Search Results (799)

This study conducts a bibliometric and content analysis based on publications indexed in the Web of Science Core Collection, aiming to map the evolution and key themes in horticultural research in the context of technological innovation and sustainability. The results reveal a strong orientation toward digitalization and automation, particularly through the integration of artificial intelligence, mechatronic systems, and sensor-based monitoring in crop management. In the field of biotechnology, keywords such as gene expression, genetic diversity, and micropropagation reflect a sustained research interest in improving crop resilience and disease resistance through genetic and in vitro propagation techniques. Furthermore, concepts such as environmental control, soilless culture, energy efficiency, and co-generation highlight the focus on optimizing growing conditions and integrating renewable energy sources into protected horticultural systems. The geographical distribution of studies highlights increased academic output in countries like India and regions of sub-Saharan Africa, reflecting a global interest in transferring advanced technologies to vulnerable areas. Moreover, collaboration networks are dominated by leading institutions such as Wageningen University, which act as hubs for knowledge diffusion. The findings suggest that future research should prioritize the development of durable, energy-efficient horticultural technologies adapted to various agro-climatic zones. It is recommended that policymakers and stakeholders support interdisciplinary research initiatives, promote knowledge transfer mechanisms, and ensure equitable access to innovation for smallholder farmers and emerging economies. Full article

Due to the limitations of pure electric power endurance, turbo-electric hybrid power systems, which offer a high power-to-weight ratio, present a reliable solution for medium- and large-sized vertical take-off and landing (VTOL) aircraft. Traditional energy management strategies often fail to minimize fuel consumption across the entire flight profile while meeting power demands under varying flight conditions. To address this issue, this paper proposes a deep reinforcement learning (DRL)-based energy management strategy (EMS) specifically designed for turbo-electric hybrid propulsion systems. Firstly, the proposed strategy employs a Prior Knowledge-Guided Deep Reinforcement Learning (PKGDRL) method, which integrates domain-specific knowledge into the Deep Deterministic Policy Gradient (DDPG) algorithm to improve learning efficiency and enhance fuel economy. Then, by narrowing the exploration space, the PKGDRL method accelerates convergence and achieves superior fuel and energy efficiency. Simulation results show that PKGDRL has a strong generalization capability in all operating conditions, with a fuel economy difference of only 1.6% from the offline benchmark of the optimization algorithm, and in addition, the PKG module enables the DRL method to achieve a huge improvement in terms of fuel economy and convergence rate. In particular, the prospect theory (PT) in the PKG module improves fuel economy by 0.81%. Future research will explore the application of PKGDRL in the direction of real-time total power prediction and adaptive energy management under complex operating conditions to enhance the generalization capability of EMS. Full article

This research investigates the factors influencing the adoption of cross-border e-commerce (CBEC) among manufacturing micro, small, and medium enterprises (MSMEs) in Thailand by integrating the Diffusion of Innovation (DOI), Resource-Based View (RBV), and Technology–Organization–Environment (TOE) frameworks with the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. The findings reveal that knowledge of e-commerce, international marketing capabilities, and security and risk concerns are primary drivers of CBEC adoption, while socio-cultural factors and cost-related issues are secondary enablers. This study contributes to the e-commerce adoption literature by developing a context-specific, integrated conceptual framework and empirically validating the causal interrelationships among technological, organizational, and environmental factors in CBEC adoption using Fuzzy DEMATEL. The results provide actionable insights for both MSMEs and policymakers to strengthen Thailand’s participation in the digital economy and advance Sustainable Development Goals (SDGs) 8 and 17. Full article

Currently, increasing anthropogenic pressure and overexploitation expose soils to various forms of degradation, including contamination, erosion, and sealing. Soil contamination, primarily caused by industrial processes, agricultural practices (such as the use of pesticides and fertilizers), and improper waste disposal, poses significant risks to human health, biodiversity, and the environment. Common contaminants include heavy metals, mineral oils, petroleum-based hydrocarbons, aromatic hydrocarbons, chlorinated hydrocarbons, and polycyclic aromatic hydrocarbons. Remediation methods for contaminated soils include physical, physicochemical, chemical or biological approaches. This review aims to specify these methods while comparing their effectiveness and applicability in different contamination scenarios. Biochemical methods, particularly phytoremediation, are emphasized for their sustainability, effectiveness, and suitability in arid and semiarid regions. These methods preserve soil quality and promote resource efficiency, waste reduction, and bioenergy production, aligning with sustainability principles and contributing to a circular economy. The integrated phytoremediation–bioenergy approaches reviewed provide sustainable and cost-efficient strategies for environmental decontamination and green development. Special attention is given to the use of lignin in bioremediation. This work contributes to the existing knowledge by outlining priorities for the selection of the most appropriate remediation techniques under diverse environmental conditions, providing a comprehensive overview for future developments. Full article

This article proposes a conversation on the limits and possibilities of collectivizing the way in which we generate and inscribe knowledge within the terms of a political economy of knowledge production and circulation regulated by hierarchies of academic and non-academic classifications, as well as those that demarcate centres and peripheries domestically and internationally through racial–gendered distributions of authority. To this end, it explores a series of collective projects elaborated within the GlobalGRACE network in Brazil (Global Gender and Cultures of Equality), which experiment with residency methodologies designed to create the necessary infrastructure for a redistribution of power, knowledge, and authority in investigations on racial–gendered violence in the peripheries of Rio de Janeiro. As collaborators in this research–action project initiated in 2018 with the Observatory of Favelas of Rio de Janeiro, here, we mobilize two of these collective projects as case studies—the dance residency of Cia Passinho Carioca and the Free School of Arts ELÃ residency—so as to reflect on our ways of knowing and experiencing racial–gendered inequalities in context. In this way, it becomes possible to propose not only questions around the production, erasure, and appropriation of knowledge but also possibilities for the broad-based circulation of dissident knowledge practices and the subsequent displacement of established authorities in the field, notably by means of a disobjectification of subjects of knowledge and exercises in authoring in the first-person plural. This entry point into the conversation on who has the power to know and control the meanings of intersectional inequalities enables a focus on practice, pedagogy, and methods to unpack the ethical and epistemological questions at hand. By centring the problem of authorship, we argue that feminist and decolonial approaches to knowing, teaching, and learning need to effectuate redistributions of power and the construction of politico-epistemic infrastructure if we have any chance of cultivating the conditions needed for liberatory knowledge practices. Full article

This paper aims to define a model for measuring the localness of a company in an innovative and reliable way, motivated by the growing consumer interest in purchasing local products and supporting local economies. The proposed Expenses Localness Indicators (ELI) model uses existing data from information systems to define Localness Indicators, and incorporates Localness Levels based on geographic and economic criteria. It can be applied to any type of financial entity and overcomes the difficulty of defining localness in e-commerce companies or digital businesses in general. Previous studies have examined the impact of localness and investigated its effectiveness as a branding strategy for managers, mainly through product traceability. The ELI model uses as data the expenses of a company paid to other financial entities. The Expenses Localness Indicators are determined based on the distribution of these payments combined with the localness of the paid financial entities. These Indicators represent the degree of localness as a percentage, ranging from 0% (non-local) to 100% (fully local), and may vary over time. The results of the presented examples indicate that a company’s localness increases as it spends more of its expenses on local financial entities and vice versa. Specific strategies have been tested using synthetic data that demonstrate the correct functioning of the model’s indicators. The ELI model could be used to provide reliable and certifiable information to consumers who want to know where their money goes when they buy products. Implementing the proposed model on a large scale would require acceptance by as many companies and states as possible. However, by making the necessary adjustments, the model could be applied on a smaller scale, supported by consumers and local governments interested in uncovering knowledge about localness. It could also be established as a valid indicator of localness to provide information that researchers, government agencies and professionals can use to promote local entrepreneurship. Full article

Anti-money laundering (AML) systems are important for protecting the global economy. However, conventional rule-based methods rely on domain knowledge, leading to suboptimal accuracy and a lack of scalability. Graph neural networks (GNNs) for digraphs (directed graphs) can be applied to transaction graphs and capture suspicious transactions or accounts. However, most spectral GNNs do not naturally support multi-dimensional edge features, lack interpretability due to edge modifications, and have limited scalability owing to their spectral nature. Conversely, most spatial methods may not capture the money flow well. Therefore, in this work, we propose LineMVGNN (Line-Graph-Assisted Multi-View Graph Neural Network), a novel spatial method that considers payment and receipt transactions. Specifically, the LineMVGNN model extends a lightweight MVGNN module, which performs two-way message passing between nodes in a transaction graph. Additionally, LineMVGNN incorporates a line graph view of the original transaction graph to enhance the propagation of transaction information. We conduct experiments on two real-world account-based transaction datasets: the Ethereum phishing transaction network dataset and a financial payment transaction dataset from one of our industry partners. The results show that our proposed method outperforms state-of-the-art methods, reflecting the effectiveness of money laundering detection with line-graph-assisted multi-view graph learning. We also discuss scalability, adversarial robustness, and regulatory considerations of our proposed method. Full article

One of the foremost challenges in today’s global economy is ensuring energy security for individual countries and regions. In the contemporary context, this security plays a pivotal role in ensuring sovereignty, fostering innovation, and bolstering competitiveness, particularly in knowledge-based economies. The pursuit of energy independence while mitigating adverse environmental impacts stands as a key priority in European Union policy. Efforts towards achieving a zero-carbon economy encompass all member states, including those in Central and Eastern Europe (CEE). This paper delves into this pressing issue by evaluating the sustainable energy security and policy efficiency of CEE countries over a 15-year period. This research employed a well-defined methodology, employing a multidimensional approach to address the complexity of the issue. The outcome of this approach was the development of the Sustainable Energy Security Index (SESI) for the countries under study, serving as a benchmark for evaluating energy security and policy effectiveness. Multiple Multi-Criteria Decision-Making (MCDM) methods, including COPRAS, EDAS, MAIRCA, and the Hurwicz criterion, were utilized to determine the SESI value. Additionally, CRITIC, equal weights, standard deviation methods, and Laplace’s criterion were employed to ascertain the weights of the indices characterizing various dimensions of sustainable energy security. The findings reveal significant disparities in energy security and policy implementation effectiveness among CEE countries. Slovenia, Croatia, Latvia, Romania, and Hungary demonstrated notably strong performance, while Poland and Bulgaria lagged behind. These results underscore the necessity of integrating findings into the energy and climate strategies of both CEE countries and the EU-27 as a whole. Full article

Agriculture is central to Nepal’s economy but faces growing challenges such as environmental degradation, labor shortages, and the increasing feminization of farming due to male outmigration. Environmental Conservation Agriculture (ECA) offers a sustainable solution, yet adoption remains inconsistent due to knowledge gaps and resource constraints. This study examines the socio-demographic, economic, and environmental factors influencing the farmers’ willingness to learn about ECA and its relationship with women’s empowerment. A cross-sectional survey of 383 ECA farmers across the Kavre, Dhading, and Chitwan districts in Bagmati Province reveals that 72.6% are willing to learn about ECA, driven by climate change concerns, economic incentives, and market access. Farmers who have experienced climate-related crop losses (64%) and those engaged in consumer-driven markets (59%) show a greater inclination to learn ECA. Spearman correlation analysis highlights key factors influencing willingness to learn, including perceptions of ECA as a climate-resilient practice, interest in ECA, and awareness of FAO’s promotion of ECA. Farmers who believe that ECA enhances sustainability, resilience, and income are also more likely to engage, while market dissatisfaction presents a challenge. Receiving ECA subsidies is positively associated with willingness to learn, highlighting the role of financial support in adoption. Women play a crucial role in agriculture but face barriers such as household responsibilities (22%), lack of education and training (18%), and limited financial access (12%). Key motivators for their participation include capacity-building initiatives (48%), financial support (16%), and empowerment programs (5%). Notably, households where women participate in early decision-making are 19% more likely to express willingness to learn about ECA, and perceptions of ECA as empowering women are positively linked to willingness to learn. Addressing these barriers through targeted policies, institutional support, and market-based incentives is essential for fostering inclusive and sustainable agricultural development. This study provides actionable insights for strengthening ECA adoption, promoting gender equity, and enhancing Nepal’s climate resilience. Full article

Although the circular economy (CE) has emerged as an innovative approach to address the challenges of protecting natural resources, the use of its strategies remains in its infancy, particularly in West Africa. This study examines the factors influencing the use of CE strategies in the wood and forestry sector in Benin. This study relied on a methodological approach based on surveys, using interview guides to collect information in both the southern and northern zones of the country. This information was collected at the level of the different actors directly involved in this sector, to identify the factors that influence the use of CE strategies using Probit models. The results show that access to information, the number of years of professional experience, the age of the actors and the type of training received are the determining factors in the use of these strategies (the models statistically significant at the 1% level). Other factors, such as knowledge of the costs and benefits of different strategies, are also identified as fundamental. Furthermore, a high financial capacity and an excess or overload of information are identified as the limiting factors for the use of these strategies. Full article

Science, technology, engineering, and mathematics (STEM) are crucial for economic development and play a significant role in achieving sustainable development goals. Despite this, there is a shortage of skilled STEM professionals and a declining interest in STEM education and careers. The Saudi Vision 2030 goal of economic diversification and sustainable development aims to transform Saudi Arabia into a knowledge-based economy driven by innovation and sustainability. This study investigates factors influencing adolescents’ attitudes toward STEM careers in Saudi Arabia, with comparative insights from Bahrain and Singapore. Structural equation models (SEM) were constructed for each country to analyze the influence of scientific self-concept, school belonging, and teacher effectiveness on students’ choices of science careers. Mediation analysis examined the interest and value of science as mediators in these relationships. Confirmatory factor analysis was conducted to validate model constructs before building SEM models. Data from TIMSS 2019 for eighth-grade students was used to develop model constructs based on relevant items from the student questionnaire. Findings reveal that students’ interest in and value of science significantly influence career decisions, with self-concept and teacher engagement playing crucial roles. Teacher effectiveness had the strongest impact on science interest in Saudi Arabia and Bahrain, while self-concept was most influential in Singapore. These results highlight the importance of fostering teacher engagement and self-concept to encourage students’ career paths in science. To support this, Saudi Arabia should enhance teacher training programs by integrating mentorship, active learning strategies, and technology driven instruction to improve student engagement. Adopting Singapore’s blended learning model can foster self-confidence and independence in STEM education, while hands-on learning and career exposure programs can strengthen students’ self-concept and long-term commitment to STEM fields. Additionally, expanding extracurricular STEM initiatives and industry partnerships will help connect classroom learning to real-world applications. By aligning STEM education reforms with these insights, Saudi Arabia can cultivate a skilled workforce that supports its economic transformation under Vision 2030. Full article

Analysis of publication intensity is an important tool for following research trends. Recent studies have recorded a decrease in the number of Polish publications on the topics of “economy” and “energy”, while global trends showed an increase in the number of publications. The present study undertakes a review of research on the topic of “education” (Sustainable Development Goal 4, SDG 4) based on the number of scientific publications in the Scopus database from 2017 to 2024. The objective of the review was to examine whether a discernible decline in the number of publications by Polish researchers in the field of education research has indeed occurred since 2021. Eight research hypotheses were proposed and tested. The following methods were used: graphical interpretation of 1,116,101 search results from scientific sources, scientometric and correlation analyses, and an analysis of the top 10 most cited publications on this topic, both in Poland and globally. The scientific contribution of this study is in testing and evaluating the hypotheses: the first, the third, the fourth, the fifth, the sixth, and the eighth hypotheses were rejected; the second and the seventh hypotheses were accepted. For the first time, the data obtained confirmed a serious problem in Polish science: since 2021, Poland’s position in the global scientific research market has been declining. The review showed the most popular branches of research in Poland and in the world. These are studies on the use of artificial intelligence, which corresponds to the sixth technological paradigm. The review also showed some differences in Polish specifics and global trends. The practical value lies in managerial recommendations for the Polish Government aimed at improving research on SDG 4. The knowledge gained advances modern knowledge about the management of education research in the context of SDG 4. This review is an important contribution to further research on the sustainability of education worldwide. Full article

Environmental pollution and the accumulation of industrial waste are increasingly serious issues that impose financial burdens on businesses and pose threats to ecosystems. As industrial production continues to grow, the volume of waste generated by humanity is rising, leading to a heightened need to search for effective waste management and recycling methods. One promising approach is the concept of a circular economy, where industrial waste, including agricultural and food processing waste, is transformed into new products. The goal is to maximize the utilization of natural resources, particularly in food production. This article presents various concepts for utilizing specific types of plant-based waste, particularly lignocellulosic, pectin, and starch wastes, in biotechnological processes aimed at producing value-added food ingredients with a technological function. The literature clearly shows that this waste can be effectively used in the cultivation of different microorganisms to produce enzymes, polyols, oligosaccharides, carboxylic acids, and biopolymers, among other products. However, further research is needed to explore more efficient and environmentally friendly methods, especially in the utilization of lignocellulose in biotechnology. This research shows knowledge gaps in existing discussed solutions. Full article

Municipal solid waste management (MSWM) is an advantageous subject for implementing circular economy (CE) strategies. In this context, the waste generation and waste collection steps of MSWM in the third largest Greek city (Patras), in western Greece, were evaluated according to the proposed CE indicators. Public opinion and knowledge on CE in MSWM were also evaluated in a small sample of citizens from the Municipality of Patras (207 individuals) through a questionnaire survey. Results showed that (a) the CE performance indicators objectively assessed circularity in MSWM; (b) Patras fared better than Greece and EU in some indicators [waste generation (kg per capita × year), food waste generation (kg per capita × year)] and worse in others [food waste composting (% w/w), WEEE recycling (kg per capita × year)]; (c) citizens have not adopted CE practices in their waste management; and (d) there is a clear reluctance to change practices in older individuals. Based on these results, some recommendations for improvement were made. These results may aid in delineating existing conditions in MSWM in large eastern Mediterranean cities and contribute to the transition toward a reduction in waste disposal and an increase in material reuse. Full article

The plastic manufacturing industry has a crucial role in the global economy with a significant impact in a wide range of fields. The chemical risk to which workers are potentially exposed is difficult to characterize and strictly related to both the products and processes adopted. Among the chemicals used, we can cite styrene, phenol, butadiene and phthalates, but nano- and microplastic particles can also be released in the work environment. In this pilot study, we present for the first time an NMR-based metabolomic approach for assessing urinary profiles of workers employed in a plastic manufacturing company. Urine samples from twelve workers and thirteen healthy volunteers were collected and analyzed by NMR spectroscopy. Forty-six urinary metabolites belonging to different chemical classes were univocally identified and quantified. The dataset so obtained was then subjected to multivariate statistical analysis to characterize each profile and highlight any differences. An alteration in some metabolites involved in several pathways, such as amino acid metabolism and NAD metabolism, was found, and a strong impact on gut microflora was also speculated. Ultimately, our work has the objective of adding a tile to the knowledge of biological effects possibly related to occupational exposure even if it is below the threshold limit values. Full article