SRM Institute of Science and Technology

The use of nanotechnology has the potential to revolutionize the detection and treatment of cancer. Developments in protein engineering and materials science have led to the emergence of new nanoscale targeting techniques, which offer renewed hope for cancer patients. While several nanocarriers for medicinal purposes have been approved for human trials, only a few have been authorized for clinical use in targeting cancer cells. In this review, we analyze some of the authorized formulations and discuss the challenges of translating findings from the lab to the clinic. This study highlights the various nanocarriers and compounds that can be used for selective tumor targeting and the inherent difficulties in cancer therapy. Nanotechnology provides a promising platform for improving cancer detection and treatment in the future, but further research is needed to overcome the current limitations in clinical translation.

India, the second largest agro-based economy with year-round crop cultivation, generates a large amount of agricultural waste, including crop residues. In the absence of adequate sustainable management practices, approximately 92 seems a very small number of metric tons of crop waste is burned every year in India, causing excessive particulate matter emissions and air pollution. Crop residue burning has become a major environmental problem causing health issues as well as contributing to global warming. Composting, biochar production and mechanization are a few effective sustainable techniques that can help to curtail the issue while retaining the nutrients present in the crop residue in the soil. The government of India has attempted to curtail this problem, through numerous measures and campaigns designed to promote sustainable management methods such as converting crop residue into energy. However, the alarming rise of air pollution levels caused by crop residue burning in the city of Delhi and other northern areas in India observed in recent years, especially in and after the year of 2015, suggest that the issues is not yet under control. The solution to crop residue burning lies in the effective implementation of sustainable management practices with Government interventions and policies. This manuscript addresses the underlying technical as well as policy issues that has prevented India from achieving a long-lasting solution and also potential solutions that have been overlooked. However, effective implementation of these techniques also requires us to look at other socioeconomic aspects that had not been considered. This manuscript also discusses some of the policy considerations and functionality based on the analyses and current practices. The agricultural waste sector can benefit immensely from some of the examples from other waste sectors such as the municipal solid waste (MSW) and wastewater management where collection, segregation, recycling and disposal are institutionalized to secure an operational system. Active stakeholder involvement including education and empowerment of farmers along with technical solutions and product manufacturing can also assist tremendously. Even though the issue of crop residue burning touches many sectors, such as environment, agriculture, economy, social aspects, education, and energy, the past governmental efforts mainly revolved around agriculture and energy. This sectorial thinking is another barrier that needs to be broken. The government of India as well as governments of other developing countries can benefit from the emerging concept of nexus thinking in managing environmental resources. Nexus thinking promotes a higher-level integration and higher level of stakeholder involvement that goes beyond the disciplinary boundaries, providing a supporting platform to solve issues such as crop residue burning.

Healthcare decisions for individual patients and for public health policies should be informed by the best available research evidence. The practice of evidence-based medicine is the integration of individual clinical expertise with the best available external clinical evidence from systematic research and patient's values and expectations. Primary care physicians need evidence for both clinical practice and for public health decision making. The evidence comes from good reviews which is a state-of-the-art synthesis of current evidence on a given research question. Given the explosion of medical literature, and the fact that time is always scarce, review articles play a vital role in decision making in evidence-based medical practice. Given that most clinicians and public health professionals do not have the time to track down all the original articles, critically read them, and obtain the evidence they need for their questions, systematic reviews and clinical practice guidelines may be their best source of evidence. Systematic reviews aim to identify, evaluate, and summarize the findings of all relevant individual studies over a health-related issue, thereby making the available evidence more accessible to decision makers. The objective of this article is to introduce the primary care physicians about the concept of systematic reviews and meta-analysis, outlining why they are important, describing their methods and terminologies used, and thereby helping them with the skills to recognize and understand a reliable review which will be helpful for their day-to-day clinical practice and research activities.

Magnonics is a budding research field in nanomagnetism and nanoscience that addresses the use of spin waves (magnons) to transmit, store, and process information. The rapid advancements of this field during last one decade in terms of upsurge in research papers, review articles, citations, proposals of devices as well as introduction of new sub-topics prompted us to present the first roadmap on magnonics. This is a collection of 22 sections written by leading experts in this field who review and discuss the current status besides presenting their vision of future perspectives. Today, the principal challenges in applied magnonics are the excitation of sub-100 nm wavelength magnons, their manipulation on the nanoscale and the creation of sub-micrometre devices using low-Gilbert damping magnetic materials and its interconnections to standard electronics. To this end, magnonics offers lower energy consumption, easier integrability and compatibility with CMOS structure, reprogrammability, shorter wavelength, smaller device features, anisotropic properties, negative group velocity, non-reciprocity and efficient tunability by various external stimuli to name a few. Hence, despite being a young research field, magnonics has come a long way since its early inception. This roadmap asserts a milestone for future emerging research directions in magnonics, and hopefully, it will inspire a series of exciting new articles on the same topic in the coming years.

The electrochemical biosensors are a class of biosensors which convert biological information such as analyte concentration that is a biological recognition element (biochemical receptor) into current or voltage. Electrochemical biosensors depict propitious diagnostic technology which can detect biomarkers in body fluids such as sweat, blood, feces, or urine. Combinations of suitable immobilization techniques with effective transducers give rise to an efficient biosensor. They have been employed in the food industry, medical sciences, defense, studying plant biology, etc. While sensing complex structures and entities, a large data is obtained, and it becomes difficult to manually interpret all the data. Machine learning helps in interpreting large sensing data. In the case of biosensors, the presence of impurity affects the performance of the sensor and machine learning helps in removing signals obtained from the contaminants to obtain a high sensitivity. In this review, we discuss different types of biosensors along with their applications and the benefits of machine learning. This is followed by a discussion on the challenges, missing gaps in the knowledge, and solutions in the field of electrochemical biosensors. This review aims to serve as a valuable resource for scientists and engineers entering the interdisciplinary field of electrochemical biosensors. Furthermore, this review provides insight into the type of electrochemical biosensors, their applications, the importance of machine learning (ML) in biosensing, and challenges and future outlook.

Zinc oxide (ZnO) is an adaptable material that has distinctive properties, such as high-sensitivity, large specific area, non-toxicity, good compatibility and a high isoelectric point, which favours it to be considered with a few exceptions. It is the most desirable group of nanostructure as far as both structure and properties. The unique and tuneable properties of nanostructured ZnO shows excellent stability in chemically as well as thermally stable n-type semiconducting material with wide applications such as in luminescent material, supercapacitors, battery, solar cells, photocatalysis, biosensors, biomedical and biological applications in the form of bulk crystal, thin film and pellets. The nanosized materials exhibit higher dissolution rates as well as higher solubility when compared to the bulk materials. This review significantly focused on the current improvement in ZnO-based nanomaterials/composites/doped materials for the application in the field of energy storage and conversion devices and biological applications. Special deliberation has been paid on supercapacitors, Li-ion batteries, dye-sensitized solar cells, photocatalysis, biosensors, biomedical and biological applications. Finally, the benefits of ZnO-based materials for the utilizations in the field of energy and biological sciences are moreover consistently analysed.

Histamine and its receptors (H1R-H4R) play a crucial and significant role in the development of various allergic diseases. Mast cells are multifunctional bone marrow-derived tissue-dwelling cells that are the major producer of histamine in the body. H1R are expressed in many cells, including mast cells, and are involved in Type 1 hypersensitivity reactions. H2R are involved in Th1 lymphocyte cytokine production. H3R are mainly involved in blood-brain barrier function. H4R are highly expressed on mast cells where their stimulation exacerbates histamine and cytokine generation. Both H1R and H4R have important roles in the progression and modulation of histamine-mediated allergic diseases. Antihistamines that target H1R alone are not entirely effective in the treatment of acute pruritus, atopic dermatitis, allergic asthma, and other allergic diseases. However, antagonists that target H4R have shown promising effects in preclinical and clinical studies in the treatment of several allergic diseases. In the present review, we examine the accumulating evidence suggesting novel therapeutic approaches that explore both H1R and H4R as therapeutic targets for histamine-mediated allergic diseases.

The human gastrointestinal tract harbors trillions of bacteria, most of which are commensal and have adapted over time to the milieu of the human colon. Their many metabolic interactions with each other, and with the human host, influence human nutrition and metabolism in diverse ways. Our understanding of these influences has come through breakthroughs in the molecular profiling of the phylogeny and the metabolic capacities of the microbiota. The gut microbiota produce a variety of nutrients including short-chain fatty acids, B vitamins, and vitamin K. Because of their ability to interact with receptors on epithelial cells and subepithelial cells, the microbiota also release a number of cellular factors that influence human metabolism. Thus, they have potential roles in the pathogenesis of metabolic syndrome, diabetes, non-alcoholic fatty liver disease, and cognition, which extend well beyond their traditional contribution to nutrition. This review explores the roles of the gut microbiota in human nutrition and metabolism, and the putative mechanisms underlying these effects.

Vanadium pentoxide (V(2)O(5)) has attracted attention for supercapcitor applications because of its extensive multifunctional properties. In the present study, V(2)O(5) nanoporous network was synthesized via simple capping-agent-assisted precipitation technique and it is further annealed at different temperatures. The effect of annealing temperature on the morphology, electrochemical and structural properties, and stability upon oxidation-reduction cycling has been analyzed for supercapacitor application. We achieved highest specific capacitance of 316 F g(-1) for interconnected V(2)O(5) nanoporous network. This interconnected nanoporous network creates facile nanochannels for ion diffusion and facilitates the easy accessibility of ions. Moreover, after six hundred consecutive cycling processes the specific capacitance has changed only by 24%. A simple cost-effective preparation technique of V(2)O(5) nanoporous network with excellent capacitive behavior, energy density, and stability encourages its possible commercial exploitation for the development of high-performance supercapacitors.

The underrepresentation of non-Europeans in human genetic studies so far has limited the diversity of individuals in genomic datasets and led to reduced medical relevance for a large proportion of the world's population. Population-specific reference genome datasets as well as genome-wide association studies in diverse populations are needed to address this issue. Here we describe the pilot phase of the GenomeAsia 100K Project. This includes a whole-genome sequencing reference dataset from 1,739 individuals of 219 population groups and 64 countries across Asia. We catalogue genetic variation, population structure, disease associations and founder effects. We also explore the use of this dataset in imputation, to facilitate genetic studies in populations across Asia and worldwide.

Considering a future scenario in which a driverless Electric Vehicle (EV) needs an automatic charging system without human intervention. In this regard, there is a requirement for a fully automatable, fast, safe, cost-effective, and reliable charging infrastructure that provides a profitable business model and fast adoption in the electrified transportation systems. These qualities can be comprehended through wireless charging systems. Wireless Power Transfer (WPT) is a futuristic technology with the advantage of flexibility, convenience, safety, and the capability of becoming fully automated. In WPT methods resonant inductive wireless charging has to gain more attention compared to other wireless power transfer methods due to high efficiency and easy maintenance. This literature presents a review of the status of Resonant Inductive Wireless Power Transfer Charging technology also highlighting the present status and its future of the wireless EV market. First, the paper delivers a brief history throw lights on wireless charging methods, highlighting the pros and cons. Then, the paper aids a comparative review of different type’s inductive pads, rails, and compensations technologies done so far. The static and dynamic charging techniques and their characteristics are also illustrated. The role and importance of power electronics and converter types used in various applications are discussed. The batteries and their management systems as well as various problems involved in WPT are also addressed. Different trades like cyber security economic effects, health and safety, foreign object detection, and the effect and impact on the distribution grid are explored. Prospects and challenges involved in wireless charging systems are also highlighting in this work. We believe that this work could help further the research and development of WPT systems.

Abstract Fish gut microbiome confers various effects to the host fish; this includes overall size, metabolism, feeding behaviour and immune response in the fish. The emergence of antimicrobial‐resistant (AMR) bacteria and hard to cure fish diseases warrant the possible utilization of gut microbes that exhibits a positive effect on the fish and thus lead to the usage of these microbes as probiotics. The widespread and systematic use of antibiotics has led to severe biological and ecological problems, especially the development of antibiotic resistance that affects the gut microbiota of aquatic organisms. Probiotics are proposed as an effective and environmentally friendly alternative to antibiotics, known as beneficial microbes. At the same time, prebiotics are considered beneficial to the host's health and growth by decreasing the prevalence of intestinal pathogens and/or changing the development of bacterial metabolites related to health. Uprise of sequencing technology and the development of intricate bioinformatics tools has provided a way to study these gut microbes through metagenomic analysis. From various metagenomic studies, ample of information was obtained; such information includes the effect of the gut microbiome on the physiology of fish, gut microbe composition of different fish, factors affecting the gut microbial composition of the fish and the immunological effect of gut microbes in fish; such this information related to the fish gut microbiome, their function and their importance in aquaculture is discussed in this review.

Click to increase image sizeClick to decrease image size AcknowledgementsWe thank the Department of Biotechnology and Indian Institute of Technology Madras for computational facilities. We wish to acknowledge Dr. C. Ramakrishnan, Dr. S. Anusuya, S. Akila Parvathy Dharshini and Dr. A. Mary Thangakani for fruitful discussions.Disclosure statementNo potential conflict of interest was reported by the authors.TableDownload CSVDisplay TableAdditional informationFundingThe work is partially supported by the Department of Biotechnology, Government of India to MMG.

The second-generation hybrid and Electric Vehicles are currently leading the paradigm shift in the automobile industry, replacing conventional diesel and gasoline-powered vehicles. The Battery Management System is crucial in these electric vehicles and also essential for renewable energy storage systems. This review paper focuses on batteries and addresses concerns, difficulties, and solutions associated with them. It explores key technologies of Battery Management System, including battery modeling, state estimation, and battery charging. A thorough analysis of numerous battery models, including electric, thermal, and electro-thermal models, is provided in the article. Additionally, it surveys battery state estimations for a charge and health. Furthermore, the different battery charging approaches and optimization methods are discussed. The Battery Management System performs a wide range of tasks, including as monitoring voltage and current, estimating charge and discharge, equalizing and protecting the battery, managing temperature conditions, and managing battery data. It also looks at various cell balancing circuit types, current and voltage stressors, control reliability, power loss, efficiency, as well as their advantages and disadvantages. The paper also discusses research gaps in battery management systems.

Abstract Artificial intelligence education (AIEd) is defined in the field of education as the utilization of artificial intelligence. There are currently many AIEd‐driven applications in schools and universities. This paper applies an artificial intelligence module combined with the knowledge recommendation to the system and develops an online English teaching system in comparison with the common teaching auxiliary system. The method of English teaching is useful in investigating the potential internal connections between evaluation outcomes and various factors. This article develops deep learning‐assisted online intelligent English teaching system that utilizes to create a modern tool platform to help students improve their English language teaching efficiency in line with their mastery of knowledge and personality. The decision tree algorithm and neural networks have been used and to generate an English teaching assessment implementation model based on decision tree technologies. It provides valuable data from extensive information, summarizes rules and data, and helps teachers to improve their education and the English scores of students. This system reflects the thinking of the artificial intelligence expert system. Test application demonstrates that the system can help students improve their learning efficiency and will make learning content more relevant. Besides, the system provides an example model with similar methods and has a referential definition.

Fossil fuels are currently the most significant energy sources. They are expected to become less available and more expensive, leading to a great demand for energy conservation and alternative energy sources. As a sustainable and renewable energy source, Biomass has piqued interest in generating bioenergy and biofuels over recent years. The thermal conversion of biomass through pyrolysis is an easy, useful, and low-cost process that can be applied to a wide variety of feedstocks. Pyrolysis characteristics of different feedstock samples can be analyzed and examined through thermogravimetric analysis (TGA). TGA has been an essential tool and widely used to investigate the thermal characteristics of a substance under heating environments, such as thermodegradation dynamics and kinetics. Studying the potential of waste biomass for generating sustainable bioenergy carves a pathway into a circular bioeconomy regime, and can help tackle our heavy reliance on nonrenewable energy sources. This study aims to give a deep insight into the wide use of TGA in aiding in the research and development of pyrolysis of different waste biomass sources. The thermal characteristics portrayed by different biomass wastes through TGA are discussed. The effects of significant pyrolysis operating parameters are also illustrated. A more comprehensive understanding of evolved products during the pyrolysis stage can be gained by combining TGA with other analytical methods. The pros and cons of using TGA are also outlined. Overall, an in-depth literature review helps identify current trends and technological improvements (i.e., integrating artificial intelligence) of TGA use with pyrolysis.

Cyber-Physical System (CPS) is a new kind of digital technology that increases its attention across academia, government, and industry sectors and covers a wide range of applications like agriculture, energy, medical, transportation, etc. The traditional power systems with physical equipment as a core element are more integrated with information and communication technology, which evolves into the Cyber-Physical Power System (CPPS). The CPPS consists of a physical system tightly integrated with cyber systems (control, computing, and communication functions) and allows the two-way flows of electricity and information for enabling smart grid technologies. Even though the digital technologies monitoring and controlling the electric power grid more efficiently and reliably, the power grid is vulnerable to cybersecurity risk and involves the complex interdependency between cyber and physical systems. Analyzing and resolving the problems in CPPS needs the modelling methods and systematic investigation of a complex interaction between cyber and physical systems. The conventional way of modelling, simulation, and analysis involves the separation of physical domain and cyber domain, which is not suitable for the modern CPPS. Therefore, an integrated framework needed to analyze the practical scenario of the unification of physical and cyber systems. A comprehensive review of different modelling, simulation, and analysis methods and different types of cyber-attacks, cybersecurity measures for modern CPPS is explored in this paper. A review of different types of cyber-attack detection and mitigation control schemes for the practical power system is presented in this paper. The status of the research in CPPS around the world and a new path for recommendations and research directions for the researchers working in the CPPS are finally presented.

In recent times, metal oxide nanoparticles (NPs) have been regarded as having important commercial utility. However, the potential toxicity of these nanomaterials has also been a crucial research concern. In this regard, an important solution for ensuring lower toxicity levels and thereby facilitating an unhindered application in human consumer products is the green synthesis of these particles. Although a naïve approach, the biological synthesis of metal oxide NPs using microorganisms and plant extracts opens up immense prospects for the production of biocompatible and cost-effective particles with potential applications in the healthcare sector. An important area that calls for attention is cancer therapy and the intervention of nanotechnology to improve existing therapeutic practices. Metal oxide NPs have been identified as therapeutic agents with an extended half-life and therapeutic index and have also been reported to have lesser immunogenic properties. Currently, biosynthesized metal oxide NPs are the subject of considerable research and analysis for the early detection and treatment of tumors, but their performance in clinical experiments is yet to be determined. The present review provides a comprehensive account of recent research on the biosynthesis of metal oxide NPs, including mechanistic insights into biological production machinery, the latest reports on biogenesis, the properties of biosynthesized NPs, and directions for further improvement. In particular, scientific reports on the properties and applications of nanoparticles of the oxides of titanium, cerium, selenium, zinc, iron, and copper have been highlighted. This review discusses the significance of the green synthesis of metal oxide nanoparticles, with respect to therapeutically based pharmaceutical applications as well as energy and environmental applications, using various novel approaches including one-minute sonochemical synthesis that are capable of responding to various stimuli such as radiation, heat, and pH. This study will provide new insight into novel methods that are cost-effective and pollution free, assisted by the biodegradation of biomass.

We used an aqueous leaf extract of Memecylon edule (Melastomataceae) to synthesize silver and gold nanoparticles. To our knowledge, this is the first report where M. edule leaf broth was found to be a suitable plant source for the green synthesis of silver and gold nanoparticles. On treatment of aqueous solutions of silver nitrate and chloroauric acid with M. edule leaf extract, stable silver and gold nanoparticles were rapidly formed. The gold nanoparticles were characterized by UV-visible spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDAX) and Fourier transform infra-red spectroscopy (FTIR). The kinetics of reduction of aqueous silver and gold ions during reaction with the M. edule leaf broth were easily analyzed by UV-visible spectroscopy. SEM analysis showed that aqueous gold ions, when exposed to M. edule leaf broth, were reduced and resulted in the biosynthesis of gold nanoparticles in the size range 20-50 nm. TEM analysis of gold nanoparticles showed formation of triangular, circular, and hexagonal shapes in the size range 10-45 nm. The resulting silver nanoparticles were predominantly square with uniform size range 50-90 nm. EDAX results confirmed the presence of triangular nanoparticles in the adsorption peak of 2.30 keV. Further FTIR analysis was also done to identify the functional groups in silver and gold nanoparticles. The characterized nanoparticles of M. edule have potential for various medical and industrial applications. Saponin presence in aqueous extract of M. edule is responsible for the mass production of silver and gold nanoparticles.

Heart related diseases or Cardiovascular Diseases (CVDs) are the main reason for a huge number of death in the world over the last few decades and has emerged as the most life-threatening disease, not only in India but in the whole world. So, there is a need of reliable, accurate and feasible system to diagnose such diseases in time for proper treatment. Machine Learning algorithms and techniques have been applied to various medical datasets to automate the analysis of large and complex data. Many researchers, in recent times, have been using several machine learning techniques to help the health care industry and the professionals in the diagnosis of heart related diseases. This paper presents a survey of various models based on such algorithms and techniques andanalyze their performance. Models based on supervised learning algorithms such as Support Vector Machines (SVM), K-Nearest Neighbour (KNN), NaïveBayes, Decision Trees (DT), Random Forest (RF) and ensemble models are found very popular among the researchers.