatest benefit, lowest toxicity) had a mean rating of 87.8/100; however, even when presented with the scenario with the lowest benefit and highest toxicity, the mean rating was still 31.5/100, suggesting that this combination would be acceptable to some individuals. Conclusions: Knowledge of ctDNA-negative status significantly reduced the number of participants preferring adjuvant capecitabine over no further therapy. When faced with ctDNA-positive status, participants preferred maximum risk reduction regardless of toxicity profile. As genomic technology advances, it is imperative that researchers and treating physicians understand its impact on patient decision making. Citation Format: Tarah Ballinger, Gregory Zimet, Elda Railey, Mary Lou Smith, Bryan Schneider. Discerning the impact of ctDNA detection on patient decisions in early-stage breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-03-11.

Can Jupiter’s Atmospheric Metallicity Be Different from the Deep Interior?

Updated formation and structure models of Jupiter predict a metal-poor envelope. This is at odds with the two to three times solar metallicity measured by the Galileo probe. Additionally, Juno data imply that water and ammonia are enriched. Here, we explore whether Jupiter could have a deep radiative layer separating the atmosphere from the deeper interior. The radiative layer could be caused by a hydrogen-transparency window or depletion of alkali metals. We show that heavy-element accretion during Jupiter’s evolution could lead to the desired atmospheric enrichment and that this configuration would be stable over billions of years. The origin of the heavy elements could be cumulative small impacts or one large impact. The preferred scenario requires a deep radiative zone, due to a local reduction of the opacity at ∼2000 K by ∼90%, which is supported by Juno data, and vertical mixing through the boundary with an efficiency similar to that of molecular diffusion (D ≲ 10−2 cm2 s−1). Therefore, most of Jupiter’s molecular envelope could have solar composition while its uppermost atmosphere is enriched with heavier elements. The enrichment likely originates from the accretion of solid objects. This possibility resolves the long-standing mismatch between Jupiter’s interior models and atmospheric composition measurements. Furthermore, our results imply that the measured atmospheric composition of exoplanets does not necessarily reflect their bulk compositions. We also investigate whether the enrichment could be due to the erosion of a dilute core and show that this is highly unlikely. The core-erosion scenario is inconsistent with evolution calculations, the deep radiative layer, and published interior models.

Environmental Impact Assessment of Urban Waste Recycling Challenges: A Review of DPSIR for Life Cycle Assessment of Municipal Solid Waste Recycling Challenges in Greater Monrovia, Liberia

This study evaluates the environmental impact of municipal solid waste management recycling probability in Greater Monrovia, using the Driver-Pressure-State-Impact-Response (DPSIR) framework and Life Cycle Assessment (LCA). Greater Monrovia generates approximately 236155 tons of recyclable waste annually, comprising biodegradable, plastics, paper, inert materials, and assorted waste. Inadequate infrastructure causes less waste collection, and most are openly dumped or burned, triggering severe environmental pollution. The LCA examines key impact categories, including global warming potential (GWP), water pollution, resource depletion, and human health impacts across four waste management scenarios. Scenario one (Landfill) identified significant emissions, contributing to global warming (194.86 kg CO2 eq), marine aquatic ecotoxicity (MAE) (2259578 kg 14-DB eq), and human toxicity (172.59 kg 14-DB eq). Scenario two (Anaerobic Digestion) illustrates lower impacts on human toxicity (237.83 kg 14-DB eq) and freshwater aquatic ecotoxicity (86.99 kg 14-DB eq), with moderate GWP (415.51 kg CO2 eq). In Scenario three, (Open Burning) results are the highest GWP (444.03 kg CO2 eq) and MAE (1426606.7 kg 14-DB eq), indicating substantial environmental and health risks. Scenario Four, a combined approach integrating landfill, anaerobic digestion, and open burning, optimizes the strengths and mitigates the weaknesses of each scenario, offering a balanced approach with reduced impacts across multiple categories. Findings indicate Scenario Two has a relatively moderate environmental impact. Assumed as the most preferred scenario based on the waste management option due to low environmental effects, thereby recommended as the appropriate technology for the MSW recycling process in Greater Monrovia, ultimately reducing environmental impacts and improving resource recovery.

The development of Maltese English

AbstractThere has been a more or less constant presence of the English language in the Maltese islands since British settlement began to establish itself during the 1800s. The necessity of accommodating foreign rulers or visitors fuelled a well‐established linguistic dexterity in the islanders, who are documented to have used what came to be designated as Maltese amongst themselves, alongside any other languages necessary with anyone else. Today, fluency in at least Maltese and English remains the preferred linguistic scenario, and both are generally considered necessary to be able to get involved in Maltese society.

Agent-based modeling and optimization of the characteristics for research-and-production clusters

This paper presents a developed agent-based simulation model for the development of research-and-production clusters in Russia implemented with the use of high-tech enterprises located in four science cities (Troitsk, Obninsk, Pushchino and Protvino) as the case study. A new approach to modeling and optimization of gross metropolitan product (GMP) is proposed, taking into account the influence of the “gravity effect” on the redistribution of labor resources between developing science cities and appropriate enterprises united in single research and research-and-production clusters An important element of this approach is the formation of various scenarios for the strategic development of the research-and-production clusters being assessed and support for the possibility of choosing the most preferable scenario using an evolutionary optimization algorithm. An enlarged simulation model has been developed and implemented in AnyLogic describing the possible development trajectories of science cities with a corresponding change in the values of the most important characteristics: the number of economically active population, the number of research-and-production enterprises, the volume of products produced in high-tech sectors of the economy, GMP, etc. The designed framework is intended primarily for the management of research-and-production clusters implementing the strategy of innovative development. Such a framework uses methods of system dynamics and agent-based simulation modeling supported in the AnyLogic system, genetic optimization algorithms and GIS mapping for science cities, etc. to implement the required functionality. The approbation of the framework was completed with the use of real data published in the approved strategies of the relevant science cities development. As a result of the numerical experiments carried out, some recommendations were proposed for the development of the research-and-production clusters under study considering their mutual influence and the existing base of resources.

Parameter impact and sensitivity analysis of a pumped hydro compressed air energy storage system

Pumped hydro compressed air energy storage systems are a new type of energy storage technology that can promote development of wind and solar energy. In this study, the effects of single- and multi-parameter combination scenarios on the operational performance of a pumped compressed air energy storage system are investigated. The impacts of 11 design parameters on the evaluation indices are explored, and the local sensitivity of each parameter is determined. Five key design parameters are selected and the global sensitivity under two-, three-, four-, and five-parameter combination scenarios are revealed. Finally, the energy and exergy flow processes in the original and seven preferred scenarios are compared and analyzed. The results show that the larger the pump efficiency, turbine efficiency, and cylinder 1 upper side cross-sectional area, and the lower the initial pressure, the higher is the ηRTE and ηX. For ED, the sensitivity of the termination air pressure is the highest, reaching 0.747. In scenarios where all three indices are increased, the maximum values of 0.586, 0.691, and 0.313 kW h/m3 are achieved for ηRTE, ηX, and ED, respectively.

What can be learned from using participatory landscape scenarios in Rio Doce State Park, Brazil?

ContextThe goal of this work is to describe and explain the conditions that trigger, enable or prevent the implementation of preferred land uses by local communities.ObjectiveThe questions this paper addresses are as follows: Is there a set of preferred scenarios for land use change? What triggers, enables and prevents the implementation of preferred land uses? What did we learn by using participatory landscape scenarios?MethodsIn order to answer the research questions, we synthesize knowledge from a long-term case study in the buffer zone of the Rio Doce State Park in Brazil by (1) Developing participatory landscape scenarios and spatially explicit models for exploring desirable futures and associated land uses, as seen by local communities; (2) Explaining the conditions that trigger, enable or prevent the implementation of preferred landscape scenarios; and (3) Synthesizing knowledge on research and practice for working towards preferred land use changes.ResultsPreferred scenarios for land use change are agroforestry, animal husbandry, tourism and conservation. Although there is biophysical potential and funding available through multiple social and environmental programs, the Rio Doce State Park’s institutional setting is confusing. Although preferred land use scenarios will likely be implemented, participatory landscape approaches require a new, strategic role and leadership by regional institutions. Universities need to bring in social theories and institutional analysis to educate a new generation of landscape stewards.ConclusionWe highlight the role of more responsive social agents and their representative institutions, including the changing role of university-based research and practice for working towards sustainable landscape outcomes.

Optimal design and experimental validation of emulsified cosmetic products: A multiscale approach

There is an increasing demand for sustainable and cost-effective chemical products, such as eco-friendly emulsified products, contributing to a resource-efficient economy and a reduction in our ecological footprint. This new paradigm challenges the chemical industry due to a lack of accurate predictive models and understanding of emulsified systems. This study presents an optimization strategy to design cosmetic emulsions through a multiscale approach, which represents an opportunity to boost and improve the design of these products. The study employs a model-based design approach considering operating conditions, product formulation, economic performance, consumer preference, and the emulsions properties at different scales. At the macroscopic scale, rheological and textural properties are considered and coupled with a Population Balance Model, which estimates the drop size distribution (i.e., microscopic scale). The optimal emulsion formulation is established for consumer preference and product profit maximization scenarios. According to the economic model, a higher level of consumer preference is expected to lead to increased product sales. However, the results also indicate that consumer preference maximization may not necessarily correlate with higher profits. Thus, the profit maximization scenario offers a better balance between consumer preference and economic performance. Also, experimental validation was performed for the product properties and operating conditions.

Genetic structuring and species boundaries in the Atlantic stony coral Favia (Scleractinia, Faviidae)

AbstractScleractinian corals are the main modern builders of coral reefs, which are major hot spots of marine biodiversity. Southern Atlantic reef corals are understudied compared to their Caribbean and Indo‐Pacific counterparts and many hypotheses about their population dynamics demand further testing. We employed thousands of single nucleotide polymorphisms (SNPs) recovered via ezRAD to characterize genetic population structuring and species boundaries in the amphi‐Atlantic hard coral genus Favia. Coalescent‐based species delimitation (BFD* – Bayes Factor Delimitation) recovered F. fragum and F. gravida as separate species. Although our results agree with depth‐related genetic structuring in F. fragum, they did not support incipient speciation of the ‘tall’ and ‘short’ morphotypes. The preferred scenario also revealed a split between two main lineages of F. gravida, one from Ascension Island and the other from Brazil. The Brazilian lineage is further divided into a species that occurs throughout the Northeastern coast and another that ranges from the Abrolhos Archipelago to the state of Espírito Santo. BFD* scenarios were corroborated by analyses of SNP matrices with varying levels of missing data and by a speciation‐based delimitation approach (DELINEATE). Our results challenge current notions about Atlantic reef corals because they uncovered surprising genetic diversity in Favia and rejected the long‐standing hypothesis that Abrolhos Archipelago may have served as a Pleistocenic refuge during the last glaciations.

Improving agricultural sustainability through farm mergers: an energy efficiency perspective

ABSTRACT The aim of this paper is to investigate agricultural sustainability as a collective issue involving multiple rather than individual farms. Through the utilization of energy consumption as a proxy, we propose a novel methodology that evaluates the impact of farm consolidations on agricultural sustainability while accounting for resource preferences. Our approach incorporates the ordered weighted averaging (OWA) operator within an inverse data envelopment analysis (IDEA) model to identify post-merger farms that meet preset efficiency targets. We employ a DEA cross-efficiency (DEA-CE) procedure to select merger plans that maximize agricultural sustainability for each preference scenario. By analysing a case study of 43 tomato greenhouse farms in Biskra, northern Algeria, our findings demonstrate that mergers can significantly enhance agricultural sustainability, surpassing the potential of individual farms by a factor of over 15. Additionally, the adoption of the most sustainable merger plan can lead to energy savings of more than 69%. Irrespective of the preference scenario, substantial energy savings in machinery, fertilizers, diesel, and electricity ranging from 22.92% to 73.73% were observed. These results emphasize the strategic role of merger processes in promoting agricultural sustainability and optimizing resource utilization.