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The sustainable development of container rail-water intermodal transport in China faces a series of deep-seated constraints. In this paper, we quantitatively summarize the development status of container rail-water intermodal transportation in China’s ports. Next, the typical problems faced by the sustainable development of rail-water intermodal transport are analyzed from the bottom constraints and direct constraints. Finally, this paper proposes strategic ideas to promote sustainable development of rail-water intermodal transport, taking into account network layout, technical equipment, data exchange rules, and policy environment.

In order to improve the operational life of highway asphalt pavements, reduce urban traffic safety accidents, and improve pavement travelling comfort, this paper analyze the frequency of different highway asphalt pavement distresses and calculates the percentage of each other based on highway asphalt pavement data sets in Shandong. The results showed that the five types of highway asphalt pavement distresses including alligator cracks, longitudinal cracks, transverse cracks, sealed cracks and patches occur with high frequency and account for 96.2% of the total proportion. For revealing the coupling principle between different highway asphalt pavement distress, this paper analyze the correlation between the five types of highway asphalt pavement distresses by Spearman correlation coefficient. The results showed that alligator cracks have a higher positive correlation with transverse cracks and longitudinal cracks and sealed cracks have a negative correlation with transverse cracks. The research findings are helpful to understand the characteristics of pavement distress conditions more clearly and to optimize he level of service of asphalt pavements on urban roads.

A scientific and reasonable assessment of port competitiveness will facilitate a comprehensive understanding of the current development of Chinese container ports along the Maritime Silk Road. Considering the network attributes of ports and the repetitive information among indicators, this paper proposes a novel port competitiveness evaluation and grading model based on entropy-improved catastrophe progression method. On the basis of a directed and weighted shipping network, the “dominance” indicator is innovatively introduced. The evaluation system including land-oriented competitiveness, sea-oriented competitiveness, hinterland support capacity and production and operation capacity provides a comprehensive assessment of port competitiveness. It is found that: land-oriented and sea-oriented competitiveness have the greatest influence on port competitiveness. A pattern of “One core, two wings, and four ports’ coordination” has been developed among coastal ports in China. The competition among ports in the Bohai Rim region is fierce, and production and operation ability of ports in the southeast coast needs to be strengthened. Fuzhou port and Rizhao port have high hinterland support and high development potential. The results of this paper can provide decision support for the development and upgrading of China’s coastal ports under the Maritime Silk Road initiative.

Building Information Modeling (BIM) is a transformative advancement for the Architecture, Engineering and Construction (AEC) industry, providing comprehensive insights throughout the building lifecycle. With its inherent 3D technical capabilities, BIM has great potential for real estate valuation in the AEC space. While there are a number of studies exploring BIM in this regard, there is limited understanding of the best mechanisms to capitalize on its valuation potential. The purpose of this paper is to delve into the literature on the use of BIM in real estate valuation, emphasizing the role of Meta-analysis. Through a systematic review of 52 publications (including journal papers, conference papers, proceedings, book chapters, and dissertations), the study identifies challenges, limitations, and gaps in current practice. The study covers research findings up to October 2023 utilizing databases such as Web of Science, Scopus and Google Scholar. The paper provides an overview of current BIM applications and suggests future research directions, making a significant contribution to the integration of 3D modeling in real estate appraisal. Notably, it highlights the critical role of meta-analysis in facilitating the understanding and utilization of BIM for real estate appraisal.

The science of ecology is incorporated into farm development and operation through agroecological techniques. A paradigm shift in agriculture is essential to combat hunger, adapt to climate trade, and mitigate environmental degradation. By doing this, researchers may further acknowledge the interdependence of farmed and nonfarmed landscapes and the variety of products and services that robust ecosystems offer, including resilience, nutrient cycling, and pest control, all of which can help sustain yields. Agro-ecology relies heavily on the knowledge and experience of farmers since it fosters independence and decreases reliance on costly outside resources. The concepts of sustainable intensification and agroecology are examined in this paper as additional strategies to address the global issue of increasing food production while lowering environmental impacts. Also, this study evaluates how effectively these approaches boost crop yields, lower environmental costs, and build resilience to climate unpredictability by closely examining existing programs, integrated management strategies, and field experiments. Supporting the findings is a comparative table that shows several techniques of sustainable intensification and how they have an effect on yields and environmental costs. In order to expand resilient, sustainable, and equitable food systems, a discussion of the necessity of a paradigm shift towards agroecological strategies is addressed in the paper's conclusion.

Biosensors are essential for transforming biological signals into electrical ones and have a wide range of uses in the biomedical, agricultural, and environmental fields. A biosensor is a device that combines biological and physicochemical elements to detect changes in physiological or biochemical states. This paper provides a comprehensive overview of the development and application of enzymatic and immunological biosensors, emphasizing their significant role in environmental, agricultural, and biomedical sectors. By leveraging the unique properties of natural polysaccharides, particularly cellulose, for their construction, these biosensors offer enhanced biocompatibility, robust mechanical strength, and costeffectiveness. This study discusses the principles underlying biosensors, including their biological recognition elements, transduction mechanisms, and output systems. Enzymatic biosensors, characterized by their use of enzymes as bio receptors, and immunological biosensors, utilizing antibodies or antigens for the detection of immunocomplex formation, are evaluated in detail. Through comparative analysis, the paper highlights the diverse functionalities, sensitivities, and applications of these biosensors, ranging from glucose and hydrogen peroxide detection to monitoring of protein markers and E. coli bacteria. The study underscores the biosensors’ ability for facilitating rapid, incredibly sensitive, and specific detection capabilities, critical for advancing scientific diagnostics, environmental surveillance, and food protection.

As an essential initial step towards clean and sustainable energy, this research focuses on innovative materials and structural designs for maximizing solar energy conversion and harvesting. Modern solar thermal and photovoltaic system technologies and supplies are examined to show how alternative electricity has become less expensive and more sustainable. The primary focus is on complex ideas like multiple junctions and tandem solar cells, which increase the efficiency of single-junction systems. The review paper investigates innovative solar power storage solutions, involving battery technology and energy storage materials, to meet the increasing need for secure and easily available sources of clean energy. The research paper explores the technology and uses of flat plate collectors, tube collectors, and solar power plants and how those are used in residential and commercial solar thermal systems. Solar energy conversion efficiency and sustainability will improve with innovations in materials and architecture. Building-integrated photovoltaics (BIPV) is one of the easiest solar system architectures that can be integrated into any residential or commercial building. Quantum dot solar cells, photovoltaic (PV) solar energy frameworks, such as CIGS thin-film solar cells, and organic photovoltaics (OPVs). Organic photovoltaics are portable and lightweight but have a low energy conversion rate, whereas quantum dot solar cells have a high energy conversion rate but face fabrication challenges.

This study examines the latest utilization of the combination of machine learning (ML) and artificial intelligence (AI) in the monitoring and upgrading of water quality, which has become a crucial component of environmental management. In this paper, a thorough examination of modern methods and recent advancements in the fields of artificial intelligence (AI) and machine learning (ML) algorithms, which have considerably enhanced the precision and effectiveness of water quality tracking systems. The study analyzes the integration of these innovations into water treatment methods, focusing their ability to more efficiently identify and reduce contaminants compared to traditional techniques. This paper examines a collection of case studies in which artificial intelligence (AI)-powered devices have been used, showcasing significant developments in the evaluation of water quality and improved levels of treatment efficiency. The present study additionally analyzes the various problems and potential future developments of Artificial Intelligence (AI) and Machine Learning (ML) within this particular domain. These challenges cover issues of scalability, data security, as well as the importance for interdisciplinary collaboration. This paper gives a comprehensive analysis of the impact of AI and ML technologies on water quality management, demonstrating their potential to transform current practices towards greater sustainability and efficiency.

Eco-design is a crucial approach in achieving sustainable manufacturing, which seeks to reduce the environmental impact of products and processes throughout their lifecycle. This paper explores the principles and tools that are used in eco-design, providing an overview of the key concepts and methods for sustainable manufacturing. The principles of eco-design are centered on minimizing the environmental impact of products and processes through the use of renewable resources, reducing waste and emissions, and improving energy and material efficiency. The paper discusses these principles in detail and highlights the benefits that can be achieved by implementing eco-design in manufacturing. The tools and methods of eco-design include life cycle assessment (LCA), design for environment (DfE), and environmental management systems (EMS) whereas DfE involves designing products and processes to minimize their environmental impact. EMS provides a framework for managing environmental performance across an organization. The paper also discusses the challenges of implementing eco-design in manufacturing, including the need for collaboration across different functions within an organization, the availability of data and resources, and the complexity of the supply chain. Organizations can implement eco design by utilizing Life Cycle Assessment, eco-labeling, and Design for the Environment. This approach can help organizations initiate or improve sustainable production practices.

This research paper provides a comprehensive review of the current state-of-the-art and prospects of smart materials for sensing and actuation applications. Smart materials, with their unique ability to respond to external stimuli, have been the subject of extensive research and development in recent years. The paper begins by discussing the various types of smart materials, including piezoelectric materials, shape memory alloys, and electroactive polymers, and their properties and applications in sensing and actuation. the paper covers the advancements in the design and fabrication of smart materials and devices, including the use of nanotechnology and 3D printing. The potential for integration with emerging technologies, such as artificial intelligence and the internet of things, is also explore. The paper provides a comprehensive and in-depth analysis of the state-of-the-art and prospects of smart materials for sensing and actuation applications. The research presented has significant implications for the development of nextgeneration smart materials and devices, with the potential to revolutionize various industries and improve our quality of life.

This research paper explores the opportunities and challenges associated with the use of machine learning and artificial intelligence in advanced materials processing. With the exponential growth of data, advanced analytical techniques and powerful computational tools, machine learning and artificial intelligence can be leveraged to develop novel materials with tailored properties, enhance process optimization, and improve manufacturing efficiencies. However, the integration of these technologies into materials processing systems is not without challenges, including data acquisition and pre-processing, algorithm selection and optimization, and the interpretation of results. This paper provides an overview of the state-of-the-art in machine learning and artificial intelligence for advanced materials processing, highlighting case studies and examples of successful applications, and identifying potential future research directions. The goal of this research is to provide insights and recommendations to accelerate the adoption of these technologies and their impact on the development of advanced materials.

This research paper investigates the future of advanced materials processing, with a focus on the innovations and challenges that lie ahead. The study begins by exploring the current state of advanced materials processing and the latest trends in the field, including the use of advanced manufacturing technologies, such as additive manufacturing, to create complex geometries and novel materials. The paper then examines the challenges facing the field, including the need to develop new processing techniques that can handle a wider range of materials and produce materials with specific properties. The study also analyses the potential impact of emerging technologies, such as artificial intelligence and machine learning, on the future of materials processing. Finally, the paper concludes with a discussion of the key innovations and trends that are likely to shape the future of materials processing, including the use of sustainable materials, the development of new nanomaterials, and the integration of advanced sensors and data analytics into the manufacturing process. Overall, this research paper provides a comprehensive analysis of the future of advanced materials processing and highlights the critical role that innovation will play in shaping the field in the coming years.

Numerical simulation and modeling play a crucial role in understanding and predicting the behavior of materials subjected to high strain rate deformation processes. These processes involve rapid deformation and loading rates, typically encountered in scenarios such as impact events, explosive detonations, metal forming, and crash simulations. By employing advanced computational techniques, researchers and engineers can gain insights into complex material behavior under extreme loading conditions. This paper provides an overview of numerical simulation and modeling approaches used in studying high-strain rate deformation processes. It discusses the challenges associated with capturing dynamic material response, the development of constitutive models, and the use of finite element analysis and computational fluid dynamics. The paper also highlights the importance of material characterization, model validation, and sensitivity analysis for accurate and reliable simulations. Additionally, it explores the application of numerical simulations in optimizing material properties, designing protective structures, and improving the performance of impact-resistant materials. Overall, this review paper emphasizes the significance of numerical simulation and modeling as powerful tools for advancing the understanding and design of high-strain rate deformation processes.

The domain of real-time biomedical imaging has seen remarkable technological advances, enhancing the efficacy of surgical interventions. This paper addresses the critical challenges associated with the implementation of real-time biomedical imaging systems for surgical guidance and discusses comprehensive solutions to mitigate these issues. It outlines the substantial computational demands for real-time processing and the necessity for high-fidelity image synthesis. The intricacies of integrating multimodal imaging data, ensuring minimal latency, and maintaining spatial accuracy for augmented reality applications are also examined. Solutions leveraging cutting-edge machine learning algorithms for image segmentation and enhancement, as well as the application of parallel processing architectures for expediting computational tasks, are presented. This manuscript also explores the potential of quantum computing paradigms in transcending conventional processing limitations. Also, the paper addresses the importance of interoperability standards for seamless integration of imaging systems in diverse surgical environments. It concludes with a discussion on the ethical implications and privacy considerations in deploying artificial intelligence in surgical settings. This paper highlights the importance of interdisciplinary innovations necessary for the advancement of real-time biomedical imaging for surgical guidance. The machine learning techniques such as CNNs, helps the trade-off with accuracy and computational speed. Whereas transfer learning procedures take 20 seconds and Federated Learning in 15 seconds represents the better performance.

Green machining is an emerging field that focuses on reducing the environmental impact of machining processes while maintaining or improving their economic efficiency. Cutting fluids are commonly used in machining operations to reduce friction and heat generated during cutting, but they can also cause negative environmental and health impacts. This paper reviews the environmental and economic impacts of cutting fluids in machining processes and presents various green machining techniques that can be used as alternatives to traditional cutting fluids. The paper also discusses the challenges associated with implementing green machining techniques and the main outcome is the potential benefits for both the environment and the economy.

The emergence of artificial intelligence (AI) with synergistic integration is currently a paradigm-shifting strategy for the direction of biomaterials development and design. This paper analyzes the connection between AI and biomaterials, explaining the significant influence of predictive modelling on the path of the area. By carefully investigating state-of-the-art studies and unique applications, it illustrates how AI-driven predictive modelling redefined biomaterial design and entered a new era of unusual accuracy and productivity. This research covers a wide variety of AI technologies, from deep neural networks to machine learning, that facilitates the development of prediction models that use large datasets to anticipate the behaviour, characteristics, and interactions of biomaterials. It examines how artificial intelligence (AI) may speed up the method of screening for viable materials, improve their qualities, and forecast there in vivo reactions. This can help translate beachside discoveries into clinical applications more quickly. This paper further explains the future prospects and problems in the field of biomaterials and AI integration, underlining the significance of interdisciplinary working together, standardization of data, and ethical concerns.

In this era of society, various sectors, including the food and beverage industry, are keen on integrating technological systems into their operational workflows to help the growth of the business itself. The adoption of technology systems in business processes, such as self-ordering system kiosks, tablets, or QR code menus, has become an emerging trend, including many stores, hotels, airports, and restaurants that eliminating inefficiency of manual ordering and reducing paper waste due to book menu. Many restaurants have been enabling customers to use a QR code method to order menus from their tables, which makes this study aim to examine the impact of self-ordering with QR codes within the scientific community. The literature review method is used in this research by analyzing 324 data encompassing a diverse range of sources, including articles, reviews, conference papers, books, and book chapters conducted since June 2023, spanning the publication years from 2018 to 2023. The analysis shows keywords related to self-service technology, technology acceptance, restaurant, etc. has been emerging trends within scientific community apart from there are gaps for further study. Nevertheless, self-ordering systems with QR codes are sought after for their potential to enhance efficiency and speed, reduce human error, save costs, improve the customer experience, and provide real-time order tracking. Using self-ordering is also related to the SDGs in improving industry, innovation, and infrastructure because it can support inclusive and sustainable industry.

System evaluation research on user experience applied in using mobile applications. Systematic review of papers taken from the last 6 years, papers published in conference publications or journals, and papers available in English. The strategy used in searching for 30 articles was to create research questions, search for keywords appropriate to the topic, carry out inclusion and exclusion and ensure the quality of the paper assessment. From various studies that evaluate application user experience, I found that there are many factors that have not been fully successful, so researchers use the questionnaire method more because they think this method is easier to reach users widely. This literature review aims to explore users’ experiences with system services, and why users who are experienced with mobile applications are likely to continue using those applications. This systematic review is a methodology for identifying, evaluating, and defining relevant research on this topic answering several research questions and using a replicable and verifiable process that aims to find out what has not met user expectations. The main findings of this literature review are the percentage results of factors that influence user experience, techniques used to evaluate user experience and the benefits of evaluating user experience.

According to WHO (2022), tuberculosis (TB) is the primary cause of ill health and the leading cause of death globally. It is estimated that approximately a quarter of the world’s population has been infected. With 372,367 cases of tuberculosis in 2022, the Philippines is among the top eight countries that accounted for more than 66% of all TB cases worldwide. Region III, along with NCR and Region IV-A, is one of the regions in the Philippines with the highest incidence of TB. This paper utilized the geographical information system (GIS) for easier visualization, and Getis-Ord Analysis, a type of spatial analysis tool for quick interpretations to provide an evidence-based framework for TB response. The spatial analysis was conducted to (1) determine if there are clusters of TB cases in the region across various periods and (2) determine if there are hot spots of TB cases in the most recent TB data covering 2019, 2020, and 2021. The results indicate that only the 2019 TB cases exhibit significant non-random clusters. It is recommended that further investigation be conducted to determine if the spatial clustering in 2019 is associated directly or indirectly with the El Niño event that occurred that year. On the other hand, the non-significance of the results for the years 2020 and 2021 may be attributed to the underreporting due to the implemented health protocols implemented to minimize the spread of COVID-19 which affected the accuracy of the reported cases. The results of the paper may be used for optimal resource allocation in addressing the spread of the disease.

The escalating production of sewage sludge in WasteWater Treatment Plant (WWTP) due to urban population growth and its management poses a substantial risk to the energetic and environmental efficiency of WWTP. This paper aims to explore the potential for sludge as a renewable energy source to reduce reliance on traditional energy through a systematic literature review of peer-reviewed articles and case studies. This overview demonstrated that various treatment methods such as anaerobic digestion, incineration, gasification, and pyrolysis are the most used and the most promising in terms of their energy outputs and effectiveness. The paper discussed the complexity of sludge composition, its financial burden on WWTP, and the crucial role in the success of these systems. Moreover, a comparative analysis of the different valorisation techniques was conducted that highlighted the energy production potential existing within each method and its underlying constraints while emphasising on the proper sludge management for overall efficiency. Finally, this paper recommended the need for sustainable, cost-effective approaches, considering legal standards for efficient WWTP.

The interaction between hazard and exposure gives rise to risk. Tsunami risk assessment is derived from both hazard assessment and vulnerability assessment. Exposure can manifest in various aspects, such as social factors (e.g., population), environmental factors (e.g., agricultural areas), or economic factors (e.g., infrastructure). Our focus in this review paper is specifically on economic exposure, with an emphasis on structural vulnerability assessment. The approaches employed in tsunami vulnerability assessment are diverse. In this paper, we categorize them into simplified and in-depth methods, encompassing: (1) Empirical vulnerability functions, (2) Index-based approach, (3) Building tsunami vulnerability model (BTV).

The focus of this study is on a pressing issue in ore geology, specifically the geodynamics of ore formation. The paper delineates a comprehensive methodology for examining the geodynamic context in regions hosting endogenous mineralization. The foundation for reconstructing geodynamics lies in geological and structural investigations into the circumstances surrounding mineralization, complemented by outcomes from physical modeling. Tectonic tension and deformation analyses of ore fields and deposits further contribute crucial insights. The study underscores that understanding the geodynamic setting is paramount for elucidating the processes leading to ore formation. This involves a detailed examination of geological structures, conditions of mineralization, and physical modeling results. By adopting this approach, the research provides a robust framework for reconstructing the geodynamic conditions prevalent during the period of ore formation. As a practical application of this methodology, the paper presents results from the reconstruction of the geodynamic situation during the ore formation period in a gold deposit situated in Western Uzbekistan. These findings contribute to a deeper comprehension of the geodynamic processes associated with the formation of valuable mineral deposits, thereby enhancing our ability to interpret and potentially predict similar occurrences in ore geology.

This paper undertakes a comprehensive analysis of the food industry's development across various foreign countries, with a focus on key sectors such as meat and meat products, dairy products, sugar, cheese, and tobacco products. The examination extends to the activities of global corporations and clusters involved in food production, forming the basis for informed proposals to enhance the efficiency and functionality of food clusters. The analysis delves into the nuanced dynamics of each sector, considering factors like production methods, market trends, and global consumption patterns. By scrutinizing the practices and strategies employed by global corporations, the paper seeks to distill valuable insights applicable to the improvement of food clusters. Understanding the success stories and challenges faced by these entities becomes instrumental in formulating actionable recommendations. The proposals put forth in the paper aim to elevate the performance and competitiveness of food clusters. These recommendations likely span areas such as technological innovation, supply chain optimization, sustainability practices, and market positioning. Drawing on the strengths observed in successful global corporations, the paper strives to provide a roadmap for food clusters to adapt and thrive in a dynamic and evolving industry landscape. This research contributes to the ongoing discourse on enhancing the food industry's efficiency and sustainability, offering practical suggestions derived from a thorough analysis of both global trends and the activities of leading corporations and clusters. The insights gleaned from this paper have the potential to guide policymakers, industry stakeholders, and researchers in their efforts to foster innovation and resilience within the food sector.

This scientific article provides an in-depth review of recent advancements in renewable energy sources, examining their significance in addressing global energy challenges. The paper covers various types of renewable energy, including solar, wind, hydropower, geothermal, and biomass, emphasizing technological developments, efficiency improvements, and environmental considerations. Additionally, the article discusses the current state of renewable energy adoption globally and its potential impact on reducing carbon emissions. The analysis integrates findings from recent studies and research papers to present a comprehensive overview of the current landscape of renewable energy technologies.

This scientific paper investigates the critical aspects associated with optimizing the species composition and age structure within forest ecosystems to achieve a state of completeness. The study emphasizes the ecological, economic, and social dimensions of forest management, with a focus on enhancing biodiversity, ensuring sustainability, and promoting resilience to environmental changes. Through a comprehensive review of literature, empirical data, and case studies, this paper provides insights into the strategic approaches and key considerations for forest stand completeness optimization.

In this study, a composite filter paper was fabricated using cellulose derived from Flax and cotton linters, along with the incorporation of basalt fiber. The aim was to develop a filter paper with enhanced filtration performance and mechanical strength.The composition and properties of the mineral filler employed in the preparation of the filter paper were thoroughly investigated. The mineral filler, which played a crucial role in influencing the properties of the composite, was carefully selected and characterized. Its particle size, surface area, and chemical composition were analyzed to understand its impact on the filtration efficiency and mechanical integrity of the filter paper.To evaluate the performance of the composite filter paper, comprehensive testing methods were employed. The filtration efficiency, pressure drop across the filter, and mechanical strength properties such as tensile strength and burst strength were assessed. These tests provided quantitative data to determine the effectiveness of the composite filter paper in capturing particles of varying sizes and its structural stability during the experimental investigation were presented in graphical form to provide a clear visual representation of the data. These graphs allowed for easy interpretation and comparison of the properties and performance of the composite filter paper under different conditions.

This paper presents a mathematical model developed to describe the dynamics of forest ecosystems. The model is based on the principles of cross-diffusion, consider the interaction between two plant species in a forest environment. The model considers various parameters, like diffusion, growth and interaction coefficients and environmental capacities between species. Factors of influence of external conditions on each species of plants are also introduced. The differential equations are solved numerically using the finite difference method. This paper studies cross-diffusion dynamics by combining classical differential equations and quantum-inspired optimization techniques. The focus is on cross-diffusion processes, where populations interact through complex mechanisms of diffusion and reaction. The study uses a hybrid approach that combines classical methods for solving differential equations with quantum optimization, a quantum computing platform. Visualization of the results is presented in the form of 3D graphs reflecting the spatial distribution of plant populations in a forest ecosystem at various time steps. The resulting mathematical model and its visualization provide a tool for a deeper understanding of the influence of various factors on the dynamics of forest ecosystems. Analysis of such a model could be useful for predicting longterm changes in forests and developing sustainable forest management strategies.

This research advocates for the implementation of sustainable practices in Uzbekistan’s electrical energy network, stressing the importance of a holistic approach to environmental management and engineering. In response to surging energy demands and the critical need for ecological resilience, the study investigates the alignment of Uzbekistan’s electrical energy sector with sustainable principles. Through a thorough analysis of environmental challenges and engineering considerations within the national energy network, the research uncovers crucial insights into establishing a sustainable energy landscape. It highlights the urgent requirement to incorporate environmentally conscious practices into the engineering frameworks of Uzbekistan’s electrical energy network. The paper explores innovative engineering solutions to mitigate the ecological impact of energy generation, transmission, and distribution, emphasizing the multifaceted dimensions of environmental management. It underscores the significance of balancing energy demands with conservation imperatives, advocating a shift towards sustainable energy practices. Beyond technical aspects, the research delves into the socio-economic implications of adopting sustainable energy in Uzbekistan. Examining potential benefits, stakeholder engagements, and required policy frameworks, the paper urges a harmonious transition towards sustainability in the electrical energy sector. By comprehensively exploring the interplay between environmental management and engineering in Uzbekistan’s electrical energy context, this paper contributes to the discourse on sustainable energy transitions.

This research explores the application of Environmental, Social, and Governance (ESG) fraud. This research also describes the trends and developments in ESG fraud from year to year. Apart from that, this research explains trends in research methods, research objects, the ESG fraud triangle, and ESG fraud schemes. To achieve all these objectives, the research methods used are bibliometrics and systematic literature review. The analytical tool used is MS. Excel and VOSviewer. The number of papers in the research sample was 66 papers. These articles contain controversial issues regarding the implementation of ESG, company performance and audits. The research results prove that the pandemic is vital in developing ESG fraud. When the pandemic hit, many researchers started researching ESG fraud, and at its peak, when the pandemic was over, there were still many researchers studying ESG fraud. There are two main findings in the research. First, pressure is a factor that often causes companies to practice ESG fraud. Second, non-financial reporting fraud schemes are often used to carry out ESG fraud practices.

Nusantara, the planned new capital city of Indonesia, aspires to be a green, smart, and sustainable city. This paper explores the political, economic, and social dimensions of Nusantara's development, focusing on the strategic decision to relocate the capital from Jakarta. The research analyzes the challenges and trade-offs involved in balancing environmental conservation with the need for urban development. It evaluates the policies and initiatives implemented to achieve the vision of a smart and sustainable city, considering the integration of technology, digital infrastructure, and data management. Drawing on comparative analysis, the paper examines historical parallels and precedents in capital relocation projects worldwide to derive lessons for Nusantara's development. The findings highlight the importance of environmental governance, public participation, and stakeholder engagement in achieving a sustainable and inclusive urban environment. The paper concludes with recommendations for policymakers and identifies avenues for future research in the field of sustainable urban development and capital relocation.

Energy poverty is an issue, which is new to the scientific field and often omitted from the research. The contemporary approaches to it are various, still the major of them points that energy poverty exists in case the national energy sector and the economy in general lack the possibilities to provide sufficient, safe, reliable, and affordable energy to the consumers. This paper examines the energy sector of Pakistan to prove or refute the idea of energy poverty existence in the country. In addition to that the energy poverty in Pakistan, in case it exists needs to be defined, its reasons are to be examined and the possible solutions for its alleviation provided. The paper proves the mentioned idea with the help of the approach from the side of international infrastructure construction. The proposed approach includes the examination of the role of BRI in energy poverty alleviation in Pakistan. While the Initiative has a significant impact on the economy of the country, its energy sector isn’t directly affected by BRI. The major results of the study encompass the following: the energy poverty measurement through index method is developed, based on demand for energy and its supply and imports’ changes; the energy poverty in Pakistan persists and can’t be alleviated by the international institutions; the effects of economic growth aren’t automatically distributed in the economy, especially in the energy sector of the country and have limited effects on energy poverty.

Large steel silos are typically thin-walled structures, widely used in agriculture and industry to store large quantities of bulk materials. In the presence of steel solids in cylindrical shells the stiffness of the contents has a positive influence on the Silo walls, similar to internal pressure. In order to clarify the influence of the interaction between steel silos and bulk materials, the paper establishes a model for the interaction between steel silos and bulk materials using finite element simulation based on the European steel silo specification, and applies the theoretical analysis of mathematical modelling. The results of the study showed that: Wheat storage material and steel silos interaction stiffness values range from 0.0025 to 0.01 N/mm3 and 0.003 to 0.015 N/mm3; the value of the lateral pressure on the wall of the silo will be reduced as the radial displacement of the wall of the silo wall increases with the movement outwards; and the wheat storage stiffness of this paper was verified by literature test results. Provides a reference for the stability of steel silos containing wheat storage material in realistic situations.

Water conservancy project is the most basic livelihood guarantee project related to social security and stability and the survival and development of various production departments, but it is facing huge financial pressure because of its large investment scale, low financial returns, long recovery cycle, positive external benefits and strong public welfare. This paper analyses the characteristics and difficulties of investment and financing of water conservancy projects, combined with the new concept of the development of water conservancy projects and the analysis of related cases, this paper puts forward some solutions to investment and financing problems, such as innovation of investment and financing mode, establishment of local water conservancy development platform company, invigorating stock assets, etc., as well as relevant policy suggestions such as overall project planning, improving investment mechanism, improving financing capacity, expanding investment returns, innovating investment and financing models, etc. It can provide reference for the overall planning and investment construction of water conservancy projects.

In the dynamic landscape of the construction industry, the integration of computer-aided design (CAD) technology has become commonplace. However, as architectural demands evolve, so do the complexities in design and management. Consequently, Building Information Modeling (BIM) technology has emerged as a pivotal tool, progressively transforming the business landscape. This paper aims to elucidate the distinctive features and advantages of BIM technology through a comparative analysis of five key characteristics. Additionally, it delves into the practical applications of BIM in both architectural design and construction management. The foundational section of the paper illuminates the principles, concepts, and inherent characteristics of BIM technology. A comprehensive exploration of the technology's evolution in the construction industry is undertaken, highlighting its pivotal role. Subsequently, the paper offers an insightful overview of how BIM is applied in architectural design and construction management. By providing a concise analysis, this paper endeavors to instill an awareness among professionals in the construction industry about the critical aspects of information management and the unique features of BIM technology. The ultimate goal is to enhance the efficiency of architectural design and construction management practices, fostering tangible advancements in China's construction industry.

Climate change as a challenge imposes an obligation on nations to indicate that climate change mitigation is at the core of their domestic policymaking. As a responsible stakeholder in climate change mitigation, India responded by announcing constitutional protection for the environment under the constitution. Since then, India has enacted several legislations to protect and conserve the environment. In 1994, the Environmental Impact Assessment (EIA) was one such attempt to forecast and mitigate possible harm to the environment. Recently, the Government of India has amended the EIA process by introducing changes to the law through the EIA Notification 2020. The paper identifies the problems associated with recent changes and produces empirical evidence to substantiate the study. It further attempts to appraise the Sustainable Development Goals and the importance given to environmental impact assessment by international organizations including the World Bank and the Asian Development Bank. The paper further studies several best practices in the European Union and concludes by suggesting law reforms in Indian law.

This review article explores the transformative impact of AI and IoT in livestock management, highlighting their pivotal role in advancing Agriculture 4.0. It delves into various technologies such as robotics, nanotechnology, and gene editing, which are reshaping farming and food systems towards sustainability. The paper emphasizes the significance of digital phenotyping in poultry, particularly in enhancing productivity, animal welfare, and sustainability through innovative genomics research and health monitoring platforms. Additionally, it examines the evolution of e-agriculture in India, focusing on government initiatives and the increasing influence of mobile technology in farming. The role of Big Data in Smart Farming is also scrutinized, revealing its extensive impact beyond primary production and its potential in reshaping supply chain dynamics and business models. The review further assesses the contributions of IoT in agricultural systems, particularly in meeting the challenges of a rapidly growing global population. Through this comprehensive analysis, the paper underscores the necessity for ongoing research and development in these areas, recognizing the potential challenges and opportunities presented by these robust, sustainable, and in creating a more technologically advanced agricultural future.

Abstract: This research paper explores the transformative impact of machine learning techniques in the field of medical treatment assistance, with a focus on the integration of Augmented Reality (AR) and Virtual Reality (VR) technologies. It investigates the ways in which machine learning, AR, and VR collectively enhance medical diagnostics, surgery, patient care, and medical training. Through an in-depth examination of recent advancements and case studies, this paper aims to demonstrate how these technologies are revolutionizing healthcare and contributing to more accurate diagnoses, minimally invasive surgeries, improved patient outcomes, and enhanced medical education.

Machine learning algorithms have quickly risen to the top of several fields' decision-making processes in recent years. However, it is simple for these algorithms to confirm already present prejudices in data, leading to biassed and unfair choices. In this work, we examine bias in machine learning in great detail and offer strategies for promoting fair and moral algorithm design. The paper then emphasises the value of fairnessaware machine learning algorithms, which aim to lessen bias by including fairness constraints into the training and evaluation procedures. Reweighting, adversarial training, and resampling are a few strategies that could be used to overcome prejudice. Machine learning systems that better serve society and respect ethical ideals can be developed by promoting justice, transparency, and inclusivity. This paper lays the groundwork for researchers, practitioners, and policymakers to forward the cause of ethical and fair machine learning through concerted effort.

The reuse of treated wastewater in agriculture is a promising solution to the water scarcity challenge faced by many regions worldwide. This review paper provides an overview of the current state of knowledge on treated wastewater reuse in agriculture, highlighting its potential benefits and challenges. The paper begins by discussing the importance of treating wastewater before reuse and the potential it offers. The benefits of using treated wastewater in agriculture are discussed, including increased water availability, improved soil fertility and reduced fertilizer use. The risks associated with the use of treated wastewater, such as the accumulation of pollutants and the potential for pathogen transmission, are also discussed. The review paper then presents some examples of reuse projects for irrigation and their success criteria. The current regulations governing the use of treated wastewater in agriculture are examined, and their evolution presented. The paper concludes with a discussion of future research needed to address the remaining challenges surrounding the use of treated wastewater in agriculture. Overall, the review paper emphasizes the importance of careful management and regulation of treated wastewater reuse in agriculture to ensure safety and sustainability to meet the growing demand for water in agriculture.

Africa is facing an urgent need to increase food production to meet increasing demands. Targeted investments in integrated agriculture and, water management systems are required to meet this challenge. However, there is a lack of comprehensive information on the potential applications of climate-smart agriculture (CSA). This paper reviews current crop modeling technologies and their applications within the scope of climate change and the CSA framework in Africa. It evaluates current research trends in various crop simulation models and suggest advanced approaches to improve crop and environmental assessment, crop management, and decision-making. A total of 140 relevant papers were considered. Results showed that 84% of studies used process-based models, with Maize being the most studied crop. Additionally, DSSAT crop models and analysis of variance models have the highest contribution of physical and empirical crop modeling studies respectively. Over 72% of studies have contributed to adaptation strategies and reducing yield gaps, while only 8% of studies have been conducted on climate change mitigation and their trade-offs with adaptation using crop models under CSA. To ensure food security through sustainable agricultural practices in Africa, there is crucial to implement CSA models with a focus on the climate change mitigation component.

Utilized the Soil and Water Assessment Tool (SWAT) across different watershed scales, from small to large, under a variety of climate conditions, aiming to quantify and mitigate the impacts of climate change on watershed hydrology and water resources. Additionally, the paper explores the development of conservation strategies for water and soil, aimed at managing both water and sediment yields effectively. By examining research at international, national, and regional levels, with a particular focus on climate change projections for Morocco, this review critically assesses the SWAT model’s operational framework, including its inputs and outputs. The operational intricacies of the SWAT model are dissected to understand its utility in hydrological modeling, emphasizing its role in climate change assessment. Through this examination, the paper highlights the expanding application of SWAT in water resource assessments globally, demonstrating its significance in understanding and addressing the challenges posed by climate change on hydrological systems worldwide.

The paper presents a comprehensive study on the ash handling system upgrade from a hydraulic conveying system to a pneumatic system in a 550 MW coal-fired power plant located in Taiwan. The ash pond used to dispose of ash from the economizer and air preheater is almost full due to having been in service for more than forty years. An alternative location to dispose of the ash is sought. The design process of finding the new location and the equipment to be used is explored. Some options for the new economizer and air preheater ash disposal site, including building a new silo or using an existing silo, are taken into consideration in terms of design, cost, and timing of execution. The project’s execution procedure is reviewed, taking into account aspects of system integration, equipment installation, and commissioning. The primary objective of this paper is to detail the design, implementation, and outcomes of the ash handling system upgrade. This upgrade is accomplished in an effort to enhance operational efficiency, reduce maintenance requirements, and improve environmental compliance. The study explores the motivations behind adopting pneumatic conveying technology, focusing on its advantages over hydraulic systems, such as reduced maintenance needs and improved dust control. The case study provides insight into the lesson learned and recommendations for similar ash conveying system upgrades in other coal-fired power plants.

This paper deals with the development of an ergonomic system for forecasting wild fires and the features of their spread, which is the object of research. The objective of the study is to make a full-fledged system for forecasting and determining the features of wild fire spread. To achieve this objective, the following tasks are solved: to carry out a comparative analysis of existing systems for forecasting the spread of wild fires in order to identify the disadvantages and advantages of these systems; based on the analysis of existing systems, put forward requirements for the ergonomic system being developed; to develop the structure of a neural network capable of forecasting the spread of wild fires in accordance with the requirements; generate a data set for training and testing the developed neural network and test its operation. To solve the tasks, techniques of analyzing large data sets are used, for example, Data Mining, regression analysis, machine learning, data processing methods such as filtering, augmentation, and others. The practical relevance of this paper lies in the fact that the developed system can be used as an auxiliary system at environmental protection enterprises.

Compressed air is widely used as an energy carrier. The compressed air production systems are a part of the auxiliary systems of offsite facilities. It is worth noting that the production of com-pressed air is quite an energy-intensive process, so the potential for energy saving is quite large. There is increasing the efficiency of the compressed air production by developing technology solutions for air preparation in this work. The system of air drying by cooling and the source of cold are considered in this paper. The paper presents a comparison of cooling systems from steam compression and absorption refrigerating machines from the point of view of heat exchange, energy consumption for their own needs, providing cold with required parameters. The economic effect of the proposed circuit solution is given.

This paper explores the relationships amongst energy consumption, greenhouse gas emissions, development, and the state of the population and the economy. Using a comparative and critical analysis of economic and developmental data, the paper addresses these questions from the perspective of Türkiye . However, the analysis, arguments and conclusions are transposable to countries in similar socio-economic conditions.

Over the several years, there has been a significantly increased in the use of educational technology through chatbot applications. This paper aims to present the use of chatbots to help students meet their achievement in the science classroom. Chatbots can enhance potential of students’ learning by providing quick feedback, satisfying response, stimulating involvement, and personalize learning which depending on the specific requirements of each student. The potential applications of chatbots in a wide variety of scientific subjects, spanning various kind of knowledge. Additionally, it evaluates the familiarity of teachers with chatbots in the classroom. The paper discuss how it is useful, possibility, and ethical concerns in science education by shedding light on the possibility and effectiveness of using chatbots as teaching aids in science classes.

The paper considers the deployment of the testbed for definition of the exploit’s execution features to detect and score cyber-attacks. The paper describes the place of the proposed testbed in the approach to the cyber-attack detection and scoring. It defines the requirements to the testbed considering the introduced approach. The testbed infrastructure is defined and deployed considering the specified requirements. The introduced testbed infrastructure is justified. Finally, the technique of the testbed implementation for the feature extraction is introduced. The proposed testbed and technique allow combining advantages of the static and dynamic approaches to the exploits analysis and detecting and scoring known and previously unseen cyber-attacks.

The foundation of a country’s sustainable economic development rests on the availability of an ample supply of electrical energy. To remain competitive on the global stage, India must ensure the provision of sufficient electricity infrastructure to fuel its economic progress. Achieving developed nation status necessitates extending electricity access to every corner of the country. India, being primarily an agrarian nation, possesses abundant agricultural waste resources. This wealth of agricultural waste presents a valuable opportunity for electricity generation. Notably, agricultural husk emerges as a promising raw material for electricity generation, provided it undergoes proper and systematic processing. This endeavor aims to introduce the concept of electricity generation from agricultural husk, with a particular focus on rural areas in India. Agricultural husk-based small and medium power plants offer a pragmatic solution for generating and distributing electricity to underserved rural communities. Within this paper, we delve into the availability of agricultural husk resources in India, explore various feasibility studies, and elucidate the principal processes for generating electricity from rice husk. The overarching goal is to support India’s journey towards future development. This paper serves as a valuable resource for both governmental and private sector entities interested in establishing agricultural husk-based power plants in rural India. Ultimately, we aspire for this document to serve as a practical guideline for addressing the substantial electricity demand prevalent in India’s rural areas.

These manuscripts present a closed-loop IGBT-based fourquadrant chopper drive system for DC motors. This paper intends to improve DC motor control’s accuracy, effectiveness, and adaptability in a variety of applications. In this paper, we build and put into practice a closed-loop control system that incorporates IGBT in order to manage the speed and torque of DC motors in both directions. A feedback system with sensors for measuring motor speed and current is used in the closed-loop control scheme to ensure perfect regulation of motor parameters. The IGBT-based chopper drive architecture allows for smooth switching between forward and reverse motor operation as well as dynamic braking, making it appropriate for applications requiring four-quadrant operation. The main benefits of our suggested system are greater motor protection through fault detection and quick responses to external disturbances, improved speed and torque management, and lower energy consumption. We show experimental data that demonstrate our design’s capacity to maintain stable motor functioning across a variety of operating situations, validating its usefulness in real-world applications. The presented system simulation result is verified in MATLAB/Simulink software. The demonstrated results are motor speed, torque, current and voltage.

In the pursuit of sustainable transportation solutions, Electric Vehicles (EVs) have emerged as a promising alternative. This research paper provides an in-depth exploration of the crucial role played by Battery Management Systems (BMS) and conducts a comprehensive comparative analysis of various energy storage technologies for Electric Vehicles. The paper begins by elucidating the intricate components and functions of BMS through an illustrative block diagram, emphasizing its significance in ensuring safe and optimal battery operation. The study then conducts a meticulous analysis of key battery attributes, including energy density, power density, capacity, charge/discharge rates, life cycles, and cost per kWh. Supported by simulated data, the comparative analysis sheds light on the distinct performance characteristics of different battery types - Lithium-ion (Li-Ion), Lithium Iron Phosphate (LiFePO4), Nickel-Metal Hydride (NiMH), and Ultracapacitor. The outcomes offer a comprehensive perspective on their strengths and trade-offs, providing valuable insights for selecting suitable energy storage solutions. By translating intricate technical information into meaningful insights, this research empowers EV industry stakeholders to make informed decisions for enhanced EV performance, economic viability, and sustainable electric mobility.