Aspect based sentiment analysis using a novel ensemble deep network
subject: Aspect-based sentiment analysis; Ensemble deep network; Graph neural network; Sentiment analysis
description: Aspect-based sentiment analysis (ABSA) is a fine-grained task in natural language processing, which aims to predict the sentiment polarity of several parts of a sentence or document. The essential aspect of sentiment polarity and global context have deep relationships that have not received enough attention. This research work design and develops a novel ensemble deep network (EDN) which comprises the various network and integrated to enhance the model performance. In the proposed work the words of the input sentence are converted into word vectors using the optimised bidirectional encoder representations from transformers (BERT) model and an optimised BERT-graph neural networks (GNN) model with convolutions is built that analyses the ABSA of the input sentence. The optimised GNN model with convolutions for context-based word representations is developed for the word-vector embedding. We propose a novel EDN for an ABSA model for optimised BERT over GNN with convolutions. The proposed ensemble deep network proposed system (EDN-PS) is evaluated with various existing techniques and results are plotted in terms of metrics for accuracy and F1-score, concluding that the proposed EDN-PS ensures better performance in comparison with the existing model. 2024, Institute of Advanced Engineering and Science. All rights reserved.
creator: Rajan A.; Manur M.
source: IAES International Journal of Artificial Intelligence, Vol-13, No. 2, pp. 1668-1678.
publisher: Institute of Advanced Engineering and Science
date: 2024-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 20894872
format: Online
language: English
type: Article
coverage: Rajan A., Department of Computer Science and Engineering, Christ University, Bangalore, India; Manur M., Department of Computer Science and Engineering, Christ University, Bangalore, India

Mahe's Memorialisation of French Colonialism
description: [No abstract available]
creator: Vijay S.; Anupama Nayar C.V.
source: Economic and Political Weekly, Vol-59, No. 20, pp. 72-73.
publisher: Economic and Political Weekly
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 129976
format: Online
language: English
type: Article
coverage: Vijay S., The Department of English and Cultural Studies, CHRIST (Deemed to be University), Bengaluru, India; Anupama Nayar C.V., The Department of English and Cultural Studies, CHRIST (Deemed to be University), Bengaluru, India

Biotechnological advancements in microplastics degradation in drinking water: Current insights and Future perspectives
subject: Analytical techniques; Biodegradation; Drinking water; Enzymes; Microplastics (MPs); Toxicity
description: Microplastics (MPs) have emerged as persistent toxicants in the recent decade. MPs are reported to present in different samples such as soil, water, wastewater, and human samples including placenta, urine etc. Recent studies have reported its presence in drinking water. MPs presence in the drinking water is of concern to the research because MPs are associated with several toxicities in animal models including human. The presented review is focused on understanding MPs abundance, sources, detection, analysis, and biotechnological approaches for its degradation. The paper discusses MPs sources, distribution, and transport in drinking water. In addition, it discusses the MPs identification in drinking water, and advances in biotechnological, metagenomics, system, and synthetic biology approaches for MPs degradation. Moreover, it discusses critically the major challenges associated with the MPs degradation in drinking water. Heterogeneity in the MPs size and shape makes it its identification difficult in the drinking water. Most of the methods available for MPs analysis are based on the dried samples analysis. Development of MPs in liquid samples may bring a breakthrough in the research. 2024 The Authors
creator: Singhal B.; Kumar S.; Mehtab S.; Aggarwal U.; Kumar V.; Umesh M.; Chakraborty P.
source: Case Studies in Chemical and Environmental Engineering, Vol-9
publisher: Elsevier Ltd
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 26660164
format: Online
language: English
type: Article
coverage: Singhal B., School of Biotechnology, Gautam Buddha University, U.P, Greater Noida, India; Kumar S., School of Biotechnology, Gautam Buddha University, U.P, Greater Noida, India; Mehtab S., Department of Chemistry, G.B. Pant University of Agriculture & Technology, Pantnagar, Uttarakhand, 263145, India; Aggarwal U., Patanjali Research Institute, (Uttarakhand), Haridwar, India; Kumar V., Bioconversion and Tissue Engineering (BITE) Laboratory, Department of Community Medicine, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai, India; Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Chakraborty P., School of Allied Healthcare and Sciences, JAIN (Deemed to be University), Whitefield, Karnataka, Bangalore, 560066, India

An Empirical Framework Using Weighted Feed Forward Neural Network for Supply Chain Resilience (SCR) Strategy Selection
subject: Artificial Intelligence (AI); Fuzzy Programming and Multi-Level Decision Support (MLDS) framework; Supply Chain Management (SCM); Supply Chain Resilience (SCR)
description: Artificial intelligence (AI)-based systems are normally data driven applications, where the model is trained to think on its own based on the external circumstances. The power of AI has reached every facet of business and common life and is even being largely explored to be adopted in life sciences and medical domains. It supports the human in decision-making through the cognitive utilities which arises out of self-learning capabilities of a model. With the exponential growth of data, supply chain management and analytics have attracted a large community of researchers to build intelligent systems which can lead to re-invention of data-driven decision systems powered by AI. Systems and literature of the past shows that AI-based technologies are promising in intelligent supply chain management (SCM) and building resilient SCMs. There is a gap in literature which addresses on the framework for decision support systems in SCM and application of AI methods for building a robust supply chain resilience (SCR) leading to more exploration on the topic. In this paper, a decision framework is proposed by incorporating fuzzy logic and recurrent neural networks (RNN) for disclosing the patterns of various AI-enabled techniques for SCRs. The proposed analysis involved data from leading literatures to determine the most adoptable and significant applications of AI in SCRs. The analysis shows that techniques such as fuzzy programing, network based algorithms, and genetic algorithms have large impact on building SCRs. The results help in decision-making by exhibiting an integrated framework which can help the AI practitioners for developing SCRs. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.
creator: Rajagopal M.; Sivasakthivel R.
source: Operations Research Forum, Vol-5, No. 2
publisher: Springer International Publishing
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 26622556
format: Online
language: English
type: Article
coverage: Rajagopal M., School of Business and Management, Lean Operations and Systems, CHRIST (Deemed to be University), Bangalore, India; Sivasakthivel R., Department of Computer Science, School of Sciences, CHRIST (Deemed to be University), Bangalore, India

Museum visit intervention in K-12 education: a scoping review
subject: K-12 education; Learning outcome; Museum visit; Scoping review; Social outcome
description: This scoping review aims to provide an overview of empirical studies on worldwide museum visit intervention in K-12 education. The study employed Mendeley citation software to identify the articles in the database. A metaanalysis PRISMA statement is used for reporting the items. Out of 135 possibly rich articles, the present study reviewed 18 studies that met the inclusion criteria and were subjected to descriptive and content analyses published between 2017 and 2021. Most of the studies are experimental and from primary school contexts. It is revealed that science is the subject matter context majority of the studies, but philosophy, disaster management, language, and environmental science are also represented. The content analysis resulted in the following learning and social outcomes. It states that social outcome is explored chiefly, followed by learning outcome. The findings indicate that museum visit intervention positively impacts students learning and social outcome. The review also identifies the need for further research on museum visit intervention in the Asia Pacific region. 2024, Institute of Advanced Engineering and Science. All rights reserved.
creator: Sahani C.; Prakasha G.S.
source: International Journal of Evaluation and Research in Education , Vol-13, No. 3, pp. 1375-1383.
publisher: Institute of Advanced Engineering and Science
date: 2024-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 22528822
format: Online
language: English
type: Article
coverage: Sahani C., Department of Education, Faculty of Education, Christ University, Bangalore, India; Prakasha G.S., Department of Education, Faculty of Education, Christ University, Bangalore, India

The development and primary validation of employee green behavior scale
subject: Confirmatory factor analysis; Employee green behavior; Organization; Principal component analysis; Workplace
description: Purpose: The increasing adverse impact of human behavior toward the environment has brought in changes in research focus on environmental behavior toward the workplace. Because the employee spends one-third of his day in his workplace, the initiatives taken by the employee also have an impact on the companys environmental stance. Therefore, the researchers gradually focus on employee green behavior (EGB) and its measurement. The study aims to devise a tool for measuring EGB. Design/methodology/approach: Two studies were carried out using the survey method using the purposive sampling technique. The data were collected (Studies 1 and 2) from managers and supervisors working in manufacturing companies located in Kolkata, India. Findings: The first study was done to extract the principal factors using an initial 30 items (N = 220). The result of the principal component analysis shows the emergence of three factors spread over 20 items with loadings above 0.40. The 20-item scale was again administered on managers and supervisors (N = 243). The second study was carried out to examine the convergent and discriminant validity as well as stability of the tool through confirmatory factor analysis (CFA) (N = 243). The result of CFA showed the presence of 16 items spread through three factors: practice and policy, digital use and recycle and reuse. Multiple fit indices support a three-factor model of the 16-item EGB scale. Research limitations/implications: The scale would be a good measure of EGB and can be used for further research. The EGB scale is a composite scale containing three major dimensions that can be used as a complete measure of EGB. Originality/value: The present research aims to fill the current gap by building a comprehensive tool for measuring EGB. The present scale has also addressed the shortcoming of the previous scale and tried to include varied proenvironmental behaviors exhibited in the workplace. 2024, Emerald Publishing Limited.
creator: Roy S.; Sia S.K.
source: Journal of Asia Business Studies, Vol-18, No. 3, pp. 784-800.
publisher: Emerald Publishing
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 15587894
format: Online
language: English
type: Article
coverage: Roy S., Department of Psychology, Christ University, Bangalore, India; Sia S.K., Department of Applied Psychology, Pondicherry University, Pondicherry, India

Metal and Ligand-Free Approach Towards the Efficient One-Pot Synthesis of Dipyridopyrimidinimine Derivatives
subject: base catalyzed; double C?N bond formation; intermolecular annulation; metal free; stable imine; tandem reactions
description: We report a facile, expeditious, user-friendly, and convenient metal-free synthesis employing base catalysis in a one-pot procedure to construct 11H-dipyrido[1,2-a : 3?,2?-d]pyrimidin-11-imine derivatives. This protocol involves a domino process leading to the formation of double C?N bonds utilising KOtBu as the base and DMAc as the superior solvent at 25 C for 2 h. The versatility of this methodology was demonstrated by its successful application to substrates with both electron-withdrawing and electron-donating functional groups, yielding novel functionalized stable 11H-dipyrido[1,2-a : 3?,2?-d]pyrimidin-11-imine derivatives in good to excellent yields. Additionally, we have discussed a plausible reaction pathway for the synthesis. 2024 Wiley-VCH GmbH.
creator: Kommuri V.C.; Vijayan A.
source: ChemistrySelect, Vol-9, No. 19
publisher: John Wiley and Sons Inc
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 23656549
format: Online
language: English
type: Article
coverage: Kommuri V.C., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, India; Vijayan A., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, India

On bivariate Teissier model using Copula: dependence properties, and case studies
subject: Applications; Bayesian; Bivariate continuous model; Copula; Dependence; FGM; Inference; MCMC; Modelling; Teissier
description: To precisely represent bivariate continuous variables, this work presents an innovative approach that emphasizes the interdependencies between the variables. The technique is based on the Teissier model and the Farlie-Gumbel-Morgenstern (FGM) copula and seeks to create a complete framework that captures every aspect of associated occurrences. The work addresses data variability by utilizing the oscillatory properties of the FGM copula and the flexibility of the Teissier model. Both theoretical formulation and empirical realization are included in the evolution, which explains the joint cumulative distribution function F(z1,z2), the marginals F(z1) and F(z2), and the probability density function (PDF) f(z1,z2). The novel modeling of bivariate lifetime phenomena that combines the adaptive properties of the Teissier model with the oscillatory characteristics of the FGM copula represents the contribution. The study emphasizes the effectiveness of the strategy in controlling interdependencies while advancing academic knowledge and practical application in bivariate modelling. In parameter estimation, maximum likelihood and Bayesian paradigms are employed through the use of the Markov Chain Monte Carlo (MCMC). Theorized models are examined closely using rigorous model comparison techniques. The relevance of modern model paradigms is demonstrated by empirical findings from the Burr dataset. The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024.
creator: Tyagi S.
source: International Journal of System Assurance Engineering and Management, Vol-15, No. 6, pp. 2483-2499.
publisher: Springer
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 9756809
format: Online
language: English
type: Article
coverage: Tyagi S., Department of Statistics and Data Science, Christ Deemed to be University, Bangalore, India

Aspect based sentiment analysis using fine-tuned BERT model with deep context features
subject: BERT; DC-BERT; Interaction layer; NLP; Sentiment analysis
description: Sentiment analysis is the task of analysing, processing, inferencing and concluding the subjective texts along with sentiment. Considering the application of sentiment analysis, it is categorized into document-level, sentence-level and aspect level. In past, several researches have achieved solutions through the bidirectional encoder representations from transformers (BERT) model, however, the existing model does not understand the context of the aspect in deep, which leads to low metrics. This research work leads to the study of the aspect-based sentiment analysis presented by deep context bidirectional encoder representations from transformers (DC-BERT), main aim of the DC-BERT model is to improvise the context understating for aspects to enhance the metrics. DC-BERT model comprises fine-tuned BERT model along with a deep context features layer, which enables the model to understand the context of targeted aspects deeply. A customized feature layer is introduced to extract two distinctive features, later both features are integrated through the interaction layer. DC-BERT mode is evaluated considering the review dataset of laptops and restaurants from SemEval 2014 task 4, evaluation is carried out considering the different metrics. In comparison with the other model, DC-BERT achieves an accuracy of 84.48% and 92.86% for laptop and restaurant datasets respectively. 2024, Institute of Advanced Engineering and Science. All rights reserved.
creator: Rajan A.; Manur M.
source: IAES International Journal of Artificial Intelligence, Vol-13, No. 2, pp. 1250-1261.
publisher: Institute of Advanced Engineering and Science
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 20894872
format: Online
language: English
type: Article
coverage: Rajan A., Department of CSE, CHRIST (Deemed to be University), Bangalore, India; Manur M., Department of CSE, CHRIST (Deemed to be University), Bangalore, India

Impact of sentimental factors on stock portfolio returns an empirical analysis
subject: Consumer sentimental factors; FF factors; Market sentimental factors; Portfolio returns; Stock market sentimental factors
description: This study aims to introduce an integrated model for understanding the influence of various sentimental factors in conjunction with macroeconomic factors on portfolio returns across ten industry sectors within the US market. These sentimental factors are categorized into market-wide, consumer, and individual stock market factors to assess their impact on industry portfolio returns. Employing the Autoregressive Distributed Lag (ARDL) model, the study evaluates the effects of macroeconomic and sentimental factors on stock market portfolio returns. The findings reveal a negative relationship between short-term interest rates and portfolio returns in specific industry sectors like manufacturing, telecom, and wholesale/retail. The study finds a positive relationship between the Hi-tech sector's risk spread and portfolio returns. Market sentimental factors positively influence portfolio returns of durable, non-durable, utility, and other sectors. Individual sentimental factors negatively impact portfolio returns in hi-tech, utility, durable, energy, and other sectors. The stock market-related individual, sentimental factor of the number of IPOs has a positive impact on portfolio returns in the energy sector and a negative impact on portfolio returns in other sectors. Consumer sentimental factors are significant positive determinants for portfolio returns in durable, energy, telecom, health, and other sectors. Discounts on closed-end funds may provide vital fundamental information regarding lower future earnings for stocks in the durable and energy sectors. The study provides valuable insights for investors to optimize their portfolio strategies in response to macroeconomic and sentimental factors within specific industry sectors. 2024 The Authors
creator: Kumar R.; K S S.
source: Heliyon, Vol-10, No. 9
publisher: Elsevier Ltd
date: 2024-01-01
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 24058440
format: Online
language: English
type: Article
coverage: Kumar R., Institute of Management Technology, Dubai, United Arab Emirates; K S S., School of Business and Management, Christ University, India

Still Waters Run Deep: Groundwater Contamination and Education Outcomes in India
subject: Education; Health; India; Water pollution
description: We investigate the impact of groundwater contamination on educational outcomes in India. Our study leverages variations in the geographical coverage and timing of construction of safe government piped water schemes to identify the effects of exposure to contaminants. Using self-collected survey data from public schools in Assam, one of the most groundwater-contaminated regions in India, we find that prolonged exposure to unsafe groundwater is associated with increased school absenteeism, grade retention, and decreased test scores and Cumulative Grade Point Average (CGPA). To complement our findings and to study the effect of one such contaminant, arsenic, we use a large nationally representative household survey. Using variations in soil textures across districts as an instrument for arsenic concentration levels we find that exposure to arsenic beyond safe threshold levels is negatively associated with school attendance. 2024 Elsevier Ltd
creator: Aggarwal K.; Barua R.; Vidal-Fernandez M.
source: Economics of Education Review, Vol-100
publisher: Elsevier Ltd
date: 2024-01-01
rights: All Open Access; Green Open Access; Hybrid Gold Open Access
relation: ISSN: 2727757
format: Online
language: English
type: Article
coverage: Aggarwal K., Christ University, India; Barua R., Centre for International Trade and Development (CITD), Jawaharlal Nehru University (JNU), India; Vidal-Fernandez M., The University of Sydney, Australia

Deep learning based model for computing percentage of fake in user reviews using topic modelling techniques
subject: Challenging task; Deep learning; Exhaustivity; Fake review detection; Topic Modelling
description: Sentiment analysis plays a vital role in real time environment for knowing the history of a product or any other specific entity. Due to large number of users in the www, chances are there that many fake users may upload the fake reviews to damage the business for the sake of money. Identifying the fake reviews or percentage of fake content in the review is yet a challenging task. In this paper, an attempt has been made to find the percentage of fake in the review data. Two methodologies are combined to address this issue. Concept of spelling checking, topic modelling and deep learning for context extraction is extensively used to build the effective model. Proposed technique is exhaustively checked for efficiency with many trails of experiments. Also, the training and testing samples were shuffled for experimentation. The results of the models show its goodness. The details of the results can be found at experiments section. 2024 The Author(s)
creator: K S S.; Danti A.; Snehitha Reddy T.; Nath V.
source: e-Prime - Advances in Electrical Engineering, Electronics and Energy, Vol-8
publisher: Elsevier Ltd
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 27726711
format: Online
language: English
type: Article
coverage: K S S., Dept of MCA, PESITM, SHIMOGA, India; Danti A., Christ university, Bangalore, India; Snehitha Reddy T., Research Scholar Department of Electronics & Communication Engineering Birla Institute of Technology, JH, Mesra Ranchi, 835215, India; Nath V., VLSI Design Group, Department of ECE, B.I.T. Mesra, (JH), Ranchi, 835215, India

Development and Psychometric Validation of Teachers Receptivity to Change Scale
subject: Factor analysis; Psychometric properties; Receptivity to change; Tool construction
description: In this article, we report the development and psychometric validation of the Teachers Receptivity to Change Scale (TRCS). The sample included secondary school teachers of Kerala, India. In India, the teachers receptivity to change becomes important in the context of the newly drafted National Education Policy, (2020) which places teachers at the center of the reforms. The present study proceeded through five phases namely item analysis, exploratory factor analysis, confirmatory factor analysis, validation of the scale, and testretest reliability. The development of the tool started with the generation of a pool of items followed by item analysis. The exploratory factor analysis extracted four factors and the confirmatory factor analysis confirmed the four-factors namely individual, organizational, educational, and bridging factors. The structural equation modelling established the four-correlated factor construct of teachers receptivity to change and an additive model indexing teachers receptivity to change as the sum of the four factors. Both the model fit indices indicated an excellent fit. The validity of the TRCS established by correlating the teachers receptivity to change and its factors with multidimensional work motivation scale and engaged teachers scale indicated a moderate correlation. The final 28 item TRCS showed adequate internal consistency (Cronbachs alpha = 0.897) and discriminant validity. The test re-test reliability analysis (Cronbachs alpha = 0.884) confirmed the temporal stability of the scale. The findings recommend a psychometric reliable and valid scale for assessing teachers receptivity to change with implications for teachers, researchers, and policy makers. De La Salle University 2023.
creator: John T.E.; Thomas B.; Sudhesh N.T.; Rajan S.K.
source: Asia-Pacific Education Researcher, Vol-33, No. 3, pp. 495-507.
publisher: Springer
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 1195646
format: Online
language: English
type: Article
coverage: John T.E., School of Education, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Thomas B., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Sudhesh N.T., Department of Psychology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Rajan S.K., Department of Psychology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India

A comprehensive investigation of ethyl 2-(3-methoxybenzyl) acrylate substituted pyrazolone analogue: Synthesis, computational and biological studies
subject: HOMO-LUMO; In-vitro and in-silico biological activity; MESP; NBO; Pyrazolones
description: In this study, we successfully synthesized ethyl 2-(3-methoxybenzyl) acrylate-substituted pyrazolones derivative (EMH) through the reaction of Baylis-Hillman acetate with pyrazolones. We conducted comprehensive screenings to evaluate its invitro antifungal, antibacterial, and antioxidant properties. The molecule demonstrated notable in vitro antifungal and antibacterial activities attributed to the presence of anisole, enhancing absorption rates through increased lipid solubility and improving pharmacological effects. Structure-activity relationship (SAR) studies supported these findings. Additionally, insilico studies delved into the molecular interactions of the synthesized molecule with DNA Gyrase, Lanosterol 14 alpha demethylase, and KEAP1-NRF2 proteins, revealing strong binding interactions at specific sites. Furthermore, we employed ab-initio techniques to theoretically estimate the photophysical properties of the compounds. Ground state optimization, dipole moment, and HOMO-LUMO energy levels were calculated using the DFT-B3LYP-6-31G(d) basis set. The theoretical HOMO-LUMO values indicated high electronegativity and electrophilicity index. NBO analysis confirmed the presence of intermolecular ONH hydrogen bonds resulting from the interaction of the lone pair of oxygen with the anti-bonding orbital. Overall, our results suggest that anisole-substituted pyrazolones derivatives exhibit promising applications in both photophysical and biological domains. 2024
creator: Palled R.; Srinivasan V.; Al-Asbahi B.A.; Naik L.; S G A.; Eelager M.P.; Sidarai A.; Madar M.
source: Chemical Physics Impact, Vol-8
publisher: Elsevier B.V.
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 26670224
format: Online
language: English
type: Article
coverage: Palled R., Department of Physics, V.M.K. S.R. Vastrad Arts, Science &V.S. Bellihal Commerce College, Karnataka, Hungund, 587118, India; Srinivasan V., Department of Chemistry, Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology, Avadi, Tamil Nadu, Chennai, 600 062, India; Al-Asbahi B.A., Department of Physics & Astronomy, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Naik L., Department of Physics and Electronics, CHRIST University, Central Campus, Karnataka, Bengaluru, 560029, India; S G A., Department of Physics, V.M.K. S.R. Vastrad Arts, Science &V.S. Bellihal Commerce College, Karnataka, Hungund, 587118, India; Eelager M.P., Department of Chemistry, Karnatak Science College, Karnataka, Dharwad, 580001, India; Sidarai A., Department of Physics, Karnatak University, Karnataka, Dharwad, 580003, India; Madar M., Department of Physics, V.M.K. S.R. Vastrad Arts, Science &V.S. Bellihal Commerce College, Karnataka, Hungund, 587118, India, Department of Physics, Karnatak University, Karnataka, Dharwad, 580003, India

Building a resilient future: collaborative sustainability regulation
subject: Advanced economies; Developing economies; Environmental; Social and Governance (ESG); Sustainability Reporting; Sustainable Development Goals
description: The challenge of sustainability lies in achieving a balance between satisfying present needs and protecting resources for future generations with an emphasis on its three pillars - environmental, social and governance. This study explored sustainable development encompassing environmental, social and governance aspects along with sustainability reporting through various sustainability frameworks. A systematic review of literature for the period 2010-23 on major worldwide sustainability frameworks was conducted, by offering insights into enhancing reporting mechanisms for a sustainable future. Secondary data related to sustainability reports were obtained from the Sustainability Accounting Standards Board and International Integrated Reporting Council, which helped in examining sector and year variations across countries. The results reflected that mandatory sustainability disclosures help to meet the United Nations Sustainable Development Goals and global sustainability frameworks help to set standards, disseminate information and promote transparency. Collaboration of investment, company action and sustainability organizations can lead to a sustainable global economy. The adoption of sustainability reporting can help organizations by fostering a proper understanding of sustainability practices, improving transparency and identifying potential business opportunities in sectors with lower sustainability. The paper provided insights into sustainability reporting published across various countries in both advanced as well as emerging and developing economies. The analysis showed which sectors and time periods have had the most sustainability reports and which areas needed to be targeted for action to advance sustainable development. 2024 The Author(s). Published by Oxford University Press on behalf of National Institute of Clean-and-Low-Carbon Energy.
creator: Job J.S.; Khanna S.
source: Clean Energy, Vol-8, No. 3, pp. 223-237.
publisher: Oxford University Press
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 25154230
format: Online
language: English
type: Article
coverage: Job J.S., Christ University, Bangalore, India; Khanna S., School of Business and Management Christ University, Bangalore, India

Assessment of the strength of grignard reagent for the synthesis of secondary and tertiary alcohols of terpenes using metal plate flow reactor
subject: Allyl magnesium chloride; Carbonyl compounds; Flow process; Grignard reagent; Metal plate reactor; Terpene alcohols
description: The secondary and tertiary alcohols of terpenes were synthesized from aldehydes, and ketones using allyl magnesium chloride by the continuous metal flow reactor method. The flow process was conducted using metal plate reactors of 10 ml capacity in the presence of solvent mixtures, instead of large amounts of pure solvent like tetrahydrofuran. The products were isolated, and confirmed using gas chromatography and Nuclear magnetic resonance techniques respectively. Subsequently, the optimization studies were conducted to obtain mild, and economical reaction conditions, by varying the amount of allyl magnesium chloride, temperature, pressure, retention time, and flow rates. A comparison between batch processes and flow processes proved the advantages of the flow process in terms of reproducibility and product yield without the requirement of excess reagents compared to the batch process. The product yield was found to be excellent (6097 %) and reproducible at (150) gram scale through flow process. The scope of the reaction was studied by synthesizing terpene alcohols using different carbonyl compounds at optimized reaction conditions, which resulted in high product yield. This research addresses a crucial gap in terpene alcohol synthesis, offering a scalable and environmentally friendly approach with broad applicability. 2024
creator: Kopparapu I.; Chidambaram R.R.; Binish C.J.; Vijayasankar A.V.; Chundattu S.J.; Cheedarala R.K.
source: Results in Engineering, Vol-22
publisher: Elsevier B.V.
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 25901230
format: Online
language: English
type: Article
coverage: Kopparapu I., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India; Chidambaram R.R., Supramolecular and Organometallic Chemistry Lab, Department of Inorganic Chemistry, School of Chemistry, Madurai Kamaraj University, Tamil Nadu, Madurai, 625021, India; Binish C.J., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India; Vijayasankar A.V., Department of Science and Humanities, CHRIST (Deemed to be University), Bengaluru, 560074, India; Chundattu S.J., Department of Science and Humanities, CHRIST (Deemed to be University), Bengaluru, 560074, India; Cheedarala R.K., Research Institute of Mechatronics, Department of Mechanical Engineering, Changwon National University, Changwon City, South Korea

Cocos nucifera L.-derived porous carbon nanospheres/ZnO composites for energy harvesting and antibacterial applications
subject: Antibacterial activity; Carbon nanomaterials; Counter electrode; DSSC; Green synthesis
description: Carbon nanomaterials (CNMs) have been the subject of extensive research for their potential applications in various fields, including photovoltaics and medicine. In recent years, researchers have focused their attention on CNMs as their high electrical conductivity, low cost, and large surface area are promising in replacing traditional platinum-based counter electrodes in dye-sensitized solar cells (DSSC). In addition to their electrical properties, CNMs have also displayed antibacterial activity, making them an attractive option for medical applications. The combination of CNMs with metal oxides to form composite materials represents a promising approach with significant potential in various fields, including energy and biology. Here, we introduce porous carbon nanospheres (PCNS) derived from Cocos nucifera L. and its ZnO composite (PCNS/ZnO) as an alternative material, which opens up new research insights for platinum-free counter electrodes. Bifacial DSSCs produced using PCNS-based counter electrodes achieved power conversion efficiencies (PCE) of 3.98% and 2.02% for front and rear illumination, respectively. However, with PCNS/ZnO composite-based counter electrodes, the efficiency of the device increased significantly, producing approximately 5.18% and 4.26% for front and rear illumination, respectively. Moreover, these CNMs have shown potential as antibacterial agents. Compared to PCNS, PCNS/ZnO composites exhibited slightly superior antibacterial activity against tested bacterial strains, including gram-positive Bacillus cereus (B. cereus) and Staphylococcus aureus (S. aureus), and gram-negative Vibrio harveyi (V. harveyi) and Escherichia coli (E. coli) with MIC values of 125, 250, 125, and 62.5g/ml, respectively. It is plausible that the outcomes observed were influenced by the synergistic effects of the composite material. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to Korean Carbon Society 2024.
creator: Varghese M.; Ninan G.G.; Jayaram S.; Sarojini S.; Balachandran M.
source: Carbon Letters, Vol-34, No. 5, pp. 1399-1411.
publisher: Springer
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 19764251
format: Online
language: English
type: Article
coverage: Varghese M., Department of Physics and Electronics, Christ University, Karnataka, Bengaluru, 560029, India; Ninan G.G., Department of Physics and Electronics, Christ University, Karnataka, Bengaluru, 560029, India; Jayaram S., Department of Life Sciences, Christ University, Karnataka, Bengaluru, 560029, India; Sarojini S., Department of Life Sciences, Christ University, Karnataka, Bengaluru, 560029, India; Balachandran M., Department of Physics and Electronics, Christ University, Karnataka, Bengaluru, 560029, India

Space taxonomy: Need for a progressive tax regime
subject: Commercialization; Space economy; Tax treatment
description: Konstantin Tsiolkovsky famously stated that while the Earth serves as the birthplace of humanity, it is not a place where mankind can indefinitely remain. Perhaps during that period, the prospect of exploring the mysteries of outer space appeared to be an unattainable aspiration. However, in the present day, there are no longer any limitations, not even the sky, since human ingenuity has facilitated access to outer space for humanity. This access is not just for the purposes of research and exploration but also for economic endeavours. Until now, the commercial utilisation of outer space has advanced at a very sluggish rate. However, firms including SpaceX, Orion Span, Virgin Galactic, and Blue Origin have achieved significant advancements in the growth of the space industry. The revenue generated by various space-related endeavours has experienced a significant 73% increase over the last ten years. The global space economy, estimated to be valued at USD one trillion in the coming years, is primarily driven by commercial activities. This presents a formidable challenge to the existing national and international taxation systems. Similar to the open seas, space is also considered res communis omnium, meaning it belongs to the entire community, and presents comparable taxing challenges with potentially uncertain solutions. The three fundamental elements of every taxation regulation, such as the Organisation for Economic Co-operation and Development or the United Nations Model Double Taxation Convention, are the taxpayer's place of residence, the origin of their income, and the methods by which they generate their money. The current tax system does not have the necessary concepts and provisions to adapt to the rapid advancements in commercial space technology. This paper examines the legal issues surrounding commercial activities conducted in space, including the nature and handling of the income generated in various legal systems. It also addresses concerns such as ta…
creator: Bhatnagar K.; Dey A.
source: Acta Astronautica, Vol-219, pp. 710-713.
publisher: Elsevier Ltd
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 945765; CODEN: AASTC
format: Online
language: English
type: Article
coverage: Bhatnagar K., School of Law, Christ University, Bangalore Campus, Karnataka, 560 029, India; Dey A., School of Law, Christ University, Bangalore Campus, Karnataka, 560 029, India

Stock market prediction employing ensemble methods: the Nifty50 index
subject: Bagging; Boosting; Fundamental analysis; Machine learning; National stock exchange fifty; Stacking; Stock market forecasting
description: Accurately forecasting stock fluctuations can yield high investment returns while minimizing risk. However, market volatility makes these projections unlikely. As a result, stock market data analysis is significant for research. Analysts and researchers have developed various stock price prediction systems to help investors make informed judgments. Extensive studies show that machine learning can anticipate markets by examining stock data. This article proposed and evaluated different ensemble learning techniques such as max voting, bagging, boosting, and stacking to forecast the Nifty50 index efficiently. In addition, an embedded feature selection is performed to choose an optimal set of fundamental indicators as input to the model, and extensive hyperparameter tuning is applied using grid search to each base regressor to enhance performance. Our findings suggest the bagging and stacking ensemble models with random forest (RF) feature selection offer lower error rates. The bagging and stacking regressor model 2 outperformed all other models with the lowest root mean square error (RMSE) of 0.0084 and 0.0085, respectively, showing a better fit of ensemble regressors. Finally, the findings show that machine learning algorithms can help fundamental analyses make stock investment decisions. 2024, Institute of Advanced Engineering and Science. All rights reserved.
creator: Manjunath C.; Marimuthu B.; Ghosh B.
source: IAES International Journal of Artificial Intelligence, Vol-13, No. 2, pp. 2047-2057.
publisher: Institute of Advanced Engineering and Science
date: 2024-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 20894872
format: Online
language: English
type: Article
coverage: Manjunath C., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Bengaluru, India; Marimuthu B., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Bengaluru, India; Ghosh B., Symbiosis Institute of Business Management, Symbiosis International (Deemed University), Bengaluru, India

HER2 siRNA Facilitated Gene Silencing Coupled with Doxorubicin Delivery: A Dual Responsive Nanoplatform Abrogates Breast Cancer
subject: breast cancer; doxorubicin; gene-drug co-delivery; HER2 siRNA; RNA interference
description: The present study investigated the concurrent delivery of antineoplastic drug, doxorubicin, and HER2 siRNA through a targeted theranostic metallic gold nanoparticle designed using polysaccharide, PSP001. The as-synthesized HsiRNA@PGD NPs were characterized in terms of structural, functional, physicochemical, and biological properties. HsiRNA@PGD NPs exposed adequate hydrodynamic size, considerable ? potential, and excellent drug/siRNA loading and encapsulation efficiency. Meticulous exploration of the biocompatible dual-targeted nanoconjugate exhibited an appealing biocompatibility and pH-sensitive cargo release kinetics, indicating its safety for use in clinics. HsiRNA@PGD NPs deciphered competent cancer cell internalization, enhanced cytotoxicity mediated via the induction of apoptosis, and excellent downregulation of the overexpressing target HER2 gene. Further in vivo explorations in the SKBR3 xenograft breast tumor model revealed the appealing tumor reduction properties, selective accumulation in the tumor site followed by significant suppression of the HER2 gene which contributed to the exclusive abrogation of breast tumor mass by the HsiRNA@PGD NPs. Compared to free drugs or the monotherapy constructs, the dual delivery approach produced a synergistic suppression of breast tumors both in vitro and in vivo. Hence the drawings from these findings implicate that the as-synthesized HsiRNA@PGD NPs could offer a promising platform for chemo-RNAi combinational breast cancer therapy. 2024 American Chemical Society.
creator: Archana M.G.; Anusree K.S.; Unnikrishnan B.S.; Reshma P.L.; Syama H.P.; Sreekutty J.; Joseph M.M.; Sreelekha T.T.
source: ACS Applied Materials and Interfaces, Vol-16, No. 20, pp. 25710-25726.
publisher: American Chemical Society
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 19448244; PubMed ID: 38739808
format: Online
language: English
type: Article
coverage: Archana M.G., Laboratory of Biopharmaceuticals and Nanomedicine, Division of Cancer Research, Regional Cancer Centre (RCC), Kerala, Thiruvananthapuram, 695011, India; Anusree K.S., Laboratory of Biopharmaceuticals and Nanomedicine, Division of Cancer Research, Regional Cancer Centre (RCC), Kerala, Thiruvananthapuram, 695011, India; Unnikrishnan B.S., Laboratory of Biopharmaceuticals and Nanomedicine, Division of Cancer Research, Regional Cancer Centre (RCC), Kerala, Thiruvananthapuram, 695011, India, Centre for Nanotechnology, Indian Institute of Technology (IIT), Uttarakhand, Roorkee, 247667, India; Reshma P.L., Laboratory of Biopharmaceuticals and Nanomedicine, Division of Cancer Research, Regional Cancer Centre (RCC), Kerala, Thiruvananthapuram, 695011, India; Syama H.P., Laboratory of Biopharmaceuticals and Nanomedicine, Division of Cancer Research, Regional Cancer Centre (RCC), Kerala, Thiruvananthapuram, 695011, India; Sreekutty J., Laboratory of Biopharmaceuticals and Nanomedicine, Division of Cancer Research, Regional Cancer Centre (RCC), Kerala, Thiruvananthapuram, 695011, India; Joseph M.M., Chemical Sciences & Technology Division (CSTD), Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science & Technology (CSIR-NIIST), Kerala, Thiruvananthapuram, 695019, India, Department of Life Sciences, CHRIST University, Banglore, 560029, India; Sreelekha T.T., Laboratory of Biopharmaceuticals and Nanomedicine, Division of Cancer Research, Regional Cancer Centre (RCC), Kerala, Thiruvananthapuram, 695011, India