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The paper obtained during the study was mainly obtained from wheat straw cellulose and Jerusalem artichoke cellulose, which contained chitosan of various concentrations. An increase in the mechanical properties of the obtained papers was observed in samples using the substance chitosan. A 1.0% chitosan was added to the paper, mainly based on various plant celluloses. It should be noted that the obtained paper products were used without bleaching due to the fact that it was recommended to use them for wrapping paper. The youngest results were observed in samples prepared from a composition of wheat straw and artichoke pulp. From the fiber morphology, it was observed that the sized paper fibers became stronger, denser and smoother. Keywords: chytazone, Natural polymers, fibers, cellulose. Biocomposites of chitosan (CS)/cellulose nanocrystals (CN) were prepared by using solution casting method. Influences of solution preparation method and CN content on the properties of composites were investigated. Mechanical stirring/ultrasonication or micro fluidization were used to disperse nanocrystals in the chitosan matrix. The prepared nanocomposites were characterized by FTIR, XRD, SEM, DSC, TGA, TMA and contact angle measurements.

The filter paper bio-templating method has become a promising pathway in the fabrication of MgO with tunned physicochemical features. The filter paper-templated MgO (MgO-FPT) has been subjected to several characterisation analyses, and it has revealed that filter paper templating has demonstrated a positive outcome toward an improvement of physicochemical features, i.e., improved surface reactivity and surface area compared to MgO prepared via direct thermal degradation method of magnesium salt (MgO-CT). As the evidence of the FTIR spectra, the MgO-FPT has demonstrated a surface rich CO2-associated functional group, which indicate the enhanced surface reactivity of the MgO, which increase of the adsorbent affinity toward CO2 (even from atmospheric surrounding). Together with the improved structural features compared to MgO-CT (two-fold high surface area), it has significantly refined the CO2 adsorption uptake capacity to almost 15 times higher than MgO-CT with only 0.247 mmol/g. This shows the potential filter paper bio-templating method for the metal oxide-based adsorbent fabrication for CO2 adsorption application.

A chitosan based coating was prepared where eggshell powder was added. Eggshell is a product that appears in large numbers in everyday life, so it has great potential as waste, which can be used to turn it into a valuable material. Cellulose sheets were made from secondary fiber, and after coated with the chitosan based solution to investigate the properties of the sheets. The results of the treated handsheets were compared with the results of the control sheet. The control sheets were compared with 4 different type of paper: coatings of chitosan with 5wt% and 10wt% eggshell powder, only chitosan coating, and paper where eggshell powder was added to the paper pulp. The use of the eggshell powder as an additive in the coating would be a promising material, because it can improve in a large extent the water resistance and the air barrier properties of the paper.

The Paper industry is an energy-intensive and one of the most energy-consuming industries in Indonesia. In this study, Paper Mill energy sources come from coal and renewable energy such as black liquor as a substitute for coal and on-grid 9MW PV system are reassessed by using optimization software, HOMER. This study aims to present a feasibility study of increasing the use of renewable energy sources in Paper Mill to reduce coal consumption for more sustainability. The software HOMER is used as a tool to determine the most feasible combination of component considered in the study. It is feasible to reduce 10,84% coal consumption kg per year with the optimal renewable energy mix consisting of additional 24MW rooftop PV system and 5,94kW hydrokinetic energy from Kampar River located 6 km from the plant. Renewable fraction increased to 16%. This study result is good for sustainable growth of Paper Mill business that investments in climate and nature to support the Indonesian government in achieving net zero emissions.

In this study, cellulose was extracted from Heliánthus tuberósus (Jerusalem artichoke) stems, and its quality indicators were thoroughly investigated. The isolation process involved the removal of impurities and non-cellulosic components, resulting in a purified cellulose sample suitable for further analysis and application.To explore the potential of Heliánthus tuberósus cellulose, composite paper was produced by incorporating basalt fiber into the cellulose matrix. The resulting paper was subjected to comprehensive testing to evaluate its mechanical properties, with a particular focus on tensile strength and tensile length.The tensile strength of the composite paper was determined using standardized testing methods, providing quantitative data on the material's ability to withstand applied forces without breaking or deforming. Tensile length, on the other hand, refers to the maximum elongation the paper can undergo before rupture occurs. These properties were assessed to gauge the overall performance and suitability of the composite paper for various applications.The obtained results were presented in a clear and concise manner, utilizing tables and graphs to facilitate data interpretation and comparison. Tables allowed for the tabulation of the measured tensile strength and tensile length values, providing a comprehensive overview of the material's mechanical characteristics. Graphs were employed to visualize trends, patterns, and potential correlations between different variables, aiding in a deeper understanding of the composite paper's behavior under various loading conditions.

Abstract. In this study, a composite material was successfully produced by incorporating waste paper and basalt fibers. The utilization of waste paper as a raw material contributes to sustainable practices and waste reduction. The physical and mechanical properties of the obtained composite material were comprehensively investigated to evaluate its potential for various applications.The physical parameters of the composite material, such as density and porosity, were measured to assess its structural characteristics. Density provides insights into the compactness and mass per unit volume of the composite, while porosity indicates the presence of voids or open spaces within the material. These parameters play a crucial role in determining the overall performance and suitability of the composite for specific applications.Furthermore, the mechanical properties of the composite material were examined to evaluate its strength, stiffness, and durability. Tensile strength, flexural strength, and impact resistance were among the key mechanical parameters studied. Tensile strength determines the material's ability to withstand pulling forces, while flexural strength measures its resistance to bending or deformation. Impact resistance evaluates the material's ability to absorb energy when subjected to sudden or dynamic loads.

A worldwide evaluation of the present status of renewable-energy generation, with a focus on photo-voltaic (PV) solar energy for the production of electricity. The most pertinent elements of the development and experiences of nations working to build and use these technologies are covered in this article. It also cites studies that highlight the efforts made by nations to reduce their emissions of green-house gas or to enhance the quality and accessibility of electric energy generation in light of their unique geographic and environmental circumstances. These studies focus in particular on remote communities that have limited access to the national power grid due to technological or financial constraints. This paper focusses on renewable-energy might serve as a starting point for assessing how clean energy affects the world's energy supply and demand, they are becoming an increasingly popular option in terms of cost and efficiency, which can attract new investors. By analysing recent data, case studies, and literature, this review aims to provide stakeholders with insights into the achievements and hurdles of solar energy, fostering informed decisions towards a sustainable and resilient energy future.

The article examines current trends in the use of green technologies in construction in order to create sustainable and environmentally friendly cities. The authors highlight various aspects of green innovation, such as energy-efficient building materials, waste management systems, sustainable infrastructure and energy efficiency of buildings. The paper also condemns the benefits of green innovation, including reducing environmental impacts, improving the energy efficiency of buildings, improving air and water quality in urban environments, and examines examples of successful implementation of green technologies in various countries and cities. The researchers call for the active introduction of green innovations in construction in order to create sustainable cities that can combine modern amenities with minimal impact on natural resources. The article emphasizes that green innovations in construction not only contribute to reducing the negative impact on the environment, but can also significantly save resources and costs for the operation of buildings in the long term. The authors draw attention to the fact that the support and development of green technologies in construction can lead to job creation, stimulate innovation and improve the quality of life in cities. The role of state and municipal authorities in promoting green initiatives, implementing sustainable construction standards, as well as providing financial incentives for enterprises actively involved in creating environmentally sustainable urban environments is also highlighted. In general, the paper notes the need to understand the importance of the transition to green innovations in construction in order to ensure the sustainability of cities, improve the quality of life of citizens, and, what is especially important in the modern world, to cope with the challenges of climate change.

Efficient use of agricultural tractors is largely determined by the operating modes of its power units. Taking into account the variable nature of external loads, it is necessary to provide structural devices in the tractor, which smooth out changes in hook load, thus reducing the negative impact of external conditions on the operation of its power plant. The present paper is devoted to the design of a tractor attachment with variable characteristics. The methods of studying the variable traction force are analyzed on the output parameters of the technological process, as well as on the power and economic indicators of the power unit. Force analysis of the proposed attachment device is carried out and formulas are obtained to determine the forces and moments at the characteristic points of the device. The paper is of interest to engineers and technicians involved in the creation of promising design schemes for tractor tractors of various operational purposes.

A growing concern over climate change and the depletion of conventional energy resources have led to the urgent need for sustainable and resilient energy solutions. The optimization of the size of renewable sources is crucial to maximizing their effectiveness. In contrast to conventional single-objective optimization, the multi-objective technique aims to achieve a trade-off between energy cost and power supply reliability. Due to this need, microgrids (MG) have emerged as a promising paradigm, allowing for localized and decentralized energy generation and distribution. Consequently, the conventional techniques for modelling and optimizing exhibit numerous limitations as the power grid continues to produce substantial volumes of high-dimensional and diverse data types. This review paper examines the use of metaheuristic algorithms in the context of multi-objective energy optimization for hybrid renewable energy-integrated microgrids. A comparative analysis of diverse metaheuristic algorithms for microgrid optimization is provided in this paper, which emulates natural phenomena, such as evolutionary processes and swarm dynamics. Based on the findings of case studies, it can be concluded that trade-offs exist between various objectives, eventually leading to the development of both resilient and efficient microgrid designs. By reviewing sustainable energy solutions, and advocating microgrids as viable alternatives to conventional centralized power systems, the review enhances the advancement of sustainable energy solutions.

Urbanization in Indonesia has led to increased waste generation, posing significant challenges to sustainability. Until now, the method for collecting and transporting waste in Indonesia is still done manually. Nusantara, the New State Capital of Indonesia, aims to address these challenges through the adoption of a Smart Waste Management System (SWMS), leveraging IoT and ICT technologies. This paper reviews the current state of technology research in this field. The proposed SWMS framework integrates various types of sensors for waste monitoring, categorizing, and real-time tracking. This system enhances operational efficiency by triggering waste pickup when bin fill levels exceed a set threshold and directing waste pickup vehicles equipped with GPS and surveillance systems to specific locations. Managed by a central management system accessible via web or mobile applications, this framework exemplifies an innovative approach to waste management in Nusantara, aligning with the city’s vision of becoming a smart and sustainable urban area. The paper concludes that integrating IoT and ICT in waste management is crucial for achieving sustainable urban environments. The successful implementation of SWMS in Nusantara could serve as a model for other cities globally.

This paper addresses the challenges posed by Industry 4.0 and the COVID-19 pandemic, which necessitate digital transformation in educational institutions. It focuses on the specific issues of integrating enterprise information systems to facilitate this transformation. The solution proposed is the development of an integrated information system to manage operational processes within educational institutions. This system targets key domains including student admissions, academics, finance, and human resources, utilizing role-based access control (RBAC) and Single Sign-On (SSO) for efficiency and security. The methodology involves a collaborative effort under the Matching Fund program by the Ministry of Education, Culture, Research, and Technology of Indonesia. This collaboration includes the Universitas Islam Indonesia and the Salman Alfarisi Yogyakarta educational institution. The approach includes defining the project, collecting, and reviewing lessons, creating a repository of these lessons, and disseminating the findings. The project successfully developed and implemented an integrated information system, addressing the initial challenges and improving organizational efficiency in the participating educational institution. The system’s deployment covered multiple key operational domains, significantly digitizing the institution’s processes. This paper contributes valuable insights and best practices from the integration project, serving as a model for other universities and educational institutions. It showcases the potential of collaborative efforts in accelerating digital transformation in education, especially in the context of Indonesia’s vast network of universities and educational institutions.

The country’s economic development and people’s lives require reliable transportation and logistics services. Therefore, road maintenance policies and techniques must be more comprehensive to ensure transportation infrastructure operations’ efficiency. The inefficiency of road maintenance, among others, is due to the failure to identify and predict the level of damage that can cause fundamental data anomalies. Therefore, the current scientific development of road maintenance must be able to take advantage of the convenience of technology. Widespread technology implementation on the Internet of Think (IoT), big data, and data mining (DM) can be a solution to developing a better pavement management system. However, implementing these technologies is challenging due to the weak conception and availability of currently available resources. This paper offers a pavement system management implementation concept that can be developed in Indonesia to improve the existing system. The study results show that IoT, big data, and DM are believed to support a more intelligent and comprehensive pavement management system. The concept offered consists of three main things: identification of damage and 3D pavement modeling, data analysis, decision support systems, and collaboration of intelligent solutions in implementing maintenance in the field. This paper is equipped with an illustration of the concept of road maintenance based on IoT, big data, and DM, which can be implemented intelligently and simply in Indonesia.

Aim of this paper is to explore the development of mining operations in deep quarries utilizing automobile and combined transport systems to overcome these challenges. The use of automobiles in mining has been a growing trend, offering flexibility, maneuverability, and increased productivity. In deep quarries, traditional automobile transport faces limitations in terms of reach and efficiency, combined transport systems incorporating a combination of automobiles, conveyor belts, and other transport mechanisms have been proposed. This paper discusses the advantages of automobile transport in deep quarries, including its ability to navigate narrow passages and transport smaller loads efficiently. It examines the integration of combined transport systems, which leverage the strengths of automobiles alongside other modes of transportation to optimize mining operations. Key considerations in the development of these systems include infrastructure design, vehicle specifications, safety protocols, and environmental impact. By implementing innovative solutions tailored to the specific challenges of deep quarry mining, such as automated vehicle control and monitoring systems, it is possible to enhance efficiency, reduce operational costs, and improve safety standards. Also, this paper highlights case studies and examples of successful implementations of automobile and combined transport systems in deep quarries around the world. These real-world examples demonstrate the feasibility and benefits of adopting such approaches in challenging mining environments. In the paper criteria requirements and recommendations for the implementation of this process are presented in the technological processes of compaction using separators, which are carried out during the construction of highways, and the interdependence of indicators is presented through tables, graphs and calculation expressions.

This paper describes an approach to the automatic generation of a mivar knowledge base of a three-dimensional logic space. This knowledge base is created to provide three-dimensional robot movement. Automatic generation of mivar knowledge bases is necessary for the further solution of the problem of planning three-dimensional routes of robots and robotic complexes. This work is the basis for solving problems of resource allocation optimization in the field of transport logistics and machine learning artificial intelligence based on the application of mivar technologies. The variant of practical realization of the automated technique of sequential removal of mivar network rules and search for new robot motion trajectories for their further comparison by the number of activated transition rules on the way from the initial location to the target one is considered. Mivar-based logic artificial intelligence technologies offer great opportunities for dynamic route finding in real time, which will help in further development of machine learning artificial intelligence in the field of transport systems. The paper is intended for researchers involved in the development of mivar expert systems for solving problems of three-dimensional movement of robots and optimizing production planning systems.

The paper considers options for reducing environmental losses in Polotsk and Novopolotsk through the development of trolleybus and tram systems – various types of urban electric transport. In order to reduce the costs of creating transport (including charging) infrastructure, as well as operating costs, the effectiveness of such systems has been determined when using not only classic types of transport, but also hybrid buses, electric buses, duo-buses. Approaches and methods have been developed to improve the quality of passenger service without deteriorating the environmental situation – this will become possible thanks to the development of tram and trolleybus traffic in Polotsk and Novopolotsk. Variants of scenarios for the use of various types of urban eclectic transport in the cities under study are presented, which will reduce investment in vehicles and the cost of creating an operational base at the expense of existing production facilities, for example, a tram fleet. The proposals outlined in the paper are aimed at improving the environmental situation in these cities by reducing the volume of emissions of harmful substances by buses, especially on the central streets

The purpose of this paper is to study the application of ChatGPT and BERT models in the field of mechanical engineering. In the context of machine learning, the ChatGPT and BERT models can be applied to various natural language processing tasks such as analyzing technical documentation and building instructions according to a particular version of the documentation, diagnosing malfunctions or customer service. The paper discusses the fundamental features of BERT and ChatGPT models, their origin, and also investigates the main architectural features and identifies the main advantages and disadvantages of the models. The paper analyzes and selects various natural language processing tasks to test the models’ ability to understand natural language in the context of machine learning. The selected criterion tasks are divided into semantic groups to identify the capabilities of ChatGPT and BERT models in each of three areas: logical inference tasks, paraphrasing tasks, and text similarity tasks. The paper also discusses the concept of operational design, which involves developing inputs that guide the models to produce desired outputs. The paper quantitatively analyzes and compares the performance of BERT and ChatGPT based models. The reasons for the bottlenecks of ChatGPT model in natural language understanding tasks are discovered and investigated. Possible improvements of ChatGPT model performance using the mivar approach are considered.

The paper provides research on the use of modern drones or unmanned aerial vehicles (UAVs) for effective work in the fields of architectural design, construction management and monitoring. The authors examined the theoretical foundations and practical features of modern unmanned aerial vehicles (UAVs) or drones. Statistics on the structure of the global UAV market are presented. The detailed description of the primary applications of drones in the construction sector is provided. The main advantages of new technologies over traditional ones are noted. The paper pays attention to the issues of increasing safety at construction sites. The introduction of innovative technologies is necessary for the development of the construction industry. The use of such technologies will reduce task completion times, improve work quality, improve safety standards and reduce costs. At the same time, the authors noted some shortcomings of modern unmanned technologies. In the conclusion of the paper, insights are presented regarding the future possibilities for integrating unmanned aerial vehicles in construction projects.

This paper describes the basic aim of Ş -proximit space for non-empty sets. The relationship between approach space and Ş-proximit space has been clarified. This paper demonstrates that all metric spaces are Ş-proximit spaces. But the opposite is not always true. We define SA-contraction and present various features and the results. In addition, we define new Ş-proximit normed space. We demonstrate that any proximit normed space is normed. But the opposite is not always true. We define the concepts of the Ş -proximit semigroup, Ş-proximit group, and Ş-proximit vector space via instances of problem-solving techniques. We also discussed the definitions of Cauchy sequence, cluster point, Ş -convergent sequence, and Ş -complete.

This paper introduces a novel method of managing railway tracks by utilizing a control system based on microprocessors. The creation and deployment of an advanced system intended to improve the effectiveness, security, and dependability of railway operations is the main objective. The suggested system makes use of cutting-edge microprocessor technology to keep an eye on, manage, and repair a number of railway infrastructure components, such as train movements, signal operations, and track integrity. The system offers an automated approach to identify and resolve any problems such track defects, signal failures, and unwanted access through real-time data collecting and processing. Additionally, the integration of predictive maintenance algorithms helps in preemptive identification of wear and tear on tracks, thereby reducing the likelihood of accidents and improving overall service quality. The paper details the architectural design of the system, its operational mechanisms, and the results of a series of simulations and real-world tests conducted to validate its effectiveness. The findings demonstrate significant improvements in operational efficiency, reduced maintenance costs, and enhanced passenger safety, illustrating the potential of microprocessor-based systems in revolutionizing railway infrastructure management.

The exploration of the cutting edge of wastewater treatment, concentrating on the ever-changing field of heavy metal remediation uses of nanotechnology is a major requisite for sustainability. The investigation covers a wide range of nanotechnology topics, such as photocatalysis, adsorption, catalysis, and novel nanomembranes, providing a thorough grasp of its crucial function in water treatment. Examining specific nanomaterials such as nanoparticles, nanotubes, and nanofibers, the study evaluates their applications, highlighting their unique contributions to heavy metal removal. However, the paper meticulously dissects the challenges hindering the widespread use of nanoparticles in wastewater treatment, with a keen focus on graphene oxide nano-sheets, magnetic nanoparticles, polymeric hydrogels, and activated carbon. Novel techniques incorporating nanotechnology for heavy metal removal are also explored. The conclusion provides a synthesis of findings and offers recommendations for overcoming existing challenges, paving the way for an enhanced integration of nanotechnology in wastewater treatment practices. This paper serves as a vital resource for researchers, practitioners, and policymakers engaged in advancing sustainable and effective solutions for heavy metal remediation in wastewater treatment systems.

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.