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Development vs. Rights A Case for Sustainable Development of Onge Tribes of Little Andaman
Human rights and environmental protections are often violated as a consequence of development activities. In addition to harming the environment, this increases the marginalisation of those who are already marginalised. The development paradigm that is based on the interests of the majority not only tends to retard the indigenous people but also renders them incapable of competing with the majority. For the indigenous people, development has always been a problem rather than a solution. Development initiatives under the umbrella of globalisation with a label of monotony, ignore the aspects of the diverse livelihoods of many indigenous peoples. The Niti Aayog proposed in its vision document, the Sustainable Development of Little Andaman, in 2021, that the island should be developed into a megacity by utilising its natural features and strategic location. The long-term objective is to develop the island into a major financial tourism hub that can rival Hong Kong and Singapore. This plan will, on the one hand, advance commerce, employment, and economic growth; on the other hand, environmental conservation issues will also arise. Concerns over this vision document have indeed been voiced by several academics, environmentalists, and conservationists due to issues with Onge indigenous rights, ecological fragility, and earthquake and tsunami susceptibility. In this context, the research article aims to study and analyse the proposed megacity project and its impact on the rights of Onge tribes and the environment. Sahana Florence and Achyutananda Mishra, 2024. -
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 -
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. -
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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. -
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. -
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. -
AN OPTIMIZATION AND PREDICTIVE MODELING TO ENHANCE THE WEAR AND MECHANICAL PERFORMANCE OF Al 5054 ALLOY FOR DEFENSE APPLICATIONS WITH TiO2 NANOPARTICLES
This study examines the effects of 2%, 4%, and 6% additions of TiO2 nanoparticles on the wear and mechanical characteristics of Al 5054 alloy reinforcement. The results demonstrate that the addition of TiO2 nanoparticles considerably increases the alloys tensile and impact strengths. Tensile strength reaches a peak of 221 MPa at 6% reinforcement and it rises gradually as the percentage of TiO2 reinforcement increases. Similarly, impact strength rises with time and, with TiO2 reinforcement, it reaches a maximum of 63 Joules at 6%. Wear analysis using Taguchi-based design determines the optimal combination of composition, disc rotation speed, load, and sliding distance to minimize a given wear rate and friction force. The SEM analysis validates that the composites exhibit enhanced wear resistance due to the uniform distribution of TiO2 nanoparticles. An Artificial Neural Network (ANN) model is also developed to predict the responses, and it achieves an overall accuracy of 83.549%. The mechanical properties and wear resistance of TiO2-reinforced Al 5054 composites can be enhanced, as it is demonstrated by these results. This information is crucial for material design and optimization across a range of engineering applications. 2024, Scibulcom Ltd.. All rights reserved. -
A thorough investigation of various goals and responses for mobile software-defined networks
Cloud computing has caused some companies to modify their IT infrastructure and maintenance procedures and may eliminate their current hardware altogether. Conventional methods of setting up a switch or router may be error-prone and unable to make full use of the capabilities of current network architectures. As many intelligent networking designs as possible must be developed for intellectualization, activation, and customization in future networks. Due to software-defined networking (SDN) technology, it's possible to control, secure, and optimize network resources, eliminating the rigid coupling between the control plane and the data plane in traditional network architectures. Here, the chapter explores the problems, difficulties, and potential solutions associated with software-defined networks (SDN), a novel concept in computer networking. Through SDN, the network gains the ability to be programmable, quick, and adaptable thanks to its separation of data and its ability to control traffic. 2023, IGI Global. All rights reserved. -
Human-Machine Interactions andAgility inSoftware Development
A modern organization cannot function without project management. Organizations, governments, and non-profits recognize how important modern project techniques are to the success of their IT projects. Many people understand that excellent project skills are crucial for remaining competitive in the workplace. Many project management concepts will help them with their everyday interactions with people and technology. Project management aims to plan, organize, motivate, and control resources to accomplish specific objectives and meet specific success criteria. The major challenge is to achieve all the project goals and objectives while respecting the preconceived constraints of the project. Project management for data science is easy with Agile. Understanding the different approaches to project management and how they can fit into information science is essential. Several project management tools are available to maintain and report on a projects progress. As proposed in this paper, a comprehensive study on project management and Agile methodologies helps enhance the teams interactions when working for data science project management. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Decomposition of graphs into induced paths and cycles
A decomposition of a graph G is a collection ? of subgraphs H1,H2,..., Hr of G such that every edge of G belongs to exactly one Hi. If each Hi is either an induced path or an induced cycle in G, then ? is called an induced path decomposition of G. The minimum cardinality of an induced path decomposition of G is called the induced path decomposition number of G and is denoted by ?i(G). In this paper we initiate a study of this parameter. -
Decomposition of graphs into induced paths and cycles
A decomposition of a graph G is a collection ? of subgraphs H1,H2,...,Hr of G such that every edge of G belongs to exactly one Hi. If each Hi is either an induced path or an induced cycle in G, then ? is called an induced path decomposition of G. The minimum cardinality of an induced path decomposition of G is called the induced path decomposition number of G and is denoted by ?i(G). In this paper we initiate a study of this parameter. -
Classification of Skin Diseases Using Convolutional Neural Networks (VGG) with Histogram Equalization Preprocessing
Skin diseases are a major global health concern for which prompt and precise diagnosis is necessary for effective treatment. Convolutional neural networks (CNN), one of the deep learning techniques, have shown potential in automating the diagnostic procedure. The goal of this research is to enhance the effectiveness of skin disease categorization by fusing the capabilities of CNNs - particularly the VGG architecture - with the histogram equalization preprocessing method. In image processing, histogram equalization is a commonly used approach to enhance the contrast and general quality of medical photographs, which include photos of skin conditions. In order to improve the characteristics and details of dermatological pictures for this study, we employed histogram equalization as a preprocessing step. This allowed CNN to extract pertinent features more quickly. 2024 IEEE. -
Intricate Plane of Adversarial Attacks in Sustainable Territory and the Perils faced Machine Intelligent Models
The issue of model security and reliability in Artificial Intelligence (AI) is a concern due to adversarial attacks. In order to tackle this issue, researchers have developed sustainable defense strategies, but certain challenges remain. These challenges involve transferability, higher computing costs, and adaptability. Striking a balance between accuracy and robustness is difficult, as defense mechanisms often come with trade-offs between the two. Real-world situations demonstrate the practical implications of sustainable adversarial AI. For example, it improves the security of self-driving vehicles, enhances the accuracy of medical imaging diagnoses, and incorporates AI-driven defenses into network intrusion detection and phishing detection systems. It is crucial to consider ethical aspects throughout this process. Future trends in adversarial AI research for cybersecurity will involve ensemble defense mechanisms, adversarial learning from limited data, and hybrid attacks. By embracing the evolving landscape, researchers and practitioners can develop sustainable AI systems that are more secure and resilient, effectively countering adversarial threats. 2023 IEEE. -
Understanding environmentally sustainable Indian travel behaviour: an analysis of 2011 census data
Using census data of non-agricultural workers for 2011, this study aims to examine trends and determinants of travel behaviour in India. Descriptive statistics accompanied by a beta regression model of proportional outcomes are implemented on the obtained data. The study finds that men are the dominant users of motorized transport in the country. Most workers travel a short distance of less than 5km, irrespective of area or gender. Population density, the share of married population and the share of rural population in a district significantly influence the share of environmentally sustainable travel behaviour displayed by that region. To the best of our comprehension, this is one of the primary studies elucidating the comparison of travel behaviour in ruralurban areas of Indian states. Not many studies in India have addressed the issue of influence of socio-demographic factors on environmentally sustainable travel choices. With this analysis, policymakers in the transportation sector can get a clearer idea of the behaviour and demands of different divisions of society. The findings of this study demand the evolution of infrastructure of public transportation and non-motorized transportation in the country in such a way that is both efficient and secure to neither impede the goals of empowerment or sustainability. The Author(s), under exclusive licence to Institute for Social and Economic Change 2023. -
Gender gap in travel behaviour and public opinion on proposed policy measures: Evidence from India
Employing primary survey data collected from Jaipur city in India, this work attempts to evaluate inconsistencies in travel behaviour based on gender. It also intends to discuss the public opinion on a few proposed policy changes which can aid in bridging the established gender gap. Stratified random sampling approach is used to gather data on travel pattern measures and socioeconomic attributes. Descriptive statistics complemented with bivariate probit model and seemingly unrelated bivariate probit model is applied on the data acquired. The obtained results confirm the existence of a gender gap in all observed measures of travel behaviour. Compared to men, women travel shorter distances, use more of non-motorised modes of transport, have lower frequency of travelling, and travel majorly for purposes other than work. Results of the study also highlight how a majority of the respondents are in favour of policy changes aimed at narrowing the observed gender disparities. The analysis demands infrastructural development of non-motorised transportation and public transportation in the city in such a way which is both efficient and secured, so as to neither obstruct the objective of empowerment nor of sustainability. 2023 John Wiley & Sons Ltd.