Right to Education Sans Development: An Analysis of the Educational Status of Children Living in Slums
description: India, as a developing country, has been facing many challenges. Of them, providing free and compulsory education to all its children is one such challenge. Despite many efforts by the law makers and executives, education to all the children remains a distant dream. Poverty and accessibility are cited as two important reasons for the short fall. Comparing to their counterparts, the situation of children living in slums is more vulnerable to exploitation. Taking into account this scenario, the present study attempts to understand the various problems faced by the children living in slums in pursuing their education. The researcher is hopeful of getting some valuable insights into the issue to support suitable remedial measures to improve the educational status of children living in slums. Bangalore alone holds around 570 slums and above 5 lakhs of people living in them. The constitution already gives the right for free education, up to 10th standard which can be utilized by them, which in turn can help in free and compulsory education for everyone. If the people are educated they can improve their standard of living and so be able to create an atmosphere altogether better than the slums. The study tries to look upon the role of social and economic situation of children in their education. It also seeks to understand the reasons for the attrition rate and will strive to find out if there is any discrimination the candidate faces while pursuing education. It also focusing the the relevance of the present Right to Education Act, (2010) on the light of data collected. It also tries to find out some solution to improve educational participation of children living in the slums of Bangalore. Education is the gateway to success in life. The importance of education is not realised by all. Education has been thought to bring about a qualitative difference in the life of individuals and groups. Significance is to bring about a social change through information about the provisi…
creator: P.V Tintu
source: Department of Sociology
date: 2013

Molecular detection of Kudoa septempunctata (Myxozoa: Multivalvulida) in sea water and marine invertebrates
subject: Kudoa septempunctata; Myxozoa; Naineris laevigata; Olive flounder; Paralichthys olivaceus
description: The exportation of cultured olive flounder (Paralichthys olivaceus) in Korea has been recently decreasing due to the infections with a myxozoan parasite Kudoa septempunctata, and there is a strong demand for strict food safety management because the food poisoning associated with consumption of raw olive flounder harbouring K. septempunctata has been frequently reported in Japan. The life cycle and infection dynamics of K. septempunctata in aquatic environment are currently unknown, which hamper establishment of effective control methods. We investigated sea water and marine invertebrates collected from olive flounder farms for detecting K. septempunctata by DNA-based analysis, to elucidate infection dynamics of K. septempunctata in aquaculture farms. In addition, live marine polychaetes were collected and maintained in well plates to find any possible actinosporean state of K. septempunctata. The level of K. septempunctata DNA in rearing water fluctuated during the sampling period but the DNA was not detected in summer (June-July in farm A and August in farm B). K. septempunctata DNA was also detected in the polychaetes Naineris laevigata intestinal samples, showing decreased pattern of 40 to 0%. No actinosporean stage of K. septempunctata was observed in the polychaetes by microscopy. The absence of K. septempunctata DNA in rearing water of fish farm and the polychaetes N. laevigata intestinal samples during late spring and early summer indicate that the infection may not occur during this period. N. laevigata was suspected as the possible alternate invertebrate host of K. septempunctata, but the actinosporean stage was not found by well plate method and further studies will be necessary. This research provides important baseline information for understanding the infection dynamics of K. septempunctata in olive flounder farms and further establishment of control strategies. 2017 The Author(s).
creator: Paari A.; Jeon C.-H.; Choi H.-S.; Jung S.-H.; Kim J.-H.
source: Fisheries and Aquatic Sciences, Vol-20, No. 1
publisher: BioMed Central Ltd.
date: 2017-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 22341749
format: Online
language: English
type: Article
coverage: Paari A., Gangneung-Wonju National University, Department of Marine Bioscience, Gangneung, Gangwon, 25457, South Korea, Gangneung-Wonju National University, East Coast Life Science Institute, Gangneung, Gangwon, 25457, South Korea, Christ University, Department of Life science, Bengaluru, Karnataka, India; Jeon C.-H., Gangneung-Wonju National University, Department of Marine Bioscience, Gangneung, Gangwon, 25457, South Korea, Gangneung-Wonju National University, East Coast Life Science Institute, Gangneung, Gangwon, 25457, South Korea, Korea Fisheries Resources Agency, East Sea Life Resources Center, Uljin, 36340, South Korea; Choi H.-S., National Institute of Fisheries Science (NIFS), Pathology Division, Busan, 46041, South Korea, NIFS, Inland Aquaculture Research Center, Changwon, 51688, South Korea; Jung S.-H., National Institute of Fisheries Science (NIFS), Pathology Division, Busan, 46041, South Korea; Kim J.-H., Gangneung-Wonju National University, Department of Marine Bioscience, Gangneung, Gangwon, 25457, South Korea, Gangneung-Wonju National University, Department of Marine Bioscience, Gangneung, Gangwon, 210-702, South Korea

MXene Composite-Based Nanogenerators and Applications
description: Energy harvesting modules are becoming increasingly vital for developing autonomous, self-powered microelectronic devices. MXenes, a class of two-dimensional (2D) transition metal carbides/nitrides, have recently gained attention as promising candidates for energy applications due to their excellent electrical conductivity, large specific surface area, and tunable properties. MXene-based nanogenerators (NGs) represent a cutting-edge advancement in energy harvesting technology, harnessing the unique properties of MXenes to enhance performance. Incorporating MXenes into composite materials facilitates efficient ion/electron transport and increases the surface charge density, leading to higher output performance. Additionally, MXenes abundant functional groups and tunable surface properties enable strong interactions with polymer matrices, resulting in composites with superior mechanical strength and flexibility. This book chapter delves into the various properties of MXenes, highlighting their importance in energy harvesting technology and their inherent piezoelectric properties. It also covers using MXene-based composite materials in NG technology, focusing on MXenepolymer, MXenemetalorganic framework (MOF), and MXenecarbon composites. Additionally, the chapter discusses the applications of these composite-based NGs in various fields, including wearable technology and biomedical devices. Finally, the chapter summarizes the recent advancements in this field and future aspects in enhancing the use of MXene in energy harvesting technology. 2026 Taylor & Francis Group, LLC.
creator: Pabba, Durga Prasad; Bangolla, Hemanth Kumar; Vaddadi, Venkata Satya Chidambara Swamy; Yadav, Sandeep Kumar; Soosairaj, Amutha; Thirumurugan, Arun; Aepuru, Radhamanohar
source: Handbook of 2D Materials for a Sustainable Future: Volume One;Volume;1;pp.373-394
publisher: CRC Press
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-104043496-3; 978-100353158-6;
format: online
language: English
type: Book chapter
coverage: Pabba D.P., Departamento de Electricidad, Facultad de Ingenier, Universidad Tecnolica Metropolitana, Santiago, Chile; Bangolla H.K., Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taipei, Taiwan; Vaddadi V.S.C.S., Departamento de Mecica, Facultad de Ciencias Ficas y Matemicas, Universidad de Chile, Santiago, Chile; Yadav S.K., Department of Physics and Electronics, Christ (Deemed to be University), Bangalore, India; Soosairaj A., Department of Physics, St. Joseph's College (Autonomous), Affliated to Bharathidasan University, Tiruchirappalli, India; Thirumurugan A., Sede Vallenar, Universidad de Atacama, Vallenar, Chile; Aepuru R., Departamento de Mecica, Facultad de Ciencias Ficas y Matemicas, Universidad de Chile, Santiago, Chile

Rain of Life, Rain of Music: Music as Life Power in Indian Thought and Contemporary Musical Traditions
subject: Ce??a; drumming; K?tiy???a?; maram; mi??vu; pakh?vaj; rain; temples of Kerala
description: Conceived as a life force, rain has a significant place in Indian thought. Sanskrit and vernacular literary and religious texts, as well as visual arts, emphasise its auspiciousness and importance in human life. Additionally, through the use of poetical images and metaphors, these texts and images associate rain with music and identify thunder with drums. Through the analysis of compositions from the repertoire of different drums such as the dhrupad pakh?vaj, the mi??vu of K?tiy???a? Sanskrit theatre, and the ritual music of Brahmanical temples of Kerala, this article studies the association of drumming with rain as a symbol of life force, consciousness and enlightenment. 2022 South Asian Studies Association of Australia.
creator: Pacciolla P.
source: South Asia: Journal of South Asia Studies, Vol-45, No. 6, pp. 1054-1071.
publisher: Routledge
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 856401
format: Online
language: English
type: Article
coverage: Pacciolla P., Department of Performing Arts, Christ University, Bangalore, India

Human Consumption of Digital Synthetic Outputs: Cross Checking Real or Fake Information
description: AI-Generated content, deepfakes and synthetic media, people are increasingly wondering how they can discern the difference between genuine and fake. People may become confused, change their minds, and make unwise decisions that put their safety at danger when they see false information and manipulated pictures and videos, such AI-generated deepfakes. AI detection techniques, and teaching people how to read and write have all helped with these difficulties. Blockchain technology analyzes the digital history of anything to make sure it is authentic. Two significant steps toward making things more open are regulatory frameworks and ethical AI practices. Users should be vigilant and examine a lot of trustworthy sources, including reverse image search or deepfake detectors. The influence of incorrect information will be lessened if individuals are more informed and encouraged to utilize internet resources properly. To use another metaphor, let's make sure that people know what they're talking about when we speak about synthetic things. 2026, IGI Global Scientific Publishing. All rights reserved.
creator: Pachauri, Deepanshu; Chandra, Saurabh; Shastri, Arunima; Behera, Prangya Parimita; Singh, Bhupinder
source: Digital Synthetic Data and Outputs;pp.337-354
publisher: IGI Global
date: 01-01-2025
rights: All Open Access; Gold Open Access
relation: ISBN: 979-833732279-7; 979-833732277-3;
format: online
language: English
type: Book chapter
coverage: Pachauri D., Sharda University, India; Chandra S., Bennett University, Greater Noida, India; Shastri A., Christ University, Bangalore, India; Behera P.P., Bhubaneswar, India; Singh B., Sharda University, India

A Hybrid Deep-ensemble Decision-Support Framework for Reliable Early Breast Cancer Detection: A Cross-validated Outcome Analysis
subject: Breast cancer detection; clinical decision support; diagnostic reliability; hybrid deepensemble learning
description: OBJECTIVE The necessity to diagnose breast cancer early and correctly is the need to minimize the diagnostic uncertainty and unwarranted clinical procedures. This paper assesses the reliability of a hybrid deep-ensemble decision-support model in terms of diagnostic reliability, stability of outcome, and translational feasibility of the model via structured clinical data to detect early breast cancer. METHODS The Wisconsin Diagnostic Breast Cancer dataset which consisted of 569 cases of benign and malignant tumors was analyzed retrospectively. The framework proposed combines the deep learning of latent representations with stacked classification, ensemble-based feature selection, and stacked classification. Performance evaluation was performed based on sensitivity, specificity, accuracy, F1-score, and area under the curve (AUC) performed using stratified 10-fold cross-validation. The statistical stability across folds and the comparison with baseline models were determined with the help of non-parametric tests (p<0.05). RESULTS The model had good diagnostic performance with an accuracy of between 91.2-100 (Mean 96), Sensitivity of 76.2-100, good specificity value, and AUC 0.973-1.000. Variability in performance between folds was low, and statistically significant enhancement as compared to baseline classifiers were present. CONCLUSION The hybrid deep-ensemble model is highly diagnostic, has robust discriminative ability, and ultimately remains stable, which demonstrates the methodological robustness and diagnostic reliability of the proposed framework as a proof-of-concept decision-support model for early breast cancer detection, with potential translational relevance subject to further external clinical validation. 2026, Turkish Society for Radiation Oncology.
creator: Pachauri, Praveen; Upreti, Kamal; Kshirsagar, Pravin; Radhakrishnan, Ganeshavishwaa V.; Krishnan, Sivaneasan Bala; Kumar, Ajay; Jain, Rituraj
source: Turk Onkoloji Dergisi;Volume;41;Issue;1;pp.43-51
publisher: Istanbul Tip Fakultesi
date: 01-01-2026
rights: All Open Access; Gold Open Access
relation: ISSN: 13007467;
format: online
language: English
type: Article
coverage: Pachauri P., Department of Computer Science, Government Polytechnic Siwan, Siwan, India; Upreti K., Department of Computer Science, Christ University, Ghaziabad, India; Kshirsagar P., Department of Electronics & Telecommunication, J D College of Engineering & Management, Nagpur, India; Radhakrishnan G.V., Department of Economics and Finance, Kalinga Institute of Industrial Technology, Bhubaneswar, India; Krishnan S.B., Singapore Institute of Technology Engineering Cluster, Singapore, Singapore; Kumar A., Dev Bhoomi Uttarakhand University, Dehradun, India; Jain R., Department of Information Technology, Marwadi University, Rajkot, India

A Novel Machine Learning-Based Prediction Method for Early Detection and Diagnosis of Congenital Heart Disease Using ECG Signal Processing
subject: classification; congenital heart disease; healthcare; internet of medical things; prediction
description: Congenital heart disease (CHD) represents a multifaceted medical condition that requires early detection and diagnosis for effective management, given its diverse presentations and subtle symptoms that manifest from birth. This research article introduces a groundbreaking healthcare application, the Machine Learning-based Congenital Heart Disease Prediction Method (ML-CHDPM), tailored to address these challenges and expedite the timely identification and classification of CHD in pregnant women. The ML-CHDPM model leverages state-of-the-art machine learning techniques to categorize CHD cases, taking into account pertinent clinical and demographic factors. Trained on a comprehensive dataset, the model captures intricate patterns and relationships, resulting in precise predictions and classifications. The evaluation of the models performance encompasses sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve. Remarkably, the findings underscore the ML-CHDPMs superiority across six pivotal metrics: accuracy, precision, recall, specificity, false positive rate (FPR), and false negative rate (FNR). The method achieves an average accuracy rate of 94.28%, precision of 87.54%, recall rate of 96.25%, specificity rate of 91.74%, FPR of 8.26%, and FNR of 3.75%. These outcomes distinctly demonstrate the ML-CHDPMs effectiveness in reliably predicting and classifying CHD cases. This research marks a significant stride toward early detection and diagnosis, harnessing advanced machine learning techniques within the realm of ECG signal processing, specifically tailored to pregnant women. 2024 by the authors.
creator: Pachiyannan P.; Alsulami M.; Alsadie D.; Saudagar A.K.J.; AlKhathami M.; Poonia R.C.
source: Technologies, Vol-12, No. 1
publisher: Multidisciplinary Digital Publishing Institute (MDPI)
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 22277080
format: Online
language: English
type: Article
coverage: Pachiyannan P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Alsulami M., Department of Software Engineering, Umm Al-Qura University, Makkah, 21961, Saudi Arabia; Alsadie D., Department of Computer Science and Artificial Intelligence, Umm Al-Qura University, Makkah, 21961, Saudi Arabia; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; AlKhathami M., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Delhi-NCR, 201003, India

Sodium AlginateEngineered CaF? NPs: Surface Passivation, and Tunable Biofunctional Performance
subject: Antimicrobial activity; Bio-interactive; CaF?; CaF?SA; Fungal strains
description: The optimization of surface chemistry in nanomaterials is vital for enhancing their applicability in advanced healthcare sectors. This study focuses on synthesizing polymer-functionalized NPs (NPs) to improve structural stability and biological efficacy against a broad spectrum of pathogens. Herein, calcium fluoride (CaF?) and sodium alginate-functionalized CaF? (CaF?SA) NPs were synthesized to determine the impact of SA on physicochemical and optical properties. The synthesized NPs were extensively characterized using XRD, UV-Vis, DLS, FTIR, PL, electron microscopy (SEM/TEM), and XPS. Their enhanced performance is attributed to defect passivation, reduced crystallite size, and the formation of a homogeneous organic-inorganic interface through strong chemical interactions between Ca? sites and alginate functional groups. The CaF?SA NPs exhibited superior broad-spectrum antimicrobial activity compared to bare CaF? against S. aureus, S. pneumoniae (Gram-positive), K. pneumoniae, E. coli (Gram-negative) and C. albicans (fungal strains). The quantitative assessments via MIC, MBC, and CFU assays confirmed effective inhibition of CaF2-SA. These findings highlight defect modulation and polymer passivation as powerful strategies, suggesting CaF?SA NPs as promising candidates for advanced bio-interactive and healthcare applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026.
creator: Pachiyannan, Prabu; Thangavelu, Indumathi
source: Journal of Inorganic and Organometallic Polymers and Materials;
publisher: Springer
date: 01-01-2026
rights: Restricted Access; Hardcopy may be available in the library
relation: ISSN: 15741443;
format: online
language: English
type: Article
coverage: Pachiyannan P., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Thangavelu I., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India

Assessing the role of trade openness, FDI, and political stability on sustainable development: Evidence from developed and developing economies
description: The study tries to investigate the long run and short run relationship between trade openness (TO), political stability (PO), and FDI on sustainable development of select developed and developing nations. Time series data from 1995 to 2021 of about 25 economies-10 developed economies and 15 developing economies-was collected and analyzed using Phillips Perron Fisher panel unit root test, panel auto regressive distributed lag (PARDL) model, and panel fully modified least squares/fully modified OLS. From the result, it found that FDI and TO are positively contributing to sustainability development index (SDI) in developing countries rather than the developed countries in the long run. In addition to this, changes in the SDI score is significantly influenced by the present and past import and export activities in developed as well as developing economies in the short run. 2023, IGI Global. All rights reserved.
creator: Pachiyappan S.; Jabez J.P.; Shylaja H.N.; John Paul R.V.; Vellaiyan S.
source: Promoting Sustainable Management Through Technological Innovation, pp. 100-116.
publisher: IGI Global
date: 2023-01-01
rights: Restricted Access
relation: ISBN: 978-166849980-1; 978-166849979-5
format: Online
language: English
type: Book chapter
coverage: Pachiyappan S., CHRIST University (Deemed), India; Jabez J.P., CHRIST University (Deemed), India; Shylaja H.N., Department of Commerce, Manipal Academy of Higher Education, Manipal, India; John Paul R.V., CHRIST University (Deemed), India; Vellaiyan S., CHRIST University (Deemed), India

Exploring the Influence Dynamism of Economic Factors on Fluctuation of Exchange Rate-An Empirical Investigation for India Using ARDL Model
subject: balance of payments; exchange rate; GDP; inflation; public debt
description: The Indian Foreign Exchange Market has experienced significant changes over the past decade, due to high degree of instability of the Indian Rupee leading to its devaluation against major global currencies. Exchange rate is considered as one of crucial indicators to determine the economic growth. Volatility of exchange rate of each day is influenced by various factors such as demand and supply, Gross Domestic Product, Interest rate, employment rate, public debt, balance of payments, inflation etc. Though there are multiple causes to determine the movement of exchange rate, but still the accurate level of causation is unpredictable. Keeping this in mind, this paper tries to attempt the relationship that exists between the exchange rate and select macroeconomic factors. To analyse the extent of influence of the selected variables on the exchange rate, the research paper uses 10 years of data spanning from Jan 2013 to Nov 2022. Further, the study uses monthly data of above-mentioned variables to bring out the analysis to meet the objectives. Descriptive statistics is used to find the characteristics of the data, correlation analysis and Ordinary Least Square method is used to find the relationship and impact level select macroeconomic factors on exchange rate. Autoregressive Distributed Lag (ARDL) model is used to find if any short run and long run association exists between the variables and the exchange rate. 2023, ASERS Publishing House. All rights reserved.
creator: Pachiyappan S.; Jain A.; Raj V.J.P.; Vellaiyan S.
source: Theoretical and Practical Research in the Economic Fields, Vol-14, No. 2, pp. 258-268.
publisher: ASERS Publishing House
date: 2023-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 20687710
format: Online
language: English
type: Article
coverage: Pachiyappan S., School of Business and Management CHRIST (Deemed to be University), Bangalore, India; Jain A., School of Business and Management CHRIST (Deemed to be University), Bangalore, India; Raj V.J.P., School of Business and Management CHRIST (Deemed to be University), Bangalore, India; Vellaiyan S., School of Business and Management CHRIST (Deemed to be University), Bangalore, India

Measurement Model of CO-PO Attainment in Higher Education: A Simplified Approach
subject: Attainment levels; Course outcome; Program outcome; Program specific outcome
description: The educational system in most countries are moving toward Outcome-Based Education (OBE) which is a student-centric teaching and learning methodology. The basic idea behind the adoption of OBE model is that the graduates should possess a sound knowledge in their respective disciplines and also have global mobility and acceptance. The Outcome-Based Education (OBE) should be based on the vision and mission of the institution. The institutions should clearly spell out the learning objectives of the program and course. The Course Outcome (CO), Program Outcome (PO), Program Specific Outcome (PSO) and Program Educational Objectives (PEO) determine clearly what the students are expected to accomplish, post their course or program respectively. This study aims to provide the simplified approach on assessment, evaluation and calculating the attainment levels of students through COs and POs in a management program. To assess the CO attainment for management courses, the authors have identified the subject Entrepreneurship Development offered in the first semester from the 2018-2020 batch of 60 students from the MBA program of an autonomous institute. The Course Outcome (CO) and Program Outcome (PO) are mapped with the Continuous Internal Assessments (CIA) and Semester Exam End (SEE) and thus the attainment levels of each CO are measured. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
creator: Pachiyappan S.; Jayaraj M.M.; Subhamathi V.; Vellaiyan S.
source: Data-Driven Decision Making, pp. 185-210.
publisher: Springer Nature
date: 2024-01-01
rights: Restricted Access
relation: ISBN: 978-981972902-9; 978-981972901-2
format: Online
language: English
type: Book chapter
coverage: Pachiyappan S., Christ University, Bangalore, India; Jayaraj M.M., Christ University, Bangalore, India; Subhamathi V., Bharath (Deemed to Be University), Chennai, India; Vellaiyan S., Christ University, Bangalore, India

Attention to Economic Factors and Its Response to Foreign Portfolio Investment: An Evidence from Indian Capital Market
subject: Equity and debt market; FPI; India; Macroeconomic factors
description: Stock market consists of a variety of investors. Among these, Foreign Portfolio Investors (FPIs) is a key investment influx. These investments can change or fluctuate due to several macroeconomic factors which can cause a shift in the dynamics of the markets in India. This paper examines the factors influencing for foreign portfolio investment in long run as well as short run. The sample comprises of 120 monthly observations on Foreign Portfolio Investment (FPIs) and Macro economic variables such as Oil prices (OP), Gross Domestic Product (GDP), Interest Rate (IR), Exchange rate of Indian Rupee with USD (ER), Inflation (CPI), Nifty Index (NSEI), 10year Bond Prices (BP) and Index of Industrial production (IIP) over a period of 10years, spanning from January 2013 to November 2022. The study employed Autoregressive Distributed Lag model (ARDL) to establish the long run association with error correction models. The result indicates that there is long run association between the Foreign Portfolio Investment and macro-economic variables. Among this, NSEI, IIP and ER played a significant role to determine FPI investments in the long run, whereas in the short run, FPI was impacted by ER and NSEI significantly. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
creator: Pachiyappan S.; Kandral A.; Shylaja H.N.; Raj V J.P.; Vellayan S.
source: Studies in Systems, Decision and Control, Vol-440, pp. 659-676.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 21984182
format: Online
language: English
type: Book chapter
coverage: Pachiyappan S., School of Business and Management, CHRIST (Deemed to be University), Bannerghatta Road Campus, Bangalore, India; Kandral A., School of Business and Management, CHRIST (Deemed to be University), Bannerghatta Road Campus, Bangalore, India; Shylaja H.N., Department of Commerce, Manipal Academy of Higher Education, Manipal, India; Raj V J.P., School of Business and Management, CHRIST (Deemed to be University), Bannerghatta Road Campus, Bangalore, India; Vellayan S., School of Business and Management, CHRIST (Deemed to be University), Bannerghatta Road Campus, Bangalore, India

Autoregressive Distributed Lag Approach for Estimating the Nexus between Net Asset Value of Mutual Fund and Economic Determinants in India
subject: large cap; macroeconomic factors; mutual fund; net asset value; small cap and mid cap
description: India has seen a phenomenal growth in cumulative mutual fund investment from Rs 7.93 trillion in 2012 to Rs 40.38 trillion in 2022, which is more than a five-fold increase since last 10 years. Retail investors are now realizing the power of savings and Systematic Investment Plans (SIP) to build long term wealth. A financial literacy wave which is sweeping across India has projected mutual funds as a significant contributor and beneficiary of this phenomenon. The evolving economic landscape of India provides investors with excellent opportunities to capitalize on these fluctuations through systematic investment in safe investment vehicles like mutual funds. The market associated with mutual funds is always subjected to economic risks. The erratic fluctuations in macroeconomic variables can largely explain the Volatility in Net Asset Value (NAV) of equity oriented mutual fund schemes. With this background, this paper examines the impact of select macroeconomic variables on mutual funds performance in India. To analyse this, monthly observations of select macroeconomic variables, average NAV of large cap, mid cap, and small cap funds collected for a period of 10 years starting from January 2013 to November 2022. Descriptive statistics is used to probe the characteristics of the variable. In addition, correlation and ordinary least square method is applied to check the existing relationship and impact level of macroeconomic factors on NAV of select schemes. Lastly, short and long run relationship is analysed using Autoregressive Distributed Lag Model (ARDL). 2023, ASERS Publishing House. All rights reserved.
creator: Pachiyappan S.; Shrivastava A.; Raj V.J.P.; Vellaiyan S.
source: Theoretical and Practical Research in the Economic Fields, Vol-14, No. 1, pp. 186-201.
publisher: ASERS Publishing House
date: 2023-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 20687710
format: Online
language: English
type: Article
coverage: Pachiyappan S., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Shrivastava A., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Raj V.J.P., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Vellaiyan S., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India

Does Green Financing affect the Sustainable Economic Growth of Emerging Economies? Evidence from Panel ARDL Model
subject: Emerging Economies; Environmental Sustainability; Green Finance; Low Carbon Technology Products; Sustainable Economic Growth
description: This study examines the nexus between green finance determinants and sustainable economic growth in Brazil, India, China, and South Africa using a panel Autoregressive Distributed Lag (ARDL) approach. These rapidly developing countries face the dual challenge of maintaining economic growth while addressing environmental sustainability. The analysis focuses on five key independent variables: Comparative Advantage in Low Carbon Technology Products, Total Trade in Low Carbon Technology Products, Trade Balance in Low Carbon Technology Products, Annual CO2 Emissions, and Lack of Coping Capacity. Short-run results indicate that Total Trade in Low Carbon Technology Products negatively affects GDP, suggesting that while green trade is expanding, it currently lacks stable, revenue-generating mechanisms. Annual CO2 Emissions and Lack of Coping Capacity positively influence GDP in the short term, reflecting continued dependence on emission-intensive industries and limited infrastructure for resilience. Comparative Advantage and Trade Balance in Low Carbon Technology Products are statistically insignificant in the short run, implying delayed economic benefits. In the long run, none of the green finance indicators show a significant relationship with GDP, possibly due to the substantial upfront investments required for green projects, which delay economic returns. The study underscores the need for strategic investments in technology, infrastructure, and governance to align economic growth with long-term sustainability goals. 2025 Sathish Pachiyappan et al., published by Oikos Institut d.o.o.
creator: Pachiyappan, Sathish; Balakrishnan, Reshma; Joseph, Augustine; Patil, Anand; Arjun, B.S.; Gowri, Shankar R.
source: ECONOMICS - Innovative and Economics Research Journal;Volume;13;Issue;4;pp.39-53
publisher: Sciendo
date: 01-01-2025
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 23035005;
format: online
language: English
type: Article
coverage: Pachiyappan S., School of Business and Management, Christ University, Bengaluru, India; Balakrishnan R., School of Business and Management, Christ University, Bengaluru, India; Joseph A., Department of Economics, Christ University, Bengaluru, India; Patil A., School of Business and Management, Christ University, Bengaluru, India; Arjun B.S., School of Business and Management, Christ University, Bengaluru, India; Gowri S.R., School of Business and Management, Christ University, Bengaluru, India

Golden Insights: Analyzing the Influence of Economic Indicators on Sovereign Gold Bond Performance in India
subject: ARDL; Exchange Rate; GDP; Gold Prices; Inflation Rate; Sovereign Gold Bonds
description: India has been the leading consumers of gold with the consumption of around 774 metric tons in 2022. The demand for gold in India is majorly associated with its culture, tradition, attractiveness, and the source for financial security (GJC,n.d.)The gold market in India plays a vital role in the economy as a stable asset and hedge against inflation due to its ability to hold value over time. In order to limit the import of gold and reduce the countrys current deficit, the Indian Government introduced Sovereign Gold Bonds in 2015 as a substitute to physical gold. As SGBs export-import values are backed by Reserve Bank of India (RBI) they are considered as an inflation hedging tool. The study aims to examine the effectiveness of SGBs, in the changing economy by understanding the impact of key economic indicators Inflation Rate, Exchange Rate, Per Capita Income, Gold Prices, and GDP Growth Rateon the performance of Sovereign Gold Bonds (SGBs) in India. 36 months observations of the selected macroeconomic variables and series wise released prices are collected for a period starting from September 2021 till August 2024 for the analysis. Descriptive statistics is applied to understand the characteristics of the variables. Further, correlation and ordinary least square method is used to check the existing relationship and impact level of macroeconomic variables on SGBs. Lastly, both long run and short run relationships of these variables are analyzed using the Autoregressive Distributed Lag Model (ARDL). 2025, Iquz Galaxy Publisher. All rights reserved.
creator: Pachiyappan, Sathish; Chandrakala, G.; Mishra, Arya; Keerthana, K.; Kumari, Samiksha; Verma, Tanvi
source: International Research Journal of Multidisciplinary Scope;Volume;6;Issue;2;pp.564-576
publisher: Iquz Galaxy Publisher
date: 01-01-2025
rights: All Open Access; Gold Open Access
relation: ISSN: 2582631X;
format: online
language: English
type: Article
coverage: Pachiyappan S., School of Business and Management, Christ University, Bangalore, India; Chandrakala G., School of Commerce and Management studies, Dayananda Sagar University, Bangalore, India; Mishra A., School of Business and Management, Christ University, Bangalore, India; Keerthana K., School of Business and Management, Christ University, Bangalore, India; Kumari S., School of Business and Management, Christ University, Bangalore, India; Verma T., School of Business and Management, Christ University, Bangalore, India

The Macro Lens: Exploring the Impact of Macroeconomic Variables on Indias Small Cap, Mid Cap, and Large Cap Indices
subject: Consumer Price Index; Domestic Institutional Investment; Foreign Institutional Investment; Gold Price; Gross Domestic Product; MIFTY Largecap 50; NIFTY Midcap 50; NIFTY Smallcap 50; Purchasing Managers Index; Reverse Repo Rate
description: Subject and Purpose of Work: This study explores the intricate relationship between key macroeconomic variables and Indias equity market segments, specifically the NIFTY Small-cap, Mid-cap, and Large-cap indices. The primary objective is to evaluate how selected macroeconomic factors influence market dynamics and investor sentiment in the Indian context. Materials and Methods: The research analyses monthly data spanning five years, from January 2019 to January 2024. The macroeconomic indicators considered include Foreign Institutional Investment (FII), Domestic Institutional Investment (DII), Consumer Price Index (CPI), Purchasing Managers Index (PMI), Treasury Bill Rate, Gold Price, and Reverse Repo Rate. Statistical techniques such as the Unit Root Test, Ordinary Least Squares (OLS), and Granger Causality Test are employed to assess the short-term and long-term impacts of these variables on market indices. Results: The findings reveal that GDP, CPI, PMI, and Gold Price exhibit no statistically significant influence on the NIFTY Small-cap, Mid-cap, or Large-cap indices, aligning with certain earlier studies. However, variables like FII, DII, Treasury Bill Rate, and Reverse Repo Rate show varying degrees of influence across the indices, highlighting the complex and segmented nature of the Indian equity market. Conclusion: These insights are valuable for investors, policymakers, and financial analysts in refining investment strategies, informing policy frameworks, and enhancing market forecasting models. The study underscores the need for continuous evaluation of macroeconomic influences to better navigate market volatility and investor behaviour. 2025 Sathish Pachiyappan et al., published by John Paul II University of Applied Sciences.
creator: Pachiyappan, Sathish; Sardana, Dhruv; Joshi, Unnati; Rajesh, Gautam; Pallickal, Abel Thomas; Chellasamy, Aarthy; Nagarathinam, Aishwarya; Joshuva, Selvakumar J.
source: Economic and Regional Studies / Studia Ekonomiczne i Regionalne;Volume;18;Issue;3;pp.376-388
publisher: Sciendo
date: 01-01-2025
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 20833725;
format: online
language: English
type: Article
coverage: Pachiyappan S., School of Business and Management, Christ University, India; Sardana D., School of Business and Management, Christ University, India; Joshi U., School of Business and Management, Christ University, India; Rajesh G., School of Business and Management, Christ University, India; Pallickal A.T., School of Business and Management, Christ University, India; Chellasamy A., School of Business and Management, Christ University, India; Nagarathinam A., School of Business and Management, Christ University, India; Joshuva S.J., School of Business and Management, Christ University, India

Driving profitable business growth through economical optimization, energy management, and industrial 5.0 innovations
description: The chapter emphasizes the significance of economic optimization, energy efficiency, and Industrial 5.0 innovations in driving sustainable growth and profitability in today's business landscape. It highlights the strategic allocation of resources to maximize efficiency and minimize costs, using lean management principles, automation, and data analytics. Energy management is crucial for reducing operational costs and mitigating environmental impact, using renewable energy sources and smart technologies. Industrial 5.0, a new era of industrial transformation, combines automation, connectivity, and data exchange, with technologies like artificial intelligence, IoT, and blockchain. 2024, IGI Global.
creator: Pachuau L.; Bhaskar D.N.S.; Manimegalai V.; Varde Y.; Harshitha Y.S.; Murugan S.
source: Cases on AI Ethics in Business, pp. 252-275.
publisher: IGI Global
date: 2024-01-01
rights: Restricted Access
relation: ISBN: 979-836932644-2; 979-836932643-5
format: Online
language: English
type: Book chapter
coverage: Pachuau L., Department of Management, Pachhunga University College, Aizawl, India; Bhaskar D.N.S., Department of Humanities and Social Sciences, Vasavi College of Engineering (Autonomous), Hyderabad, India; Manimegalai V., Department of Management Studies, Nandha Engineering College (Autonomous), Erode, India; Varde Y., Department of Management, International Institute of Management Studies, Pune, India; Harshitha Y.S., Department of Business and Management, Christ University (Deemed), Bengaluru, India; Murugan S., Gona College of Technology, India

Scripts influence on reading processes and cognition: a preamble
description: [No abstract available]
creator: Padakannaya P.; Georgiou G.K.; Winskel H.
source: Journal of Cultural Cognitive Science, Vol-6, No. 2, pp. 93-96.
publisher: Springer
date: 2022-01-01
rights: All Open Access; Bronze Open Access
relation: ISSN: 25201018
format: Online
language: English
type: Editorial
coverage: Padakannaya P., Christ University, Bengaluru, India; Georgiou G.K., University of Alberta, Edmonton, Canada; Winskel H., James Cook University, Singapore, Singapore

Editorial: Methods and applications in cognitive science
subject: drift-diffusion model (DDM); embodiment and virtual reality (VR); event-related potential (ERP); evolutionary game theory; inhibitory control; methods in cognitive science; mobile brain and body imaging (MoBi); motor imagery training
description: [No abstract available]
creator: Padakannaya P.; Puvia E.; Khalil R.
source: Frontiers in Psychology, Vol-14
publisher: Frontiers Media SA
date: 2023-01-01
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 16641078
format: Online
language: English
type: Editorial
coverage: Padakannaya P., Department of Psychology, CHRIST University, Bengaluru, India; Puvia E., Department of Psychological and Social Sciences, John Cabot University, Rome, Italy; Khalil R., School of Business, Social and Decision Sciences, Constructor University, Bremen, Germany

A Multifaceted Approach at Discerning Redditors Feelings Towards ChatGPT
subject: Generative AI; Multi-Stage Sampling; Multiple Hypothesis Testing; Opinion Mining; Topic Modelling
description: Generative AI platforms like ChatGPT have leapfrogged in terms of technological advancements. Traditional methods of scrutiny are not enough for assessing their technological efficacy. Understanding public sentiment and feelings towards ChatGPT is crucial for pre-empting the technologys longevity and impact while also providing a silhouette of human psychology. Social media platforms have seen tremendous growth in recent years, resulting in a surge of user-generated content. Among these platforms, Reddit stands out as a forum for users to engage in discussions on various topics, including Generative Artificial Intelligence (GAI) and chatbots. Traditional pedagogy for social media sentiment analysis and opinion mining are time consuming and resource heavy, while lacking representation. This paper provides a novice multifrontal approach that utilises and integrates various techniques for better results. The data collection and preparation are done through the Reddit API in tandem with multi-stage weighted and stratified sampling. NLP (Natural Language processing) techniques encompassing LDA (Latent Dirichlet Allocation), Topic modelling, STM (Structured Topic Modelling), sentiment analysis and emotional analysis using RoBERTa are deployed for opinion mining. To verify, substantiate and scrutinise all variables in the dataset, multiple hypothesises are tested using ANOVA, T-tests, KruskalWallis test, Chi-Square Test and MannWhitney U test. The study provides a novel contribution to the growing literature on social media sentiment analysis and has significant new implications for discerning user experience and engagement with AI chatbots like ChatGPT. 2024 Padarha et al., licensed to EAI.
creator: Padarha S.; Vijaylakshmi S.
source: EAI Endorsed Transactions on Internet of Things, Vol-10
publisher: European Alliance for Innovation
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 24141399
format: Online
language: English
type: Article
coverage: Padarha S., CHRIST (Deemed to be University), Pune, Lavas, India; Vijaylakshmi S., CHRIST (Deemed to be University), Pune, Lavas, India