Search

Abstract Renewable materials and material circularity are key priorities for the coming decades. While paper is the most utilized material in the packaging sector, its applications in food packaging are limited due to low barrier properties. Coating it with petroleum-based polymer barrier coatings renders it unrecyclable both mechanically and biologically. Bio-coated paper packaging, made from agricultural waste or by-products, presents environmentally favorable solutions that can benefit the biological cycle of the circular economy. The main objective of this study is to assess the applicability of grain and beer production by-products in wood pulp food packaging materials. It examines the effects of different grain by-products (industrial wheat grain processing residues and wheat bran) particles and concentrations (15 wt% and 40 wt%), as well as the impact of brewer’s yeast (Saccharomyces cerevisiae) at a concentration of 10 wt%, on the physical–mechanical and barrier properties of Northern bleached softwood kraft (NBSK) and chemithermomechanical (CTMP) pulps. Material composites were fabricated using a standard sheet forming method. Physical–mechanical properties were analyzed through tensile strength, strain at break, tear resistance, and bending stiffness tests. Barrier-related properties were analyzed through roughness, air permeance, and water contact angle tests. Results revealed that the vast majority of physical–mechanical properties decreased with the increase of both types of grain production fillers. Industrial wheat grain processing residues had a lower impact on physical–mechanical properties than wheat bran filler. A higher percentage of property decrease was absorbed in NBSK pulp than in CTMP. Roughness of CTMP can be improved by adding both industrial wheat grain processing residues and wheat bran. Wheat bran particles can increase hydrophobicity. CTMP pulp strength properties can be increased with the addition of yeast; however, the yeast additive’s effect on air permeance demonstrated a negative impact. In the case of NBSK pulp, which has higher primary strength properties, the addition of yeast does not make any significant changes. The conducted experiments demonstrated that, overall, the addition of these fillers resulted in a decline in physical–mechanical properties such as tensile strength, strain at break, tear resistance, and bending stiffness. This decline was more pronounced with higher concentrations of fillers. In the case of CTMP pulp, both types of fillers exhibited similar trends in affecting properties, whereas for NBSK pulp, wheat bran had a more significant impact compared to wheat grain processing residues. The addition of yeast generally led to a reduction in physical–mechanical properties, particularly in tensile strength and tear resistance. However, samples containing yeast displayed increased flexibility compared to controls. The influence on barrier properties varied: while yeast increased air permeability, it also enhanced surface hydrophobicity, thereby reducing the paper’s receptivity to liquids.

Abstract Large language models (LLMs) are an exciting breakthrough in the rapidly growing field of artificial intelligence (AI), offering unparalleled potential in a variety of application domains such as finance, business, healthcare, cybersecurity, and so on. However, concerns regarding their trustworthiness and ethical implications have become increasingly prominent as these models are considered black-box and continue to progress. This position paper explores the potentiality of LLM from diverse perspectives as well as the associated risk factors with awareness. Towards this, we highlight not only the technical challenges but also the ethical implications and societal impacts associated with LLM deployment emphasizing fairness, transparency, explainability, trust and accountability. We conclude this paper by summarizing potential research scopes with direction. Overall, the purpose of this position paper is to contribute to the ongoing discussion of LLM potentiality and awareness from the perspective of trustworthiness and responsibility in AI.

Abstract Autistic individuals often experience a wide range of barriers and challenges with employment across their lifetime. Despite their strengths and abilities to contribute to the workforce, many individuals experience unemployment, underemployment and malemployment. However, current supports and services are often inadequate to meet their needs. To allow autistic people to achieve vocational success, we explore four contributors to employment and expand upon the issues and potential solutions to each. These positions include the importance of family support and its consideration in the application of vocational support interventions, addressing transitional needs for autistic youth, building employer capacity, and conducting research that advises the development of meaningful programs and policies. By advocating for these positions, we aim to foster greater inclusivity and support for individuals with ASD in the workplace.

Abstract Process industry suffers from production management in terms of efficiency promotion and waste reduction in large scale manufacturing due to poor organization of the intricate relational databases. In order to enhance the suitability of intelligent manufacturing systems in process industry, this study proposed an innovative top-down structure Knowledge Graph (KG) for process fault diagnosis, and papermaking was taken as a case study. The KG consists of a normalized seven-step-built ontology, which extracted instances of papermaking knowledge via Protégé software. The exported OWL file was imported into Neo4j software for visualization of the KG. The application in papermaking drying process for fault diagnosis shows that it can depict the material and energy flows throughout the process with a clearer relationship visualization than traditional measures. They also enable rationale search for faults and identification of their potential causes. The built KG efficiently manages the vast knowledge of the process, stores unstructured data, and promotes the intelligent development of process with high reusability and dynamicity that can rapidly import new production knowledge as well as flexibly self-updating.

Abstract This paper explores citizens’ views regarding the application of participatory communication in the delivery of development services within the decentralised government system of Ghana. The participatory theory informed the core issues of this study. Data were obtained from 309 inhabitants selected from three administrative areas in the Central Region using the quota sampling technique. Questionnaires and researcher-administered survey were used to gather data and analysed using means, standard deviations, Kruskal Wallis test, independent samples t-test, and one-way ANOVA. The study revealed that issues of empowerment were moderately applied in development services. Again, people-centred approaches to the delivery of development services were lowly considered. Overall, participatory communication principles have not received adequate attention during the delivery of development services. The situation was the same across the three-tier decentralised government system. Despite their educational differences, respondents expressed similar opinions on the application of participatory development principles. Participatory communication faced challenges like the absence of well-trained development communicators, inadequate resources, low motivation on the part of local representatives, a low sense of ownership, and an absence of clear institutional policies on communication. The paper outlines key practical implications of the findings, including the need for governments to set up the necessary institutional framework to aid the incorporation of participatory communication techniques into the development strategies of Assemblies.

Abstract This paper explores the historical context and current dynamics of the transboundary water issues between India and China. Both countries share multiple transboundary river basins, with the Brahmaputra River being one of the most significant. The importance of the Brahmaputra River to both nations goes beyond just providing resources. It has implications for national security, regional stability, and human livelihoods. However, China's upstream control over the river and its extensive dam-building projects have raised concerns in downstream India and Bangladesh about potential impacts on water availability, agriculture, and livelihoods. The river system is critical for the socioeconomic well-being of millions of people, yet the competing demands for water resources have led to geopolitical tensions. The paper highlights China's strategic use of water resources, including plans for large-scale dams, which India views as a potential threat to its water security. It also underscores the importance of a nuanced understanding of hydropolitics, emphasizing the need for human security, particularly water security, in addressing these challenges. It argues that while "water wars" are unlikely, "water tensions" are significant and must be addressed through comprehensive bilateral agreements and collaborative efforts.

Abstract This paper aims to contribute knowledge about the influences of leaders’ perceptions of digitalisation on arrangements for leading the expansion of access to and application of digital technologies in K–12 education. Supporting the digitalisation of K–12 education requires digital competence. School organisers’ and school leaders’ digital competence and perceptions of digitalisation contribute to how digital technologies are employed in schools. Survey and participant observations were used to investigate leaders’ perceptions of digitalisation in K–12 education. The data were analysed using thematic analysis and theory of practice architecture. The results show that perceptions of digitalisation in K–12 education influence arrangements by allowing opportunities for enhanced quality in teaching and equality within and among schools. Further, collaborations between leaders, sharing ideas and experiences, and enhancing leadership are elements that contribute to the shaping of leaders’ perceptions of digitalisation in schools. This paper contributes to the knowledge of leaders’ perceptions of expanding the access to and application of digital technologies in schools.

Abstract East Africa struggles with a profound challenge in ensuring food security amidst the convergence of climate change, economic crises, and conflicts. This paper presents a comprehensive review of the interconnected and compounding effects of these three factors on the region’s food security landscape. It investigates the complex ways in which shifting climatic patterns disrupt agricultural systems, exacerbating food scarcity and amplifying vulnerabilities among marginalized communities. The study also examines the intertwined impact of economic downturns, which diminish access to resources, disrupt supply chains, and deepen food insecurity. Furthermore, the paper scrutinizes the ramifications of persistent conflicts, which not only displace populations but also destabilize agricultural production, aggravating food shortages. To achieve the objective of this, review the authors have collected the relevant documents through search engines of Web of Science, Google, Google Scholar, Scopus, and Science Direct databases. This review found that climate change, economic instability, and conflict are the primary challenges to food security in East Africa. Climate change exacerbates extreme weather events, rising temperatures, and pest infestations, reducing agricultural productivity and economic growth. Economic instability stems from a lack of industrialization, dependence on foreign aid, and significant investment gaps, resulting in persistent poverty and underdevelopment. Additionally, conflict and instability disrupt agricultural activities, displace populations, and restrict access to essential resources, further aggravating food insecurity. The study emphasizes the necessity for coordinated efforts among governments, international organizations, and local communities to navigate these intersecting crises and establish sustainable pathways toward enhanced food security in the region.

Abstract In recent years, the concept of sustainable infrastructure has gained popularity and is widely utilized and promoted by the international development community. However, implementation of sustainable infrastructure remains a challenge due to various enabling and disabling factors particularly related to financial arrangements and governance modes. This paper aims to fill the research gap in this area and investigate the factors that enable implementation of sustainable infrastructure, with a focus on the financial and governance aspects. To do so, the paper uses real urban railway projects in Manila, the Philippines as case studies for comparative analysis. The results suggest that from the finance and governance perspectives, public–private partnerships (PPPs) and official development assistance (ODA) finance are effective tools for implementing sustainable infrastructure, with some conditions, namely a mixture of vertical project management and horizontal process management, and the project environments having a positive effect on the trust building and collaboration among the stakeholders.

Abstract In the last century, human activities were the primary cause of air, water, and soil contamination. However, in the twenty-first century, while pollutants like sulfur oxides (SOx) and nitrogen oxides (NOx) remain significant, microplastics (MPs) have emerged as a new global environmental concern. Microplastics are plastic fragments that are less than 5 mm in diameter. Their widespread distribution in aquatic and terrestrial ecosystems has adverse impacts on various ecological systems. The presence of MPs has been well documented in diverse matrices, such as table salt, drinking water, indoor and outdoor air, beer, cold drinks, aquatic organisms, plants, and earthworms. The potential adverse effects of MPs consumption have been reported in various organisms, including earthworms and aquatic fishes; however, their potential effects on human health through respiratory, dietary, and other exposures are still being elucidated. This review provides a comprehensive overview of the current knowledge on potential sources, quantities present in water, table salt, air, and possible routes in the human body through different trophic levels. Furthermore, this paper reviews insights into the movement and accumulation of MPs at different trophic levels (i.e., aquatic, and terrestrial organisms) and their impacts on the cycling of soil carbon and nutrients (nitrogen and phosphorus). Additionally, this review paper addresses the current trends in MPs research and proposes strategic management techniques to mitigate MPs pollution.

Abstract In this paper, a neuro-adaptive PI control strategy for a water-cooled centrifugal chiller system is developed, and its control performance is examined. The system model consists of a flooded evaporator, a flooded condenser, a centrifugal compressor, and an electronic expansion valve. The overall system consists of three control loops: a compressor speed control loop, an inlet guide vane (IGV) control loop, and a condenser liquid level control loop. A neuro-adaptive control strategy for compressor speed control was designed. The control performance of the chiller was tested by carrying out simulation runs using an integrated building and HVAC (IB-HVAC) system model. The major details of the IB-HVAC model are described in this paper. Results show that the neuro-adaptive controller can adapt to new system dynamics of the IB-HVAC system and give good setpoint tracking responses under a wide range of operating conditions. The results show that the neuro-adaptive controller performs better than the constant gain PI controller in terms of speed of response and setpoint tracking properties.

Abstract The paper casts a spotlight on one of the manifold legal questions that arise with the proliferation of artificial intelligence. This new technology is attractive for many fields, including public administration, where it promises greater accuracy and efficiency, freeing up resources for better interaction and engagement with citizens. However, public powers are bound by certain constitutional constraints that must be observed, regardless of whether decisions are made by humans or machines. This includes the non-delegation principle, which aims to limit the delegation and sub-delegation of decisions affecting citizens’ rights in order to ensure governmental accountability, reviewability, and contestability. This puts some constraints on the automation of decision-making by public entities, as algorithmic decision-making entails delegating decisions to software development companies on the one hand, and to algorithms on the other. The present paper reveals and explains these constraints and concludes with suggestions to navigate these conflicts in a manner that satisfies the rule of law while maximizing the benefits of new technologies.

Abstract Necropsy, the examination of animal carcasses to determine the cause of death, is an essential skill for many professionals. Traditional training methods, however, are costly and time-consuming. The article suggests that Web-based Augmented Reality (WebAR) can offer an immersive and cost-effective training experience for laboratory animal necropsy. It describes using photogrammetry techniques to create a virtual necropsy environment consisting of 10 necropsy steps. A questionnaire was used to evaluate the usability, educational value, and drawbacks of the designed application by students who tested it. The paper outlines best practices for developing WebAR simulations, including high-fidelity 3D models and interactive elements. Additionally, it presents methods for creating new WebAR applications using specific programs or scripts. This paper highlights the potential benefits of WebAR for laboratory animal necropsy training, emphasizing its accessibility, cost-effectiveness, and scalability.

Abstract In the development of physical theories, thought experiments play a crucial role. Research on this topic began in 1976 and has continued to the present. This study aims to provide a more complete picture of the progress of thought experiments over the past two decades. To achieve this, this study employs bibliometric mapping methods. A total of 679 published papers were analyzed, including articles (504), conference papers (92), and book chapters (83). This data was retrieved from the Scopus database. The study's findings reveal that research and publications on thought experiments are highly valued and have received significant attention over the past eight years. According to the findings, 90% of the top 20 source titles contributing to thought experiments are from journals in the first and second quartiles (Q1 and Q2). This quartile ranking shows the quality and significant influence of a journal. The geographical distribution indicates that the United States contributes the most to thought experiments research, with 213 documents, 2592 citations, and 47 links. We also identified several prospective keywords that could be the focus of future research, including artificial intelligence, physics education, fiction, God, theology, productive imagination, technology, speculative design, and critical design. Therefore, this study provides a thorough picture of thought experiment research trends and future directions of potential topics that can be the focus of future researchers.

Abstract This perspective paper synthesizes insights from social work research, Critical Race Theory (CRT), and Critical Whiteness Studies (CWS) to develop a strategy for preventing White supremacy and promoting racial justice. It examines the intricate feelings of White guilt and shame, advocating for introspection, comprehension, and active engagement by White individuals toward systemic reform. The paper underscores CRT principles like Interest Convergence and Critique of Liberalism to examine concepts such as Moral Injury, Perpetration-Induced Traumatic Stress, and White Shame Culture. Three main obstacles to racial justice are identified: perceptions of power, funding dynamics, and attitudes toward White identity. The paper argues that racial healing should not be solely the responsibility of people of color, emphasizing the crucial role of White people in anti-racism work within supportive settings that foster growth rather than stress and humiliation. Focusing on prevention, the paper argues for social work practices that eliminate conditions obstructing optimal social functioning while challenging oppressive systems. This includes implementing trauma-informed approaches and fostering group work centered on empathy, relationship-building, and reflection. Advocating a strategy that champions our collective liberation, it suggests social work praxis as central to applying interpersonal and group solutions to systemic racism. The paper stresses the need for preventative funding in social services—highlighting tangible action steps and reforming funding strategies to support long-term engagement and address root causes of marginalization and oppression. This integral strategy calls for a collective push toward an equitable society, significantly enriching the discourse on CRT and CWS within social work.

Abstract Sustainable development is essential for the survival of the planet. The massive increase in GHG emissions due to human activities has put the world in unrest. The Indian construction industry is emerging and evolving at a rapid rate and has understood the grave situation, and for saving the environment has come up with innovative solutions for developing green buildings or sustainable construction. In this paper, the two different (the GRIHA Rating System and the IGBC Green New Building Rating System) of India were studied. The sample size was 40 construction professionals working on green building projects. An interview schedule was used for data collection. The data was subjected to a suitable analysis and the AHP method was applied. Based on the research findings, strategies to go green has been suggested for the IGBC and GRIHA rating system which may serve as a ready reckoner for enhancing the effectiveness and efficiency of the construction management process. Therefore, keeping in mind the above view this research paper “Review of Indian Green Building Rating Systems by Using Analytical Hierarchy Process (AHP) on Various Parameters” becomes indispensable. Hence, this research study can be considered an effort to empower construction professionals to create an extensive analysis of green building concepts and develop sustainably in India.

Abstract This paper assesses four relevant climate actions in Indian agricultural sector through the lens of United Nation’s Sustainable Development Goals (SDGs) to understand how climate actions (SDG 13) are linked with other SDGs and their targets and what measures can be taken to scale up these actions. Four board categories of climate actions are considered for this exercise: shift to less-flooded paddy water management practices; minimizing overuse of nitrogen-based fertilizer, system of rice intensification and climate smart agricultural practices. A mixed method has been followed: first, scoping review of literature between 2010 and 2022 is undertaken to capture the growing body of literature and then a normalized weighted score is used to understand the net strength of the linkages. Scoping review helped in identifying 100 studies spanned across Indo-Gangetic Plain (IGP) and the eastern part of Peninsular India. Findings from the scoring method suggest that these practices have linkages with 15 SDGs and as many as 43 SDG targets. Almost all linkages are positive (synergy) but there are a few negative linkages (trade-offs) as well. Trade-offs include exacerbating inequalities including gender, high upfront cost, requirement of skilled labor, lack of access to information and finance. This paper provides a detailed description of these trade-offs and suggests measures to tackle and minimize them.

Abstract The field of artificial intelligence (AI) is presently having a substantial influence on the advancement of career counseling education by enabling tailored guidance and evidence-based decision-making for learners. This paper aims to provide an overview about the utilization of AI in Bangladesh’s early career planning education. The utilization of AI has already been deployed in many first world country, however this is quite new to the third world country like Bangladesh. Significantly, artificial intelligence (AI) has surpassed its traditional function in professional growth and extended its reach to encompass social and emotional education. The examination of AI studies in Bangladesh requires the careful examination of several elements, such as cognitive advancement, parental engagement and oversight, and cultural heritage. This paper reveals overall all the facets of implementing AI in career planning in context of Bangladesh. Although there are several limits associated with the utilization of artificial intelligence for career assessment, it has undeniably yielded a multitude of benefits and discoveries. In the result, the two areas of data-informed making choices and career exploration are where the phenomena mentioned above are most frequently seen. Additionally, there is a growing need for cultural competency in the educational sector for both the delivery of individualized career counseling and AI-assisted employment suggestions.

Abstract Objective Bibliometrics was employed in this study to determine the research trends in the worldwide application of 3D printing technology to treat bone tumors over the previous 10 years. Methods Published from 2013 to 2022, the papers related to bone tumors treated with 3D printing were located in Web of Science Core Collection (WoSCC), PubMed, and Scopus. The screened articles were included in this bibliometric study. From these papers in WoSCC, information on annual publications, journals, keywords, countries, authors, institutions, and cited references were extracted and visualized with CiteSpace (version 6.1.R6) software to investigate the state of bone tumor treatment using 3D printing as well as research hotspots. The Carrot2 online visualization tool and Vosviewer software (version 1.6.20) were employed to visualize the publications from PubMed and Scopus, respectively, in order to ascertain the most popular research topics from both databases. Results A total of 606, 233, and 364 publications were obtained from WoSCC, PubMed, and Scopus, respectively, between the years 2013 and 2022. In WoSCC, the peak number of publications was found in 2021, with 145 publications published. Acta Biomaterialia (11 publications) and World Neurosurgery (10 publications) were the most prolific journals, and Biomaterials was the journal cited the most (244 times). Yong Zhou was the most productive author with 14 publications, while Kwok-Chuen Wong (69 citations) and William F Enneking, (69 citations) possessed the most citations. The country with the largest quantity of publications was China (207). Among all institutions, Shanghai Jiao Tong University produced the most publications (29). Rapid prototyping was the keyword with the strongest citation burst (4.73). ‘Reconstruction’, ‘surgery’, ‘resection’, and ‘design’ caught the significant attention of researchers. 3D-printed materials, pelvic reconstruction, mandibular reconstruction, computer-assisted surgical techniques, photothermal therapy, and in vitro experiments were recognized as hot subjects and trends in current research. The most frequently occurring topics in Scopus are not significantly different from those found in WoSCC. The most prevalent research areas in PubMed encompass implant, patient-specific, bioceramic, models, and pelvic.

Abstract Increasing research efforts are focused on studying the synthesis and mechanisms of nanomedicine in urologic cancer. We performed a bibliometric study of the literature on nanomedicine in urologic cancer over the last 23 years, focusing on aspects such as researchers, institutions, nations, and keywords. We searched for papers in the Web of Science Core Collection from January 1, 2001, to December 29, 2023. Only reviews and original articles written in English were considered. A total of 2386 papers satisfied the given criteria for inclusion. The publications included in the study originated from 90 nations. The United States had the largest number of published papers, accounting for more than 31.01% of the total. The leading institution in this field is the Chinese Academy of Sciences, with a publishing output of 2.35%. Farokhzad, Omid C., is the most prolific author, with 21 articles, and has garnered the most citations, totaling 6271. The latest phrase to enter the top ten most common lists was "gold nanoparticles." We searched for papers in the Web of Science Core Collection from January 1, 2000, to November 28, 2023. Only reviews and original articles written in English were considered. This is the first bibliometric study of nanomedicine in urologic cancer. This article provides a comprehensive analysis of the current state of research on nanomedicine in urologic cancer over the last 23 years. On the basis of this study, future researchers can identify noteworthy publications, journals, and potential collaborators and explore cutting-edge research directions.

Abstract Online education, while not a new phenomenon, underwent a monumental shift during the COVID-19 pandemic, pushing educators and students alike into the uncharted waters of full-time digital learning. With this shift came renewed concerns about the integrity of online assessments. Amidst a landscape rapidly being reshaped by online exam/homework assistance platforms, which witnessed soaring stocks as students availed its questionable exam assistance, and the emergence of sophisticated artificial intelligence tools like ChatGPT, the traditional methods of assessment faced unprecedented challenges. This paper presents the results of an observational study, using data from an introductory statistics course taught every semester by the author, and delves into the proliferation of cheating methods. Analyzing exam score results from the pre and post introduction of ChatGPT periods, the research unpacks the extent of cheating and provides strategies to counteract this trend. The findings starkly illustrate significant increases in exam scores from when exams of similar difficulty were administered in person (pre-Covid) versus online. The format, difficulty, and grading of the exams was the same throughout. Although randomized controlled experiments are generally more effective than observational studies, we will indicate when we present the data why experiments would not be feasible for this research. In addition to presenting experimental findings, the paper offers some insights, based on the author's extensive experience, to guide educators in crafting more secure online assessments in this new era, both for courses at the introductory level and more advances courses The results and findings are relevant to introductory courses that can use multiple choice exams in any subject but the recommendations for upper-level courses will be relevant primarily to STEM subjects. The research underscores the pressing need for reinventing assessment techniques to uphold the sanctity of online education.

Abstract When the stakeholder theory challenged the neoclassical shareholder theory, it was a step forward in the theoretical and practical debate about the role and responsibility of businesses in society and how wide the responsibility is. Today, neither of these theories go far enough to explain the responsibilities of businesses in society and neither do corporate social responsibility nor corporate sustainability given the complexity of the business environment in which companies operate and how far they are going, or how far they are pushed, to respond to grand challenges or the opportunities they may entail. The aim of this paper is to provide a theoretical exploration and a critical appraisal of the need for a paradigm shift from shareholders and stakeholders to future successors. This is grounded in a discussion about corporate social responsibility/corporate sustainability, and the relevance of environmental constraints, multilateral sustainability policies and pathways, and needs and requirements of corporate future successors that are important for businesses that want to prosper in the long-term. The findings suggest that forward-looking supranational political and economic unions, intergovernmental organizations, regional and local governments, and leading businesses have moved ahead of theory towards including intra- and intergenerational interests and the natural environment into their policies, regulations, and strategies. In doing so, they even go so far as to grant personhood to the natural environment, thereby recognizing the importance of the natural environment for their own and the prosperity of present and future generations who will be future successors of businesses. Consequently, the implication of the paper is to suggest a new theoretical lens which has a much wider scope than shareholder and stakeholder theories currently do, and a strategic roadmap, emphasizing the importance of future successors for corporate responsibility and successful business operations in the long-term and pinpoint ways forward in doing so.

Abstract In Southeast Asia, Malaysia, Thailand, Indonesia and the Philippines are defined by the World Bank as countries that failed to overcome the "middle income trap". The four Southeast Asian countries (hereinafter referred to as the "ASEAN Four") entered the ranks of middle-income economies in the late 1970s and early 1980s and achieved rapid economic development throughout the 1980s and 1990s. However, since the early 2000s, the competitive advantages of these countries’ labor-intensive industries have started to decline, while the process of industrial transformation and technological improvement has been stagnated due to the lack of innovation resources. With limited R&D input and insufficient indigenous tech innovation, these countries’ manufacturing industry show a trend of "deindustrialization" and the "middle technology trap" phenomenon emerged. As the manufacturing sector failed to generate value-added that promotes economic growth and national income increase, ASEAN Four have so far yet to enter the high-income ranks. Drawing from the cases of ASEAN Four, this paper argues that the "middle technology trap" is a key contributing factor to the “middle income trap,” and countries fallen into the “middle income trap” often experience the "middle technology trap" as a concomitant phenomenon. The paper first introduces the industrialization process of ASEAN Four while analyzes the challenges they faced in industrial structural transformation and technology advancement. It then discusses major reasons that these countries failed to step over both the "middle technology trap" and the “middle income trap”, including limited technology spillovers from FDI, R&D investment shortages and insufficient industrial policies, low-quality education system, deficient intellectual property protection and underdeveloped regional capital markets. The paper concludes with some implications for China and discussion on potential future research on distinctions of the “middle technology trap” phenomenon between upper middle-income and lower middle-income countries.

Abstract The adoption of artificial intelligence into industrial settings promises notable enhancements in productivity, quality, efficiency, competitiveness, and innovations. However, transitioning AI models from concept to full-scale industrial applications involves various complexities and challenges. These challenges are not only technical but also extend into the ethical and regulatory realms, calling for a comprehensive approach to AI integration. This paper examines the diverse hurdles faced during developing and deploying AI applications in the industrial domain. It addresses challenges in collecting the right data, construction of AI models, and ensuring that these models work accurately and responsibly when deployed in real industrial environment. Furthermore, the paper presents strategic recommendations, underscoring the necessity of ethical considerations and regulatory compliance to effectively overcome these obstacles. We provide guidelines aimed at maximizing AI's benefits in industrial environments while minimizing potential risks.

Abstract This paper evaluates the impact of an English and Business Computer Science program in the Democratic Republic of Congo (DRC), the world’s second-largest French-speaking country after France. The program addresses the gap between academic training and market needs by combining English language proficiency with essential business and computer science skills. This combination aims to equip students for success in the business and technology sectors, where English is a key language. The paper details the program’s implementation, outcomes, and evaluation, using surveys of employers and graduates, along with an analysis of student competencies and employability. The findings underscore the importance of English proficiency, along with business and technological skills, in aligning educational outcomes with job market demands, thereby improving student success.

Abstract This review paper provides a critical examination of underground hydrogen storage (UHS) as a viable solution for large-scale energy storage, surpassing 10 GWh capacities, and contrasts it with aboveground methods. It exploes into the challenges posed by hydrogen injection, such as the potential for hydrogen loss and alterations in the petrophysical and petrographic characteristics of rock structures, which could compromise the efficiency of UHS systems. Central to our analysis is a detailed overview of hydrogen solubility across various solvents, an extensive database of potential mineralogical reactions within underground storage environments, and their implications for hydrogen retention. We particularly focus on the effects of these reactions on the porosity of reservoir and cap rocks, the role of diffusion in hydrogen loss, and the consequences of multiphase flow induced by hydrogen injection. Our findings highlight the critical mineralogical reactions—specifically, goethite reduction and calcite dissolution—and their pronounced impact on increasing cap rock porosity. We underscore a notable discovery: hydrogen's solubility in non-aqueous phases is significantly higher than in aqueous phases, nearly an order of magnitude greater. The paper not only presents quantitative insights into the mechanisms of hydrogen loss but also pinpoints areas in need of further research to deepen our understanding of UHS dynamics. By identifying these research gaps, we aim to guide future studies towards enhancing the operational efficiency and safety of UHS facilities, thereby supporting the transition towards sustainable energy systems. This work is pivotal for industry stakeholders seeking to optimize UHS practices, ensuring both the effective utilization of hydrogen as a clean energy carrier and the advancement of global sustainable energy goals.

Abstract Navigating mobile robots in crowded environments poses a significant challenge and is essential for the coexistence of robots and humans in future intelligent societies. As a pragmatic data-driven approach, deep reinforcement learning (DRL) holds promise for addressing this challenge. However, current DRL-based navigation methods have possible improvements in understanding agent interactions, feedback mechanism design, and decision foresight in dynamic environments. This paper introduces the model inductive bias enhanced deep reinforcement learning (MIBE-DRL) method, drawing inspiration from a fusion of data-driven and model-driven techniques. MIBE-DRL extensively incorporates model inductive bias into the deep reinforcement learning framework, enhancing the efficiency and safety of robot navigation. The proposed approach entails a multi-interaction network featuring three modules designed to comprehensively understand potential agent interactions in dynamic environments. The pedestrian interaction module can model interactions among humans, while the temporal and spatial interaction modules consider agent interactions in both temporal and spatial dimensions. Additionally, the paper constructs a reward system that fully accounts for the robot’s direction and position factors. This system's directional and positional reward functions are built based on artificial potential fields (APF) and navigation rules, respectively, which can provide reasoned evaluations for the robot's motion direction and position during training, enabling it to receive comprehensive feedback. Furthermore, the incorporation of Monte-Carlo tree search (MCTS) facilitates the development of a foresighted action strategy, enabling robots to execute actions with long-term planning considerations. Experimental results demonstrate that integrating model inductive bias significantly enhances the navigation performance of MIBE-DRL. Compared to state-of-the-art methods, MIBE-DRL achieves the highest success rate in crowded environments and demonstrates advantages in navigation time and maintaining a safe social distance from humans.

Abstract Keeping up with the hastily growing economy implies undergoing unremitting transformation permanently. In the field of supply chain, such progress can only be guaranteed via the exploration of new horizons and innovative solutions in response to the constraints of the global market. Emerging technologies, particularly artificial intelligence, offer promising avenues for enhancing supply chain processes, with sustainability ascending as a critical consideration. Despite the recent surfacing of AI-driven applications, scant attention has been devoted to exploring their full potential within supply chain operations, particularly in conjunction with SDGs. Recognizing the untapped opportunities presented by the implementation of AI for a sustainable supply chain this study undertakes a bibliometric analysis of 236 research papers sourced from the Web of science database. The analysis utilizes R language BiblioShiny to examine the extracted papers, and dissect patterns, trends, and relationships among key concepts and themes as well as prominent topics, impactful authors, and leading journals and countries in this domain. The findings reveal substantial growth in research related to SCM, AI, and sustainability as the UK leads this field of study with 132 articles followed by India, China and the USA. Eventually, the National University of Singapore came first in terms of paper affiliations, followed by De La Salle University, and London Metropolitan University. These results only prove that sustainability is becoming more critical in the equation of AI-driven supply chains especially with the current socio-political and economic circumstances, constituting a solid base for further academic research and more innovations in the managerial and business-related policies in this field.

Abstract In 2007/2008, a triple crisis of food, fuel and finance sparked a global rush for agricultural land; tens of millions of hectares were acquired, primarily by foreign investors, within countries in the Global South. Amidst those transactions, intergovernmental organizations, national governments, investors, and community members envisioned what “success” of such investments entails. Although not explicitly defined, each stakeholder had different conceptualizations and measures of it, based upon the descriptions used and desired outcomes sought. Despite a large amount of literature analyzing the global rush for land, as far as we are aware no one has analyzed the diverse viewpoints about what success entails. This paper compares conceptualizations among four key stakeholder groups, based on ideal types from dominant narratives, and develops a typology of ideal stakeholder framing of success to allow comparisons of uses and thereby provide a foundation for researchers who are assessing the global land rush. This paper provides clarity about widely used, but inconsistently defined, framing providing an important foundation for clarity of meaning and comparative differences between stakeholders. The typology advances the discourse on the land rush by providing nuance to this widely used framing and makes explicit its diverse meanings.

Abstract This paper processes a novel hierarchical high-dimensional clustering algorithm based on the Active Learning Method (ALM), which is a fuzzy-learning algorithm. The hierarchical part of the algorithm is composed of two phases: divisible and agglomerative. The divisible phase, a zooming-in-process, searches for sub-clusters in already-found clusters hierarchically. At each level of the hierarchy, the clusters are found by an ensemble clustering method based on the density of data. This part of the algorithm blurs each data point as multiple one-dimensional fuzzy membership functions called ink-drop patterns; then, it accumulates the ink-drop patterns of all data points on every dimension separately. Next, it performs one-dimensional density partitioning to produce an ensemble of clustering solutions; after that, combining the results is done based on a novel consensus method with the aid of prime numbers. An agglomerative phase is a bottom-up approach that merges clusters based on a novel distance metric, named $${K}^{2}$$ K 2 -nearest neighbor. The algorithm is named as the Hierarchical High-Dimensional Unsupervised Active Learning Method (HiDUALM) and is explained in more detail throughout this paper. Although the classical clustering methods are not suitable for high-dimensional data clustering, the proposed method solves the problems related to speed and memory using ensemble learning, while due to its hierarchy and the use of different distance criteria, different levels of the cluster provide the clause. Experiments on synthetic and real-world datasets are presented to show the effectiveness of the proposed-clustering algorithm.

Abstract This paper contributes to the ongoing efforts aimed at enhancing Outcome-Based Education (OBE) assessment methodologies by addressing some critical gaps and exploring new solutions. Our work focuses on two main areas: firstly, this study proposes an improved assessment method for OBE. It refines traditional approaches by classifying course materials according to their relevance to learning outcomes, weighting them by importance, connecting these outcomes to student goals and assigning difficulty levels to modules. All modules are directly assessed through a final exam with a consistent rubric, and student success is measured by a holistic score that considers the weighted attainment levels across all learning outcomes and modules. Secondly, this paper provides theoretical guidance for integrating Generative Artificial Intelligence (AI) and blockchain technologies into OBE assessment. It examines the potential impact of these technologies at various assessment stages, laying the groundwork for practical implementation.

Abstract This paper examines the shifting landscape of higher education in Turkey, highlighting a disconcerting trend of politically motivated appointments, coined as “parasailing.” Departing from traditional merit-based norms, this practice of appointing professors without necessary approvals disrupts the academic environment, prompting concerns about the integrity of higher education institutions. The paper introduces the term “parasailing” to elucidate this phenomenon, emphasizing the connection between the appointed professor and their academic destination. In contrast to the widely used term “parachuting,” in Turkish academia the proposed terminology offers a better understanding of the appointment process. The subsequent sections provide an overview of the Turkish academic landscape, explore the origin of the term “parachuting,” review existing literature, define “parasailing,” and connect it to different philosophical thoughts. Overall, this paper contributes to a broader comprehension of the challenges facing Turkish higher education, urging a reconsideration of appointment procedures.

Abstract While promoting manufacturing growth is imperative to boost economic growth, potential adverse consequences on natural resources and ecology have created sustainability-related concerns and challenges. In India, with the reform processes deepening further and the business environment becoming more market-oriented over the years, the adoption of appropriate measures for sustainable manufacturing growth under such conditions would require a deeper investigation of the underlying dynamics, particularly to address the impacts of external shocks. This is especially true when external shocks alter market dynamics and, hence, input is used significantly in the manufacturing sector. Given this backdrop, the present paper examines how the major external shocks to the Indian economy during in the post-reform era have altered the resource use patterns in selected manufacturing industries. The paper uses secondary data collected from the KLEMS database of the Reserve Bank of India for the period from 1980–81 to 2019–20 and applies descriptive statistics and econometric techniques to address the research objective. It is found that energy intensity, vertical integration, capital intensity, and rate of growth of total factor productivity decreased over the decades, whereas labour productivity experienced an increasing trend in most industries. However, the trends are mixed in the case of material intensity. Further, the regression results indicate significant effects of external shocks on resource use, factor productivity, and structural changes. There are also industry-specific differences in the nature and extent of such changes. Hence, a deeper investigation of the underlying factors and impacts at a disaggregate industry level is necessary to draw more robust insights.

Abstract All over the world, waste and its disposal are becoming a more prominent issue, as landfills swell up and growing evidence points to its contribution to climate change and environmental degradation. In the developing world, waste pickers sort through solid waste and sell it to vendors, who will recycle the product into something consumable. The work they do is vital to climate change mitigation, as well as urban cleanliness. In a way, waste pickers, especially in India, are vehicles of environmental justice, but they are often discriminated against and subjected to inhumane working conditions. In this environment, the pandemic hit, making waste pickers’ already precarious life even worse. This paper attempts to fill the gap in the academic literature by compiling a systemized literature review of the impacts of COVID-19 on waste-pickers’ lives using an environmental justice perspective. The review also uses a Feminist Political Ecology perspective to illuminate the double jeopardy that female waste pickers face in the era of COVID-19, which academia often ignores. Ultimately, this paper shows that COVID-19 exacerbated the preexisting injustices that the waste picker community face and created an immense burden on women. This paper will show that it is important to notice the differentiation between female and male waste picker challenges, especially at the crux of the COVID-19 pandemic. This paper has important policy implications as well as research considerations for both environmental justice and feminist political ecology scholars.

Abstract Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide, affecting millions each year. It emerges from the colon or rectum, parts of the digestive system, and is closely linked to both genetic and environmental factors. In CRC, genetic mutations such as APC, KRAS, and TP53, along with epigenetic changes like DNA methylation and histone modifications, play crucial roles in tumor development and treatment responses. This paper delves into the complex biological underpinnings of CRC, highlighting the pivotal roles of genetic alterations, cell death pathways, and the intricate network of signaling interactions that contribute to the disease's progression. It explores the dysregulation of apoptosis, autophagy, and other cell death mechanisms, underscoring the aberrant activation of these pathways in CRC. Additionally, the paper examines how mutations in key molecular pathways, including Wnt, EGFR/MAPK, and PI3K, fuel CRC development, and how these alterations can serve as both diagnostic and prognostic markers. The dual function of autophagy in CRC, acting as a tumor suppressor or promoter depending on the context, is also scrutinized. Through a comprehensive analysis of cellular and molecular events, this research aims to deepen our understanding of CRC and pave the way for more effective diagnostics, prognostics, and therapeutic strategies.

Abstract Chimeric antigen receptor (CAR)-T-cell therapy is one of the most effective immunotherapies. CAR-T-cell therapy has achieved great success in the treatment of hematological malignancies. However, due to the characteristics of solid malignant tumors, such as on-target effects, off-tumor toxicity, an immunosuppressive tumor microenvironment (TME), and insufficient trafficking, CAR-T-cell therapy for solid tumors is still in the exploration stage. Mesothelin (MSLN) is a molecule expressed on the surface of various solid malignant tumor cells that is suitable as a target of tumor cells with high MSLN expression for CAR-T-cell therapy. This paper briefly described the development of CAR-T cell therapy and the structural features of MSLN, and especially summarized the strategies of structure optimization of MSLN-targeting CAR-T-cells and the enhancement methods of MSLN-targeting CAR-T cell anti-tumor efficacy by summarizing some preclinical experiment and clinical trials. When considering MSLN-targeting CAR-T-cell therapy as an example, this paper summarizes the efforts made by researchers in CAR-T-cell therapy for solid tumors and summarizes feasible treatment plans by integrating the existing research results.

Abstract This paper evaluates how the contribution of scientific publications on climate change from the University of São Paulo (USP) evolved between 1989 and 2022. The study conducted a bibliometric analysis of 2874 research articles collected from the Web of Science and Scopus databases to explore main trend topics and reveal influential journals and collaboration networks using the Bibliometrix software. The study shows an increasing and more significant temporal publication distribution from 2010 onwards. Based on the author’s affiliations, results indicate that the most important partnerships are national (67%), while the international co-authorships are predominantly with research collaborators of the Global North (North America and Europe). Several papers published in the period are in high-impact factor journals, evidence on climate change from USP. Environmental services, Atlantic Forest, Tropical Forest, Amazon, biodiversity, and Land use are the hotspot research topics to which USP researchers contribute. The evolution of three thematic groups was identified: (i) physical science, (ii) causes and effects, and (iii) strategies, discussed in themes such as organic matter, deforestation, and mitigation, respectively. This research is helpful to get insights into the current research development trends, to show the broadness of the scientific production, and the importance of the USP role in the climate change theme. Ultimately, it provides valuable information for further studies and suggests the possibility of advancing the research agenda on climate change with the Global South. Graphical Abstract

Abstract This paper presents a multi-strategy improved grasshopper optimization algorithm (MSIGOA), which aims to address the shortcomings of the grasshopper optimization algorithm (GOA), including its slow convergence, vulnerability to trapping into local optima, and low accuracy. Firstly, to improve the uniformity of the population distribution in the search space, the MSIGOA uses circle mapping for the population initialization. A nonlinear decreasing coefficient is utilized instead of an original linear decreasing coefficient to improve the local exploitation and global exploration capabilities. Then, the modified golden sine mechanism is added during the position update stage to change the single position update mode of GOA and enhance the local exploitation capability. The greedy strategy is added to greedily select the new and old positions of the individual to retain a better position and increase the speed of convergence. Finally, the quasi-reflection-based learning mechanism is utilized to construct new populations to improve population multiplicity and the capability to escape from the local optima. This paper verifies the efficacy of MSIGOA by comparing it with other advanced algorithms on six engineering design problems, CEC2017 test functions, and 12 classical benchmark functions. The experimental results show that MSIGOA performs better than the original GOA and other compared algorithms and has stronger comprehensive optimization capabilities.

Abstract This paper comprehends the global research scenario about incorporating cultural components in contemporary urban planning practice. Various urban cultural elements have been analysed under the umbrella of ‘Urban Cultural Dynamics’ (UCD). This study aims to identify hot spots and explore influential sources through a bibliometric investigation of the evolutionary patterns of cultural dynamics in urban planning research. Data was collected from the Web of Science core collection (1965-2021). The data mining tools VOSviewer, Biblioshiny, KNIME, and WordStat were used to analyse hot topics, keywords, influential journals, core papers, top authors, and cooperation networks of countries and institutions. The Analytical Hierarchy Process (AHP) is employed in journal analysis. The analysis showed that publications on UCD increased exponentially between 2016 and 2022. Italy (32), China (26), and Spain (18) are the top countries in total publications. Technical universities of Dresden and Munich have the most significant influence on UCD's research, with 103 and 101 total citations, respectively. Landscape and Urban Planning, Journal of Cultural Heritage, and Tourism Geographies are the top three consistently influential journals. The top ten core papers were identified. The keywords and topic analysis charted out the evolution of multidisciplinary UCD research topics. The hotspot analysis revealed the significance of cultural dynamics in sustainable urban development. The results highlighted the need for intercontinental cooperation between developed countries and the third world. The future scope of research on UCD topics is discussed in the conclusion.

Abstract This paper is based on the findings of a doctoral study that aimed to examine the role of continuing professional development (CPD) in enhancing digital transformation in selected university libraries in Uganda. One of the ways of effecting digital transformation is to continuously build the technological competencies of the librarians working in academic institutions through attending technology-related CPD. The study adopted a mixed methods approach with a convergent parallel design for collecting qualitative and quantitative data from six universities in Uganda. Quantitative data were collected from 76 librarians with a minimum degree-level qualification from the six selected universities. Qualitative data were obtained from six University Librarians working in these universities. The study findings indicated several challenges hindering librarians from participating in technology-related CPDs such as lack of management support, lack of personal interest, limited funding, and lack of opportunities, among others. The implementation of digital transformation within university libraries in Uganda was also reported to be beset by a lack of competent staff, limited management support, lack of funds, and technological gaps. Therefore, this paper presents a proposed model to address challenges hindering the digital transformation and the participation in technology-related continuing professional development activities within academic libraries. The proposed model is based on the study findings, and it draws from Watkin and Marsick’s learning organisation model, andragogy theory, the technology-organisation-environment framework, and extant literature. The model will guide academic libraries in the implementation of a conducive environment to necessitate staff development and implementation of digital transformation.

Abstract In this paper, a novel Many-Objective Whale Optimization Algorithm (MaOWOA) is proposed to overcome the challenges of large-scale many-objective optimization problems (LSMOPs) encountered in diverse fields such as engineering. Existing algorithms suffer from curse of dimensionality i.e., they are unable to balance convergence with diversity in extensive decision-making scenarios. MaOWOA introduces strategies to accelerate convergence, balance convergence and diversity in solutions and enhance diversity in high-dimensional spaces. The prime contributions of this paper are—development of MaOWOA, incorporation an Information Feedback Mechanism (IFM) for rapid convergence, a Reference Point-based Selection (RPS) to balance convergence and diversity and a Niche Preservation Strategy (NPS) to improve diversity and prevent overcrowding. A comprehensive evaluation demonstrates MaOWOA superior performance over existing algorithms (MaOPSO, MOEA/DD, MaOABC, NSGA-III) across LSMOP1-LSMOP9 benchmarks and RWMaOP1-RWMaOP5 problems. Results validated using Wilcoxon rank sum tests, highlight MaOWOA excellence in key metrics such as generational distance, spread, spacing, runtime, inverse generational distance and hypervolume, outperforming in 71.8% of tested scenarios. Thus, MaOWOA represents a significant advancement in many-objective optimization, offering new avenues for addressing LSMOPs and RWMaOPs’ inherent challenges. This paper details MaOWOA development, theoretical basis and effectiveness, marking a promising direction for future research in optimization strategies amidst growing problem complexity.

Abstract The multi-quay berth allocation problem (MQBAP) is an important problem in the planning of seaside operations (POSO) to find the best berthing solution for all the vessels. In this paper, an efficient method based on equilibrium optimizer (EO) is proposed for MQBAP. The dynamic multi-swarm strategy (DMS) is proposed to improve rapid decline problem in population diversity during the iterative process of EO, which is subsequently applied to MQBAP. In this paper, a certain improvement is also made on the original model of MQBAP by proposing an alternate quay selection mechanism, which aims to make the MQBAP model more complete. To verify the effectiveness of the proposed algorithm on MQBAP, this paper uses six test cases and seven comparative algorithms to verify it comprehensively from total service cost, berthing time, and berthing location. The results show that DEO achieved the smallest total service costs of 7584 and 19,889 on medium-scale, and 44,998, 38,899, and 57,626 on large-scale systems.

Abstract The system known as project-based learning, which is applied to specific courses without compromising the coverage of the necessary technical material, uses projects to drive knowledge. The plan and implementation of project-based learning in Chinese teaching as a major project, which embraces undergraduate creativity and places an emphasis on real-world, open-ended projects are discussed in this paper. In this paper, research on optimization method of project-based learning design for Chinese teaching based on optimized interference-tolerant fast convergence zeroing neural network (PBLD-ITFCZNN-BRO). It consists of three stages, import phase, main stage and evaluation stage. In the initial phase, the teacher separated the students to groups before the lecture to make sure that every group poses various traits, with some strong leadership skills and hands-on skills. The second phase of the PBL procedure helped transform what is primarily a passive learning environment (taking notes, listening, and sitting) into a more dynamic, student-centered, and interactive one. Students presented data, articulated their concepts, and then optimized their approaches to problem-solving during the evaluation step. The teachers concluded by summarizing. The performance of the proposed PBLD-ITFCZNN-BRO approach contains 15.26%, 20.42% and 21.27% greater accuracy, and 15.61%, 17.50% and 20.24% greater precision rate, compared with Investigation of Computer Network Technology on New Media Problem-Basis Learning Teaching Mode (CNT-PBLTM), PBL Model Basis application on Deep Learning in Physical Education Classroom Integrating Production with Education (PBL-DL-PEC), Interdisciplinary project-based learning: experiences with reflections from teaching electronic engineering at china (PBL-EEC) techniques, respectively.

Abstract Infrastructure networks are critical components of contemporary society, and numerous approaches have been suggested for the selection of strategies to protect these networks. However, for uncertain environments, research on attack and defense game models for infrastructure networks is limited. Therefore, after reviewing the existing approaches, a method based on interval-valued intuitionistic fuzzy set (IVIFS) theory is proposed for attack and defense games in critical infrastructure networks. First, we present the process of constructing the game model proposed in this paper, which mainly includes the formulation of the cost model, the strategies, and the method of generating IVIFS payoffs. Next, the Nash equilibria of the game are identified by a pair of nonlinear programming models based on IVIFS theory. Finally, experiments are conducted on a target scale-free network, and an investigation into the variation patterns of the Nash equilibria under different circumstances is also conducted. We provide explanations for these variation patterns by considering payoffs from the perspective of mathematical programming models. Furthermore, we find that compared to the existing attack and defense game model with crisp payoffs, the model proposed in this paper leads to superior Nash equilibria. Our work is a preliminary attempt to analyse attack and defense games for infrastructure networks based on IVIFS theory, providing a method for assessing payoffs in uncertain environments for the attacker and defender. This topic deserves further study.

Abstract The provision of sustainable housing should factor energy efficiency, the use of sustainable building methods and materials and address the current associated barriers. This consideration triggered an ongoing study in UK which has so far conducted a bibliometric analysis of 275 papers using the VOSviewer software. More papers have been published in the last 5 years compared to the previous 15, and the UK is less engaged in successful collaborations in comparison to other economically developed nations. The lesser use of innovation in the UK has been identified. Also, the uses of sustainable methods and materials in residential housing are not fully exploited for achieving energy efficiency. A future research direction emerging is the potential to study the combined impact of using innovative materials and methods to achieve greater energy efficiency in UK housing provision. Through technological innovations and the need to move from fossil fuels (for example, through the use of heat pumps) a new approach can move the UK closer to achieving net-zero in housing provision and operations.

Abstract The paper proposes a hybrid algorithm for forecasting multiple correlated time-series data, which consists of two main steps. First, it employs a multivariate Bayesian structural time series (MBSTS) approach as a base step. This method allows for the incorporation of potentially high-dimensional regression components, and it utilizes spike and slab priors to identify a parsimonious model. Second, the algorithm includes a post-model fitting diagnostic step where the residuals from the MBSTS step are processed through a multi-input/output temporal convolutional network (M-TCN) with multiple time scale feature learning. This step serves as an alternative to traditional subjective residual-based diagnostic procedures in time-series analysis, with the aim of improving forecasting accuracy. The key advantage of the M-TCN is its ability to capture sequential information efficiently. The M-TCN expands the field of convolution kernel without increasing the number of parameters, thus enhancing the capacity of model to capture complex sequential patterns. The paper presents two applications showcasing the effectiveness of the proposed hybrid algorithm. First, it utilizes pre-lockdown data from eleven Nifty stock sectoral indices to predict stock price movements, including the initial post-lockdown upturn. In the second application, it focuses on stock market data from pharmaceutical companies involved in manufacturing COVID-19 vaccines. In both cases, sentiment data sourced from newspapers and social media serve as the regression component. Through rigorous analysis, the paper demonstrates that the hybrid model outperforms various benchmark models, including LSTM, Bidirectional Encoder Representations from Transformers (BERT)-based LSTM, Deep Transformer Model, and GRU, among others, in terms of forecasting accuracy. This underscores the utility of the hybrid algorithm, particularly in predicting stock market trends during the COVID-19 pandemic period and its associated market dynamics.

Abstract This study examines the readiness of Jordanian-listed firms toward the application of Computer Assisted Audit Tools and Techniques (CAATTs) during the post-Covid-19 epidemic period. In particular, this study investigates the auditee perspective regarding the factors impacting the adoption of CAATTs based on the Organizational Readiness for Change (ORC) and the Technology Readiness Index (TRI) models. A cross-sectional survey was developed and distributed to 138 employees working in the accounting departments of Jordanian-listed firms. Partial least square structural equation modeling (PLS-SEM) was employed as the statistical analysis method to examine the study hypotheses. The results show a significant direct relationship of motivation for change, staff attributes, institutional resources, organizational climate and discomfort on readiness for change. Moreover, the results reveal that perceived fear of Covid-19 has a moderating effect on the direct relationship between motivation for change and readiness for change. However, the proposed relationships between optimism, innovativeness, and insecurity with readiness for change were not significant. This paper highlights the readiness toward CAATTs application from the auditee perspective rather than the external auditors. Moreover, this paper considers the changes in the work environment resulting from the Covid-19 pandemic on the motivation for change toward CAATTs. Lastly, the paper reveals the moderating role of perceived fear of Covid-19 on the influence of motivation for change on readiness to change. Hence, this paper set the basis for policymakers and practitioners toward evaluating the readiness of Jordanian-listed firms for CAATTs application.

Abstract Technical progress has a tremendous potential to reduce carbon dioxide emissions by reducing energy consumption, a major concern across production units. However, the existing empirical literature concerning technical efficiency and carbon intensity is scanty. Thus, this paper examines the relationship between technical efficiency and carbon intensity for the organized manufacturing sector of two states, Maharashtra and Odisha, and the all-India level from 2001 to 2018. The paper uses data envelopment analysis to estimate technical efficiency scores. It applies the 2006 Intergovernmental Panel on Climate Change Tier 1 methodology for estimating carbon intensity for each 3-digit manufacturing industry in all three sample cases. The study has used static panel regression and fractional logit regression techniques to examine the deterministic relationship between technical efficiency and carbon intensity. The result shows that technical efficiency is highly sensitive to carbon intensity in the Indian manufacturing industries. The findings also addressed that the size of the industries also reduces the technical performance of manufacturing units. This paper also confirmed that increased profit could boost the Indian manufacturing industries’ technical efficiency. Thus, this study addresses that carbon intensity as a proxy for the manufacturing sector’s potential to affect climate change plays a crucial role in explaining the technical efficiency variations across industries. Thus, it calls for better policies aimed at reducing the emissions of industries specifically to achieve sustainable growth for the Indian manufacturing sector.

Abstract The purpose of this study is to examine how physics students position themselves compared to other student groups on various attitudes and opinions relevant to the tradition of “scientific skepticism”. Previous research has shown physics students identifying and having mindsets in line with the epistemic ideas from this philosophical tradition, promoting disbelief in epistemically unfounded ideas, and skeptical inquiry as a tool for evaluating claims. In this, we employ quantitative constructs testing conspiracy beliefs and supernatural beliefs along with established psychological constructs for social dominance orientation, and the conspiracy mentality questionnaire that have previously been shown to have interconnectedness. After showing several direct comparisons between different student groups, the paper also examines other elements that can influence “scientific skepticism”, like education level, education type, and gender via multivariate regression analysis. The results suggest physics students tend to position themselves to the end of the spectrum on several constructs connected to scientific skepticism, both compared to students from the humanities and social sciences, and students from other STEM (science, technology, engineering, and mathematics) fields, and the regression analysis finds being a physics student contributes a statistically significant contribution along the tested dimensions. The paper discusses possible reasons for this and what this tells us about physics students and physics education.

Abstract Natural resources such as fish are vital for improving human livelihood and serving as sources of food, income and employment opportunities in Ethiopia. But, its degradation and overexploitation lead to anxiety about the living standards of human beings and other living things. The degradation of these resources, which is caused by the less common participation of all stakeholders in protecting the resources, is the most challenging issue in the country. The objective of this paper is to review fishery production and management and their challenges, the extent of the overexploitation of natural resources, the contributions of collective action in fishery production and management, and fishery collective action challenges in Ethiopia. The review paper identified that the existence of a lack of strong coordination among different actors like local communities, the government, development agents, research centers and donor organizations whose concern are with the fishery sector caused the degradation of water bodies and fishery resources in Ethiopia. These issues resulted in challenges in fishery resource production and management, mismanagement in solving social differences among local communities, and low cooperation among communities in protecting fish resources. Besides, these challenges also caused a limited expansion of fishery collective action, overexploitation of fishery resources, and less concern for the protection of fish diversity species in the country. Therefore, essential policy implications forwarded are creating and improving joint collaboration between fish users, local communities, government institutions and development agents; organizing and empowering the local communities in collective action to involve them in the fishery sector to contribute to practical improvements in the protection, production, management and sustainability of fish resources.