The 100 most-cited articles in Heliyon, 2024

Over the past decade, there has been a notable surge in AI-driven research, specifically geared toward enhancing crucial clinical processes and outcomes. The potential of AI-powered decision support systems to streamline clinical workflows, assist in diagnostics, and enable personalized treatment is increasingly evident. Nevertheless, the introduction of these cutting-edge solutions poses substantial challenges in clinical and care environments, necessitating a thorough exploration of ethical, legal, and regulatory considerations. A robust governance framework is imperative to foster the acceptance and successful implementation of AI in healthcare. This article delves deep into the critical ethical and regulatory concerns entangled with the deployment of AI systems in clinical practice. It not only provides a comprehensive overview of the role of AI technologies but also offers an insightful perspective on the ethical and regulatory challenges, making a pioneering contribution to the field. This research aims to address the current challenges in digital healthcare by presenting…

Water contamination is an escalating emergency confronting communities worldwide. While traditional adsorbents have laid the groundwork for effective water purification, their selectivity, capacity, and sustainability limitations have driven the search for more advanced solutions. Despite many technological advancements, economic, environmental, and regulatory hurdles challenge the practical application of advanced adsorption techniques in large-scale water treatment. Integrating nanotechnology, advanced material fabrication techniques, and data-driven design enabled by artificial intelligence (AI) and machine learning (ML) have led to a new generation of optimized, high-performance adsorbents. These advanced materials leverage properties like high surface area, tailored pore structures, and functionalized surfaces to capture diverse water contaminants efficiently. With a focus on sustainability and effectiveness, this review highlights the transformative potential of these advanced materials in setting new benchmarks for water purification technologies. This article delivers an…

The incidence of water pollution in developing countries is high due to the lack of regulatory policies and laws that protect water bodies from anthropogenic activities and industrial wastewater. Industrial wastewater contains significant amounts of heavy metals that are detrimental to human health, aquatic organisms, and the ecosystem. The focus of this review was to evaluate the sources and treatment methods of wastewater, with an emphasis on technologies, advantages, disadvantages, and innovation. It was observed that conventional methods of wastewater treatment (such as flotation, coagulation/flocculation, and adsorption) had shown promising results but posed certain limitations, such as the generation of high volumes of sludge, relatively low removal rates, inefficiency in treating low metal concentrations, and sensitivity to varying pH. Recent technologies like nanotechnology, photocatalysis, and electrochemical coagulation have significant advantages over conventional methods for removing heavy metals, including higher removal rates, improved energy efficiency, and greater…

Advanced oxidation processes (AOPs) are a growing research field with a large variety of different process variants and materials being tested at laboratory scale. However, despite extensive research in recent years and decades, many variants have not been transitioned to pilot- and full-scale operation. One major concern are the inconsistent experimental approaches applied across different studies that impede identification, comparison, and upscaling of the most promising AOPs. The aim of this tutorial review is to streamline future studies on the development of new solutions and materials for advanced oxidation by providing guidance for comparable and scalable oxidation experiments. We discuss recent developments in catalytic, ozone-based, radiation-driven, and other AOPs, and outline future perspectives and research needs. Since standardized experimental procedures are not available for most AOPs, we propose basic rules and key parameters for lab-scale evaluation of new AOPs including selection of suitable probe compounds and scavengers for the measurement of (major) reactive…

This paper undertakes a comprehensive investigation into incorporating sustainability within higher education, aligning with the United Nations' Sustainable Development Goals (SDGs). Utilizing quantitative and qualitative research methods, our study delves into the status quo, methodologies, and impacts of sustainability education across a spectrum of international and local settings, with a specific lens on the United Arab Emirates. Our analysis spans various topics, from best practices in sustainability integration and educational frameworks to the influence of global initiatives like the Impact Ranking on promoting SDG-aligned transformations within academic institutions. Highlighting case studies from the UAE, we provide concrete evidence of successful sustainability strategies and interventions. These are juxtaposed with a global overview that uncovers the varying challenges and opportunities present in implementing sustainability education worldwide. Among our key findings is the essential role of interdisciplinary approaches and the critical need for active faculty…

Introduction: Higher education institutions face persistent challenges of student retention and academic progress. Personalized adaptive learning has the potential to address these issues as it leverages educational technology to tailor learning pathways according to individual student needs. Objective: To elucidate the key characteristics of personalized adaptive learning in higher education and its impact on academic performance and engagement. Methods: The Joanna Briggs Institute scoping review methodology was followed. Key international databases were searched to retrieve articles. The titles and abstracts of selected studies were imported into Covidence. Peer-reviewed journal articles, theses, and dissertations focusing on undergraduate students engaged in personalized adaptive learning, published between 2012 and 2024 were included. Data was extracted and charted in Covidence. Results were summarised through a narrative synthesis and visually presented in a PRISMA-ScR flow diagram. Results: This review included 69 eligible studies. The findings reveal insights into the…

Hyperspectral imaging has emerged as an effective powerful tool in plentiful military, environmental, and civil applications over the last three decades. The modern remote sensing approaches are adequate for covering huge earth surfaces with phenomenal temporal, spectral, and spatial resolutions. These features make HSI more effective in various applications of remote sensing depending upon the physical estimation of identical material identification and manifold composite surfaces having accomplished spectral resolutions. Recently, HSI has attained immense significance in the research on safety and quality assessment of food, medical analysis, and agriculture applications. This review focuses on HSI fundamentals and its applications like safety and quality assessment of food, medical analysis, agriculture, water resources, plant stress identification, weed & crop discrimination, and flood management. Various investigators have promising solutions for automatic systems depending upon HSI. Future research may use this review as a baseline and future advancement analysis.

Flavonoids are organic compounds characterized by a range of phenolic structures, which are abundantly present in various natural sources such as fruits, vegetables, cereals, bark, roots, stems, flowers, tea, and wine. The health advantages of these natural substances are renowned, and initiatives are being taken to extract the flavonoids. Apigenin, galangin, hesperetin, kaempferol, myricetin, naringenin, and quercetin are the seven most common compounds belonging to this class. A thorough analysis of bibliographic records from reliable sources including Google Scholar, Web of Science, PubMed, ScienceDirect, MEDLINE, and others was done to learn more about the biological activities of these flavonoids. These flavonoids appear to have promising anti-diabetic, anti-inflammatory, antibacterial, antioxidant, antiviral, cytotoxic, and lipid-lowering activities, according to evidence from in vitro , in vivo , and clinical research. The review contains recent trends, therapeutical interventions, and futuristic aspects of flavonoids to treat several diseases like diabetes, inflammation,…

Water holds great significance as a vital resource in our everyday lives, highlighting the important to continuously monitor its quality to ensure its usability. The advent of the. The Internet of Things (IoT) has brought about a revolutionary shift by enabling real-time data collection from diverse sources, thereby facilitating efficient monitoring of water quality (WQ). By employing Machine learning (ML) techniques, this gathered data can be analyzed to make accurate predictions regarding water quality. These predictive insights play a crucial role in decision-making processes aimed at safeguarding water quality, such as identifying areas in need of immediate attention and implementing preventive measures to avert contamination. This paper aims to provide a comprehensive review of the current state of the art in water quality monitoring, with a specific focus on the employment of IoT wireless technologies and ML techniques. The study examines the utilization of a range of IoT wireless technologies, including Low-Power Wide Area Networks (LpWAN), Wi-Fi, Zigbee, Radio Frequency…

The agriculture sector is confronted with numerous challenges in the quest for accurate crop yield estimation, which is essential for efficient resource management and mitigating food scarcity in a rapidly growing global population. This research paper delves into the application of advanced Artificial Intelligence (AI) techniques to enhance crop yield estimation in the context of diverse agricultural challenges. Through a systematic literature review and analysis of relevant studies, this paper explores the role of AI methods, such as Machine Learning (ML) and Deep Learning (DL), in addressing the complexities posed by geographical variations, crop diversity, and cultivation areas. The review identifies a wealth of AI-powered solutions employed in crop yield prediction, emphasizing the importance of precise environmental and agricultural data. Key factors contributing to accurate estimation include temperature, rainfall, soil type, humidity, and various vegetation indices, such as NDVI, EVI, LAI, and NDWI. The research paper also examines the algorithms frequently utilized in the…

Federated learning (FL) is a distributed machine learning process, which allows multiple nodes to work together to train a shared model without exchanging raw data. It offers several key advantages, such as data privacy, security, efficiency, and scalability, by keeping data local and only exchanging model updates through the communication network. This review paper provides a comprehensive overview of federated learning, including its principles, strategies, applications, and tools along with opportunities, challenges, and future research directions. The findings of this paper emphasize that federated learning strategies can significantly help overcome privacy and confidentiality concerns, particularly for high-risk applications.

This mixed-method study explores the acceptance of ChatGPT as a tool for Metacognitive Self-Regulated Learning (MSRL) among academics. Despite the growing attention towards ChatGPT as a metacognitive learning tool, there is a need for a comprehensive understanding of the factors influencing its acceptance in academic settings. Engaging 300 preservice teachers through a ChatGPT-based scenario learning activity and utilizing convenience sampling, this study administered a questionnaire based on the proposed Technology Acceptance Model at UTM University's School of Education. Structural equation modelling was applied to analyze participants' perspectives on ChatGPT, considering factors like MSRL's impact on usage intention. Post-reflection sessions, semi-structured interviews, and record analysis were conducted to gather results. Findings indicate a high acceptance of ChatGPT, significantly influenced by personal competency, social influence, perceived AI usefulness, enjoyment, trust, AI intelligence, positive attitude, and metacognitive self-regulated learning. Interviews and record…

The field of lightweight composite structures has witnessed significant advancements in recent years, revolutionizing numerous industries through their exceptional combination of strength, weight reduction and versatility. This review paper provides a comprehensive and in-depth analysis of these ground breaking materials. It elucidates fundamental concepts of lightweight composite structures, exploring their composition, classification, physical and mechanical properties as well as recent strides in their engineering applications. Crucially, this review highlights the recent progress and developments of lightweight composite materials. From aerospace to automotive, from construction to sporting goods, these advanced materials are transforming various industries by combining strength with reduced weight. Emphasizing the role of lightweight composites in energy-efficient systems, the paper underscores their significance in resource optimization and sustainable engineering practices. A detailed examination of various types of composites, such as polymer matrix composites, ceramic…

Deep Reinforcement Learning (DRL) has gained significant adoption in diverse fields and applications, mainly due to its proficiency in resolving complicated decision-making problems in spaces with high-dimensional states and actions. Deep Deterministic Policy Gradient (DDPG) is a well-known DRL algorithm that adopts an actor-critic approach, synthesizing the advantages of value-based and policy-based reinforcement learning methods. The aim of this study is to provide a thorough examination of the latest developments, patterns, obstacles, and potential opportunities related to DDPG. A systematic search was conducted using relevant academic databases (Scopus, Web of Science, and ScienceDirect) to identify 85 relevant studies published in the last five years (2018-2023). We provide a comprehensive overview of the key concepts and components of DDPG, including its formulation, implementation, and training. Then, we highlight the various applications and domains of DDPG, including Autonomous Driving, Unmanned Aerial Vehicles, Resource Allocation, Communications and the Internet of…

Despite the wave of enthusiasm for the role of Artificial Intelligence (AI) in reshaping education, critical voices urge a more tempered approach. This study investigates the less-discussed 'shadows' of AI implementation in educational settings, focusing on potential negatives that may accompany its integration. Through a multi-phased exploration consisting of content analysis and survey research, the study develops and validates a theoretical model that pinpoints several areas of concern. The initial phase, a systematic literature review, yielded 56 relevant studies from which the model was crafted. The subsequent survey with 260 participants from a Saudi Arabian university aimed to validate the model. Findings confirm concerns about human connection, data privacy and security, algorithmic bias, transparency, critical thinking, access equity, ethical issues, teacher development, reliability, and the consequences of AI-generated content. They also highlight correlations between various AI-associated concerns, suggesting intertwined consequences rather than isolated issues. For…

A Digital Twin (DT) is a digital copy or virtual representation of an object, process, service, or system in the real world. It was first introduced to the world by the National Aeronautics and Space Administration (NASA) through its Apollo Mission in the '60s. It can successfully design a virtual object from its physical counterpart. However, the main function of a digital twin system is to provide a bidirectional data flow between the physical and the virtual entity so that it can continuously upgrade the physical counterpart. It is a state-of-the-art iterative method for creating an autonomous system. Data is the brain or building block of any digital twin system. The articles that are found online cover an individual field or two at a time regarding data analysis technology. There are no overall studies found regarding this manner online. The purpose of this study is to provide an overview of the data level in the digital twin system, and it involves the data at various phases. This paper will provide a comparative study among all the fields in which digital twins have been…

Post-hoc comparison procedures are commonly used to determine which group means differ after a significant analysis of variance (ANOVA). Several post-hoc tests have been proposed, but their use requires certain assumptions to be met, such as normality, equality of variance, and balanced group size. This review examined the statistical literature on post-hoc tests and their use in the environmental and biological sciences. Through this review, we found that post-hoc tests are effective but often inadequately used in these sciences. We conducted a search of reputed search engines to identify articles in which post-hoc tests were used and found ten post-hoc tests used in the environmental and biological literature. Tukey HSD (30.04%), Duncan's (25.41%) and Fisher's LSD (18.15%) were the most commonly used post-hoc tests over the past 20 years, whereas the Games-Howell (1.13%), Holm-Bonferroni (1.25%), and Scheffe's tests (2.25%) were the least used. The choice of post-hoc test depended on the statistical method used prior. In addition, the assumptions of applying post-hoc tests were…

Mycotoxins, harmful compounds produced by fungal pathogens, pose a severe threat to food safety and consumer health. Some commonly produced mycotoxins such as aflatoxins, ochratoxin A, fumonisins, trichothecenes, zearalenone, and patulin have serious health implications in humans and animals. Mycotoxin contamination is particularly concerning in regions heavily reliant on staple foods like grains, cereals, and nuts. Preventing mycotoxin contamination is crucial for a sustainable food supply. Chromatographic methods like thin layer chromatography (TLC), gas chromatography (GC), high-performance liquid chromatography (HPLC), and liquid chromatography coupled with a mass spectrometer (LC/MS), are commonly used to detect mycotoxins; however, there is a need for on-site, rapid, and cost-effective detection methods. Currently, enzyme-linked immunosorbent assays (ELISA), lateral flow assays (LFAs), and biosensors are becoming popular analytical tools for rapid detection. Meanwhile, preventing mycotoxin contamination is crucial for food safety and a sustainable food supply. Physical,…

Plastic products are indispensable across various applications, yet their disposal poses significant environmental hazards, such as groundwater contamination, soil degradation, and marine ecosystem threats, impacting both human health and ecological balance. Key issues include rapid development and population growth, inadequate technical skills for hazardous waste management, insufficient infrastructure for recycling, and a general lack of awareness regarding regulations. This study offers a comprehensive analysis of plastic waste generation, its sources, current management practices, and its environmental impacts, along with mitigation measures. Globally, predictions indicate that plastic production could exceed 650 million tons by 2050, representing a staggering more than 22000 % increase compared to 1950, highlighting the pressing need for action. Moreover, due to their chemical structures and prolonged degradation periods, plastic waste (PW) can lead to cancer, nervous system damage, rapid genetic changes, and metabolic disorders in humans. In that scenario, waste-to-energy and…

Lead (Pb) is a highly toxic contaminant that is ubiquitously present in the ecosystem and poses severe environmental issues, including hazards to soil-plant systems. This review focuses on the uptake, accumulation, and translocation of Pb metallic ions and their toxicological effects on plant morpho-physiological and biochemical attributes. We highlight that the uptake of Pb metal is controlled by cation exchange capacity, pH, size of soil particles, root nature, and other physio-chemical limitations. Pb toxicity obstructs seed germination, root/shoot length, plant growth, and final crop-yield. Pb disrupts the nutrient uptake through roots, alters plasma membrane permeability, and disturbs chloroplast ultrastructure that triggers changes in respiration as well as transpiration activities, creates the reactive oxygen species (ROS), and activates some enzymatic and non-enzymatic antioxidants. Pb also impairs photosynthesis, disrupts water balance and mineral nutrients, changes hormonal status, and alters membrane structure and permeability. This review provides consolidated…

Rapid advancements in the field of 3D printing in the last several decades have made it possible to produce complex and unique parts with remarkable precision and accuracy. Investigating the use of 3D printing to create various high-performance materials is a relatively new field that is expanding exponentially worldwide. Automobile, biomedical, construction, aerospace, electronics, and metal and alloy industries are among the most prolific users of 3D printing technology. Modern 3D printing technologies, such as polymer matrices that use fiber-reinforced composites (FRCs) to enhance the mechanical qualities of printed components greatly, have been useful to several industries. High stiffness and tensile strength lightweight components are developed from these materials. Fiber-reinforced composites have a wide range of applications, such as military vehicles, fighter aircraft, underwater structures, shelters, and warfare equipment. Fabricating FRCs using fused deposition modeling (FDM) is also advantageous over other 3D printing methods due to its low cost and ease of operation. The…

Carbon dots (CDs) have emerged as a versatile and promising carbon-based nanomaterial with exceptional optical properties, including tunable emission wavelengths, high quantum yield, and photostability. CDs are appropriate for various applications with many benefits, such as biocompatibility, low toxicity, and simplicity of surface modification. Thanks to their tunable optical properties and great sensitivity, CDs have been used in sensing as fluorescent probes for detecting pH, heavy metal ions, and other analytes. In addition, CDs have demonstrated potential as luminescence converters for white organic light-emitting diodes and light emitters in optoelectronic devices due to their superior optical qualities and exciton-independent emission. CDs have been used for drug administration and bioimaging in the biomedical field due to their biocompatibility, low cytotoxicity, and ease of functionalization. Additionally, due to their stability, efficient charge separation, and low recombination rate, CDs have shown interesting uses in energy systems, such as photocatalysis and energy…

The advancement of artificial intelligence (AI) and the ubiquity of social media have become transformative agents in contemporary educational ecosystems. The spotlight of this inquiry focuses on the nexus between AI and social media usage in relation to academic performance and mental well-being, and the role of smart learning in facilitating these relationships. Using partial least squares-structural equation modeling (PLS-SEM) on a sample of 401 Chinese university students. The study results reveal that both AI and social media have a positive impact on academic performance and mental well-being among university students. Furthermore, smart learning serves as a positive mediating variable, amplifying the beneficial effects of AI and social media on both academic performance and mental well-being. These revelations contribute to the discourse on technology-enhanced education, showing that embracing AI and social media can have a positive impact on student performance and well-being.

The construction industry faces many challenges, including schedule and cost overruns, productivity constraints, and workforce shortages. Compared to other sectors, it lags in digitalization in every project phase. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies revolutionizing the construction sector. However, a discernible gap persists in systematically categorizing the applications of these technologies throughout the various phases of the construction project life cycle. In response to this gap, this research aims to present a thorough assessment of the deployment of AI and ML across diverse phases in construction projects, with the ultimate goal of furnishing valuable insights for the effective integration of these intelligent systems within the construction sector. A thorough literature review was performed to identify AI and ML applications in the building sector. After scrutinizing the literature, the applications of AI and ML were presented based on a construction project life cycle. A critical review of existing literature…

Microbial fuel cells (MFCs) are promising for generating renewable energy from organic matter and efficient wastewater treatment. Ensuring their practical viability requires meticulous optimization and precise design. Among the critical components of MFCs, the membrane separator plays a pivotal role in segregating the anode and cathode chambers. Recent investigations have shed light on the potential benefits of membrane-less MFCs in enhancing power generation. However, it is crucial to recognize that such configurations can adversely impact the electrocatalytic activity of anode microorganisms due to increased substrate and oxygen penetration, leading to decreased coulombic efficiency. Therefore, when selecting a membrane for MFCs, it is essential to consider key factors such as internal resistance, substrate loss, biofouling, and oxygen diffusion. Addressing these considerations carefully allows researchers to advance the performance and efficiency of MFCs, facilitating their practical application in sustainable energy production and wastewater treatment. Accelerated substrate…

AI-powered chatbots hold great promise for enhancing learning experiences and outcomes in today's rapidly evolving education system. However, despite the increasing demand for such technologies, there remains a significant research gap regarding the factors influencing users' acceptance and adoption of AI-powered chatbots in educational contexts. This study aims to address this gap by investigating the factors that shape users' attitudes, intentions, and behaviors towards adopting ChatGPT for smart education systems. This research employed a quantitative research approach, data were collected from 458 of participants through a structured questionnaire designed to measure various constructs related to technology acceptance, including perceived ease of use, perceived usefulness, feedback quality, assessment quality, subject norms, attitude towards use, and behavioral intention to use ChatGPT. Structural model analysis (SEM) Statistical techniques were then utilized to examine the relationships between these constructs. The findings of the study revealed that Perceived ease of use and…

Energy generation and management are relevant for both utilities and electricity users, and they can be improved by incorporating sophisticated technology on smart grid. This opens up the possibility of transforming existing industries into a new era of enhanced networks that will give an intelligent, responsive, and bi-directional automatic management system for power generation, transmission, and distribution. The traditional grid is transitioning from a centralized generation structure to a more dispersed smart grid structure. In order to build this new decentralized structure, loads must be fully integrated into the grid and adequately separated from the main grid. The smart grid allows for the integration of loads that are clean, cost-effective, and efficient. The growing level of distributed generation (DG) integration puts the grid under strain, resulting in perturbations with dynamic responses. This paper discussed a detailed review of current developments in smart grid through the integration of renewable energy resources (RERs) into the grid. The purpose of this study is…

Microplastics have become omnipresent in the environment, including the air we inhale, the water we consume, and the food we eat. Despite limited research, the accumulation of microplastics within the human respiratory system has garnered considerable interest because of its potential implications for health. This review offers a comprehensive examination of the impacts stemming from the accumulation of microplastics on human lung airways and explores the computational benefits and challenges associated with studying this phenomenon. The existence of microplastics in the respiratory system can lead to a range of adverse effects. Research has indicated that microplastics can induce inflammation, oxidative stress, and impaired lung function. Furthermore, the small size of microplastics allows them to penetrate deep into the lungs, reaching the alveoli, where gas exchange takes place. This raises concerns about long-term health consequences, such as the development of respiratory diseases and the potential for translocation to other organs. Computational approaches have been…

Biogenic amines (BAs) are low-molecular decarboxylation products of amino acids formed during microbial fermentation. Several fermented foods may contain BAs such as histamine, tyramine, and/or phenylethylamine, at levels above documented toxic doses. Dietary exposure to foods containing high levels of BAs is associated with many adverse health effects, such as migraines, elevated blood pressure, and tachycardia. BA-mediated toxicity may occur at levels a hundred times below regulatory and suggested toxic doses, depending on an individual's sensitivity and factors such as alcohol consumption and certain medications. Although BAs occur in a wide variety of fermented foods, food safety and public health professionals are not well informed about the potential health risks and control strategies in these foods. In this review, we highlight the health risks and symptoms linked to BA exposures, the BA levels found in different fermented foods, regulatory and suggested toxic doses, and risk mitigation strategies to inform food industry and public health professionals' practice.

Background: The healthcare landscape is rapidly evolving, with artificial intelligence (AI) emerging as a transformative force. In this context, understanding the viewpoints of nursing professionals regarding the integration of AI in future nursing care is crucial. Aims: This study aimed to provide insights into the perceptions of nursing professionals regarding the role of AI in shaping the future of healthcare. Methods: A cohort of 23 nursing professionals was recruited between April 7, 2023, and May 4, 2023, for this study. Employing a thematic analysis approach, qualitative data from interviews with nursing professionals were analyzed. Verbatim transcripts underwent rigorous coding, and these codes were organized into themes through constant comparative analysis. The themes were refined and developed through the grouping of related codes, ensuring an authentic representation of participants' viewpoints. Results: After careful data analysis, ten key themes emerged including: (I) Perceptions of AI readiness; (II) Benefits and concerns; (III) Enhanced patient outcomes; (IV)…

High protein content, excellent amino acid profile, absence of anti-nutritional factors (ANFs), high digestibility and good palatability of fishmeal (FM), make it a major source of protein in aquaculture. Naturally derived FM is at risk due to an increase in its demand, unsustainable practices, and price. Thus, there is an urgent need to find affordable and suitable protein sources to replace FM. Plant protein sources are suitable due to their widespread availability and low cost. However, they contained certain ANFs, deficiency of some amino acids, low nutrient bioavailability and poor digestibility due to presence of starch and fiber. These unfavourable characteristics make them less suitable for feed as compared to FM. Thus, these potential challenges and limitations associated with various plant proteins have to be overcome by using different methods, i.e. enzymatic pretreatments, solvent extraction, heat treatments and fermentation, that are discussed briefly in this review. This review assessed the impacts of plant products on growth performance, body composition, flesh…

In the dynamic landscape of modern education, the search for improved pedagogical methods, enriched learning experiences, and empowered educators remains a perpetual pursuit. In recent years, a remarkable technological innovation has asserted its dominance in education: Knowledge Graphs (KGs). These structured representations of knowledge are increasingly proving to be indispensable tools, fostering advancements driven by the growing recognition of their essential role in enriching personalised learning, curriculum design, concept mapping, and educational content recommendation systems. In this paper, a systematic literature review (SLR) has been conducted to comprehensively examine KG construction methodologies and their applications across five key domains in education. In each examined study, we highlight the specific KG functionalities, knowledge extraction techniques, knowledge base characteristics, resource requirements, evaluation criteria, and limitations. This paper distinguishes itself by offering a broad overview of KGs in education, analyzing state-of-the-art…

Consumer demand for natural or 'clean-label' food ingredients has risen over the past 50 years and continues growing. Consumers have become more aware of their health and, therefore, insist on transparency in the list of ingredients. Preservatives are the most crucial food additives, ensuring food safety and security. Despite tremendous technological advancements, food preservation remains a significant challenge worldwide, primarily because most are synthetic and non-biodegradable. As a result, the food industry is placing more value on microbiota and other natural sources for bio-preservation, leading to the substitution of conventional processing and chemical preservatives with natural alternatives to ensure 'clean-label.' General Standard for Food Additives (GSFA) includes some of these 'clean-label' options in its list of additives. However, they are very rarely capable of replacing a synthetic preservative on a 'one-for-one' basis, putting pressure on researchers to decipher newer, cleaner, and more economical alternatives. Academic and scientific research has led to the…

Deep Eutectic Solvents (DESs) emerge as innovative 21st-century solvents, supplanting traditional ones like ethanol and n-hexane. Renowned for their non-toxic, biodegradable, and water-miscible nature with reduced volatility, DESs are mostly synthesized through heating and stirring method. Physicochemical properties such as polarity, viscosity, density and surface tension of DESs influenced their application. This review paper gives the overview of application of eco-benign DESs in fruits, vegetables, cereals, pulses, spices, herbs, plantation crops, oil seed crops, medicinal and aromatic plants, seaweed, and milk for the extraction of bioactive compounds. Also, it gives insight of determination of pesticides, insecticides, hazardous and toxic compounds, removal of heavy metals, detection of illegal milk additive, purification of antibiotics and preparation of packaging film. Methodologies for separating bioactive compounds from DESs extracts are systematically examined. Further, safety regulations of DESs are briefly discussed and reviewed literature reveals prevalent utilization…

] is remarkably similar to the hard tissue of the human body and the uses of this material in various fields in addition to the medical sector are increasing day by day. In this research, mustered oil, soybean oil, as well as coconut oil were employed as liquid media for synthesizing nanocrystalline HAp using a wet chemical precipitation approach. The X-ray diffraction (XRD) study verified the crystalline phase of the HAp in all the indicated media and discovered similarities with the standard database. Several prominent models such as the Scherrer's Method (SM), Halder-Wagner Method (HWM), linear straight-line method (LSLM), Williamson-Hall Method (W-M), Monshi Scherrer Method (MSM), Size-Strain Plot Method (SSPM), Sahadat-Scherrer Method (S-S) were applied for the determination of crystallite size. The stress, strain, and energy density were also computed from the above models. All the models, without the Linear straight-line technique of Scherrer's equation, resulted in an appropriate value of crystallite size for synthesized products. The calculated crystallite sizes were 6.5 nm…

High-resolution remotely sensed images pose challenges to traditional semantic segmentation networks, such as Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs). CNN-based methods struggle to handle high-resolution images due to their limited receptive field, while ViT-based methods, despite having a global receptive field, face challenges when processing long sequences. Inspired by the Mamba network, which is based on a state space model (SSM) to efficiently capture global semantic information, we propose a semantic segmentation framework for high-resolution remotely sensed imagery, named Samba. Samba utilizes an encoder-decoder architecture, with multiple Samba blocks serving as the encoder to efficiently extract multi-level semantic information, and UperNet functioning as the decoder. We evaluate Samba on the LoveDA, ISPRS Vaihingen, and ISPRS Potsdam datasets using the mIoU and mF1 metrics, and compare it with top-performing CNN-based and ViT-based methods. The results demonstrate that Samba achieves unparalleled performance on commonly used remotely sensed…

Cellulose degradation is a critical process in soil ecosystems, playing a vital role in nutrient cycling and organic matter decomposition. Enzymatic degradation of cellulosic biomass is the most sustainable and green method of producing liquid biofuel. It has gained intensive research interest with future perspective as the majority of terrestrial lignocellulose biomass has a great potential to be used as a source of bioenergy. However, the recalcitrant nature of lignocellulose limits its use as a source of energy. Noteworthy enough, enzymatic conversion of cellulose biomass could be a leading future technology. Fungal enzymes play a central role in cellulose degradation. Our understanding of fungal cellulases has substantially redirected in the past few years with the discovery of a new class of enzymes and Cellulosome. Efforts have been made from time to time to develop an economically viable method of cellulose degradation. This review provides insights into the current state of knowledge regarding cellulose degradation in soil and identifies areas where further research is…

Realizing integrated biorefineries producing multiple fuels, chemicals and materials from sustainable biomass feedstocks holds promise for transitioning industries onto low-carbon trajectories. However, widespread commercial implementation remains elusive despite two decades of technological advancements. This review synthesizes current literature to provide a comprehensive analysis of key multi-dimensional barriers inhibiting the scale-up of biorefineries. The review discusses the technical challenges around biomass conversion processes. Economic viability concerns such as high capital costs and lack of market competitiveness are also assessed. The review also evaluates the regulatory and policy complexities that poses risks and uncertainties in the scaling up of biorefineries. Socio-political acceptance hurdles including community engagement and public perception are also reviewed. The interconnected nature of these challenges is emphasized and strategies are recommended to enable full potential realization, covering areas such as enhanced stakeholder collaboration, advanced…

People who work in dangerous environments include farmers, sailors, travelers, and mining workers. Due to the fact that they must evaluate the changes taking place in their immediate surroundings, they must gather information and data from the real world. It becomes crucial to regularly monitor meteorological parameters such air quality, rainfall, water level, pH value, wind direction and speed, temperature, atmospheric pressure, humidity, soil moisture, light intensity, and turbidity in order to avoid risks or calamities. Enhancing environmental standards is largely influenced by IoT. It greatly advances sustainable living with its innovative and cutting-edge techniques for monitoring air quality and treating water. With the aid of various sensors, microcontroller (Arduino Uno), GSM, Wi-Fi, and HTTP protocols, the suggested system is a real-time smart monitoring system based on the Internet of Things. Also, the proposed system has HTTP-based webpage enabled by Wi-Fi to transfer the data to remote locations. This technology makes it feasible to track changes in the weather from any…

The Global South comprising economically disadvantaged regions of the world face various challenges such as limited access to electricity, clean water, industrialization, and food security. Solar energy, as a sustainable and abundant resource, holds great potential to address these challenges. Despite its immense potential, the Global South encounters hurdles related to technology adoption, infrastructure, and financial constraints. This review examines the history, classifications, global statistics, merits, and demerits of solar technology in the Global South. Furthermore, it delves into various applications of solar energy, including extreme environments, residential electricity generation, transportation, and industrial usage in this region. This study concludes by providing new insighths and highlighting the significant role solar energy can play in shaping the future of the Global South if challenges are adequately addressed, and opportunities are embraced.

The topic of consumer food choice has received much attention among researchers and stakeholders within the food industry. However, in order to better facilitate food consumption towards a more sustainable direction, we need increased knowledge and understanding of factors that influence consumers' food choice. This study is a systematic review of reviews conducted between 2017 and 2021, summarising and synthesising reviews on food choice. The aim is to provide an update of the current knowledge on consumer food choice, point out what is already known, and identify knowledge gaps to enable a prioritisation for future research. The analysis highlights decisive factors in food choice, i.e. product, available information, price, context, personal and group influences and sensory perceptions. The synthesis of findings follows a socioecological model, integrating four different levels of the social and environmental systems: the physical food environment, the social and community level, interpersonal relations and, finally, individual characteristics such as psychological and behavioural…

In recent decades, environmental pollution has become a significant problem for human health and environmental impact. The high accumulation of heavy metals in waters and soils from different sources was conducted by finding efficient and environmentally friendly treatment methods and materials for their removal. Natural zeolites have found wide-ranging applications in environmental remediation and protection, considering various treatment and modification methods designed to enhance the natural zeolites' adsorptive or ion-exchange capabilities for increased efficiency. This paper briefly consolidates the recent scientific literature related to the main characteristics of natural and modified zeolites, the advantages and limitations of their environmental remediation application, and summarizes the methodologies applied to natural zeolites in order to improve their properties. Their application for removing heavy metals from water systems and soils is also comprehensively discussed. This review highlights the excellent potential of natural zeolites to be used after specific…

Integrating artificial intelligence (AI) with electrochemical biosensors is revolutionizing medical treatments by enhancing patient data collection and enabling the development of advanced wearable sensors for health, fitness, and environmental monitoring. Electrochemical biosensors, which detect biomarkers through electrochemical processes, are significantly more effective. The integration of artificial intelligence is adept at identifying, categorizing, characterizing, and projecting intricate data patterns. As the Internet of Things (IoT), big data, and big health technologies move from theory to practice, AI-powered biosensors offer significant opportunities for real-time disease detection and personalized healthcare. Still, they also pose challenges such as data privacy, sensor stability, and algorithmic bias. This paper highlights the critical advances in material innovation, biorecognition elements, signal transduction, data processing, and intelligent decision systems necessary for developing next-generation wearable and implantable devices. Despite existing limitations, the…

Machine learning (ML) can make use of agricultural data related to crop yield under varying soil nutrient levels, and climatic fluctuations to suggest appropriate crops to achieve the highest possible production. The aim of this study was to evaluate the efficacy of five distinct ML models in generating practical recommendations for crop selection that could be readily adopted by end-users. The study utilized public datasets on NPK, soil pH, and three climatic factors (temperature, rainfall, and humidity) to train five different ML models: Support vector machine, XGBoost, Random forest, KNN, and Decision Tree. The model was trained using yields of individual data sets of 11 agricultural and 10 horticultural crops, as well as combinations of both types of agri-horticultural crops. The results showed that using individual data sets for each crop category resulted in better outcome than combining the data sets for both categories. Among the five ML models used, the XGBoost demonstrated the highest level of accuracy. The precision rates of XGBoost for recommending agricultural crops,…

This comprehensive review investigates a variety of creative approaches in the field of sustainable food packaging biomaterials in response to growing environmental concerns and the negative effects of traditional plastic packaging. The study carefully looks at new developments in biomaterials, such as biodegradable polymers, ceramics, composites, and metal alloys, in response to the growing need for environmentally suitable substitutes. It highlights how they might replace conventional plastic packaging and lessen environmental damage. Moreover, the incorporation of nanotechnology into packaging is closely examined due to its crucial function in improving barrier qualities, introducing antimicrobial properties, and introducing smart packaging features. The investigation includes edible coatings and films made of biodegradable polymers that offer new sensory experiences in addition to prolonging the shelf life of products. The review emphasizes the use of biomaterials derived from food processing and agricultural waste, supporting environmentally responsible methods of producing…

MXenes are a group of 2D transition metal carbonitrides, nitrides and carbides that have become widely recognized as useful materials since they were first discovered in 2011. MXenes, with their exceptional layered structures and splendid external chemistries, have excellent electrical, optical, and thermal properties, making them suitable for catalysis, biomedical uses, environmental remediation, energy storage, and EMI shielding. Over forty MXene compounds with surface terminations like hydroxyl, oxygen, or fluorine are hydrophilic and easily integrated into various applications. Advanced synthesis methods, including selective etching and etchant modifications, have broadened MXene surface chemistries for customized mechanical, thermal, and electrical applications. Integrating MXenes into polymer composites has demonstrated notable promise, enhancing the host polymers' electrical conductivity, thermal stability and mechanical strength. The MXene-polymer composites demonstrate remarkable prospective on behalf of advanced purposes, including flexible electronics, high-performance…

The rapid improvement of artificial intelligence (AI) in the educational domain has opened new possibilities for enhancing the learning experiences for students. This research discusses the critical need for personalized education in higher education by integrating deep learning (DL) techniques to create customized learning pathways for students. This research intends to bridge the gap between constant educational content and dynamic student needs. This research presents an AI-driven adaptive learning platform implemented across four different courses and 300 students at a university in Faisalabad-Pakistan. A controlled experiment compares student outcomes between those using the AI platform and those undergoing traditional instruction. Quantitative results demonstrate a 25 % improvement in grades, test scores, and engagement for the AI group, with a statistical significance of a p-value of 0.00045. Qualitative feedback highlights enhanced experiences attributed to personalized pathways. The DL analysis of student performance data highlights key parameters, including enhanced…

Ethnopedagogy serves as an educational approach capable of reshaping societal dynamics by preserving cultural values, thereby reinforcing a multicultural national identity. This study explored the potential of ethnopedagogy in revitalizing local wisdom within early childhood character education in Indonesia. This case study was performed at Pertiwi Kindergarten in Puro Pakualaman, Yogyakarta, Indonesia. Data were gained through interviews and document analysis with teachers, parents, and school principals. Research data were checked for validity using data triangulation. The research findings demonstrated that ethnopedagogy enhanced children's awareness of local culture and nurtures character development by integrating local wisdom values into the learning process. Furthermore, involving local communities in character education improved community engagement in the educational journey, bolstering a sense of ownership over the school or learning environment, and strengthening social networks within the community. Ethnopedagogy is recommended to apply in early childhood education to…

Rural tourism has been widely recognized as a means of promoting the revival of traditional villages and has been supported by numerous researchers. It has the potential to provide significant social and economic advantages, making it a popular strategy for rural development in both developed and developing countries. Nevertheless, a growing body of research has substantiated the significant disruptions that rural tourism has imposed on traditional villages. This study employed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) qualitative method to systematically analyze 92 papers from WOS and SCOPUS that investigate the impact of rural tourism on traditional villages. The papers were categorized into five groups: spatial, economic, sociocultural, and holistic. This categorization allowed for the identification of the purpose, theme, sub-topics, research methods, and data sources used in these papers, which in turn provided an overview of the characteristics and overall trends in research in this field. It compensates for the deficiencies of lesser…

The increasing need for dyes in the textile sector, has led to significant environmental consequences such as natural water contamination. Textile dyes in water can hinder algae and aquatic plant growth, break down into harmful intermediates, and affect the aquatic food chain. Terrestrial animals may also encounter these dyes through consumption or exposure. Cationic and anionic dyes like methylene blue, malachite green, rhodamine B, methyl orange, eosin y and methyl red can cause skin irritation, carcinogenicity, mutagenicity, and teratogenicity. Therefore, the presence of these dyes in natural and wastewater streams pose significant threats to the aquatic ecosystems, ecological systems and human health. Effective management and remediation of textile dye effluents is crucial to mitigate these risks. Although regulatory bodies like ecological and toxicological association of the dyestuffs manufacturing Industry (ETAD) are working on addressing these risks, more challenges still persist due to nature of textile dyes, lack of enforcement of these regulations on textile dye industries…

Industrial organic dyes represent a significant portion of pollutants discharged into the environment, particularly by the textile industry. These compounds pose serious threats to living organisms due to their high toxicity. Various techniques have been explored for the degradation of organic dyes, among which heterogeneous photocatalysis utilising titanium dioxide (TiO 2 ) stands out as a promising technology. However, the practical application of TiO 2 as photocatalyst has limitations for the following reasons; First, TiO 2 has a low sensitivity to visible light due to a large band gap which can be 3.2 eV for the anatase polymorph. Second, the recombination rate of photo-induced electron-hole pairs in TiO 2 is very fast. Recent research studies have brought to light that a silver-doped titanium dioxide nanocomposite could be one of the promising answers to these problems. This nanocomposite has garnered significant attention because of its unique features that suggest the manifestation of more effective concepts to minimize the electron-hole recombination and broaden light…

The accurate measurement and analysis of human movement are essential in fields ranging from rehabilitation and neuroscience to sports science and ergonomics. Traditional methods, though precise, are often constrained by cost, accessibility, and controlled environments. The advent of machine learning (ML) pose estimation models (PEMs) offers an alternative solution, enabling detailed motion analysis using low-cost imaging systems in various settings. The aim of this review is to evaluate ML PEMs and their impact on human movement sciences, focusing on recent advancements in machine learning and computer vision for accurate, non-invasive motion analysis using low-cost imaging systems. A narrative review was conducted by searching electronic databases, including PubMed and Google Scholar, using key terms such as "machine learning," "pose estimation models," and "human movement sciences." Thematic analysis identified key advancements, applications, and challenges in ML PEMs across clinical, sports, and ergonomic contexts. The review highlights the development, capabilities, and…

The poly (lactic-co-glycolic acid) (PLGA) based nanoparticles have been applied for drug delivery due to their simple preparation, biodegradability, and ideal biocompatibility. In this study, the factors affecting the degradation of PLGA-based nanoparticles are reviewed, encompassing the ratio of PLA to PGA, relative molecular weight, crystallinity, and preparation process of PLGA nanoparticles. The drug release behavior of PLGA-based nanoparticles, such as the degradation environment, encapsulated drug properties of polymers, and drug loading rates, are also discussed. Since gastrointestinal cancer is one of the major global threats to human health, this paper comprehensively summarizes the application of PLGA nanoparticles in gastrointestinal cancers from diagnosis, chemotherapy, radiotherapy, and novel tumor treatment methods (immunotherapy, gene therapy, and photothermal therapy). Finally, the future application of PLGA-based drug delivery systems in treating gastrointestinal cancers is discussed. The bottleneck of application status and the prospect of PLGA-nanoparticles in…

The rapid evolution of Artificial Intelligence (AI) and its widespread adoption have given rise to a critical need for understanding the underlying factors that shape users' behavioral intentions. Therefore, the main objective of this study is to explain user perceived behavioral intentions and use behavior of AI technologies for academic purposes in a developing country. This study has adopted the unified theory of acceptance and use of technology (UTAUT) model and extended it with two dimensions: trust and privacy. Data have been collected from 310 AI users including teachers, researchers, and students. This study finds that users' behavioral intention is positively and significantly associated with trust, social influence, effort expectancy, and performance expectancy. Privacy, on the other hand, has a negative yet significant relationship with behavioral intention unveiling that concerns over privacy can deter users from intending to use AI technologies which is a valuable insight for developers and educators. In determining use behavior, facilitating condition, behavioral…

A novel concept of developing multi-principal elements, or compositional complex alloys is referred as high-entropy alloys (HEAs). This review addresses the role of entropy in alloying additions along with the effect of various elements listed in the periodic table in forming the HEAs. Phase formation rules and the associated parameters along with their significance are discussed. The physical metallurgy technique is elaborated with reference to the high-entropy effect, severe lattice distortion effect, sluggish diffusion effect, and cocktail effects. Various types of HEAs such as light weight HEAs, nanoprecipitate HEAs, ultrafine-grained HEAs, dual-phase HEAS and TRIP/TWIN HEAs are discussed. Further, the effects of mechanical alloying in HEAs are presented. Finally, the microstructural effects and mechanical properties of HEAs are addressed with reference to the published literature.

Artificial intelligence has advanced significantly in recent years, affecting multiple aspects of life. In particular, this has had an impact on the machine translation of texts, reducing or removing human interaction. Artificial intelligence (AI)-based translation software models have thus become widely available, and these now include Google Translate, Bing, Microsoft Translator, DeepL, Reverso, Systran Translate, and Amazon Translate. Several computer-aided translation (CAT) tools such as Memoq, Trados, Smartcat, Lokalise, Smartling, Crowdin, TextUnited, and Memsource are also available. More recently, artificial intelligence has been applied in the development of applications such as ChatGPT, ChatSonic, GPT-3 Playground, Chat GPT 4 and YouChat, which simulate conversational responses to researchers' inquiries, mimicking human interactions more directly. This study thus aimed to examine any remaining contrasts between human and AI translation in the legal field to investigate the potential hypothesis that there is now no difference between human and AI translation. The paper thus…

As a consequence of environmental quality changes as well as changes in our population's lifestyle, there is rapidly increasing variability and many so-called lifestyle disorders, allergies, and food intolerances (also known as non-allergic food hypersensitivity). Unhealthy eating practices, an inappropriate food composition with an excessive energy intake, a high intake of saturated fats, simple sugars, and salt, as well as an inadequate intake of fibre, vitamins, and substances with preventive effects (such as antioxidants), are some of the factors causing this detrimental phenomenon. Enhanced consumption of plant foods rich in valuable secondary metabolites such as phenolic acids and flavonoids with the benefit on human health, food research focused on these components, and production of foods with declared higher content of biologically active and prophylactic substances are some ways how to change and improve this situation. A unique class of hydroxylated phenolic compounds with an aromatic ring structure are called flavonoids. One unique subclass of flavonoids is quercetin.…

Integrating wind power with energy storage technologies is crucial for frequency regulation in modern power systems, ensuring the reliable and cost-effective operation of power systems while promoting the widespread adoption of renewable energy sources. Power systems are changing rapidly, with increased renewable energy integration and evolving system architectures. These transformations bring forth challenges like low inertia and unpredictable behavior of generation and load components. As a result, frequency regulation (FR) becomes increasingly important to ensure grid stability. Energy Storage Systems (ESS) with their adaptable capabilities offer valuable solutions to enhance the adaptability and controllability of power systems, especially within wind farms. This research provides an updated analysis of critical frequency stability challenges, examines state-of-the-art control techniques, and investigates the barriers that hinder wind power integration. Moreover, it introduces emerging ESS technologies and explores their potential applications in supporting wind power…

Corrosion significantly threatens the structural integrity of steel-based constructions like buildings and industrial units. Traditional corrosion inhibitors, such as chromates, are associated with environmental and health risks. This has led to a growing interest in environmentally sustainable alternatives, with plant extracts emerging as promising candidates. These extracts are widely available, sustainable, and eco-friendly. This review aims to explore the potential of plant extracts as corrosion inhibitors for various types of steel. After examining current scientific literature, over 40 plant extracts have been identified that exhibit corrosion inhibition properties. These extracts have been thoroughly analyzed to understand their effectiveness in preventing corrosion. The review elucidates the mechanisms by which these extracts interact with metal surfaces to form protective layers, effectively hindering the corrosion process. In this review, we focus on the challenges associated with utilizing plant extracts as inhibitors, including optimal extract concentration and…

This comprehensive meta-analysis investigates the significant factors influencing consumer decision-making in e-commerce. Predominantly focusing on the parameters of trust, perceived risk, perceived security, and electronic word-of-mouth (e-WOM), this study provides insightful revelations on their integral roles in shaping e-commerce purchasing decisions. The findings demonstrate that trust, perceived risk, perceived security, and e-WOM significantly influence consumers' e-commerce purchasing decisions. Perceived Risk plays a substantial moderating role in the relationship between Trust and e-commerce purchasing decisions, amplifying the importance of managing and minimizing risk in online transactions to cultivate consumer trust. Contrastingly, the roles of Perceived Security and e-WOM do not hold the same moderating effect on the trust-purchasing decision nexus, underscoring the direct yet unmoderated influence these factors have on e-commerce purchasing behaviors. Furthermore, The research reveals no significant size effect difference among respondents from high-income and…

The substantial increase in the human population dramatically strains food supplies. Farmers need healthy soil and natural minerals for traditional farming, and production takes a little longer time. The soil-free farming method known as vertical farming (VF) requires a small land and consumes a very small amount of water than conventional soil-dependent farming techniques. With modern technologies like hydroponics, aeroponics, and aquaponics, the notion of the VF appears to have a promising future in urban areas where farming land is very expensive and scarce. VF faces difficulty in the simultaneous monitoring of multiple indicators, nutrition advice, and plant diagnosis systems. However, these issues can be resolved by implementing current technical advancements like artificial intelligence (AI)-based control techniques such as machine learning (ML), deep learning (DL), the internet of things (IoT), image processing as well as computer vision. This article presents a thorough analysis of ML and IoT applications in VF system. The areas on which the attention is concentrated include…

In natural environments, persistent pollutants such as heavy metals and organic compounds, are frequently sequestered in sediments, soils, and mineral deposits, rendering them biologically unavailable. This study examines phytoremediation, a sustainable technology that uses plants to remove pollutants from soil, water, and air. It discusses enhancing techniques such as plant selection, the use of plant growth-promoting bacteria, soil amendments, and genetic engineering. The study highlights the slow removal rates and the limited availability of plant species that are effective for specific pollutants. Furthermore, it investigates bioavailability and the mechanisms underlying root exudation and hyperaccumulation. Applications across diverse environments and innovative technologies, such as transgenic plants and nanoparticles, are also explored. Additionally, the potential for phytoremediation with bioenergy production is considered. The purpose of this study is to provide researchers, practitioners, and policymakers with valuable resources for sustainable solutions.

This systematic review examined, through the UTAUT2 model, the factors influencing the acceptance of artificial intelligence (AI) applications in university contexts. A total of 50 scientific texts published between 2018 and 2023 were analyzed and selected after a rigorous search of specialized databases. These findings confirm the versatility of UTAUT2 in elucidating technological adoption processes in higher education. Performance expectancy and hedonic motivation emerged as significant predictors of intentions and effective use among students, faculty, and administrative staff. Among students, perceived ease of use and social influence were also relevant. The analysis revealed differences in adoption patterns between STEM and non-STEM disciplines and between public and private institutions. Despite widespread positive perceptions of AI's potential, barriers such as distrust and lack of knowledge persist. The research also identified moderating and mediating factors, such as prior technology experience and technological self-efficacy. These results have important implications for…

Vibration Analysis (VA) is the most commonly used technique in predictive maintenance. It allows the diagnosis of faults, especially those in the early stages. The use of VA is important for maintenance costs and downtime savings, making decisions about repair and total replacement. The method has been applied in many industries and proven to be effective. It is applicable to rotating, non-rotating equipment, continuous processes or even construction structure. In this paper, vibration analysis fundamentals as well as many studies on the method's application are reviewed. The purpose is to give an overview of how vibration analysis is used in many industries including petroleum to show its potential in petroleum industry. VA has been used in many areas from transportation, refinery to drilling and production. However, there are still rooms for improvement and implementation. One potential application is detecting faults in Electric Submersible Pump (ESP) system. ESP is located downhole making it susceptible to faults and defects that could be difficult to detect using conventional…

The increasing emissions of greenhouse gases (GHG) and pollutants like particulate matter and nitrogen oxides (NOx) have led to environmental concerns. Hybrid and electric powertrains are being introduced as means to reduce pollutant emissions, especially at the local level. Additionally, the finite availability of fossil fuel sources, which are used to produce gasoline and diesel, highlights the need for alternative technical solutions. One approach to partly address these issues is lightweighting, which involves reducing the weight of vehicles to minimize their impact during the use phase. Mathematical models are employed to simulate the longitudinal dynamics of vehicles and estimate the energy required to accomplish driving missions. Appropriate metrics have been developed to quantify energy-saving effects that, in addition, can support the decision making, design, and development phase of future vehicles. To facilitate this process, it would be useful to build a database of ERV (Energy Reduction Value) and FRV (Fuel Reduction Value) figures derived through a unified procedure.…

This study investigates the determinants of ChatGPT adoption among university students and its impact on learning satisfaction. Utilizing the Technology Acceptance Model (TAM) and incorporating insights from interaction learning, collaborative learning, and information quality, a structural equation modeling approach was employed. This research collected valuable responses from 262 students at King Faisal University in Saudi Arabia through the use of self-report questionnaires. The data's reliability and validity were assessed using confirmation factor analysis, followed by path analysis to explore the hypotheses in the proposed model. The results indicate the pivotal roles of interaction learning and collaborative learning in fostering ChatGPT adoption. Social interaction played a significant role, as researchers engaging in conversations and knowledge-sharing expressed increased comfort with ChatGPT. Information quality was found to substantially influence researchers' decisions to continue using ChatGPT, emphasizing the need for ongoing improvement in the accuracy and relevance…

There is an urgent need to explore climate-resilient alternative agriculture production systems that focus on resilience, resource efficiency, and disease management. Hydroponics, a soilless cultivation system, gaining interest as it reduces the dependency on agricultural land, and pesticides, and can be implemented in areas with poor soil quality, thus mitigating the negative effects of extreme weather events. Potato is an essential dietary staple crop grown throughout the world and is a major source of food security in underdeveloped countries. However, due to the climatic changes, it is predicted that a significant loss in the suitability of land for potato production would occur, thus leading to potato yield loss. Recently, many case studies have emerged to highlight the advancement of agricultural hydroponic systems that provide a promising solution to the massive production of potato mini tuber at high efficiency. This review paper evaluates popular hydroponic methods and demonstrates how hydroponic has emerged as the go-to, long-term, sustainable answer to the perennial…

Protein engineering mechanisms can be an efficient approach to enhance the biochemical properties of various biocatalysts. Immobilization of biocatalysts and the introduction of new-to-nature chemical reactivities are also possible through the same mechanism. Discovering new protocols that enhance the catalytic active protein that possesses novelty in terms of being stable, active, and, stereoselectivity with functions could be identified as essential areas in terms of concurrent bioorganic chemistry (synergistic relationship between organic chemistry and biochemistry in the context of enzyme engineering). However, with our current level of knowledge about protein folding and its correlation with protein conformation and activities, it is almost impossible to design proteins with specific biological and physical properties. Hence, contemporary protein engineering typically involves reprogramming existing enzymes by mutagenesis to generate new phenotypes with desired properties. These processes ensure that limitations of naturally occurring enzymes are not encountered. For example,…

Nanotechnology has emerged as a powerful tool in addressing global challenges and advancing sustainable development. By manipulating materials at the nanoscale, researchers have unlocked new possibilities in various fields, including energy, healthcare, agriculture, construction, transportation, and environmental conservation. This paper explores the potential of nanotechnology and nanostructures in contributing to the achievement of the United Nations (UN) Sustainable Development Goals (SDGs) by improving energy efficiency and energy conversion, leading to a more sustainable and clean energy future, improving water purification processes, enabling access to clean drinking water for communities, enabling targeted drug delivery systems, early disease detection, and personalized medicine, thus revolutionizing healthcare, improving crop yields, efficient nutrient delivery systems, pest control mechanisms, and many other areas, therefore addressing food security issues. It also highlights the potential of nanomaterials in environmental remediation and pollution control. Therefore, by…

As global energy demand and warming increase, there is a need to transition to sustainable and renewable energy sources. Integrating different systems to create a hybrid renewable system enhances the overall adoption and deployment of renewable energy resources. Given the intermittent nature of solar and wind, energy storage systems are combined with these renewable energy sources, to optimize the quantity of clean energy used. Thus, various optimization strategies have been developed for the integration and operation of these hybrid renewable energy systems. Existing studies have either reviewed hybrid renewable energy systems or energy storage systems, however, these studies ignored energy storage systems integrated with hybrid renewable energy systems. This study offers a comprehensive analysis of the optimization methods used in hybrid renewable energy systems (HRES) integrated with energy storage systems (ESS). We examined the optimization models used in the integration of HRES and ESS, their objectives, and the common constraints. Based on our review, capacity and CO 2…

Carbon nanotube (CNT)-polymer composites exhibit significant advancements in mechanical, electrical, and thermal properties, enabling numerous promising applications. This review delves into recent research on manufacturing methods, filament extrusion, additive manufacturing (AM), properties, and applications of CNT polymer composites. Factors like processing conditions, polymer types, and CNT concentrations determine the ultimate properties of the composite material. The dispersion of CNT within various manufacturing techniques, such as melt mixing, solution mixing, and in-situ polymerization, significantly impacts the properties of the composite material. These composite materials are extensively used in AM, particularly in 3D printing, where filament blends are extruded and printed to custom-shaped objects. The finding underscores the effect of CNT content on the properties of CNT-polymer composite material in different applications. However, gaps remain in optimizing manufacturing processes and AM techniques, essential for tailoring these composites to specific application…

Sustainable smart ecotourism, utilizing smart technologies like smartphones, artificial intelligence (AI), and the Internet of Things (IoT), aims to minimize harm to natural and cultural ecosystems, promoting education and environmental conservation. This review aims to examine the concept of sustainable smart ecotourism, analyzing existing literature to gain insights into the significance, components, challenges, and contributions to sustainable development on a global scale. A systematic review was conducted to evaluate sustainable smart ecotourism using PRISMA guidelines. The review focused on scholarly, peer-reviewed studies from developing countries, using databases like ScienceDirect, Jstor, Taylor & Francis, and IEEE. The study used Joanna Briggs Institute and Cochrane Risk of Bias tools to assess study quality. Thematic analysis techniques were used to extract and synthesize data, identifying patterns and trends relevant to smart ecotourism sustainability. Dual analyst verification ensured data integrity and reliability. After conducting a thorough quality evaluation using…

Wear (erosion/abrasion) and corrosion act in synergy in several industrial installations where corrosive fluids circulate together with a solid phase causing mutual damage. High entropy alloys (HEAs) are promising materials to be used in that type of environments because of their outstanding chemical, electrochemical and mechanical properties. While several review articles are currently available on corrosion, mechanical properties, development of HEAs, microstructure, and HEA coatings, there is an undeniable lack of a comprehensive and critical review focusing on the tribological behaviour and tribocorrosion of bulk HEAs. This work aims to collect, summarise, and critically review the major accomplishments and progresses of HEAs over the last 20 years dealing with wear, corrosion, and wear-corrosion resistance. It highlights the most significant aspects that can influence the performance of HEAs including the change of the base alloying elements, the influence of the temperature, heat treatment, and wear test parameters (load, velocity, duration, distance). Furthermore, operating…

Monocytes and macrophages are essential components of innate immune system and have versatile roles in homeostasis and immunity. These phenotypically distinguishable mononuclear phagocytes play distinct roles in different stages, contributing to the pathophysiology in various forms making them a potentially attractive therapeutic target in inflammatory conditions. Several pieces of evidence have supported the role of different cell surface receptors expressed on these cells and their downstream signaling molecules in initiating and perpetuating the inflammatory response. In this review, we discuss the current understanding of the monocyte and macrophage biology in inflammation, highlighting the role of chemoattractants, inflammasomes, and integrins in the function of monocytes and macrophages during events of inflammation. This review also covers the recent therapeutic interventions targeting these mononuclear phagocytes at the cellular and molecular levels.

Parkinson's Disease (PD) is a prevalent neurodegenerative disorder with significant clinical implications. Early and accurate diagnosis of PD is crucial for timely intervention and personalized treatment. In recent years, Machine Learning (ML) and Deep Learning (DL) techniques have emerged as promis-ing tools for improving PD diagnosis. This review paper presents a detailed analysis of the current state of ML and DL-based PD diagnosis, focusing on voice, handwriting, and wave spiral datasets. The study also evaluates the effectiveness of various ML and DL algorithms, including classifiers, on these datasets and highlights their potential in enhancing diagnostic accuracy and aiding clinical decision-making. Additionally, the paper explores the identifi-cation of biomarkers using these techniques, offering insights into improving the diagnostic process. The discussion encompasses different data formats and commonly employed ML and DL methods in PD diagnosis, providing a comprehensive overview of the field. This review serves as a roadmap for future research, guiding the development of…

This paper introduces a new metaheuristic technique known as the Greater Cane Rat Algorithm (GCRA) for addressing optimization problems. The optimization process of GCRA is inspired by the intelligent foraging behaviors of greater cane rats during and off mating season. Being highly nocturnal, they are intelligible enough to leave trails as they forage through reeds and grass. Such trails would subsequently lead to food and water sources and shelter. The exploration phase is achieved when they leave the different shelters scattered around their territory to forage and leave trails. It is presumed that the alpha male maintains knowledge about these routes, and as a result, other rats modify their location according to this information. Also, the males are aware of the breeding season and separate themselves from the group. The assumption is that once the group is separated during this season, the foraging activities are concentrated within areas of abundant food sources, which aids the exploitation. Hence, the smart foraging paths and behaviors during the mating season are…

Seafood, being highly perishable, faces rapid deterioration in freshness, posing spoilage risks and potential health concerns without proper preservation. To combat this, various innovative preservation and packaging technologies have emerged. This review delves into these cutting-edge interventions designed to minimize spoilage and effectively prolong the shelf life of fresh seafood products. Techniques like High-Pressure Processing (HPP), Modified Atmosphere Packaging (MAP), bio-preservation, and active and vacuum packaging have demonstrated the capability to extend the shelf life of seafood products by up to 50%. However, the efficacy of these technologies relies on factors such as the specific type of seafood product and the storage temperature. Hence, careful consideration of these factors is essential in choosing an appropriate preservation and packaging technology.

Along with traditional academic knowledge, 21st-century skills are crucial for equipping students with a competitive future. Project-based learning (PBL) cultivates these competencies among learners as an instructional approach. This research aimed to construct and analyze a PBL framework designed to weave 21st-century skills into high school education. Data collection involved a survey questionnaire based on an extensive literature review administered to students from ten government-run girls' high schools, where mathematics was taught using the PBL approach. Employing Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) via the Analysis of Moment Structures (AMOS) software, the study meticulously calculated chi-square values, modification indices, and standardized estimates to validate the framework's effectiveness. The results showed a significant enhancement in collaborative learning, problem-solving, critical thinking, and positive attitudes toward mathematics among students, mediated by the PBL approach. The Heterotrait-Monotrait Ratio (HTMT) values were…

Due to the special property of food waste (FW), anaerobic digestion of food waste is facing many challenges like foaming, acidification, ammonia nitrogen and (NH 4 + -N) inhibition which resulted in a low biogas yield. A better understanding on the problems exiting in the FW anaerobic digestion would enhance the bio-energy recovery and increase the stable operation. Meanwhile, to overcome the bottle necks, pretreatment, co-digestion and additives is proposed as well as the solutions to improve biogas yield in FW digestion system. At last, future research directions regarding FW anaerobic digestion were proposed.

Ethiopia is a rainfall-based agricultural country that is susceptible to the impacts of climate change and risk. Floods and droughts, which happen more frequently and intensely, significantly and negatively influence agricultural production. The objective of the meta-analysis is to identify impacts on various sectors, adaptation strategies, and the challenges of climate change in the Ethiopian context. Twenty-three peer-reviewed articles were identified from ScienceDirect and Web of Science, followed by PRISMA guidelines, and analyzed using Stata version 13. The results reveal that climate change negatively impacts agriculture (by changing crop suitability, phenology, and productivity), the environment, and society, resulting from shifting temperature and rainfall patterns. Temperature variations, patterns of precipitation, and severe weather conditions have profound implications for agricultural productivity, water resources, ecosystems, and human well-being, which are multifaceted and interlinked. In addition, the reviewed articles informed us that farmers have used different…

The concept of this review underscores a significant shift towards sustainable agricultural practices, particularly from the view point of microbial biotechnology and nanotechnology. The global food insecurity that causes increasing ecological imbalances is exacerbating food insecurity, and this has necessitated eco-friendly agricultural innovations. The chemical fertilizers usage aims at boosting crop yields, but with negative environmental impact, thus pushing for alternatives. Microbial biotechnology and nanotechnology fields are gaining traction for their potential in sustainable agriculture. Endophytic fungi promise to synthesize nanoparticles (NPs) that can enhance crop productivity and contribute to ecosystem stability. Leveraging on endophytic fungi could be key to achieving food security goals. Endophytic fungi explore diverse mechanisms in enhancing plant growth and resilience to environmental stresses. The application of endophytic fungi in agricultural settings is profound with notable successes. Hence, adopting interdisciplinary research approaches by combining…

CRISPR/Cas systems have become integral parts of nucleic acid detection apparatus and biosensors. Various CRISPR/Cas systems such as CRISPR/Cas9, CRISPR/Cas12, CRISPR/Cas13, CRISPR/Cas14 and CRISPR/Cas3 utilize different mechanisms to detect or differentiate biological activities and nucleotide sequences. Usually, CRISPR/Cas-based nucleic acid detection systems are combined with polymerase chain reaction, loop-mediated isothermal amplification, recombinase polymerase amplification and transcriptional technologies for effective diagnostics. Premised on these, many CRISPR/Cas-based nucleic acid biosensors have been developed to detect nucleic acids of viral and bacterial pathogens in clinical samples, as well as other applications in life sciences including biosecurity, food safety and environmental assessment. Additionally, CRISPR/Cas-based nucleic acid detection systems have showed better specificity compared with other molecular diagnostic methods. In this review, we give an overview of various CRISPR/Cas-based nucleic acid detection methods and highlight some advances in their…

Synthesis of nanoparticles through the green approach using plant and vegetable extracts has gained popularity since they are thought to be efficient and cost-effective materials. This study is designed to synthesize zinc oxide nanoparticles (ZnO-NPs) from onion waste peel extract ( Allium cepa L.) via the green synthesis approach. The synthesized ZnO-NPs were characterized by utilizing the UV–Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), Energy Dispersive X-ray (EDX), Field Emission Scanning Electron Microscopy (FE-SEM) and X-ray Powder Diffraction (XRD)techniques. The nanoparticles formation was confirmed by the UV–Vis sharp absorption spectra at 318 and 322 nm. The synthesized ZnO-NPs size and shape was revealed by the XRD and SEM respectively. Smallest nanoparticle average crystallite size was found 57.38 nm with hexagonal shape. The bioactive functional groups that are in charge of capping and stabilizing the ZnO-NPs was assured by the FTIR data. Further, prepared ZnO-NPs were used to assess their possible antioxidant and antibacterial properties. DPPH test…

This study investigates Ficus Macrocarpa tree bark fibers (FMB) as a sustainable alternative reinforcement for polymer composites. The Industrial Revolution marked the evolution of polymer composites with synthetic material reinforcement, leading to environmental concerns. Natural fibers have recently gained prominence as efficient alternatives for polymer composites. Despite numerous natural fibers being considered, ensuring a sustainable raw material source remains crucial. In this study, fibers were extracted from FMB and subjected to alkali treatment to evaluate their impact on physical, chemical, and thermal properties. Initially, the extracted fibers measured 253.80 ± 15 μm in diameter, reduced to 223.27 ± 12 μm post-alkali treatment. Chemical analysis showed an increase in cellulose content to 59.7 wt%, a 23.34 % improvement over untreated fibers (48.4 wt%). The crystalline index for untreated and treated fibers measured 80.20 % and 84.75 %, respectively, with no noticeable changes in the cellulose phase. Additionally, the crystalline size increased to 3.21 nm.…

In recent years, the integration of artificial intelligence (AI) and machine learning (ML) into education, particularly for Personalized Language Learning (PLL), has garnered significant attention. This approach tailors interventions to address the unique challenges faced by individual learners. Large Language Models (LLMs), including Chatbots, have demonstrated a substantial potential in automating and enhancing educational tasks, effectively capturing the complexity and diversity of human language. In this study, 52 foreign language students were randomly divided into two groups: one with the assistance of a Chatbot based on LLMs and one without. Both groups learned the same series of target words over eight weeks. Post-treatment assessments, including systematic observation and quantitative tests assessing both receptive and productive vocabulary knowledge, were conducted immediately after the study and again two weeks later. The findings demonstrate that employing an AI Chatbot based on LLMs significantly aids students in acquiring both receptive and productive vocabulary…

Recent advancements in polymer science and engineering underscore the importance of creating sophisticated soft materials characterized by well-defined structures and adaptable properties to meet the demands of emerging applications. The primary objective of polymeric composite technology is to enhance the functional utility of materials for high-end purposes. Both the inherent qualities of the materials and the intricacies of the synthesis process play pivotal roles in advancing their properties and expanding their potential applications. Polypyrrole (PPy)-based composites, owing to their distinctive properties, hold great appeal for a variety of applications. Despite the limitations of PPy in its pure form, these constraints can be effectively overcome through hybridization with other materials. This comprehensive review thoroughly explores the existing literature on PPy and PPy-based composites, providing in-depth insights into their synthesis, properties, and applications. Special attention is given to the advantages of intrinsically conducting polymers (ICPs) and PPy in…

This review critically examines the progress and challenges in the field of nanostructured tungsten oxide (WO 3 ) gas sensors. It delves into the significant advancements achieved through nanostructuring and composite formation of WO 3 , which have markedly improved sensor sensitivity for gases like NO 2 , NH 3 , and VOCs, achieving detection limits in the ppb range. The review systematically explores various innovative approaches, such as doping WO 3 with transition metals, creating heterojunctions with materials like CuO and graphene, and employing machine learning models to optimize sensor configurations. The challenges facing WO 3 sensors are also thoroughly examined. Key issues include cross-sensitivity to different gases, particularly at higher temperatures, and long-term stability affected by factors like grain growth and volatility of dopants. The review assesses potential solutions to these challenges, including statistical analysis of sensor arrays, surface functionalization, and the use of novel nanostructures for enhanced performance and selectivity. In addition, the…

Mining wastewater can have adverse effects on the ecosystem; thus, treatment before discharging into the environment is of utmost importance. This manuscript reports on the effect of mining wastewater on the environment. Moreover, the currently used, effective and commercialised mine wastewater treatment technologies such as SAVMIN®, SPARRO®, Biogenic sulphide, and DESALX® are reported in this study. These technologies integrate two or more separation processes, which have been proven to be effective for the high recovery of salts and water for reuse. Some of the technologies reported can significantly recover salts and >95% of water. Modern pilot-stage and laboratory-scale treatment systems used for the recovery and removal of metals are also reported herein. Since some treatment technologies can generate highly toxic sludge and other waste products, the management of the generated waste was also considered. Some studies have focused on the treatment of wastewater at the laboratory level using the adsorption process. Most adsorbents exhibit promising results; however, there is…

Seaweed cultivation has garnered significant interest, driven by its wide range of biomass benefits. However, comprehensive assessments from various perspectives are imperative to ensure the sustainable cultivation of seaweed. Biotic and Abiotic factors can significantly impact seaweed yield in complex commercial farming. Biotic factors include bacteria, fungi, viruses, and other algae, while abiotic factors include environmental conditions such as temperature, salinity, light intensity, and nutrient availability. Additionally, the susceptibility of seaweeds to pests and diseases further compounds the issue, leading to potential crop losses. This study endeavours to shed light on the immense potential of macroalgae cultivation and underscores the pressing need for scientific advancements in this field. The comprehensive review clearly explains the latest developments in seaweed cultivation and highlights significant advances from diverse seaweed research. Moreover, it provides insightful glimpses into possible future developments that could shape the trajectory of this promising…

The internet of things and growing demand for smaller and advanced devices has created the problem of high heat production in the electronic equipment which greatly reduces the work performance and life of the electronic instruments. Thermal interface materials (TIMs) are placed in between heat generating micro-chip and the heat dissipater to conduct all the produced heat to the heat sink. Development of suitable TIMs with excellent thermal conductivity (TC) in both in-plane and through-plane directions is a very important need at present. For efficient thermal management, polymer composites are potential candidates. But in general their thermal conductivity is low compared to that of metals. The filler integration into the polymer matrix is one of the two approaches used to increase the thermal conductivity of polymer composites and is also easy to scale up for industrial production. Another way to achieve this is to change the structure of polymer chains, which fall out of the scope of this work. In this review, considering the first approach, the authors have summarized recent…

Carbon emissions are increasing due to continued urban developments and the growth of the human population, leading to environmental issues such as global warming. Moving towards the future, projected population growth will cause an increase in energy demand. Without the transition to cleaner energy generation, a high dependency on electricity generation by fossil fuels will emit more harmful gases, worsening the impacts of global warming. Therefore, the energy industry is moving towards cleaner alternatives through renewable energy (RE) technologies. However, in the future power grid, more technological development and implementation of cutting-edge research methods will be required to upsurge the percentage of clean electricity generation to attain net zero. Renewables, energy storage systems (ESS), grid technologies, and building energy management systems (BEMS) are key technologies emerging to aid green electrification in the electricity, industry, commercial and transportation sectors. This review discusses the technical challenges and solutions that contribute towards…

Endophytic bacteria, living inside plants, are competent plant colonizers, capable of enhancing immune responses in plants and establishing a mutual relationship with them. Endophytic bacteria have been described as being used to control phytopathogenic fungi while exhibiting plant growth-promoting activity. Here, we discussed the mechanisms of phytopathogenic fungi control and plant growth-promoting actions discovered in some major groups of beneficial endophytic bacteria such as Bacillus , Paenibacillus, and Pseudomonas . Most of the studied strains in these genera were isolated from the rhizosphere and soils, and a more extensive study of these endophytic bacteria is needed. It is essential to understand the underlying biocontrol and plant growth-promoting mechanisms and to develop an effective screening approach for selecting potential endophytic bacteria. We have suggested a screening strategy for potential endophytic bacteria based on mechanistic phenomena. This review will help study and screen biocontrol and plant growth-promoting endophytic bacteria for sustainable…

Huge volumes of organic matters are produced on Earth via photosynthesis and their disposal is a serious threat to the environment and public health all over the world. Nevertheless, these agricultural wastes possess a chemical composition conducive to mushroom cultivation. Lignocellulosic wastes, comprising cellulose, hemicellulose and lignin, offer vital nutrients for mushroom growth. Oyster mushrooms are well known for their unique ability to degrade lignocellulosic materials, making them valuable contributors to the process of organic waste decomposition and nutrient cycling in ecosystems. Employing agricultural by-products as a substrate for mushroom cultivation presents a sustainable approach to waste reduction and the production of nutritionally enriched food. Cultivating oyster mushrooms, presents an economically feasible and environmentally friendly method of transforming waste materials into highly nutritious food. These edible mushrooms are widely grown worldwide, comprising around 27 percent of the total global production. Oyster cultivation has rapidly increased in Asia…

Antimicrobial peptides (AMPs) are a critical component of the innate immune system, playing a key role in defending against a variety of pathogenic microorganisms. While many AMPs act primarily on the cell membrane of target pathogens, leading to lysis and subsequent cell death, less is known about their nonlytic membrane activity. This nonlytic activity allows AMPs to target and disrupt bacterial cells without causing lysis, leading to bacterial death through alternative mechanisms.Understanding these nonlytic properties of AMPs is crucial, as they present a promising alternative to traditional antibiotics, which can induce bacterial resistance and have adverse effects on human health and the environment. The mechanisms by which AMPs exhibit nonlytic membrane activity are still being explored. However, it is believed that AMPs penetrate the bacterial membrane and interact directly with internal cellular components such as DNA, RNA, and various enzymes essential for microbial survival and replication. This interaction disrupts metabolic homeostasis, ultimately resulting in bacterial…

Extreme weather events, rising temperatures, and shifting rainfall patterns pose significant threats to developing countries with fragile social, economic, and political structures. While research has intensified on socioeconomic impacts of climate change, existing survey studies exhibit substantial scope variations and seldom concurrently analyze these impacts, hindering policy coordination. This study reviews literature on the broad spectrum of socioeconomic impacts of climate change to discern trends and underscore areas requiring additional attention. The survey unveils that, across various socioeconomic indicators, the most vulnerable groups bear a disproportionate burden of climate change, with long-term impacts forecasted to surpass medium-term effects. Adaptation and mitigation options are feasible but must be tailored to local contexts.

The average global temperature is rising due to anthropogenic emissions. Hence, a systematic approach was used to examine the projected impacts of rising global temperatures on heatwaves in India and provide insights into mitigation and adaptation strategies. With over 24,000 deaths attributed to heatwaves from 1992 to 2015, there is an urgent need to understand India's vulnerabilities and prepare adaptive strategies under various emission scenarios.This situation is predicted to worsen as heatwaves become more frequent, intense, and long-lasting. Severe heatwaves can exacerbate chronic health conditions, vector-borne diseases, air pollution, droughts and other socio-economic pressures causing higher mortality and morbidity. Heatwaves with severe consequences have increased and are expected to become more frequent in Indian climatic and geographical conditions. As per the future projection studies, the temperature could rise ±1.2 ° C to ±3.5 ° C and will start reducing by the end of 2050. The study also provides data from the research that employs climatic models and statistical…

Blockchain technology can potentially be a bedrock for the energy record-keeping system. This study examined several critical factors that affect users' intention to accept Blockchain technology for the Smart grid. The proposed model is based on the Technology Organization Environment framework, which is examined using Structural Equation Modelling. Based on the study findings, it has been indicated that the relative advantage shows a significant effect and matters the most during the Blockchain technology adoption in the Smart grid. The innovativeness, cost saving, and regulatory support also significantly influence the intention to use the Blockchain technology. The innovativeness and traceability show a significant influence on upper management support. The traceability shows a substantial impact on cost savings. However, innovativeness shows an insignificant effect on cost savings. The traceability and competitive pressure do not affect the intention to use the Blockchain technology. This study has extended the Technology Organization Environment theory, which predicts the…

Research on the lead halide-based perovskite solar cells have obtained considerable interest in photovoltaic industry owing to their higher efficiency, easy manufacturing, light-weight and low cost. However, these lead halide-based solar cells are not suitable to manufacture commercially because of the toxicity of lead-based materials. In this context, a lead-free perovskite, cesium-bismuth iodide (Cs3Bi2I9) is considered as a potential alternative to the lead halide-based cell due to their non-toxicity and stability, but this perovskite cannot be matched with random hole transport layer (HTL) and electron transport layer (ETL) materials compared to lead halide-based perovskite because of their crystal structure and band gap. Therefore, in this study, performance comparison of different ideal HTL and ETL materials for Cs3Bi2I9 perovskite layer were studied using SCAPS-1D device simulation on the basis of open circuit voltage, short circuit current, power conversion efficiency (PCE) and fill factor (FF) as well as several novel PSC configuration model were designed that can direct…

This study presents the development and implementation of an Internet of Things (IoT)-based real-time water quality monitoring system tailored for water treatment plants (WTPs). The system integrates advanced sensor technologies to continuously monitor key water quality parameters such as pH, dissolved oxygen (DO), total dissolved solids (TDS), and temperature. Data collected by these sensors is transmitted through a robust communication network to a centralized monitoring platform that utilizes cloud-based storage and analytics. The system's design includes a PLC-based control mechanism, allowing for flexible setup modifications and the easy addition of new monitoring parameters. The IoT-based system, powered by a low-energy 29-W configuration, offers accurate and reliable data with a minimal error margin of 0.1-0.2 across various parameters. The research highlights the system's ability to provide real-time alerts, historical data logging, and remote monitoring, all of which contribute to enhanced operational efficiency, proactive maintenance, and informed decision-making. This…

The role of artificial intelligence (AI) in education has been extensively studied, focusing on its ability to enhance learning and teaching processes. However, the precise impact of AI adoption on academic performance in open and distance learning (ODL) remains largely unexplored. This systematic literature review critically evaluates AI's impact on academic performance within ODL environments. Drawing from a curated selection of 64 papers from an initial pool of 700, spanning from 2017 to 2023 and sourced from Scopus, Google Scholar, and Web of Science, this study delves into the multifaceted role of AI in enhancing learning outcomes. The meta-analysis reveals a diverse methodological landscape: machine learning methods, employed in 29.69 % of the studies, stand out for their ability to predict academic achievement, which is matched in prevalence by classical statistical methods. Although less common at 3.13 %, hybrid methods are a burgeoning area of research, while a significant 40.63 % of works prioritise nonempirical methods, focusing on theoretical analysis and literature…