Efficient Resource Research Articles

Pathway Selection for Enhancing the Efficiency of Psychological Crisis Intervention Resource Integration during Major Emergencies: Evidence from China

In major emergencies, psychological crisis intervention plays a critical role in safeguarding public mental health and supporting post-disaster recovery. However, uneven resource allocation underscores the urgent need for more efficient resource integration pathways. This study, based on data from Chinese governmental and health departmental reports in 2022, employs a Data Envelopment Analysis (DEA) and a fuzzy-set Qualitative Comparative Analysis (fsQCA) to evaluate the efficiency of psychological crisis intervention resource integration across various regions. It investigates the combined effects of internal and external factors on improving integration efficiency through a configurational approach. The findings reveal that while the overall efficiency of resource integration is relatively high, there are notable differences between institutions. The analysis identifies five key pathways: policy support-driven (H1), professional capability-driven (H2), comprehensive synergy-driven (H3), resource optimization (NH1), and community empowerment (NH2). Despite regional disparities, effectively integrating key resources can enhance overall efficiency. Coordinating internal and external factors and optimizing essential resources are crucial for improving the effectiveness of psychological crisis interventions. This research offers actionable insights into integration strategies to strengthen psychological crisis intervention during emergencies. The findings also provide practical solutions to improve disaster preparedness and intervention efficiency, addressing a key gap in crisis resource management research.

경합에서 외부성의 경로에 대한 소고

Many economic, political and social interactions can be modeled as a contest in which participants expend resources to win prizes. The theory of contest examines the effect of such contests on resource allocation, efficiency and social welfare. Many contests are associated with externality. The received literature has identified the size of prize, cost and the number of participants as channels through which externality is realized. This note classifies the channels of externality in contests in the received literature. This note then suggests the winning probability and the diffusion of contests as new channels of externality in contests. Specifically, the present note emphasizes the negative effect on social welfare of diffusion of rent-seeking activities.

Transfusion burden and willingness to pay for temporary alleviation of anemia status in transfusion-dependent beta-thalassemia patients in China

BackgroundTransfusion-dependent β-thalassemia (TDT) is one of the global public health concerns highlighted by the World Health Organization. Patients with TDT require regular blood transfusion to survive. However, the availability of blood resources is extremely limited. The purpose of this study was to investigate transfusion burden and willingness to pay (WTP) for temporary remission of anemia status among patients with TDT and to explore the associated factors.MethodsAdult patients with TDT were recruited through cluster sampling across several high-incidence provinces in China. Consenting patients completed online questionnaires on demographic information, transfusion burden and WTP with real-time WeChat communication assistance from researchers. The guiding techniques of double-bounded dichotomous choices and open-ended questions in the contingent valuation method (CVM) were used to obtain participants’ WTP for 1 unit of leukocyte-depleted red blood cells. WTP calculations were performed using maximum likelihood estimation, with further insights gained through subgroup analysis based on gender, family monthly income level and convenience of blood transfusion.ResultsThe analysis included 149 TDT patients from five high-incidence provinces, with an average monthly income of $198.5. Patients received an average of 3.7 units per transfusion, 15.4 times annually, with an average WTP of $70.4 per unit (95% CI [62.0, 78.9]). Estimated WTP for temporary anemia alleviation per transfusion totaled $260.6, exceeding monthly income by 1.32 times. Higher WTP was observed among males, higher-income households, and those with at least junior education. Lower WTP was noted among patients with lower transfusion volumes and those needing to travel for transfusion or during hospitalization for blood transfusion.ConclusionHigh WTP indicated a strong desire for temporary anemia relief. Most TDT patients faced significant economic and transfusion burden. The evident gap in meeting clinical needed underscores the urgent demand for innovative treatments to reduce transfusion dependency, potentially transforming TDT care and improving socioeconomic well-being and clinical outcomes. These findings supported evidence-based decision-making for TDT pharmacoeconomics and efficient healthcare resource allocation in China.

Simplified efficiency calibration methods for scintillation detectors used in nuclear remediation

Our study introduces innovative methods to address waste reduction and enhance resource efficiency in nuclear cleanup processes. We focus on sustainable nuclear technology, aligning with goals for cleaner production and environmental protection. We developed two novel methods, termed “oversimplified” and “simplified,” for easily determining the photopeak efficiency of NaI(Tl) scintillation detectors. These methods, along with a “general” solution method, were validated with calibrated radioactive sources such as 241Am, 57Co, 133Ba, 137Cs, and 60Co, and were used to commission a NaI(Tl) scintillation detector system at Chalk River Laboratories (CRL) for nuclear remediation. The system demonstrated high accuracy, making it suitable for screening unstable isotopes at contaminated sites. This screening tool significantly reduces the number of soil samples requiring detailed characterization, thereby lowering operational costs. The NaI(Tl) detector system was calibrated for near-contact geometry, which is commonly used at CRLs. Detection limits were established for this configuration. By improving the efficiency calibration of scintillation detectors, our study advances sustainable nuclear remediation practices, promoting environmental sustainability and cleaner production processes.

Predicting future hospital antimicrobial resistance prevalence using machine learning

BackgroundPredicting antimicrobial resistance (AMR), a top global health threat, nationwide at an aggregate hospital level could help target interventions. Using machine learning, we exploit historical AMR and antimicrobial usage to predict future AMR.MethodsAntimicrobial use and AMR prevalence in bloodstream infections in hospitals in England were obtained per hospital group (Trust) and financial year (FY, April–March) for 22 pathogen–antibiotic combinations (FY2016-2017 to FY2021-2022). Extreme Gradient Boosting (XGBoost) model predictions were compared to the previous value taken forwards, the difference between the previous two years taken forwards and linear trend forecasting (LTF). XGBoost feature importances were calculated to aid interpretability.ResultsHere we show that XGBoost models achieve the best predictive performance. Relatively limited year-to-year variability in AMR prevalence within Trust–pathogen–antibiotic combinations means previous value taken forwards also achieves a low mean absolute error (MAE), similar to or slightly higher than XGBoost. Using the difference between the previous two years taken forward or LTF performs consistently worse. XGBoost considerably outperforms all other methods in Trusts with a larger change in AMR prevalence from FY2020-2021 (last training year) to FY2021-2022 (held-out test set). Feature importance values indicate that besides historical resistance to the same pathogen–antibiotic combination as the outcome, complex relationships between resistance in different pathogens to the same antibiotic/antibiotic class and usage are exploited for predictions. These are generally among the top ten features ranked according to their mean absolute SHAP values.ConclusionsYear-to-year resistance has generally changed little within Trust–pathogen–antibiotic combinations. In those with larger changes, XGBoost models can improve predictions, enabling informed decisions, efficient resource allocation, and targeted interventions.

Investigating the physical characteristics and antibacterial properties of the cork back from Quercus variabilis

This study presents for the first time results on structure feature, basic physical properties, torrefaction treatment, adsorption property, component content and antimicrobial properties of the cork back from Quercus variabilis. The cork back consisted of numerous white stone cell bundles with a dense and firm texture and irregularly shaped cells exhibiting considerable deformation and wrinkles. The cork back had the average density of 0.37 g/cm3, average hardness of 91.60 HA and the average thickness was 31.44 % of the total cork thickness. The average colorimetric parameters values of L*, a*, and b* of the cork back were 21.92, 2.34, and 6.42, respectively. Increasing torrefaction temperature increased the quality loss of the cork back, decreased energy yield and volatile matter content, and increased ash and fixed carbon content. With the elevation of fixed carbon, the higher calorific value of the cork back also increased. Following high-temperature torrefaction at 300 °C, the higher calorific value of cork back was 24.00 MJ/kg which increased by 30.29 % compared to untreated cork back. The cork back powder had significant adsorption performance for methylene blue and the maximum adsorption capacity could reach 511.61 mg/g. Compared with cork，the cork back had a high content of lignin and polysaccharides, with a suberin content of only 4.07 %. The total extractives content in cork back was 7.49 %. The water extractives of the cork back exhibited the most significant inhibitory effect on Escherichia coli, with the lowest inhibitory concentration recorded at 2 mg/mL. This research offers essential data for the processing and utilization of the cork back, which contributes to enhance the utilizing efficiency of cork resources.

Preparation of the sandwiched PS-SiO2-PVAc-SiO2 electrospinning fiber membrane with super-hydrophobic and self-cleaning and its performance in oil-water emulsion separation

Oil-water emulsion separation could improve the efficiency of oil resources and reduce environmental pollution. The efficiency of oil-water separation was directly affected by the surface hydrophobicity of the membrane and its reliability and reusability. Therefore, the construction of a reliable and reusable super-hydrophobic surface was very important. In this research, the EFM with sandwich structure of PS-SiO2-PVAc-SiO2 was easily fabricated by a three times liquid phase induction process and heat treatment. The PS-SiO2-PVAc-SiO2 EFM was first formed by a triple liquid phase induction process, then the EFM was heat-treated, the PVAc, which is a heat-sensitive material, resulting in SiO2 nanoparticles being welded onto PS fibers. The rolling contact angle experiment at an inclination of 8° proved that the PS-SiO2-PVAc-SiO2 EFM has super-hydrophobic properties. Meanwhile, the PS-SiO2-PVAc-SiO2 EFM showed excellent stability and reliability of super-hydrophobic properties after the EFM was washed or taped. In addition, the PS-SiO2-PVAc-SiO2 EFM had self-cleaning function and fine oil-water separation property. The oil-water separation efficiency was over 99.50 % and the flow rate was 68 L/m2h. After 5 times of oil-water separation, the flux and separation efficiency did not decrease significantly, which proved that the PS-SiO2-PVAc-SiO2 EFM could be reusable.

Public deliberation to assess patient views on biosimilar medication switching for the treatment of inflammatory bowel disease

BackgroundBiosimilars are highly similar, but not identical, versions of originator biologic medications. Switching patients to biosimilars presents an opportunity to mitigate rising drug costs and expand patient access to important biologic therapies. However, decreased patient acceptance and adherence to biosimilar medications have been reported, which can lead to loss of treatment response, adverse reactions, and inefficient resource utilization. Understanding patient perceptions of biosimilars and biosimilar switching is needed to inform patient-centered care strategies that promote efficient resource utilization.MethodsWe used democratic deliberation methods to solicit the informed and considered opinions of patients regarding biosimilar switching. Patients with inflammatory bowel disease (IBD; n = 29) from the Veterans Health Administration (VHA) participated in 5-hour deliberation sessions over two days. Following educational presentations with experts, participants engaged in facilitated small group discussions. Transcripts and facilitators’ notes were used to identify key themes. Participants completed surveys pre- and post-deliberation to collect sociodemographic and clinical features as well as to assess IBD treatment knowledge and attitudes toward care and approaches to biosimilar switching.ResultsFive major themes emerged from the small group discussions in the context of biosimilar switching: 1) concerns about adverse consequences and unclear risk-benefit balance; (2) importance of communication and transparency; (3) desire for shared decision making and patient involvement in treatment decisions; (4) balancing cost-saving with competing priorities; and (5) advocating for individualized care and prioritization based on risk levels. These views led participants to favor approaches that prioritize switching the sickest patients last (i.e., those with poorly controlled disease) and that offer patients control and choices around biosimilar switching. Participants also expressed preferences for combining elements of different approaches to maximize fairness.ConclusionsApproaches to biosimilar switching should consider patients’ desires for transparency and effective communication about biosimilar switching and engagement in their medical decision-making as part of patient-centered care. Incorporating patient preferences around biosimilar switching is critical when navigating the quality and affordability of care in resource constrained settings, both within the VHA and in other healthcare systems.

Mega corruptions in mega projects: Debating the dynamics of dam construction in Ethiopia

Background This study critically examines the dynamics of corruption within Ethiopia’s dam construction projects, focusing on the Grand Ethiopian Renaissance Dam (GERD the Gilgel Gibe series, and Genale Dawa. The research highlights how weak management practices, insufficient oversight, and centralized decision-making, resulting in contribute to inflated costs, project delays, and compromised construction quality. A comprehensive understanding of these issues is crucial for addressing the challenges that impede Ethiopia’s infrastructure development. Methods A qualitative research approach was employed, integrating both primary and secondary data sources. The study utilized four theoretical frameworks—Principal-Agent Theory, Rent-Seeking Theory, Institutional Theory, and Neo-Patrimonialism—to analyze the structural and behavioral factors enabling corruption in Ethiopia’s dam construction projects. Results The study found that corruption is largely driven by weak management practices, insufficient oversight, and centralized decision-making. These factors contribute to inflated project costs, significant delays, and compromised construction quality. The lack of transparency and inadequate monitoring exacerbate these issues, leading to inefficient resource use and undermining the projects’ intended benefits. Economic impacts include increased public debt and strained financial resources. Socially, corruption erodes public trust and adversely affects the communities involved. The findings also highlight how information asymmetry and misaligned incentives contribute to corruption, with weak governance structures and informal networks further exacerbating the problem. These issues lead to cost overruns, increased debt, and diminished public confidence, which negatively impacts development outcomes. Conclusions While corruption in Ethiopia’s dam construction projects poses significant challenges, it is not insurmountable. Strengthening legal and regulatory frameworks, enhancing institutional capacity, promoting community participation, and leveraging international cooperation are crucial for mitigating these risks. Recommendations include implementing e-procurement systems, establishing independent oversight bodies, and promoting transparency to ensure these mega projects achieve their intended economic and social benefits.

Predicting potential biomass production by geospatial modelling: The case study of citrus in a Mediterranean area

Residual biomass from agricultural production and processing, such as citrus pulp and olive pomace, is an important resource for energy production. In particular, this is the case in regions where transformation industries are concentrated.Current biomass estimates often focus on actual production data, that may not fully capture the biomass potential across all suitable cultivation areas. To bridge this gap, the study predicts the overall potential biomass available for energy production, taking into account the total area suitable for citrus cultivation.The research is focused on the study of citrus species in the province of Syracuse, Sicily, Italy. The methodology combines Geographic Information System (GIS) tools, for data interpolation and map overlays, with Software for Assisted Habitat Modelling (SAHM) for local level simulations.The results of the different models showed accurate and spatially coherent predictions, with AUC values ranging from 0.85 to 0.90, and highest potentialities in the northern and eastern regions of the study area. The results highlighted potential citrus cultivation on 47,706 ha and estimated 184,340 t of biomass, 16,461,520.82 Nm3 of biogas, and 8110 t of digestate. The results of the study identified potential areas for both increasing biomass production and optimising the distribution of digestate, thus demonstrating the utility of these thematic maps as a decision support tool for land management. The simulations and the methodology applied in this study indicated potential economic and environmental benefits to be gained from sustainable by-product management. This approach facilitates the optimisation of decision-making processes for land planning, thereby contributing to the broader objective of improving resource efficiency and sustainability in the agricultural production and processing sectors.

Insects as Sustainable Feed: Enhancing Animal Nutrition and Reducing Livestock Environmental Impression.

Insects are emerging as a promising alternative source in animal nutrition, offering high protein content and a low environmental impression compared to traditional feed sources. This abstract explores the potential role of insects in reducing the environmental impact of livestock production. Insects such as black soldier fly larvae, mealworms, and crickets are rich in essential nutrients, including proteins, amino acids, fatty acids and so on. They can be efficiently farmed on organic waste streams, contributing to resource efficiency and waste lessening. Additionally, insect farming needs a small quantity of water, less land, and emits fewer greenhouse gases than conventional animal feed production. Despite these benefits, several challenges must be addressed to realize their potential, including regulatory approval, consumer acceptance, production scalability, and ensuring consistent nutritional quality. By overcoming these challenges through research, innovation, and policy support, insects can be integrated into mainstream animal feed systems, significantly reducing the environmental impact of livestock farming and contributing to a more sustainable agricultural future.

BLOCKCHAIN AND ITS APPLICATION IN THE DEFENCE SECTOR

The digital transformation of the economy affects many sectors, including the defence sector, which is sensitive from both a national and international perspective. The digitalisation of the economy is based on technologies such as robotics, autonomy, additive manufacturing technologies (3D printing), augmented reality, big data, quantum computers, artificial intelligence and blockchains. In this article, we will take a closer look at the latter, namely blockchain technology. We will briefly outline its main properties and advantages, which make it particularly attractive for use in the defence sector, and dwell on its application to implement such a tool as smart contracts. One of the key advantages of blockchain in the context of military operations is ensuring transparency and traceability of supplies. In today's realities, logistical problems can cost lives, but blockchain helps prevent fraud and improve coordination between interacting communication nodes. Thanks to the use of blockchain technologies, each unit of supply can be recorded in an immutable register, which allows you to track its path from sender to recipient. This reduces the risk of loss or theft, and simplifies the process of monitoring and verifying the accuracy of information about deliveries. In addition, the decentralised nature of the blockchain enhances the security of military communications, protecting them from interception and attack. Each message is encrypted in such a way that it can only be read by the addressee. This ensures a high level of confidentiality and data protection, as information transmitted through the blockchain is distributed among numerous network nodes, making it difficult for attackers to access. By using cryptographic methods, the blockchain ensures that even in the event of a successful attack, attackers will not be able to alter or falsify information. Creating a tamper-proof ID system will help fight counterfeiting and improve the process of identifying wounded or fallen soldiers. By assigning unique and unchangeable authenticators to personnel, equipment or weapons, one hundred per cent identification of military entities can be ensured. This allows for accurate tracking of the movement and status of each soldier and equipment, which contributes to more efficient resource management. This system also increases the level of trust in the information provided, as it is recorded in the blockchain and cannot be changed or deleted. The introduction of blockchain technology in the defence sector can bring significant benefits, including increased security, transparency and efficiency. However, this process is accompanied by numerous challenges and risks that need to be considered and overcome for successful integration.

Designing an optimal task scheduling and VM placement in the cloud environment with multi-objective constraints using Hybrid Lemurs and Gannet Optimization Algorithm

ABSTRACT An efficient resource utilization method can greatly reduce expenses and unwanted resources. Typical cloud resource planning approaches lack support for the emerging paradigm regarding asset management speed and optimization. The use of cloud computing relies heavily on task planning and allocation of resources. The task scheduling issue is more crucial in arranging and allotting application jobs supplied by customers on Virtual Machines (VM) in a specific manner. The task planning issue needs to be specifically stated to increase scheduling efficiency. The task scheduling in the cloud environment model is developed using optimization techniques. This model intends to optimize both the task scheduling and VM placement over the cloud environment. In this model, a new hybrid-meta-heuristic optimization algorithm is developed named the Hybrid Lemurs-based Gannet Optimization Algorithm (HL-GOA). The multi-objective function is considered with constraints like cost, time, resource utilization, makespan, and throughput. The proposed model is further validated and compared against existing methodologies. The total time required for scheduling and VM placement is 30.23%, 6.25%, 11.76%, and 10.44% reduced than ESO, RSO, LO, and GOA with 2 VMs. The simulation outcomes revealed that the developed model effectively resolved the scheduling and VL placement issues.

Preparation Method and Benefit Analysis for Unburned Brick Using Construction Solid Waste from Residue Soil

Highly efficient resource utilization of construction solid waste has significant environmental and socioeconomic benefits. In this study, a fabrication method and process optimization of unburned brick from construction residue soil were investigated based on experiments. The effects of cementing the material content, the raw material treatment process, the brick moisture content, and the molding method on the compressive strength of unburned brick were studied and discussed. The experimental results show that 5–20% of ordinary cement can produce a strength grade of 5 MPa–20 MPa for unburned brick, and the utilization rate of the residue soil is greater than 80%. In the case of well-dispersed residual particles, complete drying and rolling are not necessary, and soil particle size within 5 mm is beneficial for obtaining proper sand grading and low mud content, which will improve the strength of unburned brick. The pressure for the press forming of unburned brick should be 10 MPa, and the optimal moisture content of the residue-soil mixture is about 13%. The proposed residue-soil unburned brick has remarkable environmental and economic benefits with low carbon emissions, low cost, and high profit. The methods proposed and optimized in this study can provide important technical support for realizing the large-scale production of residue-soil unburned brick.

Deep Learning for Robust Facial Expression Recognition: A Resilient Defense Against Adversarial Attacks

Adversarial attacks can be extremely dangerous, particularly in scenarios where the precision of facial expression identification is of utmost importance. Hiring adversarial training methods proves effective in mitigating these threats. Although effective, this technique requires large computing resources. This study aims to strengthen deep learning model resilience against adversarial attacks while optimizing performance and resource efficiency. Our proposed method uses adversarial training techniques to create adversarial examples, which are permanently stored as a separate dataset. This strategy helps the model learn and enhances its resilience to adversarial attacks. This study also evaluates models by subjecting them to adversarial attacks, such as the One Pixel Attack and the Fast Gradient Sign Method, to identify any potential vulnerabilities. Moreover, we use two different model architectures to see how well they are protected against adversarial attacks. It compared their performances to determine the best model for making systems more resistant while still maintaining good performance. The findings show that the combination of the proposed adversarial training technique and an efficient model architecture outcome in increased resistance to adversarial attacks. This also improves the reliability of the model and saves more resources for computation. This is evidenced by the high accuracy results achieved at 98.81% accuracy on the CK+ datasets. The adversarial training technique proposed in this study offers an efficient alternative to overcome the limitations of computational resources. This fortifies the model against adversarial attacks, resulting in significant increases in model resilience without loss of performance.

Leveraging ICT and Generative AI in Higher Education for Sustainable Development: The Case of a Lebanese Private University

This study investigates the interaction of information and communication technology (ICT) and higher education in driving sustainable development, with a special emphasis on the rising significance of generative AI tools such as ChatGPT. This quantitative study, conducted in a Lebanese private university, looks into the impact of ICT, specifically generative AI, on promoting sustainability in higher education. A questionnaire was distributed to university instructors to determine how these technologies contribute to sustainable practices in academic environments. The results, which were evaluated using descriptive statistics and correlation analysis, show that ICT tools, professional instructor development, and the upkeep of educational infrastructure all contribute considerably to Lebanon’s sustainable development. Furthermore, integrating generative AI into educational processes has the potential to improve personalized learning, resource efficiency, and content production, all of which contribute to sustainability goals. The study concludes by exploring the findings’ broader implications, acknowledging their shortcomings, and suggesting future research possibilities.

Retraction Note: Energy transition and the role of circular supply chains: toward resource efficiency and sustainable economic practices

Retraction Note: Energy transition and the role of circular supply chains: toward resource efficiency and sustainable economic practices

A gender perspective on the circular economy: A literature review and research agenda

AbstractThe circular economy (CE) challenges the traditional linear economic model by emphasizing the importance of resource efficiency, recycling, and regeneration in society. However, the role of gender in CE practices remains underexplored. This article presents a systematic literature review on how gender dynamics intersect with CE, highlighting the implications of gendered labor distribution, access to resources, and decision‐making processes. Women, often pivotal in household and community resource management, are underrepresented in policy and research. Gender perspectives are therefore crucial for addressing social, environmental, and justice dimensions within CE. The study employs the lens of care labor to reveal power imbalances and the exclusion of marginalized groups, advocating for inclusive policies to achieve socially sustainable and equitable CE futures. The review identifies the overrepresentation of women in undervalued, informal activities and the dominance of men in highly valued, technologically advanced CE roles. It also underscores the benefits of gender diversity in corporate governance, which enhances sustainability practices. The article calls for a deeper examination of gender's impact on CE, suggesting a research agenda to integrate gender perspectives, enhance CE effectiveness, and promote equity. The findings indicate that addressing gender inequalities in CE is essential to prevent replicating the shortcomings of the linear economy and to foster innovative, inclusive, and sustainable development.

Bibliometric Trends and Insights into the Potential of Maize (Zea mays) under the Framework of Conservation Agriculture

In spite of the detrimental effects of climate change and decreasing resource efficiency, maize farming is essential to the world’s food and nutritional security. With regard to sustainable maize farming in this environment, conservation agriculture (CA) offers a framework that holds promise in terms of low soil disturbance, perennial soil cover, and sustainable crop rotation. In order to acquire more profound information on the research advancements and publication patterns related to maize under CA scenarios, a bibliometric analysis was conducted. This involved utilizing René Descartes’s Discourse Framework to extract and screen 2587 documents spanning the years 2001 to 2023 from the Dimensions.ai database. The mapping showed that different stakeholders were becoming more interested in maize research under various CA pathways, with a greater emphasis on reaching the second sustainable development target, or “zero hunger”. The most influential journals were “Soil and Tillage Research” and “Field Crops Research”, with 131 and 85 papers with 6861 and 6186 citations, respectively. The performance analysis found “Christian L. Thierfelder” and “Mangi Lal Jat” as the eminent researchers in the areas of maize research under CA. Thus, the International Maize and Wheat Improvement Center (CIMMYT) and the Indian Agricultural Research Institute (IARI) were identified as the important institutions in conducting research pertaining to maize under CA systems, while the United States, India, and Mexico emerged as prominent countries with notable collaboration efforts for imparting research under the given scenarios. Three thematic clusters delineating keywords from three distinct sections—key drivers, objectives, and methodology—were identified through co-word analysis using word clouds, tree maps, and thematic networking of the keywords from the abstract and titles of screened publications. These thematic clusters highlighted the growing emphasis on region-specific studies under CA, particularly in sub-Saharan Africa and the Indo-Gangetic plain, to enhance the resilience of the agri-food system. Therefore, mapping maize’s potentialities within the CA framework has revealed the field’s dynamic nature and offers insightful information to researchers and policymakers that could help them plan future studies and cooperative initiatives aimed at boosting the productivity and sustainability of maize-based systems under the CA framework.

Scenario analysis of supply‐ and demand‐side solutions for circular economy and climate change mitigation in the global building sector

AbstractResidential and non‐residential buildings are a major contributor to human well‐being. At the same time, buildings cause 30% of final energy use, 18% of greenhouse gas emissions (GHGE), and about 65% of material accumulation globally. With electrification and higher energy efficiency of buildings, material‐related emissions gain relevance. The circular economy (CE) strategies, narrow, slow, and close, together with wooden buildings, can reduce material‐related emissions. We provide a comprehensive set of building stock transformation scenarios for 10 world regions until 2060, using the resource efficiency climate change model of the stock–flow–service nexus and including the full CE spectrum plus wood‐intensive buildings. The 2020–2050 global cumulative new construction ranges from 150 to 280 billion m2 for residential and 70‐120 billion m2 for non‐residential buildings. Ambitious CE reduces cumulative 2020–2050 primary material demand from 80 to 30 gigatons (Gt) for cement and from 35 to 15 Gt for steel. Lowering floor space demand by 1 m2 per capita leads to global savings of 800‐2500 megatons (Mt) of cement, 300‐1000 Mt of steel, and 3‐10 Gt CO2‐eq, depending on industry decarbonization and CE roll‐out. Each additional Mt of structural timber leads to savings of 0.4‐0.55 Mt of cement, 0.6‐0.85 Mt of steel, and 0.8‐1.8 Mt CO2‐eq of system‐wide GHGE. CE reduces 2020–2050 cumulative GHGE by up to 44%, where the highest contribution comes from the narrow CE strategies, that is, lower floorspace and lightweight buildings. Very low carbon emission trajectories are possible only when combining supply‐ and demand‐side strategies. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges.