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Sustainable approach to life in water: Science and ethics of the oceans
Oceans have always remained a mystery to humankind. We owe the oceans the very air we breathe. Oceans are storehouses of nutrient rich food that can alleviate the hunger of many generations to come, offer rich minerals and medicines to cure many diseases, regulate the temperature of our planet, stabilize weather patterns, and provide livelihood for many in the fishing and tourism industry. But sadly they are overexploited and polluted to the core. The very fact that these mighty oceans have started showing the ill effects of anthropogenic activities itself is testimony to the tremendous greed of humanity. Among all the mighty oceans, the Arctic ocean is the most sensitive and vulnerable to these changes as it holds a pivotal position in maintaining life on Earth by different mechanisms. The Sustainable Development Goal (SDG) 14 of the United Nations underlines the urgent need to conserve marine resources and give equal rights to people in all countries to enjoy these resources. The current review is an attempt to highlight the enormous number of ways in which oceans have helped humankind, the serious threats the oceans are facing now, and how best we can have a sustainable approach to halt the total crashing of our great ocean systems. 2021 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
An impact of antibacterial efficacy of metal oxide nanoparticles: A promise for future
Since its advent, nanotechnology has seen applications in diverse fields including the biomedical domain. Many metal oxide nanoparticles (NP) have shown good antimicrobial properties. Their small size and ability to inhibit a broad spectrum of bacterial species have made them promising candidates in our search of antimicrobial agents. Since, they don't target a specific protein in a microbial species, the chances of the microbe gaining resistance is also less. This is indeed a great advantage over antibiotics, most of which target specific proteins of bacteria. Most of the pathogenic bacteria have gained resistance against commonly used antibiotics. In this context there is a dire need of antimicrobials with a broader spectrum of action. Metal oxide nanoparticles like: ZnO NPs and CuO NPs easily fit into this category. They can suppress microbial growth by reactive oxygen species production, thereby causing damage to biomolecules, cation release, interactions with membrane and ATP depletion. One of the challenges with metal oxide NP is their cytotoxicity. Scientists are in search of degradable and less toxic metal oxide NP. The current review focuses on the relative advantages and limitations of various metal oxides NPs in inhibiting microbial growth. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
An ancestral genomic locus in Mycobacterium tuberculosis clinical isolates from India hints the genetic link with Mycobacterium canettii
Background: Tuberculosis remains a worldwide public health emergency. To better understand M. tuberculosis and to identify genomic variations characteristic to the Indian clinical isolates by a low-cost method, a genomic subtractive hybridization between M. tuberculosis H37Rv and a clinical isolate from South India was performed. Results: This revealed a novel 0.4-kb subtractive fragment which was used as a handle to pull out a 4.5-kb genomic region characteristic to the clinical isolate and was absent in H37Rv. On further studies, this 4.5-kb region was found to be present in 91% of the M. tuberculosis clinical isolates screened from Kerala, a state in South India. Interestingly, this novel region has 99% identity (with 100% query coverage) with genomic regions of M. canettii. Discussion: The present study hypothesizes that this locus was present in the recent common environmental ancestor of mycobacteria, retained to the maximum extent in M. canettii and ancestral isolates of M. tuberculosis, and later deleted in other modern lineages of M. tuberculosis. Thus, this region may serve as one of the links between the pathogenic mycobacteria and the environmental species. We also propose that the Indian isolates of M. tuberculosis might be closely related to the putative progenitor M. prototuberculosis with respect to this locus. More studies on other genomic loci from different strains of M. tuberculosis are required to establish more links in this direction. 2020, Springer Nature Switzerland AG. -
Agricultural nanotechnologies: Future perspectives of bio-inspired materials
Bio-inspired designs have been used by humankind in understanding and modelling novel materials which have applications in diverse fields like disease diagnostics, drug delivery, agriculture, energy storage, industry, etc. Superhydrophobicity, directional adhesion, structural colour, self-cleaning, antireflection, etc. are some of the useful attributes for which we have relied a lot on nano level biomimetics. Bioinspired nanolevel designs have been explored in the field of agriculture too. Such nanomaterials and nanodesigns have been used to increase crop yields. They also find uses in fertilizer application and replacement of many harmful chemical pesticides, which are generally overused. Increasing population, increased longevity of people and the urgent need for sustainable environment have led to a dire need for exploration and adaptation of such novel technologies which can help in feeding the growing population. Nanoscale products and technologies can also help in reducing the accumulation of excess fertilizers, pesticides, etc. in soil, which can go a long way in cleaning up the environment. The current attempt is intended to portray the latest developments and future possibilities of bioinspired NT in diverse fields of agriculture like synthesis and delivery of novel pesticides and fertilizers, nanocarriers for gene delivery, sensors to monitor and assess soil conditions, plant pathogen detection and plant nanobionics to detect pollutants. 2023 Bentham Science Publishers. All rights reserved. -
Ramifications of Climate Change Induced by Anthropogenic Factors on Global Fish Population Scenario
One of the important consequences of climate change is its effect on the global fish population. Though not very highly pronounced each year, the effect of climate change is of cumulative nature. Global aquaculture is being affected by temperature changes of both water and air. Fluctuations in the ocean surface temperatures, ocean current patterns, wind speeds, and wave directions, all have its impact on aquaculture. Each year we see more and more incidences of extreme weather conditions in different parts of the world, be it in the form of hurricanes, heavy floods, etc. Fishes are subjected to various stress factors which in turn take a toll on its growth and development. This can lead to lower weight gain and increased mortality due to higher susceptibility to diseases. This, coupled with direct unsustainable anthropogenic activities in the oceans and rivers may lead to collapse of the marine and freshwater ecosystem. Recent studies have identified specific regions where marine aquaculture production will be positively and negatively affected. One of the sustainable ways of developing aquaculture in the coming decades would be by developing region-wise strategies to maintain or increase fish population levels and thus meet the global seafood demands even in 2050. The current review is an attempt to assess the effects of ocean warming, ocean acidification, and ocean deoxygenation on the growth, survival, and diversity of marine lifeforms and suggest ways to stop a complete collapse of marine fish population by 2050, the year for which the complete collapse is predicted based on projections. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Multidrug Resistant Bacteria: The Fatal Menace in Healthcare
Mapana Journal of Sciences, Vol-11 (1), pp. 31-47. ISSN-0975-3303 -
The Latest Technology and its Integration for the Development of Healthcare(Medical)
Healthcare advances that use Artificial Intelligence (AI) to analyze data, use devices, and identify patients offer new possibilities for better patient care, cutting costs, and growing the medical sector. The age of specialized human health tests has begun. It uses noninvasive instruments, sound, visual the use of photography, electronic health tools, embedded health instruments, fluidic diagnostic tracking, and combined data analysis to provide people with tailored medical suggestions. These technologies contribute to early identification and comprehending of health issues linked to chronic illnesses and general health using information analysis and AI-driven ideas. Notable uses include a Parkinson's and Huntington's Under certain circumstances, diabetes, cancer, kidney disease, heart problems, elderly care, and a number of healthcare areas. Industry changes are expected as a result of the latest breakthroughs in outdoor monitors, AI-driven evaluation of data, and healthcare testing technologies. AI systems give data to people and health workers, possibly better their way of life and cutting healthcare costs. These include: tracking the effectiveness of medicines, finding chronic illnesses early, and offering individualized care using medical trends and DNA. In relation to healthcare studies and sensor tracking, this study explains new technologies and advances in diverse fusion methods, materials, and processes. Precise diagnostic info, small merchandise dimensions, and cost are high considerations. Healthcare workers, patients, consumers all benefit from more personal health care services thanks to the merging of AI with information streams. The text highlights both advantages and hurdles while showing the way toward upcoming displays and academic papers that follow a path of growth in the industry. 2024 IEEE. -
Accentuated bioavailability of bioactive compounds in foods by nanotechnology-based delivery approaches
One of the perennial problems faced by the food industry is the poor bioavailability of nutrients, arising generally due to lowered solubility or inadequate absorption by the gastrointestinal tract. Nanotechnology-based encapsulation techniques have shown to significantly enhance the bioavailability of various food bioactive compounds. Targeted delivery of specific nutrients to specific organs, low toxicity, maximization of nutrient uptake, extended release of nutrients, and enhanced texture and flavor are the major advantages of such systems, a few of which are discussed in this review. In keeping with these pertinent paradigms, the current review also highlights how food nanotechnology-based delivery systems ensure efficient bioaccessibility of dietary compounds that otherwise cannot be maximally achieved under in vivo conditions or by using biopolymer-based encapsulation. However, as with any technology, this also comes with its own set of drawbacks and lacunae, which are also presented in the current review. With the surge in global population, emphasis should be placed on optimizing bioavailability of vital food nutrients, catering to Sustainable Development Goals (SDGs) 2 and 3. In a global landscape, a collaborative effort from regulatory bodies, consumers, and manufacturers will enable satisfactory, efficient, and safe commercialization of nanotechnological delivery systems for functional foods and bioactives. 2026 Codon Publications -
Facial emotion recognition using convolutional neural networks
Emotional expressivity has always been a simple job for people, but computer programming is much harder to accomplish. Image emotions may be recognised by recent developments in computer vision and machine learning. In this article, we present a new method to detect face emotion. Use neural networks convolutionary (FERC). The FERC is based on a CNN network of two parts: the first portion removed the backdrop of the image, the second part removed the face vector. The expressional vector (EV) is utilised in the FERC model to detect the fve different kinds of regular facial expressions. The double-level CNN is continuous and the weights and exponent values of the final perception layer vary with each iteration. In that it improves accuracy, FERC varies from widely utilised CNN single-level technology. Moreover, EV generation prevents the development of a number of issues before a new background removal process is used (for example distance from the camera). 2021 -
Human-Centered Insights Into ChatGPT in General Education: A Mixed-Methods Analysis of Scopus Publications
Artificial intelligence has become the need of the hour with balancing technological advancement and the timeless values of critical thinking, creativity, and ethical learning. Educators and students looking for writing assistance, quick access to information, communicating with others, or developing their language skills will consider CharGPT to be the most useful tool. This chapter focuses on user per-spectives, attitudes and concerns towards CharGPT to essentially guide the ethical development. These trends reveal that ChatGPT has rapidly transitioned from a novel tool to a mainstream academic companion, making it imperative to investigate not just its technological potential but its human-centered implications for general education. This study was conducted through a mixed approach with a systematic analysis of Scopus published research. The authors also extracted Scopus published data and analyzed it using NVivo and VOS viewer software. The sentiment analysis proved that the maximum number of studies affirmed positivity emphasizing the wider acceptance of Chat GPT. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Blurred Image Processing and IoT Action Recognition in Academy Training Sport
Smart wearable technologies utilising devices connected to the web (IoT) are on the rise, and many of these new applications involve the identification of athletic performance. Many people across the world participate in soccer, also called football in some regions. Soccer players practise discrete actions (like shooting and passing) in order to ingrain them in muscle memory and speed up their reflexes during actual games. There is always a compromise between blur and noise when processing images. Denoising naturally softens an image because noise is high-frequency information. Deblurring, on the other hand, causes additional noise in the final product. The need to brighten an image in low-light conditions only adds to the difficulty. Noise is introduced into the image during the brightening process itself. Images taken while moving, especially those of wildlife (though not exclusively), will have more blur than those taken while still. Many previous projects have focused on a single problem, but very few have attempted to address the entire set of problems simultaneously. So, we set out to make a way to turn these lowlight, fuzzy images into high-contrast, clear images. A fuzzy invariant space is the result of the union of several fuzzy invariant spaces. After numerous iterations of processing a blurred image, the final stage is to utilise a progressive restoration procedure. The experimental findings demonstrate the effectiveness of the suggested technique in reducing calculation error, improving the recovery effect, and avoiding the noise caused by numerous deconvolutions. This work introduces new concepts and methods for recognition research by applying fuzzy image processing to the study being human mobility and the detection of activities in the realm of IoT. Using the Kinect, an IoT somatosensory camera, we are able to collect 15 3D skeletal elements via its software development kit (SDK). This led to the study of kinesiology and the creation of a motion resolution model that works well with the Internet of Things. 2022 IEEE. -
COBOTS: Vital role in significant domains
The term COBOT refers to "collaborative robot, " which is created by combining humans and robots to increase the efficacy and efficiency of industrial processes. Cobots have extensive applications in various sectors, including healthcare, motoring, production, electronics, space exploration, logistics, and astronomy. Industry 5.0 is a development that aims to combine human specialists' creativity with accurate, intelligent, and efficient technologies to revolutionize manufacturing processes worldwide. Therefore, in the age of Industry 5.0, there is a great demand for Cobots with high, quick advancement, and low costs. Industry evolution, fundamentals of Cobots, how they differ from robots, key features, basic components, the significant role of Cobots in Industry 5.0, challenges and limitations, future scope, and ethical aspects of Cobots are covered in this chapter. This book chapter is a comprehensive manual for academic researchers and corporate executives to learn about Cobots completely. 2024, IGI Global. All rights reserved. -
Smart AI Tool for Accident Damage Detection
Accidents and fatalities from motor vehicle accidents are major concerns despite substantial advancements in safety technology. Because of this, the industry has made significant investments in creating new safety features, like cutting-edge driver assistance systems, and raising public awareness of safe driving habits. In general, car accidents can result in severe damage to the vehicles involved, and assessing and repairing that damage can be time-consuming and expensive. Manual inspection of vehicles is prone to errors and often requires trained professionals to identify the extent and location of the damage. Therefore, there is a need to develop an automated system that can detect and assess the damage caused to vehicles using AI and deep learning techniques. An image-based processing technique, YOLOv3, is proposed in this work to automate damage detection on automobiles. In the work, we used CNN to create a Mask R-convolutional neural Networks model to identify the location of damage on a car. The damaged area is precisely marked in the images. The base weights from the Mask R-CNN COCO dataset are used to train the model. 21 epochs are used to process the images. The surface of the damage is highlighted in the final image using a color splash technique after processing. Auto insurance firms, vehicle rental companies, and repair shops would all benefit from this automated method of determining the degree of exterior vehicle damage and then calculating the severity of that damage. The value of fraudulent auto insurance claims can also be reduced. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Future Innovation in Healthcare by Spatial Computing using ProjectDR
Spatial Computation is the next step in the continuing convergence between the digital and physical realms. It is a set of inventions and developments that can better our lives through learning the real world, acknowledging and connecting our connection to, and traveling through various locations in the world. The lack of modern, precise, and effective diagnosis limits the rehabilitation of patients, despite technical advancements in medicines. The capabilities of spatial computing are expanded in a healthcare framework during the care and treatment of the patient. In this article, our purpose is to clarify the function of ProjectDR in the field of healthcare, which enables the display of medical images, such as CT scans and MRI results, directly on the patient's body in a manner that moves as patients do. 2021 IEEE. -
Systematic Literature Review on Industry Revolution 4.0 to Enhance Supply Chain Operation Performance
Industry 4.0 is a notion in which industries automate systems and processes, innovate digitally, and share information. It aims to obtain a smart factory in an attempt to lessen required time in responding to consumer demand or unexpected circumstances and to enhance organizational productivity. The integration of Industry 4.0 and supply chain management (SCM) ensures immense development opportunities for manufacturing firms. This article provides a systematic literature review and formulation of the existing research on Industry 4.0 in SCM, resulting in some intriguing analyses that will be useful to academics and industry, particularly top managers. The content of the article is classified into three categories: exploratory vs. confirmatory, qualitative vs. quantitative, and management level vs. technology level. The findings will benefit managers in understanding the significance of Industry 4.0 and its relationship with SCM. The formation of clusters and their affiliations has resulted in the emergence of new areas requiring managerial attention. The article concludes by examining the possibilities of the present and future research. 2022 ACM. -
Python's role in predicting type 2 diabetes using insulin DNA sequence
This chapter examines how Python can assist in predicting type 2 diabetes using insulin DNA sequences, given the substantial problem that biologists face in objectively evaluating diverse biological characteristics of DNA sequences. The chapter highlights Python's various libraries, such as NumPy, Pandas, and Scikit- learn, for data handling, analysis, and machine learning, as well as visualization tools, such as Matplotlib and Seaborn, to help researchers understand the relationship between different DNA sequences and type 2 diabetes. Additionally, Python's ease of integration with other bioinformatics tools, like BLAST, EMBOSS, and ClustalW, can help identify DNA markers that could aid in predicting type 2 diabetes. In addition, the initiative tries to identify unique gene variants of insulin protein that contribute to diabetes prognosis and investigates the risk factors connected with the discovered gene variants. In conclusion, Python's versatility and functionality make it a valuable tool for researchers studying insulin DNA sequences and type 2 diabetes prediction. 2023, IGI Global. All rights reserved. -
Classroom mathematics learning: Association of joy of learning and school connectedness among high school students in India
Mathematics learning experiences can influence the overall academic and socio-emotional development of a child. The present study investigates the mediating effect of mathematics anxiety and emotional engagement on the relationships between teacherstudent interaction, the joy of learning, and school connectedness. Two mediation models were tested for the dependent variables: the joy of learning and school connectedness, using Hayes' process macro in SPSS on a sample of 774 eighth-standard students from Indian schools. The study's results indicate the presence of a serial mediation effect on the relationship between teacherstudent interaction and joy of learning, teacherstudent interaction, and school connectedness through mathematics anxiety and emotional engagement. The study emphasized the role of mathematics learning within the overall framework of joy of learning and school connectedness.. 2024 Wiley Periodicals LLC. -
Student Perceptions and Experiences in Mathematics Classrooms: A Thematic Analysis
Classroom experiences contribute to learners' perceptions and interest in a particular subject. The present study aims to understand students' perception of mathematics learning by exploring their classroom experiences. The study sample consisted of 17 eighth-grade students in English-speaking urban schools in South India. The data was collected through a semi-structured interview schedule. The thematic analysis presents five themes student personal factors, teacher-related, content-related, classroom environment and utility value. Teachers characteristics and mathematics content were the essential factors contributing to students' perceptions and experiences. The study highlights the utility value of the content to help students see the application of the subject in real-world situations. Understanding students' perception of mathematics learning would help to choose appropriate content and teaching methods in the curriculum. The study highlights the need for educational and psychological interventions, focusing on student-teacher engagement and curriculum development to enhance mathematics learning. (2023). All Rights Reserved. -
Mathematics Self-Efficacy, Utility Value and Well-Being Among School Students in India: Mediating Role of Student Engagement
Teaching and learning mathematics has many challenges, including student engagement, attitudes and beliefs toward mathematics. Students experience stress and anxiety while learning mathematics. Mathematics is perceived as a complex subject. Student self-efficacy and a sense of utility value of mathematics topics can impact student learning and well-being. The current study aims to examine the mediating role of student engagement on the relationship between mathematics self-efficacy, utility value and well-being among students. A cross-sectional survey of 774 eighth-grade students (491 male and 283 female) from India was carried out using standardized scales to measure the study variables. The mediation analysis tested two conceptual models. The findings indicate that student engagement mediates the relationship between self-efficacy and student well-being (model 1), and student engagement mediates the relationship between utility value and student well-being (model 2). The structural equation model results indicate an acceptable fit of the tested conceptual models. The study findings call for focusing on socio-emotional aspects of mathematics learning to improve the well-being of students. 2023 Research Council on Mathematics Learning.