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Rights of Indigenous Peoples Vis-a-Vis Environmental Justice in the Himalayan Region
In the global mountain ecosystems, the Himalayan region has a unique place. These geo-dynamically vibrant mountains are home to a diverse range of flora, fauna, human populations, and cultures. Although the region is rich in natural resources, most of its population remains marginalised. The Himalayan environment and people have been closely intertwined since antiquity. However, the conditions in this delicate resource region are currently getting worse due to human activities. The attempts to modify the Himalayan environment for developmental purposes have been causing environmental imbalance significantly impacting the security of the Himalayan ecosystem and its inhabitants. Environmental justice demands addressing environmental issues in the Himalayan region from the viewpoint of impacted and indigenous peoples communities. Acknowledging the aforementioned, this chapter endeavours to explore, examine and comprehend the notion of environmental justice concerning the rights and interests of the indigenous population inhabiting the Himalayan region. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. -
A review on ethanol tolerance mechanisms in yeast: Current knowledge in biotechnological applications and future directions
Saccharomyces cerevisiae is one of the prominent strains in the brewing and bioethanol industries and has been used for many industrial purposes for ages. Though the organism is an outstanding ethanol producer, the major limiting factor is the stress the organism undergoes during fermentation. One of the significant stresses is the ethanol stress, created by ethanol accumulation in the medium. The ethanol starts to interact with the yeast cell membrane; further, as ethanol concentration increases, it affects a lot of cell organelles. Thereby, cellular activities get disrupted, causing cell death and hence reducing ethanol production. The organism has developed many strategies to overcome this stress by activating the stress response pathway, which regulates many genes involved in modifying the cell membrane cell wall, renaturation of proteins, and altering the metabolism. However, with higher ethanol concentrations, the yeast cells will be unable to tolerate, leading to cell death. Hence, to minimize cell death at higher ethanol concentrations, there is a need to understand the effect of ethanol and its response by the organism; this helps improve the ethanol tolerance of the organism and, thereby, ethanol production. Although many research works are carried out to understand the vital aspect of the tolerance and are reported, very few review papers cover all these points. Hence, this review is designed to include information on all the elements of ethanol tolerance, i.e., ethanol tolerance of different strains of S. cerevisiae, the effect of ethanol on the yeast cells, the mechanism used to tolerate the ethanol, and various techniques developed to improve the ethanol tolerance of the yeast cells. 2024 Elsevier Ltd -
Exploring the pharmaceutical potential of discarded ink glands from Amphioctopus aegina
Ocean is called the Natural Medicine Chest of the New Millennium, as it encompasses diverse marine ecosystems that are rich in bioactive compounds. One of the fascinating organisms is cephalopods as they are known for their inking capabilities. The ink, composed mainly of melanin and mucous, has garnered attention for its diverse bioactive properties. In addition to melanin, components like Quinones, 8-hydroxy-4-quinolone, and various amino acids exhibit anti-oxidant and other therapeutic activities. Researches have shown that cephalopod ink can possess anti-inflammatory, anti-cancer, anti-microbial, anti-hypertensive, anti-ulcerogenic, and antiretroviral properties. However, these ink glands are discarded in the seafood industry. Amphioctopus aegina is one of the octopus species found in Indian waters and is less explored. This study was conducted to explore the chemical composition and pharmaceutical properties of the discarded ink glands of A. aegina. The study revealed the gland of this organism to be rich in bioactive compounds like alkaloids, phenols and flavonoids. Antioxidant studies revealed both aqueous and ethanol extracts showed good antioxidant capability, with remarkable radical scavenging activity, with IC50 values-65.76 g/mL and 51.7 g/mL respectively. The extracts also showed moderate inhibition of protein denaturation and were non-toxic to RAW264.7 cell lines. These findings highlight A. aegina ink as a promising source of therapeutic biomolecules and offer a sustainable approach for valorizing cephalopod waste. 2026, ScienceIn Publishing. All rights reserved. -
Effectiveness of museum visits: attitude and learning of history
This quasi-experimental study investigates the effectiveness of museum visit on 6th-grade students attitude towards and learning of history. The study engaged 120 students in the museum visit intervention. That includes, 60 students in the experimental group and 60 students in the control group. The study design included pre-test and post-test measures. The study administered an achievement test and an attitude scale toward history. The study analyzed the data using the repeated measures analysis of variance (ANOVA) statistical test. The studys result revealed that the experimental group outperformed the control group in achievement test scores of histories. The museum-visit group expressed a more positive attitude towards history learning and engagement. These findings underscore museums potential as experiential learning environment, offering knowledge and fostering a positive attitude towards history. The study recommends the future researchers to conduct similar empirical studies in science subjects as a venue for place-based pedagogy in the Indian context. 2024, Institute of Advanced Engineering and Science. All rights reserved. -
Museum visit intervention in K-12 education: a scoping review
This scoping review aims to provide an overview of empirical studies on worldwide museum visit intervention in K-12 education. The study employed Mendeley citation software to identify the articles in the database. A metaanalysis PRISMA statement is used for reporting the items. Out of 135 possibly rich articles, the present study reviewed 18 studies that met the inclusion criteria and were subjected to descriptive and content analyses published between 2017 and 2021. Most of the studies are experimental and from primary school contexts. It is revealed that science is the subject matter context majority of the studies, but philosophy, disaster management, language, and environmental science are also represented. The content analysis resulted in the following learning and social outcomes. It states that social outcome is explored chiefly, followed by learning outcome. The findings indicate that museum visit intervention positively impacts students learning and social outcome. The review also identifies the need for further research on museum visit intervention in the Asia Pacific region. 2024, Institute of Advanced Engineering and Science. All rights reserved. -
Opportunities and challenges while conducting field trips to the museum: a narrative review
The museum visit field trip engages and motivates the children in various activities. Field trips to the museum provide the students with a constructivist and experiential learning environment as they construct knowledge through observing the artifacts. The present study describes the possible opportunities and challenges for school children while conducting field trips to the museum. The study employed a narrative review technique to address the research question raised. The study selected the literature reviews from 2012-2023, including studies on field trips to the museum for the academic engagement of school children. The data includes 50 peer-reviewed journal articles categorized into five categories: students overall development, experiential learning opportunities, the museum as a resource, the role of teachers, the school, and museum authority. Results revealed that the museum is a resource for learning and is perfect for improving students cognitive and affective development towards the various school subjects and helping them enhance their participatory learning opportunities. However, teachers knowledge, infrastructure, parental consent, and legitimization with the school authority are some challenges in conducting museum visit field trips. Future research may focus on conducting empirical studies, which include school-museum collaboration, to enhance the horizon of school and community knowledge. 2025, Institute of Advanced Engineering and Science. All rights reserved. -
Museum visit as an academic engagement activity: teachers perspective
The educational value of museums are immense as they are the storehouse of artifacts depicting history, culture, and science. Teachers must tap this resource to provide students the experiential learning. Bangalore is one of the metropolitan cities of India, hosting variety of museums where artifacts related to various school subjects such as history, geography, science, art, culture, technology, and music are found. Therefore, the present study aims to find out the teachers' perspective on museum visits as an academic engagement activity and a resource for experiential learning. The study employed a descriptive survey design to understand school teachers' perspectives on museum visits in Bangalore. A convenient sampling method yielded 200 complete responses from school teachers. The study revealed that despite knowing about the field trip to museum as a source of learning, teachers revealed several constraints in organization and implementation of such visits. Having understood teachers perspective, study suggests future research may delve into students' learning engagement on a field trip. 2025, Intelektual Pustaka Media Utama. All rights reserved. -
Energy-Efficient Cluster-Based Reliable Routing Using Hybrid Nutcracker and Improved Sand Cat Optimization Algorithm for Extending Network Lifetime in WSNs
In wireless sensor networks (WSNs), sensor nodes are deployed in a target region for sensing environmental physical parameters to attain the objective of reactive decision-making. These sensor nodes necessitate energy for processing and forwarding the sensed data to the base station (BS) for better data delivery in WSNs. Balanced energy utilization in WSNs prevents the problem of hotspot, and dynamic cluster head (CH) selection with reliable route establishment is a vital decision-making approach that helps in optimal path selection with maximized energy conservation. In this paper, a nutcracker and sand cat optimization algorithm (NCSCOA)based multiobjective CH selection and sink node mobility scheme is propounded for enabling rapid and reliable data transmission with reduced energy consumption in heterogeneous WSNs. This NCSCOA handled the problem of hotspot as well as isolated nodes and facilitated loop-free routing with the support of the improved nutcracker optimization algorithm (INCOA) that makes the decision of routing using local and global search optimization processes. It constructed an energy-level matrix (ELM) by deriving the impactful factors of intercluster formation, distance between CH and BS, residual energy (RE), and node density for achieving optimal CH selection and route determination. In specific, improved sand cat optimization algorithm (ISCOA) is used during the intercluster formation phase by discovering the optimized path between source and destination during route establishment. Simulation-based findings of the proposed NCSCOA confirmed its efficacy by improving the mean number of alive nodes by 23.18%, reducing energy consumption and delay by 21.86% and 20.98% compared to benchmarked protocols. 2025 John Wiley & Sons Ltd. -
Financial services and green investment on ESG investing for a sustainable future
The financial services industry is transforming as investment businesses become greener. The urgency of global environmental challenges has boosted investor interest in ESG investment. Although long-s tanding, ESG investing remains specialized. ESG factors in investment portfolios may increase economic and social satisfaction, according to this paper. These factors may harm investment portfolios. A worldwide green finance legal framework aims to avoid greenwashing, establish standards, and encourage sustainable development. It examines how ESG efforts effect green money using many research approaches. Risk assessments and industry trends are examined for the company. A resilient and fair economy with ESG investments requires financial services, according to the results. This occurred because financial services are vital. 2025, IGI Global Scientific Publishing. All rights reserved. -
Pangenomics for developing viral disease-resistant plants: Harnessing synergenetic pangenomics for advanced viral disease resistance in crops
Agriculture plays a pivotal role in the global economy, but it also faces several significant challenges. One major challenge is the necessity to sustainably provide food for a rapidly expanding population. Additionally, agriculture must withstand the threat of different disease-causing pathogens, including various microorganisms like bacteria, viruses, and fungi. Viral diseases significantly impact crop growth, vitality, and yields, posing substantial threats to global agriculture. Despite their compact genomes, the viruses still lead to major losses in crop production. The study of plant viruses began over a century ago with the tobacco mosaic virus discovery, marking the inception of plant virology. Since then, hundreds of viruses have been identified, many of which induce severe damage to various crops. Viruses exhibit extensive genetic diversity, with RNA serving as the predominant genetic material. This genetic diversity profoundly influences their reproductive cycles and lifestyles, necessitating innovative strategies for disease management. This chapter discusses different pathogenic viruses along with various approaches to pest management, including the emergence of pangenomics as one of the advanced tools for understanding the diversity of genes among plant populations. Pangenomics encompasses both function-based and structure-based approaches, elucidating the core and dispensable genomes that contribute to discovering many agronomic traits related to disease resistance mechanisms, crop yield, flowering time, etc. Integrating the information from pangenomics into plant virology can revolutionize agriculture by enhancing crop production and crop yield, and also engineering viral disease-resistant plants to ensure global food security. 2025 Elsevier Inc. All rights reserved. -
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Psychological impact of olfactory branding: The future of smell marks in India
Scents have been used by business organizations for commercializing their products since historic times. Because of the psychological connect that a consumer immediately makes as he smells something unique, olfactory branding is considered as a very productive and effective marketing tool. Trademark law attempts to protect a brand's identity with the ultimate motive of preventing consumers from deceptively similar goods. Scholars and businesses have been raising their voice in a demand call for smell mark protection under trademark law, arguing that smell is just as important for identifying the origin-point of a product for a consumer as is the brand's logo or name or product shape. While the US courts have been liberal in granting smell mark registrations, EU courts have interpreted the graphical representation requirement under trademark law very strictly. Indian law, though not entirely closed on the prospect of smell mark protection, is inclined toward the EU position. After analyzing the current legal scenario, this article explores the more fundamental question as to the feasibility of smell marks, questioning their justification under the philosophical foundations of trademark law, the subjective associations of consumers with respect to smells, the difficulty in evidence analysis by courts in infringement suits and the apprehension relating to the functionality doctrine. 2022 John Wiley & Sons Ltd. -
CHARM: Context-based Hierarchical Association Rule Mining for Analyzing Purchase Patterns
Data mining is now an essential part of business intelligence, specially in the retail analytics, allowing companies to derive meaningful insights out of big volumes of transaction data. This paper uses Context-Based Hierarchical Association Rule Mining to study purchase behavior in Indian retail outlets through Apriori algorithm that helps to take effective decissions. The available literature primarily employs flat item association models and lacks contextual dimensions and profit-oriented outcomes of rules, which also creates an evident gap in the current research. The study combines various contextual aspects, including product category, sub-category, region, and state, to produce the multilevel association rules indicating the product relationship under different sales levels of the products following an hierarchy. The Lift and Conviction metrics are applied along with support and confidence to eliminate the coincidental patterns and make the rules in business reliable. Support-based filtering and a minimum threshold of confidence of 0.1 are used to determine separate patterns of co-purchase that are significant. In order to make business relevant, the level of profit is involved as a result which puts into emphasis rules which lead directly to financial performance. The findings show that context-enriched rules offer a better insight into customer buying behavior and retailers have the opportunity to identify profitable cross-selling opportunities that more traditional flat associated analysis might otherwise miss. The hierarchical structure allows improving interpretability through associating items with larger contextual properties, which will be useful in designing the promotion, product placement, and optimizing the regional strategy. Overall, this paper presents the combination of contextual and profit-driven parameters as a concept that can be used to provide a data-driven basis of strategic retail decision-making and sustainable competitive advantage. 2026 IEEE. -
Empowering BRICS economies: The crucial role of green finance, information and communication technologyand innovation in sustainable development
This study delves into the crucial role of green finance, information and communication technology (ICT), technological innovation, and renewable energy in the Brazil, Russia, India, and China (BRICS) countries from 2000 to 2021. The findings highlight the importance of green finance in reducing the ecological footprint and promoting eco-friendly initiatives, sustainable practices, environmental technology innovation, and heightened environmental awareness. This means 1% increase in green related finance has reduced ecological footprint by 0.72% in BRICS economies. Additionally, technological innovation and the consumption of renewable energy play a significant role in enhancing environmental sustainability. Conversely, the study reveals that ICT has a considerable impact on the ecological footprint, but the interaction effect with green finance helps to mitigate its negative effects and improve the environmental quality. Meanwhile, non-renewable energy, gross domestic product (GDP) per capita, and urbanization have an adverse effect on the environment. To strengthen green finance in BRICS countries, governments can establish comprehensive policy frameworks that prioritize sustainability and create a conducive climate for incentivizing investment in environmentally friendly endeavors. 2024 ERP Environment and John Wiley & Sons Ltd. -
Enhanced Wavelet Block Shrinkage Technique For Mammogram Denoising Using K-Means Clustering And Neural Networks
The proposed research study introduces a novel approach for denoising digital mammograms by improving the existing wavelet block shrinkage filtering method with K-Means clustering and a convolutional neural network. This approach involves decomposing both the original and noisy mammograms into frequency subbands using 2D discrete wavelet transformation. The resulting subbands are then grouped into multiple clusters based on similar features of the wavelet coefficients, employing K-Means clustering. This represents an improvement over the traditional block shrinkage method, which uses fixed-size blocks. These clusters from the original and noisy mammograms are paired to train a convolutional neural network, which serves as an optimal shrinkage function. This neural network-based thresholding mechanism replaces traditional hard and soft thresholding methods that rely on a universal threshold. Test results demonstrate that the proposed enhanced wavelet block shrinkage mechanism achieves a 20% improvement in peak signal-to-noise ratio and a 5% increase in structural similarity index score compared to traditional wavelet block shrinkage. Authors. -
HALC: An AI-Driven Legal Decision-Making Framework - A Qualitative NVivo Case Study on Tribal Rights
This study proposes a structured human-AI collaboration framework for legal and ethical decision-making, integrating artificial intelligence with human expertise. Unlike fully automated AI systems, it prioritizes transparency, accountability, and ethical oversight. Through expert interviews with legal professionals and AI technologists, we identified key challenges, including bias, lack of explainability, and the need for human validation. Using thematic analysis in NVivo, we developed a stepwise framework that ethically collects data, applies AI-driven analysis, ensures human oversight, and informs policy decisions. This approach enhances human judgment rather than replacing it, with potential applications in law, governance, and public policy. Future research will test and refine this framework. 2025 IEEE. -
Exact solutions for unsteady mixed convection flow of nanoliquid with exponential heat source: Bruggeman and batchelor nanofluid model
The objective of this paper is to explore the influence of exponential heat source and radiative heat on the thermal and mass transport of nanofluid flow over a vertical sheet. Unlike traditional nanofluid models, the Bruggeman and Batchelor models are utilized to estimate the thermal conductivity and dynamic viscosity of the nanofluid. The water-based copper nanoliquid is considered. Mass flux boundary condition is employed. The governed differential problem is solved by Laplace Transform Method (LTM) for exact solutions. The impact of dimensionless sundry parameters on flow distributions is analyzed and bestowed graphically. The rate of heat transfer has been assessed. Also, the slope of the linear regression line through data points is determined in order to quantify increase/decrease in the Nusselt number. Results exhibited that all the flow fields (velocity and temperature) are increasing functions of thermal and solutal Grashof numbers. Also, the presence of exponential heat source highly affects the heat transfer performance. 2018 by American Scientific Publishers All rights reserved. -
An efficient design and comparison of machine learning model for diagnosis of cardiovascular disease
Cardiovascular disease has a significant global impact. Cardiovascular disease is the primary cause of disability and mortality in most developed countries. Cardiovascular disease is a condition that disturbs the structures and functionality of the heart and can also be called heart disease. Cardiovascular diseases require more precise, accurate, and reliable detection and forecasting because even a small inaccuracy might lead to fatigue or mortality. There are very few death occurrences related to cardio sickness, and the amount is expanding rapidly. Predicting this disease at its early stage can be done by employing Machine Learning (ML) algorithms, which may help reduce the number of deaths. Data pre-processing can be employed here to eliminate randomness in data, replace missing data, fill in default values if appropriate, and categorize features for forecasting and making decisions at various levels. This research investigates various parameters that are related to the cause of heart disease. Several models discussed here will come under the supervised learning type of algorithms like Support Vector Machine (SVM), K-nearest neighbor (KNN), and Nae Bayes (NB) algorithm. The existing dataset of heart disease patients from the Kaggle has been used for the analysis. The dataset includes 300 instances and 13 parameters and 1 label are used for prediction and testing the performance of various algorithms. Predicting the likelihood that a given patient will be affected by the cardiac disease is the goal of this research. The most important purpose of the study is to make better efficiency and precision for the detection of cardiovascular disease in which the target output ultimately matters whether or not a person has heart disease. 2023, Bentham Books imprint. All rights reserved. -
Sustainable driven Predictive Approaches to Address Climatic Crisis: Issues and Challenges
The issue of climate crisis is currently one of the critical challenges humanity faces in the present era and it holds significant implications, for the future of our planet. To gain an understanding and mitigate the impacts of climate change several methods have been developed to model and forecast future climate trends. This paper critically analyzes sustainable techniques utilized in studying the climate crisis, such as statistical models, machine learning algorithms and climate simulations. The strengths and limitations of each method is analyzed while also considering the factors that can affect their accuracy and reliability. By consolidating existing research on this subject our aim is to provide insights into the effective sustainable approaches for predicting our climates future trajectory while offering suggestions for further research, in this crucial field. 2023 IEEE. -
Revisiting Television in India: Mapping the Portrayal of Women in Soap Operas
This article attempts to map the portrayal of women in popular soap operas on television in India. It begins with the discourses around portrayal of women on Doordarshan in the pre-liberalisation era and goes on to analyse a few soap operas in the past one decade. With substantive review of visual texts, it aims to disprove the claim that there is a paradigm shift especially with respect to the portrayal of women in the contemporary and so-called progressive soap operas. It concludes by comparing all the phases of development of television in India with respect to construction of women and stating how very little and inconsequential change has occurred in this regard in spite of all the efforts from the state and the intellectual community. 2018 Indian Sociological Society.