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Partial slip and Joule heating on magnetohydrodynamic radiated flow of nanoliquid with dissipation and convective condition
Numerical investigation of three-dimensional flow of an electrically conducting nanofluid over a bidirectional stretching surface is proposed here. The slip flow over a convectively stretching sheet is considered. The flow is caused due to a non-linear stretching surface and Lorenz force. Water and copper nanoparticles are used to form nanoliquid. Suitable transformations are employed to reduce the conservation equations into nonlinear coupled, multidegree ordinary differential equations. Resultant nonlinear two-point boundary value problem is numerically integrated using Runge-Kutta-Fehlberg fourth-fifth order method. Computed results are verified with existing results under limiting cases. The influences of pertinent parameters on different flow fields are evaluated and presented via graphical and tabular form. It is found that the thermal radiation and convective heating at boundary stabilizes the thermal boundary layer growth. 2017 The Authors -
Particle swarm optimization- based support vector regression for predictions: Approach and applications
For centuries, people have drawn inspiration from nature, and there is always more to learn and discover. The Particle Swarm Optimization (PSO) algorithm, a stochastic optimization algorithm based on population and inspired by the intelligent collective behavior of certain animals like fish schools or flocks of birds, is one of the most well-known nature-inspired algorithms presented in this work. As more was known about the fundamentals of this methodology, researchers produced new iterations to satisfy varying needs, new applications in diverse domains, theoretical research on the effects of different parameters, and a multitude of algorithm variations. PSO-support vector regression (SVR) is one such variant of this algorithm. SVR is a kind of Support Vector Machine (SVM) that solves regression problems. It seeks to identify a function that diverges from the actual values observed by no more than a given margin. The main idea is to retain the error under a certain threshold. PSO optimizes SVR parameters, including regularization, epsilon, and kernel parameters. This combination takes advantage of the strengths of both approaches. In this chapter, we will discuss the importance of the PSO-SVR algorithm in predicting the outcomes of real-world applications classified as healthcare, environmental, industrial, commercial, smart city, and other broad applications. 2025 selection and editorial matter, Sulabh Bansal, Aprna Tripathi, Shilpa Srivastava and Prem Prakash Vuppuluri; individual chapters, the contributors. -
Partition Refugees in Jammu Cry for Protection of Land and Job Rights
Article 370 was presented as an obstacle in the complete integration of Kashmir and it had denied citizenship and land rights to around 1.5 lakh West Pakistan Refugees (all Hindus) since their migration in 1947. However, after the lapse of merely five years of the abrogation, these WPRs, the new citizens of Jammu and Kashmir, have started feeling disillusioned and demanding protection of lands and jobs under Article 371 of the Indian Constitution. 2024 Economic and Political Weekly. All rights reserved. -
Partner betrayal trauma and trust: Understanding the impact on attachment style and self-esteem
Dismissal of an individual's emotional experience by their significant others can have a massive impact on the psychological well-being of the individual. Betrayal trauma discusses the prevalent social phenomenon and its short- as well as long-term impacts on an individual. This study focused on betrayal trauma in romantic relationships. It aimed to find its relation with an individual's self-esteem and attachment styles, with trust as a mediating variable. The tools used in the study- were the partner betrayal trauma trust scale, adult attachment scale and self-esteem scale, each of which was a self-report measurement scale circulated among young adults in the Indian population. The study consisted of 140 participants (n = 140) with a mean age of 21.7 and a standard deviation (SD) of 2.05. The participants included 85% female, 16% male, 3% of the participants identified as genderfluid, and 2% of the participants preferred not to mention their gender. The results from the study show that betrayal trauma in romantic relationships is related to an individual's attachment style and self-esteem. A positive significant correlation was found between betrayal trauma, self-esteem and attachment style, which reveals the impact of betrayal trauma on the psychological well-being of an individual. These findings may aid mental health practitioners in helping young adults resolve their relationship crises and enhance their lifestyles in India. 2024 Elsevier Masson SAS -
Passenger flow prediction from AFC data using station memorizing LSTM for metro rail systems
Metro rail systems are increasingly becoming relevant and inevitable in the context of rising demand for sustainable transportation methods. Metros are therefore going to have a consistently expanding user-base and hence user satisfaction will require meticulous planning. Usage forecast is clearly an integral component of metro planning as it enables forward looking and efficient allocation of resources leading to greater commuter satisfaction. An observation from studying the usage of Kochi Metro Rail Ltd. is that there is a consistently occurring temporal pattern in usage for every station. But the patterns differ from station to station. This hinders the search for a global model representing all stations. We propose a way to overcome this by using station memorizing Long Short-Term Memory (LSTM) which takes in stations in encoded form as input along with usage sequence of stations. This is observed to significantly improve the performance of the model. The proposed architecture with station parameter is compared with algorithms like SVR (support vector regression) and neural network implementation with the best architecture to testify the claim. The proposed model can predict the future flow with an error rate of 0.00127 MSE (mean squared error), which is better than the other models tested. CTU FTS 2021. -
Past decade of supercapacitor research Lessons learned for future innovations
Due to their high power density, long cycle stability, and quick charge/discharge rates, supercapacitors are gaining popularity in the field of energy storage devices. These distinct features have enabled supercapacitors to create their own space in the energy storage device realm. This review addresses contemporary ways to increase not just the power density, rate capability, cycle stability, and other properties of supercapacitors, but also their energy density utilising hybrid topologies. Because electrodes are the most significant component of a supercapacitor cell and the last decade mainly focused on the material realm, this paper focuses on the design of hybrid supercapacitor electrodes with high specific capacitance, as well as the explication of the mechanisms involved. We have also given an insight about the merits and demerits of various electrode materials that have been employed till date. The new trends and improvement in supercapacitor development are also summarized. 2023 Elsevier Ltd -
Patent Dispute settlement through Arbitration and the public policy concerns
India is a developing nation, which had shown both progress and decline in economy over the years. Intellectual property rights are considered as an important asset of a nation. National legislations are made in par with the international conventions and treaties, more concentration on the industry and investments are needed for the development of the nation. Patent legislations changed on basis of the national and international needs. The monopoly right granted for an invention is on the basis of their intellectual skill. Patent dispute settlement mechanisms are mainly patent office through controller of patent, District Court & High Court and the patent tribunals. Patent is granted for 20years in India. The patent holder can utilize the same within this short span of time. Hence all the patent holders and the public challenging the validity of the patent, expect a speedy justice in patent disputes. This research paper addresses the question as to whether subject matters that can be referred for arbitration can be limited on grounds of public policy. Further the paper will address the issues as to whether arbitration can be effective mechanism for settling patent disputes in India. 2023 Brazilian Center for Mediation and Arbitration - CBMA. All Rights Reserved. -
PATENTABILITY OF BIOTECHNOLOGY INVENTIONS: Indian Ethical Guidelines
Advances in technology have made patenting of biotechnology inventions mandatory. The patent law system contains general clauses prohibiting the patenting of inventions contrary to public order or morality. Recent years have brought numerous debates on limiting the possibility of patent protection for biotechnology inventions for ethical reasons. The existing literature examines bioethical justification in terms of the principles of respect for autonomy, non-maleficence, beneficence and justice. The primary purpose of this study is to explore the uncertainty of ethics guidelines provided by the Indian Council of Medical Research (ICMR) and section 3(b) of the Indian Patents Act 1970 and the applicability of the bioethics principles. 2023 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore), ISSN: 0253-7222. -
Patents and Innovations for Digital Sustainability
With technology growing at a rapid pace, a major issue which is being faced is the problem of effective energy usage and sustainability such that the future generation does not have to bear the brunt of our actions. Through the course of the chapter, the various innovations and patents in the field of digital sustainability are explored which are vital for the preservation of the planet. Patents play a crucial role in promoting innovations and development, as well as protecting the rights of inventors. The varied recent developments in the field of energy sustainability and explaining their work while assessing their contribution to the field are the focus of this chapter. The chapter also provides a comprehensive overview of the relationship between patents and innovations in digital sustainability, offering insights and guidance for researchers, practitioners, and policymakers working in this field. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa. -
Path Planning of KR6 R900 Vision Sensor Assisted KUKA Industrial Robot for Pick and Place Application
In this paper, a new multi-objective functions comprising of squared values of joint jerk, acceleration, torque rate and total travel time subjected to kinematic and dynamic constraints have been formulated for achieving optimal trajectory for industrial applications. Then four different multi-objective optimization algorithmsthe multi-objective particle swarm optimization technique (MOPSO), the multi-objective genetic algorithm (MOGA), non-dominated sorting genetic algorithm-II (NSGA-II) and the proposed multi-objective enhanced teaching learning-based optimization (MOETLBO)have been utilized to obtain the optimal solution for trajectory planning. Finally, the experimental validation of the proposed technique and the summarization of simulation results have been done as a comparative study of the four different metaheuristic techniques for pick and place application of KR6 R900 KUKA industrial manipulator. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Pathway toDetect Cancer Tumor byGenetic Mutation
Cancer detection is one of the challenging tasks due to the unavailability of proper medical facilities. The survival of cancer patients depends upon early detection and medication. The main cause of the disease is due to several genetic mutations which form cancer tumors. Identification of genetic mutation is a time-consuming task. This creates a lot of difficulties for the molecular pathologist. A molecular pathologist selects a list of gene variations to analyze manually. The clinical evidence strips belong to nine classes, but the classification principle is still unknown. This implementation proposes a multi-class classifier to classify genetic mutations based on clinical evidence. Natural language processing analyzes the clinical text of evidence of gene mutations. Machine learning algorithms like K-nearest neighbor, linear support vector machine, and stacking models are applied to the collected text dataset, which contains information about the genetic mutations and other clinical pieces of evidence that pathology uses to classify the gene mutations. In this implementation, nine genetic variations have been taken, considered a multi-class classification problem. Here, each data point is classified among the nine classes of gene mutation. The performance of the machine learning models is analyzed on the gene, variance, and text features. The gene, variance, and text features are analyzed individually with univariate analysis. Then K-nearest neighbor, linear support vector machine, and stacking model are applied to the combined features of a gene, variance, and text. In the experiment, support vector machine gives better results as compared to other models because this model provides fewer misclassification points. Based on the variants of gene mutation, the risk of cancer can be detected, and medications can be given. This chapter will motivate the readers, researchers, and scholars of this field for future investigations. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Pathways for Sustainable Food Security: Status, Challenges, and Opportunities in Developing World
Food security is a significant concern in developing countries because of the dense population of disadvantaged individuals, insufficient food resources, and restricted availability of retail options. Food availability, quantity, and consumption are significantly influenced by social conditions. This study aims to analyze the present circumstances, challenges, and potential prospects in order to suggest pathways towards achieving sustainable food security in developing countries. The study utilizes a comprehensive approach to identify the vital societal elements that impact food security, through the analysis of pertinent literature and case studies from multiple nations. The variables encompass affluence, gender, education, social capital, and culture. This study investigates the causal relationship between these variables and the occurrence of food insecurity. It proposes strategies that foster sustainable agriculture, social protection, community empowerment, and gender equality as potential remedies. The report asserts that addressing the socioeconomic determinants impacting food security is crucial for emerging nations to attain sustainable food security. Attaining sustainable food security necessitates a comprehensive approach that acknowledges the significance of social factors and focuses on the holistic well-being of individuals. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Patient Digital Twins for Dynamic Hospital Supply Chain Management AI-Based Predictive Resource Allocation
The fusion of Digital Twin (DT) technology and Artificial Intelligence (AI) holds great promise for the optimization of hospital supply chain management and resource allocation. This paper proposes a patient-specific digital twin framework aimed at forecasting hospital staffing needs and aiding supply planning by means of AI-based analytics. Preprocessing and modeling of hospital records that included admission information, medical procedures, room types, usage of supplies, and patterns of staffing were achieved by utilizing advanced machine learning algorithms. The strategy illustrated better performance compared to baseline strategies and had interpretability from feature importance analysis, which emphasized length of stay, critical care admissions, and specialized procedures as influential drivers of staffing requirements. The results show that the patient digital twin can optimize operational efficiency, avoid supply deficits, and facilitate evidence-based decisions. The suggested framework is consistent with the vision of contemporary healthcare supply chains in that it promotes resilience, flexibility, and smart resource management. 2025 IEEE. -
Patient Monitoring System for Elderly Care using AI Robot
The use of robots in numerous industries has expanded in recent decades. Self-guiding robots have started to arise in human life, particularly in sectors pertaining to the lives of old people. Age-related population growth is accelerating globally. As a result, there is a rising need for personal care robots. The purpose of this requirement is to increase opportunities for mobility and support independence. To meet this demand, a robot with specific functionalities to help older people has been designed. The standard values of healthcare parameters are stored in the database by recording and comparing the current values the system will give an alarm and also sends a message to the doctor or caretaker so that a proper care would be given to the patients. We are including a preset distance value to monitor the elder people. Here we are using some sensors to detect the health parameters from the person. Robot have designed to intimate the family members if any changes occur in the health parameters. It helps the people to stay alone in home with safe manner. 2022 IEEE. -
Patients trust in the Indian healthcare system and its impact on the intention to use artificial intelligence-based healthcare chatbots
Purpose: Indian patients have different medicine systems available at the service that alter their healthseeking behaviour (HSB). This study aims to examine the beliefs and behaviour of patients in India towards the healthcare system and how it affects their intention to use healthcare chatbots. Design/methodology/approach: A survey instrument was developed from standard scales and validated by experts. The data was collected from 397 respondents in an urban area and tested using a structural equation model in SAS JMP software. Findings: The study found that awareness and perception of chatbots and distrust on doctors and health systems impact trust in a chatbot. The results show that trust in chatbots influences the intention to use chatbots. The belief in alternative medicine systems and HSB also influence the intention to use chatbots. The study findings also imply that health-care chatbots should cater to HSB and the belief in alternative medicine. Research limitations/implications: The study was conducted only among the urban population because services based on technology are more available in metro cities. Bengaluru is considered the representative population of urban India. Practical implications: The level of disruption that chatbots can provide to the healthcare system makes this study significant. The study findings will help to manage the factors that can enable chatbot inclusivity, as the current system is inaccessible to many patients. Originality/value: This paper addresses an identified need to study patients trust in the Indian healthcare system and their intention to use chatbots. The level of disruptions these chatbots can cause in the health-care system is undeniable and patients trust in these chatbots will eventually transform the health-care sector. 2024, Emerald Publishing Limited. -
Patients trust in the Indian healthcare system and its impact on the intention to use artificial intelligence-based healthcare chatbots
Purpose: Indian patients have different medicine systems available at the service that alter their healthseeking behaviour (HSB). This study aims to examine the beliefs and behaviour of patients in India towards the healthcare system and how it affects their intention to use healthcare chatbots. Design/methodology/approach: A survey instrument was developed from standard scales and validated by experts. The data was collected from 397 respondents in an urban area and tested using a structural equation model in SAS JMP software. Findings: The study found that awareness and perception of chatbots and distrust on doctors and health systems impact trust in a chatbot. The results show that trust in chatbots influences the intention to use chatbots. The belief in alternative medicine systems and HSB also influence the intention to use chatbots. The study findings also imply that health-care chatbots should cater to HSB and the belief in alternative medicine. Research limitations/implications: The study was conducted only among the urban population because services based on technology are more available in metro cities. Bengaluru is considered the representative population of urban India. Practical implications: The level of disruption that chatbots can provide to the healthcare system makes this study significant. The study findings will help to manage the factors that can enable chatbot inclusivity, as the current system is inaccessible to many patients. Originality/value: This paper addresses an identified need to study patients trust in the Indian healthcare system and their intention to use chatbots. The level of disruptions these chatbots can cause in the health-care system is undeniable and patients trust in these chatbots will eventually transform the health-care sector. 2024, Emerald Publishing Limited. -
Patients' Perception about the Influence of CRM Factors in Selected Health Care Units
The primary motivation behind this exploration study targets introducing a portion of the CRM ideas and components, CRM procedure to take proactive measures towards the customer to Health supplier to improve patients' satisfaction, loyalty fabricates a decent connection with patients and increment income. Patients' consideration, needs, and making associations with patients is an everyday schedule action in a well-being supplier. CRM is fundamental in this foundation customer satisfaction, the customer saw worth and customer relationship the board upgrade the relationship of the customer with the support up the general execution of the Hospital. The exploration configuration depends on quantitative examination, hence the information was gathered through an organized poll, five Likert-scales, SPSS, relapse, and SEM Model were utilized to figure out the results. This audits and distinguishes fundamental service quality, framework, the executives, and correspondence is identified with patients' satisfaction and loyalty in the private clinics in Andhra Pradesh. This investigation features the degree of service quality of the clinic services chosen by the test respondents.. This paper is an endeavour to discover connections between patients' views of customers' satisfaction and customers' loyalty and to propose ideas to have better CRM rehearses. 2021 by authors, all rights reserved. Authors agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License -
Patriarchal Constraints in Everyday Lives: Gender Roles, Matrilineality, and the Status of Contemporary Khasi Women
The Khasi tribe from Meghalaya in northeast India practices a matrilineal system, which is believed to be more egalitarian than patrilineal systems. The women of the Khasi tribe are often regarded as having a higher status than other women in India. However, despite belonging to a matrilineal society, Khasi women still face challenges in their social lives stemming from patriarchal constructs. This qualitative study examines the social status and subsequent challenges faced by Khasi women in contemporary India. Using in-depth interviews and observations of thirty urban and rural Khasi women in the East Khasi Hills District of Meghalaya, the study reveals how Khasi women experience contradictory and challenging roles, relationship dynamics, and gender stereotypes in their lives. More studies should examine the problems and challenges that Khasi women face in their society despite the benefits of a matrilineal system. 2026 Bridgewater State College. All rights reserved. -
Patriarchy and Wifehood: A Feminist Reading of One Part Woman and Singarevva and the Palace
Marriage is a socially approved relationship between a man and a woman that binds each other into a permanent, official relation of husband and wife. In a patriarchal culture, the husbands personify dominance and liberty, whereas the wives are expected to be the epitome of fidelity, fecundity and chastity. In the Indian context, the intense devotion of wives towards their husbands defines married women as pativratas. The present study intends to analyze the various aspects that contribute to and shape the formation of the identity of a wife in a marital space through Ponna and Singarevva, the female protagonists of the novels One Part Woman and Singarevva and the Palace, respectively. The paper demonstrates how these female protagonists identity as wives gets suppressed over a period of time and how they succeed in reconstructing their identities, sailing against all odds stacked against them. The paper views these issues through the feminist theoretical lens. 2024 IUP. All Rights Reserved. -
Pattern Identification and Recommender System Based on Skin Undertone in ApparelA Deep Learning Approach
The fashion industry has undergone significant transformations driven by technological advancements, shifting consumer preferences, and the rise of e-commerce. Traditional retail models have been disrupted, giving consumers unprecedented access to information and options, making personalization crucial for success. The industry has also embraced inclusivity, offering diverse clothing lines that cater to various body types, skin tones, and cultural backgrounds. Technology plays a pivotal role in this evolution, enhancing design, manufacturing, marketing, and sustainability practices. Despite these advancements, existing recommendation systems often overlook individual characteristics such as skin undertones and pattern preferences, as well as the dynamic nature of fashion trends. This study aims to address these limitations by developing a novel AI-powered recommendation system that integrates personalized factors with real-time fashion trends. The proposed system will analyze customer data, including browsing history, social media activity, and purchases, to provide accurate and tailored fashion suggestions. By incorporating individual traits and the latest trends, the research seeks to create a more effective and responsive recommendation engine, ultimately enhancing the consumer shopping experience and helping fashion brands stay competitive in a rapidly evolving market. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.