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Social cognition, person perception, and social categorisation as building blocks of the theory of mind
Day-to-day life presents us with numerous new experiences and exposure to different people, with social functioning being a major portion of one's living days. The theory of mind, a mental map of an individual in automating behaviour, is a process and product of one's social cognitions. There are evident changes across generations in terms of these cognitions and social processing, hence showing need for understanding the theory of mind of different generations, breaking it down into its component parts. The present study was conducted to understand the components of the theory of mind in relation to social functioning. Sixty-three participants across three different generations, Generation X, Millennials, and Generation Z, were subjected to focused group discussions and the collected data analysed using a grounded theory approach. The analysis identified five components of the theory of mind applicable to all generations: social perception, social judgment, people perception, people preference, and social categorisation. 2024, IGI Global. -
An exploration of python libraries in machine learning models for data science
Python libraries are used in this chapter to create data science models. Data science is the construction of models that can predict and act on data, which is a subset of machine learning. Data science is an essential component of a number of fields because of the exponential growth of data. Python is a popular programming language for implementing machine learning models. The chapter discusses machine learning's role in data science, Python's role in this field, as well as how Python can be utilized. A breast cancer dataset is used as a data source for building machine learning models using Python libraries. Pandas, numpy, matplotlib, seaborn, scikitlearn, and tensorflow are some Python libraries discussed in this chapter, in addition to data preprocessing methods. A number of machine learning models for breast cancer treatment are discussed using this dataset and Python libraries. A discussion of machine learning's future in data science is provided at the conclusion of the chapter. Python libraries for machine learning are very useful for data scientists and researchers in general. 2023, IGI Global. All rights reserved. -
Emotional Intelligence and Cross-Cultural Adaptation of Indian Students in the Context of Interstate Education
India is known for its cultural diversity based on several factors, such as language, religion, race, and customs. In India, people used to move from one place to another for various purposes, and this was particularly the case with students in pursuit of education. In such situations, cross-cultural adaptation is one of the factors that facilitate their adjustment to new cultures and surroundings. Cross-cultural adaptation is needed when a person has to live in a different cultural setting than their own native place. Being sensitive to others emotions is essential when one lives in a new place. Emotional intelligence helps in that way and influences cross-cultural adaptation. Therefore, the present study was intended to explore the influence of emotional intelligence on cross-cultural adaptation. As many as 332 students, aged 17 to 29, who moved to another state for education, participated in the study. Emotional Intelligence Scale and Cross-Cultural Adjustment Scale were used for data collection. The components of emotional intelligence, such as self-emotional appraisal (SEA) and others emotional appraisal (OEA), were found to significantly influence expatriate adjustment. Furthermore, SEA and OEA have also influenced cultural novelty and the use of emotions (UOE). Students from rural areas were found to have more cross-cultural adaptation in the presence of their friends company compared to urban dwellers. In summary, the current study emphasizes the importance of higher emotional intelligence for better cross-cultural adaptation. 2025 Common Ground Research Networks. All rights reserved. -
Emotional Intelligence and Cross-Cultural Adaptation of Indian Students in the Context of Interstate Education
India is known for its cultural diversity based on several factors, such as language, religion, race, and customs. In India, people used to move from one place to another for various purposes, and this was particularly the case with students in pursuit of education. In such situations, cross-cultural adaptation is one of the factors that facilitate their adjustment to new cultures and surroundings. Cross-cultural adaptation is needed when a person has to live in a different cultural setting than their own native place. Being sensitive to others emotions is essential when one lives in a new place. Emotional intelligence helps in that way and influences cross-cultural adaptation. Therefore, the present study was intended to explore the influence of emotional intelligence on cross-cultural adaptation. As many as 332 students, aged 17 to 29, who moved to another state for education, participated in the study. Emotional Intelligence Scale and Cross-Cultural Adjustment Scale were used for data collection. The components of emotional intelligence, such as self-emotional appraisal (SEA) and others emotional appraisal (OEA), were found to significantly influence expatriate adjustment. Furthermore, SEA and OEA have also influenced cultural novelty and the use of emotions (UOE). Students from rural areas were found to have more cross-cultural adaptation in the presence of their friends company compared to urban dwellers. In summary, the current study emphasizes the importance of higher emotional intelligence for better cross-cultural adaptation. 2025 Common Ground Research Networks. All rights reserved. -
Hierarchical Retrieval Augmentation Generation for Multimodalized Woman's Companion
Empowering Women in society currently face many health-related problems due to the lack of health literacy. Specifically, people are not open to talking about such as sexually transmitted diseases and mental health problems, and counselling is considered taboo in most parts of the world. Some female children grow up under the care of single fathers who are sometimes unaware of the menstrual cycle and the necessary precautions. The solution presented by the research to overcome the problem is a women's health chatbot using Large Language Models (LLM). The research proposes an enhanced retrieval augmentation generation (RAG) architecture that uses the Cloudbased API to get a faster response from the LLM. The women's health chatbot secures data privacy by not saving conversations and being available for 24 hours. Addressing various women's health concerns-such as menstrual health, mental health, pregnancy, and menopause-the chatbot employs the LangChain framework for processing and indexing health-related documents into a vector store for efficient retrieval. The chatbot also features an alert mechanism to identify critical conversations, such as those involving suicidal thoughts, and sends alerts to specified contacts. This integrated approach aims to improve access to accurate health information and support women to make informed health decisions. 2025 IEEE. -
Reinforcement Learning for Quantum Phase Estimation Using Deep Q-Network
Quantum Phase Estimation(QPE) is a fundamental quantum algorithm that is used for the estimation of eigenphases of unitary operators. Its main goal is to determine the phase associated with each eigenstate. Usually, it take steps such as prepare quantum states, apply controlled unitaries, inverse quantum fourier transformation, and measurement. This study uses the OpenAI Gym framework to build a customized QPE environment. Here, the phase of a randomly generated target unitary operator is estimated using a quantum circuit. Through interaction with this environment, the DQN agent learns the best course of action to increase phase estimation accuracy. It exhibits more flexibility in noisy environments and reduces estimating mistakes. With its insights and approaches for further study in this area, this effort represents a significant advancement in the use of Deep Reinforcement Learning in quantum computing. A Comparative analysis between IBM Quantum(ibm kyiv) and the Aer Simulator on the OpenAI Gym environment using RL agents has been done. 2025 IEEE. -
Voice Assistants in Marketing: A Transformative Tool
The current world is moving in the digital platform. Transformation of technology is evident in the field of marketing, and customers are also very much interested in exploring the destructive technology in the field of marketing. Voice Assistants in Marketing are the recent tendency in the marketing field and assure an immersive experience for the customers. The study attempts to explore the role of voice assistants in marketing, its applications in various industries, the knowledge level of the respondents towards various technology interfaces in voice marketing, and the factors building the trust level of voice marketing techniques. It adopts the descriptive research design, and the required data for the study is collected using the structured questionnaire in the mail survey method from 210 respondents through purposive sampling. The data gathered was organized and analyzed using SPSS, and factor analysis was employed to reduce the dimensions of the variables. The results and the explanations are summarized at the end. Voice assistants in marketing are an emerging technique that is transforming the livelihood of the marketing phenomenon. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Evaluation of Photoswitching Properties for Hockey Stick-Shaped Mesogens Bearing Azo Benzene Moieties
In this paper, we report the photoresponsive behavior of hockey stick-shaped mesogens bearing azo wing with different terminal alkoxy chains at one terminal end. Except for the compound E16, which exhibits SmC along with nematic phase, all other mentioned compounds exhibit nematic phase alone. Influence of chain length on the photophysical properties were investigated using UV-Vis spectroscopy. It is observed here that influence of chain length is negligible on thermal back relaxation time. Spectroscopic investigation with variable intensities of UV light studies reveals that reverse cis-trans isomerization process was inversely proportional to the intensity of illuminated light. The present study also reveals that the structure-property relationship plays a dominant role on shape anisotropic structures. A spectroscopic study of the solid sample using guest-host mixture was also carried out and the compilation of results forecast these mesogens as ideal candidates for optical storage devices. Copyright 2021 Sunil, Monika, Shanker, Hegde and Prasad. -
Simulation of the Electrical Control Unit (ECU) in Automated Electric Vehicles for Reliability and Safety Using On-Board Sensors and Internet of Things
The adaptation of the energy storage system (ESS) with high power and energy density remains a difficulty for electric vehicles (EVs), despite the increasing demand they are experiencing around the world. A lightweight, compact ESS is necessary to deliver the responsive performance and driving range that modern vehicles need. When planning for widespread use of EVs, it's important to give careful attention to the factors of ESS selection, sizing, and administration. One of the most promising future mobility alternatives is the hybrid electric vehicle (HEV), which offers improved fuel economy and lower pollution levels. As a result, one of the most pressing needs is for automakers to develop new technologies for vehicle design that might help lessen emissions and boost economy. The environmental impact of emissions from light-duty cars is growing in tandem with the annual increase in the number of such vehicles on the road. The usage of other modes of transportation, such as ships and planes, is on the rise, but road transportation will always be the most common. Electronic Control Units, or ECUs, have been increasingly commonplace in cars during the past few decades. Vehicle network multicore CPU scheduling is notoriously difficult. This study's findings consist of a straightforward power-sharing control approach for the HESS based on battery and UC, with the goal of extending the battery's useful life in a city environment. 2023 IEEE. -
Is there spill-over effect among metals?
This paper was aimed at examining the existence of volatility spill-over between precious and industrial metals by estimating Multi-variate GARCH model. Metals chosen for this study were aluminium, copper, gold and silver. Data from 1st march 2004 to 31st March 2018 were used for the analysis. Significant clustering effect was found in the variance of all the metals studied. Significantly strong volatility spill-over was found between aluminium and copper when compared to other metals. It was also noted that the persistence of volatility spill-over between copper and aluminium is the least among other metals. Since there is significant spill-over between aluminium and copper, portfolio managers are advised to avoid investing in them together in their portfolios. 2019 SERSC. -
Mapping the Field of Research; Computational Intelligence and Innovation
This paper measures and maps the past studies in the field of Computational Intelligence and Innovation and further understand the application of Computational Intelligence in the field of study of innovation related to businesses. The bibliometric analysis shows the associations of various sub themes of research that was done between the period 2000 to Aug 2022. Scopus database is used to collect relevant documents of the field of study where 115 documents are sourced. The descriptive nature of the field of studies is analyzed in detail and further using VOS Viewer, the network analysis study is conducted to understand the association of authors, author country publication, themes and publication pattern, in detail. Further, an in-depth review analysis is done to understand the application of Computational Intelligence in the fields of Business Management and Social Science with aids innovation in the respective fields. Recent studies focus on machine learning, neural network, digital transformation, internet of things and other upcoming areas. The growth in these sub themes exhibit the multidisciplinary research happening in this field. This is paving way for future researchers to use the already found computing intelligence techniques to varied subject areas like medicine, management, economics etc., to foster innovation. 2022 IEEE. -
Grading of Apples Using Multiple Features
Apple is the most demanding food product that has the utmost importance when it comes to drupes. Food is the very basic necessity for our survival. Every new day brings a change, and the demand for a better quality is no greed. Quality food benefits the health of the living beings, and thus, it increases the economic growth of our country. There is a huge possibility that identifying the different varieties of apples is quite a tedious job for these traders and time consuming. Generally, identification is done manually by the very three basic senses: sight, hearing and smell. In the proposed work, an image processing technique is used to differentiate between the varieties of apples such that the manual process can be eliminated. Commercially available seven varieties of apple with various size, shape and color are considered to create database. Apples are purchased from different places across Karnataka, India to create the database. Various spatial and frequency domain based features are extracted from the images of apple. Naive Bayes, Random Forest and Multilayer perceptron (MLP) classifiers are used and got motivating results. An average accuracy of 78.47% is obtained using methods like Fourier Transform and Discrete Cosine Transform. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
In-silico analysis of the mechanism of action ofNerium oleanderbioactive compounds againstHelicoverpa armigera
Helicoverpa armigera is one of the most destructive agricultural pests worldwide, noted for its wide host range, high fecundity, and rapid development of resistance to synthetic insecticides. To address this threat, sustainable botanical alternatives are urgently needed. In this study, Nerium oleander, a toxic ornamental plant rich in secondary metabolites, was evaluated as a potential botanical insecticide through in silico assays. Methanolic extracts were subjected to phytochemical screening, confirming the presence of alkaloids, saponins, cardiac glycosides, coumarins, and terpenoids. Gas Chromatography-Mass Spectrometry (GC-MS) profiling identified 20 major compounds, including terpenoids, fatty acids, sterols, and phenolics, with 2-methoxy-4-vinylphenol (2.7 %), neophytadiene (1.7 %), and phytol (0.9 %) among the key constituents. Cytochrome P450, a central detoxification enzyme in insects, was chosen as the molecular target. Docking analysis revealed strong binding affinities, with phytol (?6.92 kcal/mol, Ki 8.12 ?M), neophytadiene (?6.43 kcal/mol, Ki 14.57 ?M), and 2-methoxy-4-vinylphenol (?5.87 kcal/mol, Ki 45.13 ?M) demonstrating significant inhibitory potential. These findings indicate that N. oleander metabolites may disrupt detoxification pathways in H. armigera, providing a mechanistic basis for their insecticidal action and supporting the plant's promise as a candidate for integrated pest management. 2025 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. LtdThis is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/ -
Antecedents of Farmers' Intentions to Adopt Drone Technology: Integrating TAM and TPB Models in Agriculture
This study examines farmers' behavioral intentions toward adopting drone technology in agriculture using a quantitative approach. Data will be collected from farmers familiar with Agri-based technologies through purposive sampling, with esponses analyzed via structural equation modeling (IBM SPSS AMOS V21). The study integrates the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) to understand key factors influencing adoption. Findings highlight that farmers' knowledge of drone operations and economic factors impact their acceptance, while regulations and perceived behavioral control contribute to reluctance. Although the study focuses on farmers, future research can explore perspectives of agricultural specialists, AgriTech start-ups, and policymakers. The insights will help stakeholders enhance the adoption, quality, and flexibility of agricultural technologies. Uniquely, this study addresses the gap in research by examining the role of regulations and behavioral control in farmers' decisions on drone adoption. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Financial Literacy and Fintech : A Double-Edged Sword for Millennial Investors Behavioral Biases
Purpose: The current research focused on investigating the moderating effect of financial literacy and financial technology on the heuristic behavior of millennials. Research Approach: The research was based on the primary data; a survey method questionnaire was prepared to collect the data needed for the present research. With the purposive sampling method, 526 responses were collected from millennial investors. The partial least square-structural equation modeling (PLS-SEM) method was applied to infer the moderating effect of financial literacy and financial technology on millennials heuristic behavior. Findings: The results showed that financial literacy significantly moderated the relationship between millennials heuristics and behavioral biases, whereas financial technology had no moderating effect. Research Implications: Millennial investors were slammed or benefited by the stock market performance. The research aimed to help them understand their behavioral changes during market anomalies. Financial advisors and regulatory bodies should consider the studys outcome as it contributes to mitigating the misconception of behavioral bias. Originality: There are numerous articles describing individual investors behavioral biases, but the current researchs uniqueness was to measure the moderating effect of financial literacy and financial technology on millennials heuristics and behavioral biases and a significant contribution to the world of research in behavioral finance. 2025, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Chemical fingerprinting of Peganum harmala seeds via UVVis, XRD, TGA, FTIR, and GC-MS techniques; In vitro assessment of cytotoxic properties
Peganum harmala L., a perennial herb traditionally valued for medicinal and ritual uses, was comprehensively profiled to elucidate its chemical composition and cytotoxic potential. Methanolic seed extracts contained diverse primary and secondary metabolites, including alkaloids, flavonoids, saponins, glycosides, steroids, proteins, and carbohydrates. Proximate analysis revealed high moisture (45.88 %) and crude fibre (18.39 %) with moderate fat (14.74 %) and protein (7.67 %) levels. Spectroscopic studies supported the presence of ?-carboline alkaloids: FTIR spectra showed characteristic functional group vibrations, UVVis displayed a strong absorption at 440 nm, and X-ray diffraction revealed semi-crystalline patterns enriched in harmine and harmaline. GCMS provided definitive chemical identification, detecting harmine (53.13 %) and harmaline (39.12 %) as major constituents. Thermal analyses (TGADTA and DTG) indicated multiphase decomposition typical of complex organic matrices. Cytotoxicity assessment using the MTT assay on L929 fibroblast cells demonstrated a dose-dependent decline in cell viability, with an LC50 of 243.9 ?g/mL, signifying moderatehigh cytotoxic potential. These findings validate the ethnomedicinal significance of P. harmala and underscore its promise for phytomedicine, nutraceutical applications, and pharmaceutical research, while highlighting the necessity of standardized and regulated use to ensure efficacy and safety. 2025 -
Interrogating Populist Tendencies within the Left Rhetoric in Kerala
After the disintegration of the Soviet Union, there has been an increasing shift from class-based politics to politics based on mobilising "people" within the left-wing political praxis and rhetoric. Such tendencies are visible even within the left rhetoric in Kerala. In the particular context of Kerala, this process is enmeshed with sub-nationalist sentiments and concerns around vikasanam (development). It is possible that this tendency can metamorphose into different directions, depending on the tactical priorities of the left in Kerala. 2022 Economic and Political Weekly. All rights reserved. -
Parametric effect of minimum quantity lubrication unit using RSM technique to improve the machinability of Inconel 718
In recent years, a rapid demand of superalloys has been seen in all industrial sectors. Few growing industries such as aerospace and biomedical industries are in need of this superalloy for fabrication of variety of products. Inconel 718 is one such superalloy which is being used for the manufacture of these productions due to high tensile strength, corrosion resistance, hardness and toughness. Due to these superior quality feature of this material friction is being seen at the tool-work interface region. This friction can be reduced by minimum quantity lubrication (MQL) unit which provides coolant at the right time. This paper discusses the minimum quantity lubrication unit used in computer numerical control (CNC) milling machine to improve the machinability of Inconel 718 by reduction of temperature at tool-work interface region and also the parametric effect using response surface methodology (RSM). Minimum quantity lubrication unit allows the cutting fluid to flow out of the nozzle at minimum speed to the cutting region which provides maximum volume of heat removal at very minimized usage of fluid. RSM technique is being implemented to improvise the experimental runs with proper way of extracting the readings and providing the observations. Instead of generating huge datas, RSM shows the accurate path of providing the data in a specified generative table. [copyright information to be updated in production process] 2022 -
Variable parametric test to improve the machinability of Inconel-718 using Tungsten Carbide tool
The Inconel-718 is a nickel based super alloy containing an old age hardening alloy of nickel-chromium as addition which provides increased strength without its decrease in ductility. It is known as a difficult to cut material due to certain properties like high thermal resistance, high creep, corrosion resistance having the capability of retaining toughness and strength at high temperatures. Inconel-718 has a large number of applications in the world of manufacturing such as aircraft gas turbines, steam turbine power plants, reheaters and reciprocating engines. Due to such superior quality functions, its machining becomes more challenging for which Tungsten Carbide is one of the tools to improve the machinability to 2.64%. In this paper, parametric tests has been carried out in CNC machining to determine the tool performance and improve the machining conditions. 2021 Elsevier Ltd. All rights reserved. -
A Study on the impact of print advertisement on the youth population
International Journal of Multidisciplinary Research Vol. 1, Issue 12 (IV) pp. 91-98, ISSN No. 2277-9302