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Role of Triguna Personality Towards Emotional Expression in Relation to Emotional Regulation
With the changing times, people are more aware of their emotions regarding how to express and regulate them. The present generation is more active and expressive than the previous generation as they understand the significance of emotions in ones life. The body of literature claims that a person with better emotional understanding and expression is expected to have meaningful emotional regulation irrespective of the generation they represent. Traditional Indian Philosophy defines three essential characteristics, Sattva (purity, harmony), Rajas (activity, passion), and Tamas (resistance, darkness), that influence human behavior and experience. The degree to which one of the gunas predominates in an individual, to that extent, we characterize that person with that guna. The complicated interactions between Trigunas personality, emotional expression, and emotional regulation are examined. Considering the available facts, the present research focuses on exploring the association between emotional expression and emotion regulation strategies and the effect of the triguna personality in it, across two generations within the family. To accomplish this, a cross-sectional research design will be used to explore the generational difference, followed by a correlational research design to study the associations among variables for participants within each group. Participants would include the parents (mothers, 45 to 50 years) and their children (siblings, 18 to 24 years). The data was collected from 30 families. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Role of Triguna Personality Towards Emotional Expression in Relation to Emotional Regulation
With the changing times, people are more aware of their emotions regarding how to express and regulate them. The present generation is more active and expressive than the previous generation as they understand the significance of emotions in ones life. The body of literature claims that a person with better emotional understanding and expression is expected to have meaningful emotional regulation irrespective of the generation they represent. Traditional Indian Philosophy defines three essential characteristics, Sattva (purity, harmony), Rajas (activity, passion), and Tamas (resistance, darkness), that influence human behavior and experience. The degree to which one of the gunas predominates in an individual, to that extent, we characterize that person with that guna. The complicated interactions between Trigunas personality, emotional expression, and emotional regulation are examined. Considering the available facts, the present research focuses on exploring the association between emotional expression and emotion regulation strategies and the effect of the triguna personality in it, across two generations within the family. To accomplish this, a cross-sectional research design will be used to explore the generational difference, followed by a correlational research design to study the associations among variables for participants within each group. Participants would include the parents (mothers, 45 to 50 years) and their children (siblings, 18 to 24 years). The data was collected from 30 families. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Organizational Factors Impacting the Retail Industry's Adoption of Blockchain Technology
Indian retail is undergoing a transformation due to rapid digitization and shifting consumer preferences. Blockchain technology is changing retail chain management by boosting efficiency, security, and transparency. This technology can also alter Indian retail operations by enabling verified transactions and improving inventory management to build consumer trust. Blockchain technology adoption in retail depends on organizational readiness, technological knowledge, and top management support. This study examines organizational aspects affecting blockchain adoption in retail and develops and validates a model for organizational characteristics affecting blockchain adoption. Thus, the study examines three key blockchain adoption intention constructs of blockchain knowledge, organizational readiness, and organizational support. Retailers received surveys online and the data was analyzed using SEM. The study supports that organizational management support (p?=?0.017) and organizational readiness (p?=?0.008) are significant precursors to the intention to adopt this technology. The study concludes that organizations must support and improve their readiness for modern technology with the top management's cooperation. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Linking the Path to Zero Hunger: Analysing Sustainable Development Goals Within the Context of Global Sustainability
A global framework, the Sustainable Development Goals of the United Nations, are designed to tackle the most urgent global issues. SDG 2, which stands for Zero Hunger, demonstrates a robust interconnection with the remaining seventeen goals since achieving food security and improved nutrition requires an all-encompassing approach that addresses the interconnected challenges presented by poverty, health, education, gender equality, climate change, and sustainable resource management. Within this framework, the research endeavors to ascertain the interrelationships among SDG 2 and other goals and analyze the critical goals that drive the achievement of SDG 2. Furthermore, the study provides an exhaustive analysis of the positions adopted by different nations concerning SDG 2. The results indicate that the SDGs are interconnected; while SDG 2 is closely linked to several other SDGs, their respective impacts differ. Furthermore, it has been determined that policies are crucial to attaining the SDGs. Without a transformation in agri-food systems that enhances resilience and facilitates the provision of affordable, nutritious foods and healthy diets, the current state of affairs will persist. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
A Novel Survey for Young Substellar Objects with the W-band Filter. VII. Water-bearing Objects in the Core of the ? Ophiuchi Cloud Complex
We present a study of very low mass stars and brown dwarfs in the rich star-forming core of the ? Ophiuchi cloud complex. The selection of the sample relies on detecting the inherent water absorption characteristic in young substellar objects. Of the 22 water-bearing candidates selected, 15 have a spectral type of M6 or later. Brown dwarf candidates too faint for membership determination by Gaia have their proper motions derived by deep-infrared images spanning 6 yr. Astrometric analysis confirms 21/22 sources as members, with one identified as a contaminant. Infrared colors and the spectral energy distribution of each water-bearing candidate are used to diagnose the mass, age, and possible existence of circumstellar dust. A total of 15 sources exhibit evidence of disks in their spectral energy distributions, as late as in M8-type objects. Spectroscopy for bright candidates has confirmed one as an M8 member and verified two sources (with disks) exhibiting signatures of magnetospheric accretion. 2025. The Author(s). Published by the American Astronomical Society. -
Trusted explainable AI based implementation for detection of neurodegenerative disorders (ND)
The potential of explainable artificial intelligence (XAI) in detection of neurodegenerative disorders (ND) holds great promise in the field of healthcare. These diseases interfere with the daily functioning and independence of a person. The current studies lack in highlighting the aspect of explainability in their predictions and the various algorithms cannot provide any plausible explanations for their predictions making it difficult for medical professionals to place trust in their findings. Thus, the proposed framework aims to bridge this gap by exploring the development of a trustworthy framework for XAI-based ND detection, focusing on key aspects that can significantly impact its effectiveness and acceptance. The framework makes use of Trust-based SHAP (SHapley Additive exPlanations) values in classification. By computing trust values, the framework ensures more reliable predictions and increases interpretability, instilling confidence in clinicians and patients. The results show that with the inclusion of the trust-driven framework, the accuracy of the algorithm increased from 93.33% in the normal circumstances to 98.21%, highlighting the efficacy of the framework as compared to the other works. This shows that a trustworthy framework for XAI-driven ND detection can reshape care by enabling early detection, personalized treatment plans and enhancing decision-making process. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
Metaverse for Sustainable Development: Trends and Applications
Unlock the future of technology and sustainable development by purchasing Metaverse for Sustainable Development: Trends and Applications, a comprehensive guide that delves into immersive application building, groundbreaking innovations, and the transformative potential of the metaverse across various industries. Metaverse for Sustainable Development: Trends and Applications explains the fine details of metaverse application building, demonstrating how integrated platforms in association with a suite of tools come in handy for enabling application construction. The metaverse is the next big thing influenced by virtual and augmented reality paradigms. This user experience will be more immersive and mesmerizing, empowering innovative, disruptive, and transformative technologies to create a spectacular platform for visualizing and realizing business-critical and people-centric metaverse systems. This book explores various metaverse models for healthcare information systems, including the latest technologies, such as the Brain-Computer Interface. Through real-world data and case studies, readers will gain a comprehensive understanding of the metaverses potential for the Internet of Things, blockchain, artificial intelligence, 5G, and 3D modelling for creating and sustaining immersive virtual worlds. Metaverse for Sustainable Development: Trends and Applications is a vital resource for understanding the end-to-end implementation of metaverse technologies. 2025 Scrivener Publishing LLC. -
Quantum technologies outreach and AI
Quantum computing is one of the buzzing technologies in this modern computational era. Quantum computing is purely based on quantum mechanics as few dormant applications and advanced studies of quantum computers are integrated with quantum mechanics. This paper highlights the seven perspectives of quantum computing which is essential to get deep insights of quantum computing. The seven prerequisites are superposition, decoherence, entanglement, linear algebra, classical mechanics, quantum Fourier analysis and many body systems. The main objective of this paper is to find few stupendous impacts of this computing which will complement and explore various applications of artificial intelligence like weather pattern identification, traffic prediction, e-mail spam filtering, logistics optimisation, etc. This paper discusses visions of the top quantum computing companies and their contributions to quantum technologies. In this paper, a comparative analysis has been presented between quantum computing and classical computing. The major challenges which quantum computing faces have been addressed. Copyright 2025 Inderscience Enterprises Ltd. -
Economic Growth, Human Resource Development, and Climate Resilience in BRICS A Panel Data Analysis
Present study employs panel data analysis on BRICS economies data spanning from 2000 to 2023, to examine the impact of human resource development, renewable energy consumption, and carbon emissions on GDP per capita of BRICS economies,finding that while human capital strongly drives growth, renewable energy has a positive but weaker effect, and carbon emissions remain tightly linked to GDP, underscoring the persistent reliance on carbon-intensive industries, ultimately highlighting the need for policy shifts toward sustainable growth through education, clean energy transitions, and regulatory frameworks that balance industrialization with climate resilience. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Analyzing SDGs in high-and-low-emission industries: a comparative study of sustainability reports
This study assesses different Sustainable Development Goals (SDGs) in high- and low-polluting industries through a comparative analysis of sustainability reports. The objective is to evaluate SDG-related terms in reports from 16 companies across four sectorsCement, Automobile, Electric Equipment, and ITover five years. Using Python for data extraction and the text2sdg package in R programming for SDG term detection, the study identifies both prioritized and overlooked SDGs. Results indicate that high and low-polluting industries share similar SDG focus areas. SDGs 6 (Clean Water and Sanitation), 12 (Responsible Consumption and Production), and 13 (Climate Action) received the most attention. In contrast, SDGs 1 (No Poverty), 2 (Zero Hunger), 5 (Gender Equality), 10 (Reduced Inequalities), and 14 (Life Below Water) are consistently underrepresented. The findings suggest that both categories of industries acknowledge the importance of sustainability, yet significant gaps remain in addressing social and environmental challenges. This research contributes to the broader discourse on corporate sustainability and its role in achieving the 2030 Agenda, offering actionable insights for industries to increase their focus on less-considered SDGs. By identifying areas of improvement, the study supports efforts to foster more inclusive and environmentally responsible business practices. The Author(s) 2025. -
EcoFlow choices: factors influencing sustainable menstrual hygiene product decisions
This study examines how knowledge and emotional response (affect) influence consumer buying behaviour toward eco-friendly menstrual hygiene products, with a particular focus on the mediating role of affect. A cross-sectional design was employed, and data were collected via an online survey of 356 urban Indian women using purposive sampling. Data were analysed using Structural Equation Modelling (SEM) with SPSS (v25) and AMOS (v24). The results reveal that both knowledge and affect significantly shape purchasing decisions. However, affect exerts a stronger influence than knowledge alone. Importantly, affect also mediates the relationship between knowledge and buying behaviour, underscoring the critical role of emotional engagement in promoting sustainable consumer choices. These findings suggest that marketing strategies should not only aim to inform consumers but also foster positive emotional connections with eco-friendly products. The study offers meaningful contributions to the field of green consumer behaviour and carries important implications for sustainability-driven marketing practices. It supports the goals of the United Nations Sustainable Development Agenda, particularly SDG 3 (Good Health and Well-being) and SDG 12 (Responsible Consumption and Production), by highlighting how promoting eco-friendly menstrual hygiene products can reduce environmental impact and support womens health. This research provides insightful implications for policymakers, marketers, and sustainability advocates to guide sustainable consumption behaviour among people. 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Rhetoric as an instrument for manipulation and distortion of truth an analysis of Orwell's 1984
Aristotle, in his Rhetoric, points out that all individuals indulge in rhetoric to demonstrate the truth or righteousness in what one wants to say. Problems arise only when rhetoric is used to appeal to emotions, rather than reason. In the current times, when rhetoric is used by leaders for propaganda, to whip up emotions in terms of nationalism and racism, George Orwell's remark that "political language is designed to make lies sound truthful and murder respectable,"6 sounds relevant. The author examines Orwell's 1984 to demonstrate how rhetoric is a powerful tool in the hands of political leaders that can control the thoughts of individuals, to the extent of reducing them to non-entities. In an era where manufacture of consent is possible, the paper highlights how the quality of rhetoric has vitiated over time and the concern that the abuse of language prevalent in fascist regimes of Hitler and Stalin is slowly creeping into democracies too. A peaceful and harmonious existence is possible only when political leaders engage in responsible rhetoric and are willing to dialogue with dissenting voices. 2017 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
Soil classification using active contour model for efficient texture feature extraction
Precision farming is a systematic approach in agriculture that aims in improving economic and environment status of the farmers. It is achieved by having prior knowledge on soil texture, nutrient, pH and other climatic conditions. Hence this paper proposes a soil classification for crop prediction approach that uses an active contour algorithm for band estimation in Fourier domain for efficient texture feature extraction. This approach initially segments the soil sample and extracts into the color and texture features. The approach proposes a texture feature extraction where the image is initially transformed to Fourier domain of a 2D-discrete Fourier transform. The image in the Fourier domain is classified into high and low-frequency bands. The cut off frequency is decided by final contour of active contour method, where initial circular contour is used for estimating final contours on Fourier coefficients. This leads to the estimation of an irregular-shaped cut off frequency along with the 2D Fourier coefficients, instead of using a circular-shaped cut off frequency. A local binary pattern (LBP) from the high-frequency band image extracts texture feature. The extracted texture and color features are trained using a fully connected network. Active contour-based proposed model was evaluated by metrics F1-score, accuracy, specificity, sensitivity, and precision on soil datasets of Kaggle and IRSID. The accuracy, F1-score, specificity, precision, and sensitivity of proposed approach active contour-based were estimated as 97.89%, 97.87%, 99.46%, 98.11 and 97.94% respectively when evaluated in the Kaggle dataset. The evaluation results of proposed active contour model based soil classification outperform other traditional approaches. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
A Systematic Literature Review on Image Preprocessing and Feature Extraction Techniques in Precision Agriculture
Revolutions in information technology have been helping agriculturists to increase the productivity of the cultivation. Many techniques exist for farming, but precision agriculture (PAg) is one technique that has gained popularity and has become a valuable tool for agriculture. Nowadays, farmers find it difficult to get expert advice regarding crops on time. As a solution, image processing techniques (IPTs) embedded PAg applications are developed to support farmers for the benefit of agriculture. In recent years, IPT has contributed a lot to provide a significant solution in PAg. This systematic review provides an understanding on preprocessing and feature extraction in PAg applications along with limitations. Preprocessing and feature extraction are the major steps of any application using IPTs. This study gives an overall view of the different preprocessing, feature extraction, and classification methods proposed by the researchers for PAg. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Digital Soil Texture Classification Using Machine Learning Approaches
The texture of the soil is an important factor to consider during cultivation. The water transmission property is being regulated by the texture of the soil. To determine sand, silt and clays percentage present in a soil sample, a conventional laboratory method is used, which consumes more time. Digitization in agriculture has given a new direction of innovative research in agriculture domain. In this paper, based on image processing an efficient model has been developed for soil texture classification. Eight different image preprocessing techniques were used for the image enhancement. Out of that, the linear contrast adjustment found to be best in image enhancement. A feature vector was calculated by extracting six different features from the enhanced image. The feature vector of an image is input to the machine learning classifier. The various classifiers used in this research work are SVM, KNN, ANN and PNN. The accuracy of the classifiers was SVM (0.98), KNN (0.89), ANN (0.89) and PNN (0.86). From the result, it is found SVM model has higher rate in classification of soil. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Image Processing and Artificial Intelligence for Precision Agriculture
Precision agriculture is a novel approach to increase the productivity of crops that employs recent technologies such as Artificial Intelligence, WSN, cloud computing, Machine Learning, and IoT. This paper reviews the development of different techniques effectively used in precision agriculture. The paper details the technological impact on precision agriculture followed by the different image processing schemes such as Satellite imagery and unmanned aerial vehicle (UAV). The role of precision agriculture is disease detection, weed detection from UAV images, and detection of trees and contaminated soils from satellite imagery is discussed. It reviews the impact of artificial intelligence (AI) namely machine learning &deep learning in precision agriculture. The performance of the recent image processing schemes in precision agriculture is analyzed. The paper also discusses the challenges that exist in implementing the precision agriculture system. 2022 IEEE. -
An empirical study on the clients perspective in decision making with regard to lawyer selection for trial courts: Does grey hair matter?
In higher courts, statutory interpretation and persuasion of the court with new perspectives on legal principles are critical. Whereas, the main focus of the subordinate courts is on evidential underpinnings. Hence, the lawyers in all courts are an indispensable part of the judicial process and play a seminal role in the dispensation of justice. The existing literature demonstrates that engaging a senior lawyer increases the chances of winning cases. However, young lawyers today make their mark by establishing their own offices, succeeding in the profession, while some remain the dark horses of their incumbent seniors. Against this backdrop, the authors explore the clients perception of the lawyer selection process and the significance of lawyers age using a mixed methods approach. The data for this study was gathered from trial court clients using a convenient sampling method. The qualitative data were collected by conducting semi-structured interviews with clients. Interviews were analysed at a thematic level and broad themes were identified and used as constructs for a quantitative survey questionnaire. The quantitative data were analysed through Pearson correlation, regression analysis, and factor analysis. The study determined that lawyers efficiency is a key factor considered by trial court clients in selecting their lawyers. The results also revealed that there exists a significant positive correlation between the age of the lawyer and the clients decision making when choosing their lawyers. In the end, the implications of the findings are discussed. 2022, The Author(s), under exclusive licence to O.P. Jindal Global University (JGU). -
Orhan pamuks the white castle as a text on secular discourse
The impact of religious thought and practice on literature and culture was very evident till the latter part of the nineteenth century. But with the publication of Darwins Origin of Species, voices of dissent were heard from the scientific and literary world. Writers strongly felt that the objective of literature was not to be dogmatic, but to provide the necessary ingredients that would contribute to a healthy and secular society. The emergence of postmodernism saw religion once again taking center stage. This paper seeks to understand what secularism is, and the evolution in meaning this term has undergone over the ages. In this process, the theories and ideas of religious and political thinkers are examined to understand the essence of the term secularism. In an era when religious fundamentalism is on the rise and literature is censured on religious or cultural grounds, the paper analyzes Orhan Pamuks The White Castle and concludes with the contention that the text can definitely be a source of secular discourse (which indeed is the essence of religious texts) that nations can emulate, contrary to the idea of narrow secular nationalism currently being propagated by States. IUP Publications. All rights reserved. -
Weighted Mask Recurrent-Convolutional Neural Network based Plant Disease Detection using Leaf Images
Large losses in output, money, and quality/quantity of agricultural goods are incurred due to plant diseases. Seventy percent of India's GDP is tied to the agricultural sector, thus protecting plants from diseases is crucial. For this reason, it is important to keep an eye on plants from the moment they sprout. The usual approach for this omission is naked eye inspection, which is more time-consuming, costly, and requires significant skill. Thus, automating the method for detecting diseases is necessary to speed up this process. It is imperative that image processing methods be used in the creation of the illness detection system. Disease detection involves a number of processes, including Weighted Mask R-CNN, GLCM feature extraction, Multi-thresholding image pre-processing, and K means image segmentation classification. The weighted Mask R-CNN outperforms the standard RNN, the Mask R-CNN, and the CNN in terms of accuracy and recall in analytical trials by a significant margin. 2023 IEEE. -
A Comprehensive Survey of Methods for Identifying Counterfeit Banknotes Using Image Processing and Machine Learning
The world economy is threatened by counterfeit currencies. Counterfeit currencies are often difficult, time-consuming and ineffective to identify manually. Automated methods based on image processing techniques and machine learning algorithms are helpful in detecting counterfeit notes. This survey paper reviews the current strategies on fake banknote detection using image processing techniques and machine learning algorithms. We discuss various stages of the detection process, including image acquisition, preprocessing, feature extraction and classification. Furthermore, we analyze the limitations and comparative performance of different algorithms and approaches mentioned in the literature. The survey aims to provide insights into the various methodologies, challenges and future directions in the field of fake banknote detection, facilitating the development of more robust and effective counterfeit detection systems. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.