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A Comprehensive Review on Antibacterial, Anti-Inflammatory and Analgesic Properties of Noble Metal Nanoparticles
Their health industry is facing challenges due to a rise in mortality rates brought on by various multi-drug-resistant bacterial strains. As a result, new and improvedantibacterial drugs are urgently needed. Similarly, when some unwanted foreign pathogensenter the cellular premises to disturb its homeostasis, inflammation develops as an immune reaction. However, these immune responses also become a double-edged sword when the inflammatory reaction lasts for a long time, and pain is also linked to inflammatory responses. Inflammation and pain are both signs of tissue injury. Pain is,by definition, an unpleasant experience that ultimately interferes with their normalwell-being. Hence, bacterial infection, inflammation, and pain need medical assistance to maintain homeostasis. Conventional medicines possess so many repercussive effects, which then demand a replacement with a less toxic and more efficient modern drug. In their review article, for the first time, they present recent advancements in biomedical applications such as the antimicrobial, anti-inflammatory, and analgesic properties of noble metal nanoparticles. Noble metals have limited availability in the earth's crust. Hence, their physicochemical characterizations and applications are greatly limited. Still, there are some interesting research findings that offer a significant ray of hope for the health sector all over the world. 2023 Wiley-VCH GmbH. -
A comprehensive review on application of atomic force microscopy in Forensic science
The primary objective of forensic investigation of a case is to recognize, identify, locate, and examine the evidence. Microscopy is a technique that provides crucial information for resolving a case or advancing the investigation process by analyzing the evidence obtained from a crime scene. It is often used in conjunction with suitable analytical techniques. Various microscopes are employed; scanning probe microscopes are available in diverse forensic analyses and studies. Among these, the atomic force microscope (AFM) is the most commonly used scanning probe technology, offering a unique morphological and physico-chemical perspective for analyzing multiple pieces of evidence in forensic investigations. Notably, it is a non-destructive technique capable of operating in liquid or air without complex sample preparation. The article delves into a detailed exploration of the applications of AFM in the realms of nanomechanical forensics and nanoscale characterization of forensically significant samples. 2024 Elsevier Ltd and Faculty of Forensic and Legal Medicine -
A comprehensive review on bifunctional catalysts for efficient electrochemical hydrogen production from wastewater
The authors regret the wrong project number in the acknowledgement part, which has been renewed this year in the Korea's side. It is an important issue since the achievement of the funded project requires a correct project number during assessment. Therefore, the authors sincerely hope that the editor could kindly consider to change the content (project number) in the acknowledgement part as follow: Old number: New number: < This work was supported by the SEED money scheme, CHRIST University, Bangalore (CU-ORS-SM-24/32) and National Research Foundation of Korea (Project: RS-202400343361) The authors would like to deeply apologise for any inconvenience caused. 2025 Hydrogen Energy Publications LLC -
A comprehensive review on energy management strategy of microgrids
Renewable energy resources are a one-stop solution for major issues that include drastic climate change, environmental pollution, and the depletion of fossil fuels. Renewable energy resources, their allied storage devices, load supplied, non-renewable sources, along with the electrical and control devices involved, form the entity called microgrids. Energy management systems are essential in microgrids with more than one energy resource and storage system for optimal power sharing between each component in the microgrid for efficient, reliable and economic operation. A critical review on energy management for hybrid systems of different configurations, the diverse techniques used, forecasting methods, control strategies, uncertainty consideration, tariffs set for financial benefits, etc. are reviewed in this paper. The novelty of reformer based fuel cells, which generates hydrogen on demand, thereby eliminating the requirement of hydrogen storage and lowest carbon footprint is discussed for the first time in this paper. The topics requiring extended research and the existing gap in literature in the field of energy management studies are presented in the authors perspective, which will be helpful for researchers working in the same specialization. Papers are segregated based on multiple aspects such as the configuration, in particular, grid-tied, islanded, multi microgrids, the control strategies adopted besides the identification of limitations/factors not considered in each work. Moreover, at the end of each section, the literature gap related to each category of segregated group is identified and presented. 2023 The Author(s) -
A Comprehensive Review on Fault Data Injection in Smart Grid
Nowadays, power generation at the utility side and transfer to the demand side have been controlled by the smart grid. Day-by-day entire power distribution process has moved in multiple directions and connects more residential and industrial sectors. Due to these phenomena, more monitoring, and security processes have been adopted in smart grid to control fault data injection, cyber-attack, and physical side attackers in smart grids. This research study analyzes the fault data injection in smart grid with respect to the malicious data, signal, and connectivity process. As a part of this research study, a survey has been done on various techniques to control the faults in smart grid. The analysis carried out in this study is very helpful to identify and determine the suitable method to control the fault in smart grid. Along with these, a countermeasure against the FDI is also summarized on the cyber-attack and physical attack. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Comprehensive Review on Heart Disease Risk Prediction using Machine Learning and Deep Learning Algorithms
Cardiovascular diseases claim approximately 17.9 million lives annually, with heart attacks and strokes accounting for over 80% of these deaths. Key risk factors, including hypertension, hyperglycemia, dyslipidemia, and obesity, are identifiable, offering opportunities for timely intervention and reduced mortality. Early detection of heart disease enables individuals to adopt lifestyle changes or seek medical treatment. However, conventional diagnostic methods, such as electrocardiogramscommonly used in clinics and hospitals to detect abnormal heart rhythmsare not effective in identifying actual heart attacks. Additionally, angiography, while more precise, is an invasive method, financial strain on patients, and high chances of incorrect diagnosis, highlighting the need for alternative approaches. The main goal of this study was to assess the accuracy of machine learning techniques, including both individual and combined classifiers, in early detection of heart diseases. Furthermore, the study aims to highlight areas where additional research is necessary. Our investigation covers a decade period from 2014 to 2024, including a thorough review of pertinent literature from international conferences and top journals from the databases like Springer, ScienceDirect, IEEEXplore, Web of Science, PubMed, MDPI, Hindawi and so on. The following keywords were used to search the articles: heart disease risk, heart disease prediction, data mining, data preprocessing, machine learning algorithms, ensemble classifiers, deep learning algorithms, feature selection, hyperparameter optimization techniques. We examine the methodologies used and evaluate their effectiveness in predicting cardiovascular conditions. Our findings reveal notable progress in applying machine learning and deep learning in cardiology. The study concludes by proposing a framework that incorporates current machine learning techniques to enhance heart disease prediction. The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE) 2024. -
A Comprehensive Review on Image Restoration Methods due to Salt and Pepper Noise
Digital images are well-use in various fields like satellite communication, mobile communication, medical and security. Visualized information helps the people to understand the things easily by seen. Improper capturing, age of camera lens, imperfect storage and transmission leads to introduce noise in the image. Gaussian noise, salt and pepper/impulse noise and speckle noise may affect the original image due to aforementioned reasons. Out of these, impulse noise/salt and pepper noise is one of the major types, degrades the image with black and white spots it results loss of required information. Hence, restoration of ground- truth image from such type of noisy image is a challenging task to provide quality and clarity visuals to users. Several linear and non-linear methods have been proposed by researchers since more than four decades. Nonlinear methods based on; median filtering approach; adaptive median filter approach; median filter with switching condition; and median filter with rank order type; are proposed from early 1980s onwards. All of these operated directly on pixels in spatial domain. Hence, they are very easy to implement and most of them are not that much robust at middle and higher noise density circumstances. Further, various researchers have been implemented linear methods such as wavelet transform methods like SWT and DWT. Majority of these are works well upto 50% noise density conditions and very few works well on higher and multiple noise density conditions also. To overcome these problems CNNs based methods have been developed tremendously by various researchers from last decade and these methods require huge database to train the network model. Most of these, achieved good accuracy rates at higher and multiple noise conditions. Hence, here a detailed review report is presented on impulse noise removal methods with their Peak Signal to Noise Ratio (PSNR). 2023 IEEE. -
A comprehensive review on natural macromolecular biopolymers for biomedical applications: Recent advancements, current challenges, and future outlooks
Versatile material properties coupled with high degree of biocompatibility and biodegradability has made biopolymers as potential candidates for diverse applications in the biomedical field. Natural biopolymers derived from various plant, animal and microbial sources with different biochemical compositions are extensively used in biomaterial industry with or without further medication to their native form. Biopolymeric biomaterials have been employed in a wide range of biomedical applications like tissue engineering, drug delivery, bone regeneration, wound dressings and cardiovascular surgery. Carbohydrate based biopolymers and protein based biopolymers are extensively used for several applications in the biomedical field including cartilage regeneration, periodontal tissue regeneration, bone regeneration, corneal regeneration, drug delivery and wound healing. This review work presents a comprehensive outlook on the applications of various biopolymers in biomedical field. The work elaborates the biochemistry of these polymers with special focus on their crucial properties in the biomedical industry. Further a detailed description on the most recent application of various biopolymers in the biomedical filed is presented in this review. This work further summarizes the current challenges and future prospects in the use of biopolymers in biomedical field. 2024 The Author(s) -
A Comprehensive Review on the Antimicrobial and Photocatalytic Properties of Green Synthesized Silver Nanoparticles
With the advancement of technology, there is a growing demand for new nanoparticles that are viable, eco-friendly, non-toxic, and non-hazardous, as well as having unique chemical and physical properties. Silver nanoparticles are currently promising for antibacterial, antimicrobial, and photocatalytic applications. Because of their toxicity, nanosilver particles are now widely used in various applications, including cosmetics, clothing, sunscreen, medicinal, sensing, antibacterial, antimicrobial, and photocatalytic. The importance of plant extracts in the synthesis of AgNPs is emphasized. The various mechanisms and characterization techniques used in the study of silver nanoparticles will also be covered. This review also discusses the role of green synthesized AgNPs in antimicrobial and photocatalytic applications, which adds to our understanding of improving health, and the environment and preventing contagious diseases. 2022 by the authors. -
A Comprehensive Review on the Electrochemical Sensing of Flavonoids
Flavonoids are bioactive polyphenolic compounds, widespread in the plant kingdom. Flavonoids possess broad-spectrum pharmacological effects due to their antioxidant, anti-tumor, anti-neoplastic, anti-mutagenic, anti-microbial, anti-inflammatory, anti-allergic, immunomodulatory, and vasodilatory properties. Care must be taken, since excessive consumption of flavonoids may have adverse effects. Therefore, proper identification, quantification and quality evaluations of flavonoids in edible samples are necessary. Electroanalytical approaches have gained much interest for the analysis of redox behavior and quantification of different flavonoids. Compared to various conventional methods, electrochemical techniques for the analysis of flavonoids offer advantages of high sensitivity, selectivity, low cost, simplicity, biocompatibility, easy on-site evaluation, high accuracy, reproducibility, wide linearity of detection, and low detection limits. This review article focuses on the developments in electrochemical sensing of different flavonoids with emphasis on electrode modification strategies to boost the electrocatalytic activity and analytical efficiency. 2022 Taylor & Francis Group, LLC. -
A comprehensive review on the need for integrated strategies and process modifications for per- and polyfluoroalkyl substances (PFAS) removal: Current insights and future prospects
Alarming concern over the persistence and toxicity of per- and polyfluoroalkyl substances (PFAS) in the environment has created an imperative need for designing and redesigning strategies for their detection and remediation. Conventional PFAS removal technologies that uses physical, chemical, or biological methods. Increase in the diversity and quantity of PFAS entering the environment has necessitated the need for developing more advanced and integrated strategies for their removal. Despite of the advances reported in this domain, there exist a huge research gap that need to be mentored to tackle the problems associated with mitigation of combined toxicity of wide variety of PFAS in the environment. The possibility of PFAS to combine with other emerging contaminants poses an additional threat to the existing treatment methods thereby stressing the need for a continuous monitoring and updating the treatment processes. This review work aims at understanding the structure, entry, and fate of different types of PFAS in to the environment. Further an in-depth discussion regarding the different levels of toxicity associated with PFAS is elaborated in the review. The process description of recent PFAS remediation techniques along with their significance, limitations and possibility of integration is discussed in detail. Further a detailed outlook on the advantages and limitations of PFAS removal methods and an insight into the recently developed PFAS removal methods is outlined in this review. 2024 The Authors -
A comprehensive review on tissue culture studies and secondary metabolite production in Bacopa monnieri L. Pennell: a nootropic plant
Bacopa monnieri L. Pennell, commonly known as Brahmi, is an important medicinal plant that belongs to the family Plantaginaceae. Brahmi is rich in innumerable bioactive secondary metabolites, especially bacosides that can be employed to reduce many health issues. This plant is used as a neuro-tonic and treatment for mental health, depression, and cognitive performance. Brahmi is also known for its antioxidant, anti-inflammatory, and anti-hepatotoxic activities. There is a huge demand for its raw materials, particularly for the extraction of bioactive molecules. The conventional mode of propagation could not meet the required commercial demand. To overcome this, biotechnological approaches, such as plant tissue culture techniques have been established for the production of important secondary metabolites through various culture techniques, such as callus and cell suspension cultures and organ cultures, to allow for rapid propagation and conservation of medicinally important plants with increased production of bioactive compounds. It has been found that a bioreactor-based technology can also enhance the multiplication rate of cell and organ cultures for commercial propagation of medicinally important bioactive molecules. The present review focuses on the propagation and production of bacoside A by cell and organ cultures of Bacopa monnieri, a nootropic plant. The review also focuses on the biosynthesis of bacoside A, different elicitation strategies, and the over-expression of genes for the production of bacoside-A. It also identifies research gaps that need to be addressed in future studies for the sustainable production of bioactive molecules from B. monnieri. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
A Comprehensive Review on Using Electronic Waste as a Construction Material
The study explores the use of electronic waste (E-waste) as a sustainable alternative in a variety of construction applications, addressing the rising global issue of E-waste management. E-waste, consisting of both metallic and non-metallic components, contains valuable and hazardous materials, which can lead to environmental damage, if improperly managed. The study demonstrates different methods for incorporating E-waste into bituminous mixes, high-strength concrete, and other composite materials. Research shows that, using E-waste improves the strength as well as durability properties of concrete. It acts as a practical alternative for disposing of E-waste and promotes the use of sustainable building methods. Furthermore, the potential of employing E-waste in the construction of flexible pavements is reviewed, which demonstrates positive results in improving the mechanical characteristics of asphalt mixtures. The study also highlights how E-waste can help with sustainable building methods by cutting down on landfill waste, preserving natural resources, and lowering carbon footprints. The results show that the use of E-waste not only offers a more suitable choice than traditional materials but also helps to lessen pollution from solid waste, which is consistent with worldwide efforts to improve environmental sustainability. Overall, this study shows that E-waste is a useful material for the construction, providing a creative waste management strategy that is in line with worldwide sustainability objectives. The results indicate that E-waste can be an important source of eco-friendly building materials, reducing environmental pollution and encouraging responsible resource utilization, if it is treated and integrated properly. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
A Comprehensive Review onCrop Disease Prediction Based onMachine Learning andDeep Learning Techniques
Leaf diseases cause direct crop losses in agriculture, and farmers cannot detect the disease early. If the diseases are not detected early and correctly, the farmer must undergo huge losses. It may lead to the wrong pesticide or over pesticide, directly affect crop productivity and economy, and indirectly affect human health. Sensitive crops have various leaf diseases, and early prediction of these diseases remains challenging. This paper reviews several machine learning (ML) and deep learning (DL) methods used for different crop disease segmentation and classification. In the last few years, computer vision and DL techniques have made tremendous progress in object detection and image classification. The study summaries the available research on different diseases on various crops based on machine learning (ML) and deep learning (DL) techniques. It also discusses the data sets used for research and the accuracy and performance of existing methods. It does mean that the methods and available data sets presented in this paper are not projected to replace published solutions for crop disease identification, perhaps to enhance them by finding the possible gaps. Seventy-five articles are analysed and reviewed to find essential issues that involve additional study for future research in this domain to promote continuous progress for data sets, methods, and techniques. It mainly focuses on image segmentation and classification techniques used to solve agricultural problems. Finally, this paper provides future research scope and challenges, limitations, and research gaps. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Comprehensive Study for Application of Blockchain Technologies for the Decentralized Grid Utilization Possibilities
This thorough research explores the world of blockchain technology and its significant effects on the use of decentralized grids. Decentralized networks have shown promise in addressing the rising need for renewable energy and effective resource management. Blockchain, a technology based on distributed ledgers, presents creative approaches to improve grid oversight, enable through peer-to- energy trade, and guarantee openness and protection in the management of the grid. This paper investigates the advantages and disadvantages of using blockchain in decentralized grids. From trading in renewable energy to grid optimization and demand response, we examine a variety of use cases and applications. We offer insight into the practical viability and scalability of blockchain-based solutions through a thorough analysis of real-world deployments and case reports. We also address the legislative and technological challenges to be solved before blockchain technology can realize its full potential in decentralized grid setups. Our research strongly emphasizes that regulatory architectures, seamless integration, and standardization all contribute to supporting the harmonious adaptation of blockchain technology worldwide. This study provides lawmakers, industry players, and investigators in the efforts to build a sustainable and effective energy future with an informative tool: it will shed light on the potential and constraints presented by blockchain technology in a decentralized environment of grid usage. 2025 IEEE. -
A Comprehensive Study of Blockchain Technology Based Decentralised Ledger Implementations
Information management and decentralized, secure transactions are made possible by the groundbreaking idea of blockchain technology. Blockchain has attracted considerable attention from a wide range of businesses as a result of the rising popularity of cryptocurrencies like Bitcoin and Ethereum. The primary goal of this paper is to present a thorough examination of decentralized ledger systems based on blockchain technology. It examines at the basic ideas, underpinnings, and real-world uses of blockchain in many industries. The ability to scale, effectiveness, privacy, security, seamless integration, governing scenarios, and consumption of energy are just a few of the technical factors that are looked at in relation to the deployment of blockchain technology. In this research paper we also pinpoint forthcoming developments and future prospects for the blockchain industry like Solutions for scalability at the subsequent layer, protocols for seamless integration, integration with the Internet of Things (IoT), apps for decentralized finance (DeFi), and digital currencies that are issued by central banks (CBDCs) are a few examples. 2023 IEEE. -
A Comprehensive Study on Computer-Aided Cataract Detection, Classification, and Management Using Artificial Intelligence
The day-to-day popularity of computer-aided detection is increasing medical field. Cataract is a main cause of blindness in the entire world. Compared with the other eye diseases, computer-aided development in the area of cataract is remaining underexplored. Several researches are done for automated detection of cataract. Many study groups have proposed many computer-aided systems for detecting cataract, classifying the different type, identification of stages, and calculation of lens power selection prior to cataract surgery. With the advancement in the artificial intelligence and machine learning, future cataract-related research work can undergo very useful achievements in the coming days. The paper studies various recent researches done related to cataract detection, classification, and grading using various artificial intelligence techniques. Various comparisons are done based on the methodology used, type of dataset, and the accuracy of various methodologies. Based on the comparative study, research gap is identified, and a new method is proposed which can overcome the disadvantages and gaps of the studied work. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Comprehensive Study On Detection Of Emotions Using Human Body Movements: Machine Learning Approach
Identifying emotions from human beings is the most challenging area in artificial intelligence. There are different modules used to identify emotions like speech, face, EEG, Physiological Signals, and body movement. However, emotional recognition from body movement is the need of time. The review focuses on identifying various emotions with the help of the full-body movement model and the parts-based model. The aim of the survey is to identify the recent work done by the researchers with the help of full-body movements and body parts-based models. Recently, little research has been done on the identification of emotions using body movements, but most of the time it has succeeded to some extent. Identifying various human emotions using body movements is a really very challenging task. This research work discovers that the various popular machine learning algorithms like Support Vector Machines, Neural Networks, and convolutional neural networks are majorly used to identify basic emotions. 2023 American Institute of Physics Inc.. All rights reserved. -
A Comprehensive Study on E-learning Environments for Deaf or Hard of Hearing Learners
Quality education is the fundamental right of every individual regardless of the disabilities they have. For the Deaf or Hard of Hearing (d/DHH) people, e-learning is the most promising way to access the educational materials referred to as digital learning objects (LO) at any time and space which increase their autonomous learning skills. This form of instruction delivery was widely accepted during the outbreak of Covid-19. Hence a background study has been conducted to investigate the challenges in teaching the d/DHH learners during the pandemic. This research work aims at providing a personalized e-learning environment to the d/DHH student community belonging to St. Clare Oral Higher Secondary School for The Deaf, situated in Kerala. To build personalized systems, the primary step is to review the existing e-learning solutions available in the literature and the adaptation techniques implemented by them to offer personalization in line with the components of traditional adaptive e-learning systems. The study carried out in this paper illuminates the need of personalized e-learning platforms that adapt the basic needs, abilities and disabilities of deaf learners which will find the 'best learning solutions' in the form of learning objects. 2023 IEEE. -
A Comprehensive Study on Electric Vehicle Charging Infrastructure
Issues of global warming and hike in the fuel price have taken electric vehicles (EVs) to be popular among the ordinary people. But the main drawbacks are related to the vehicle price and the scarcity of charging infrastructure. In this paper, a review of various charging infrastructures of electric vehicles that are existing and emerging are discussed. The paper also gives an overview of the charging standards for EVs. The Electrochemical Society