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Evolving corporate sustainable development: a case study of Mysore Paper Mills Limited
In 1987, the World Commission on Economic Development (WCED) popularized the term sustainable development in its well-cited report, Our Common Future. According to this report, sustainable development is defined as the development that meets the needs of the present without compromising the ability of future generations to meet their own needs. The WCED asserted that sustainable development required simultaneous adoption of environmental, economical, and equity principles. Bansal (Strategic Management Journal, 26(3), 197218, 2005) has conducted a study of Canadian firms in the oil and gas, mining, and forestry industries from 1986 to 1995. The study found that both resources based and institutional factors influence corporate sustainable development. This paper studied the corporate sustainable development of Mysore Paper Mills Ltd. from 1995 to 2011 using the same model. The study found that independent variables with significant impact on environmental integrity and overall sustainability were fines, penalties, court cases (total) involved by the company, and log of total assets. On economic prosperity, the independent variable with significant impact is log of total assets. For social equity, the independent variable with significant impact is foreign sales as percentage of total sales, number of fines/penalties/court cases (total), number of fines/penalties/court cases (environmental), log(total assets), and return on equity. 2013, Springer Science+Business Media Dordrecht. -
Quantum optimization for machine learning
Machine learning is a branch of Artificial Intelligence that seeks to make machines learn from data. It is being applied for solving real world problems with huge amount of data. Though, Machine Learning is receiving wide acceptance, however, execution time is one of the major concerns in practical implementations of Machine Learning techniques. It largely comprises of a set of techniques that trains a model by reducing the error between the desired or actual outcome and an estimated or predicted outcome, which is often called as loss function. Thus, training in machine learning techniques often requires solving a difficult optimization problem, which is the most expensive step in the entire model-building process and its applications. One of the possible solutions in near future for reducing execution time of training process in Machine learning techniques is to implement them on quantum computers instead of classical computers. It is conjectured that quantum computers may be exponentially faster than classical computers for solving problems which involve matrix operations. Some of the machine learning techniques like support vector machines make extensive use of matrices, which can be made faster by implementing them on quantum computers. However, their efficient implementation is non-trivial and requires existence of quantum memories. Thus, another possible solution in near term is to use a hybrid of Classical Quantum approach, where a machine learning model is implemented in classical computer but the optimization of loss function during training is performed on quantum computer instead of classical computer. Several Quantum optimization algorithms have been proposed in recent years, which can be classified as gradient based and gradient free optimization techniques. Gradient based techniques require the nature of optimization problem being solved to be convex, continuous and differentiable otherwise if the problem is non-convex then they can find local optima only whereas gradient free optimization techniques work well even with non-continuous, non-linear and nonconvex optimization problems. This chapter discusses a global optimization technique based on Adiabatic Quantum Computation (AQC) to solve minimization of loss function without any restriction on its structure and the underlying model, which is being learned. Further, it is also shown that in the proposed framework, AQC based approach would be superior to circuit-based approach in solving global optimization problems. 2020 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. -
Optimizing Algorithmic Trading Through DRL: A Comparative Analysis of Single-Agent and Multi-Agent Models
This work investigates how Deep Reinforcement Learning (DRL) can elevate algorithmic tradingespecially in fast-paced, high-frequency markets. We propose a full-fledged framework to compare different setups, from solo agents to multi-agent systems, applying DRL methods like Proximal Policy Optimization (PPO), Deep Q-Network (DQN), and Advantage Actor-Critic (A2C), along with combinations of these. We trained on hourly stock data from 24 firms over two years (Jan 1, 2020Jan 1, 2022) and tested performance over the next year (Jan 1, 2022Jan 1, 2023). We evaluated key factorsreturns, risk control, and how well these models adapt to changing markets. The single-agent PPO model stood out, achieving a remarkable profit factor of 28.07 on BIDU and keeping peak drawdowns frequently under 1%. This demonstrates both solid capital protection and high risk-adjusted performance. Ensemble models showed balanced performance in both single-agent and multi-agent setups, achieving a Sharpe ratio of 0.75 and Sortino ratios up to 7.7, outperforming existing benchmarks. Comparative analyses revealed that ensemble strategies enhance market responsiveness and improve both stability and profitability in volatile environments. Sensitivity analysis confirmed the robustness of model performance across various hyperparameter settings. Overall, the proposed DRL-based ensemble framework demonstrates strong potential to improve real-world HFT systems by delivering more adaptive, stable, and efficient algorithmic trading solutions. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
The impact of Bacillus subtilis NJ22, a Fe-resilient soil isolate as a potent plant Growth-Promoting agent to Spinacia oleracea L
A soil isolate Bacillus subtilis NJ22 showed remarkable Fe tolerance up to 500g/mL. Along with Nitrogen fixation and phosphate and potassium solubilisation, the isolate NJ22 also showed other plant growth promoting traits including IAA, Ammonia, Siderophore, HCN production capabilities. The isolate, NJ22 substantially improved the growth of Spinacia oleracea in Fe-stressed soil. Soluble Fe content increased in soil containing PGPR. The Author(s) under exclusive licence to Society for Plant Research 2025. -
Plasmonic Ag-Integrated Mesoporous Mn2O3TiO2 Thin Films for Efficient Solar Hydrogen Production
The present work describes the synthesis of mesoporous Mn2O3TiO2 (TiMn) and Ag-integrated TiMn (TiMnAg) nanocomposites, and their superior photocatalytic activity in a thin-film form was demonstrated for solar H2 generation in direct sunlight. The integration of metallic Ag and TiMn significantly enhanced solar H2 production due to the combined effect of Schottky junction and heterojunction formation. The PIRET (plasmon-induced resonance energy transfer) effect of Ag and the consequent energy transfer to the surrounding lattice, and heterogeneous distribution of metal ions on the TiO2 surface with possible synergistic interactions among them, are additional reasons for efficient solar-to-chemical energy conversion. TiMnAg-1 (0.5 wt % Ag-loaded on TiMn) and TiMn-3 (TiO2:Mn = 1:0.03 mol ratio) showed the highest H2 production rate (9.05 mmolh1g1), which is 60 times higher than that of bare TiO2 (0.16 mmolh1g1). TiMnAg-1 fabricated in a thin-film form shows 5.2 times higher solar H2 production activity than its powder counterpart. The interconnected mesoporous network in TiMnAg-1 is an additional advantage, which enhances diffusion and mass transfer during the reaction. The plausible photocatalytic reaction mechanism of the TiMnAg nanocomposites involves direct energy and electron transfer from metallic Ag nanoparticles and Mn2O3 species, respectively, to TiO2, which is then utilized for the reduction of H+ to H2. 2026 American Chemical Society -
Nanoremediation of Groundwater Contaminants Through Mycosynthesized CuONPs and ZnONPs
The global wide threatening problem is the pollution, especially water and soil pollution are biggest threats to our people. The pollution not only damages the resources but also enters the ecosystem and impairs our health. The pollution disfigures the fertility of the soil and contaminates the groundwater table which is the most reliable source of all living organisms. Due to urbanization of people and scarcity of the water resources, the people rely on the groundwater for the domestic and drinking needs. Earlier researches include the bioremediation and physico-chemical mechanisms in removal of toxic/heavy metals from water but still faced several post-treatment issues. The advancement in science and technology paved a path as nanotechnology to overcome these problems. In this current investigation, the CuO nanoparticles (CuONPs) and ZnO nanoparticles (ZnONPs) were synthesized from endophytic fungal strain and characterized which were previously reported. The groundwater samples were collected near, in, and around of the garbage-dump site of Vellalore-Kurichi village, Coimbatore, Tamil Nadu, India; three areas were selected, and water samples were collected. The basic physico-chemical parameters such as BOD, COD, TDS, hardness, pH, chlorides, sulfates, nitrates, and heavy metal(s) of the collected samples were analyzed. The adsorption studies were initiated with three different concentrations of CuONPs and ZnONPs in 100mL of polluted groundwater samples, and the kinetics was started with 0th min and extended till 180min. The adsorption rate increased with the increase in time; the CuONPs and ZnONPs adsorbed the few pollutants that also included arsenic (V) effectively. The nanoremediated samples were further taken to determine the effectiveness in aiding the plant growth promotion, and this was executed in Trigonella sp. plants. The plants were grown well which was compared to the control plants, and the phytochemical assessment was carried out. The presence of phytochemicals of the plants grown in nanoremediated samples was similar to that of control plants. Further, the CuONPs and ZnONPs have the ability in remediating the pollutants/contaminants in the groundwater. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
APPLICATION OF ARTIFICIAL INTELLIGENCE IN PHARMACEUTICAL INDUSTRY
Artificial Technology is the blockbuster technology today. Pharmaceutical industry is no exception to the technology onslaught. Pharmaceutical industry adapting to the Artificial Intelligence (AI) to improve the overall performance of the industry processes, through improved efficiency in the operations and reduced lead time in the drug discovery. This is done through AIs ability of scanning huge data to speed up the drug discovery stage by identifying prospective drug candidates through technology like Structure-Based Virtual Screening (SBVS) and Fragment-Based Drug Discovery (FBDD). A nascent drug approach called as drug repurposing is very prospective through AI, and AI makes it possible to integrate nanotechnology, targeted drug development and personalised treatment based on genetic and proteomic data. AI has huge applications in the very important drug development stage of clinical trials. Selection of suitable participants, predicting drug responses will have huge cost reduction with the AI technology. In addition to drug trials, AI is transforming the pharmaceutical marketing process. Personalised communication, predictive sales forecasting, automated content generation and sentiment analysis are some of the possible as of now. These applications make the companies offer tailor made marketing strategies specific to physicians and patients and monitor the brand reputation and bring efficiency in the supply chain. Albeit the potential benefits, adoption of AI fully in the pharmaceutical industry has its own challenges. In the areas of data privacy, regulatory compliance and ethics related to drug testing, AI could face serious challenges. As the technology evolves, AI will have its impact on the pharmaceutical industry offering huge growth opportunities. India could emerge as a potential superpower in the pharmaceutical industry if AI is properly harnessed for industry growth. India can be the pharmacy for the entire world in the coming days if industry finds a way to utilize AI properly. 2024, Indian Pharmaceutical Association. All rights reserved. -
Platform Business Model for Intelligent Supply Chain Operations
Platform economy involves technology to connect the dispersed network of participants. The Platform Business Model denotes a triangular participation between; the platform itself, the supplier and the consumer. The global market is witnessing a rise of digital platforms with an increase in the power of algorithms and cloud-based computing, connecting millions of participants in the network. The technological advancement makes the digital platforms a formidable force that ushers in change and brings out economic revolution across the globe. Many entrepreneurs have been created by these platforms, the workforces have the freedom to choose their work time and job, leading to an economically vibrant society. Platform businesses exist across various verticals, even in manufacturing setup. A variety of goods can be produced in a flexible assembly line. Hence the concept of outsourcing may require new definition from low-cost labour-based countries to high technology low-cost countries. There may be a transformation of economies shifting towards service, as major manufacturers may reorient themselves into service operators. Overall, the platform business model would make the entire operation more transparent with real time data transfer between the participants, leading to efficiency across the entire chain of business activities. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Telemedicine-The New Digital Healthcare Platform
The concept of Telemedicine was known to the public since 1970s but the real potential was realized only during the pandemic Covid-19. The pandemic has reviewed Telemedicine and has given a wide acceptance among the public within a short span of time. This technology enabled tele-healing offers very little direct interaction between the healthcare providers and the patients. This article explores the technology requirements, ethical, and legal challenges, and opportunity to offer different healthcare services through Telemedicine. There is a scope for this technology morphing into platform models like what we have for social media. As more people start using telemedicine, the other healthcare services could be identified and offered for each individual. It can be concluded that telemedicine offers huge potential to take health benefits at places where health infrastructure could not be offered due to scalability issues. 2023, Indian Pharmaceutical Association. All rights reserved. -
Usage of social media in education: A paradigm shift in the Indian education sector
The pandemic is anticipated to have a significant economic impact, and it already has a terrible effect on schooling worldwide. Due to the coronavirus's quick spread, educational institutions worldwide are making the drastic leap from delivering course materials in person to doing so online. The rapid use of digital technology represents a significant paradigm change that may ultimately transform the Indian educational system. The COVID-19 scenario provides an opportunity to test new tools and technology to make education more relevant for students who cannot travel to campuses. With online learning and evaluation, there is a chance to increase knowledge and productivity while acquiring new skill sets and expedited professional talents. In this chapter, the authors have examined the educational difficulties and opportunities brought on by the sudden COVID-19 epidemic, followed by a discussion of how the Indian educational system has to be recalibrated. Copyright 2023, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. 2023 by IGI Global. All rights reserved. -
Social media usage in indian banking and financial institutions
Due to technological innovation, the economy is transitioning from a market-driven to a network-oriented status, and social media has seized the leading I.T. trends in the technology sector. A paradigm change in banking and inance operations has occurred due to the upswing in innovation, transformation, and digitalisation in Indian banking and inancial organisations. The development of online banking, mobile apps, mobile banking, and tools like debit and credit cards has changed how customers utilise banking and inancing services. Thanks to social media and digital marketing, banks may now be practical tools for supporting customers' enterprises and gaining target prospects. To provide customers with rapid and eicient service in the post-pandemic age, Indian banks and inancial institutions are rushing to modernise their technology infrastructure and digital goods. Social media ofers users attractive options for 24-hour access to information and the use of inancial services across temporal and geographic boundaries. 2023 by IGI Global. All rights reserved. -
Addressing B5G and 6G Network Connectivity Issues in Rural Regions
As regions move towards the next generation of wireless technology, addressing connectivity challenges in rural regions is critical for the development of Beyond 5G (B5G) and 6G networks. While urban areas may benefit from the advanced capabilities of these technologies, rural communities face significant barriers to accessing high-speed, reliable internet. These challenges, including limited infrastructure, geographical constraints, and financial obstacles, hinder economic development, education, and healthcare opportunities in rural areas. To bridge this digital divide, innovative solutions in network design, spectrum management, and infrastructure investment are essential. By addressing these connectivity issues, B5G and 6G networks have the potential to create inclusive, equitable access to new services and opportunities for rural populations. Addressing B5G and 6G Network Connectivity Issues in Rural Regions explores the transformative potential of advanced networking technologies in rural settings. It delves into the pressing issue of connectivity challenges faced by rural communities and outline how emerging B5G and 6G networks can address these obstacles. This book covers topics such as digital technology, policymaking, and social inclusion, and is a useful resource for communications professionals, business owners, engineers, economists, academicians, researchers, and scientists. 2025 by IGI Global Scientific Publishing. All rights reserved. -
An Effective BiLSTM-CRF Based Approach to Predict Student Achievement: An Experimental Evaluation
Currently, massive volumes of data are accumulated in databases when people configure new requirements and services. Data mining techniques and intelligent systems are emerging for managing large amounts of data and extracting actionable insights for policy development. As digital technology has grown, it has naturally become intertwined with e-learning practices. In order to facilitate communication between instructors and a diverse student body located all over the world, distance learning programs rely on Learning Management Systems (LMSs). Colleges can better accommodate their students' individual needs by using and analyzing interaction data that reveals variances in their learning progress. Predicting pupils' success or failure is a breeze with the help of learning analytics tools. Better learning outcomes might be achieved through early prediction leading to swift focused action. Preprocessing, feature selection, and model training are the three components of the proposed method. Data cleansing, data transformation, and data reduction are the preprocessing steps used here. It used a CFS to enable feature selection. This study has used a BiLSTM-CRF hybrid approach to train the model. When compared to tried-and-true techniques like CNN and CRF, the proposed method performs effectively. 2024 IEEE. -
Intellectual capital independent directors and leverage as determinants of sustainable growth in Indian pharmaceutical companies listed in the NSE NIFTY pharma index
This research investigates how Intellectual Capital (IC) influences the Sustainable Growth Rate (SGR) of Indian pharmaceutical firms that are part of the NSE NIFTY Pharma index. This study delves deeper into the moderating influence of Independent Directors and examines the control effect of Leverage (Debt-Equity Ratio) on this relationship. A descriptive research design was utilized, employing panel data from FY 2015 to FY 2024. The dataset was obtained from the Prowess database (CMIE), and the Two-Step System GMM method was utilized with STATA 18 to guarantee a thorough econometric analysis. The findings indicate that Intellectual Capital (IC) plays a crucial role in enhancing SGR, thereby reinforcing the Resource-Based View (RBV). Independent Directors effectively moderate this relationship, strengthening Agency Theory. Nonetheless, leverage has a detrimental effect on SGR, consistent with Pecking Order Theory. Pharmaceutical companies ought to allocate resources towards Intellectual Capital, enhance corporate governance, and uphold appropriate debt levels to ensure sustained long-term growth. This study effectively combines IC, corporate governance, and financial leverage in the Indian pharmaceutical sector, providing valuable concrete insights for policymakers, academics, and industry experts. The Author(s) 2026. -
Surface Roughness Analysis in AWJM for Enhanced Workpiece Quality
Abrasive Water Jet Machining is a distinctive manufacturing process that effectively removes material from a workpiece by employing a high-pressure stream of water combined with abrasive particles. The final quality of the machined surface is directly influenced by various process parameters, such as the traverse speed, hydraulic pressure, stand-off distance, abrasive flow rate, and the specific type of abrasive used. In recent times, extensive research has been undertaken to enhance the performance of AWJM, with a specific focus on critical performance measures like surface roughness. This paper presents the latest advancements in AWJM research, with particular attention given to enhancing performance measures, implementing process monitoring and control, and optimizing process variables for applications involving high-carbon steel. 2024 E3S Web of Conferences -
Analysis of multimode oscillations caused by subsynchronous resonance on generator shaft /
European Journal of Electrical Engineering, Vol.20, Issue 4, pp.455-468 -
Characterization and comparison studies of Bentonite and Flyash for electrical grounding
Earthing or Grounding is an Electrical system consists of electrodes which serves as an electrical connection from an electric circuit in the system to the earth or ground. Traditional Earthing- where we mix charcoal and salt offers low resistance to the fault current flow developed from a Low operating Voltages. Since operating voltages are high now a days, Short circuit current also increased. Traditional method of Earthing is replaced by chemical Earthing.Bentonite which is mainly used in chemical Earthing serves the requirement of Low resistance Earthing pits and also have the property to retain the moisture. In this paper an attempt had been made to assure the Flyash usage in the grounding pit and this paper discusses the Characterization, Comparison and Field Studies on Earthing Pit constructed with Bentonite and Fly ash layers. 2015 IEEE. -
Study of generator shaft behaviour during subsynchronous resonance using finite element method
Scientific research in electric power stations includes various online monitoring and control of equipments. Turbine and generator plays a key role in generating power. Frequency response analysis of the shaft which connects turbine and generator is used to detect the steady state response. It will enable the user to understand and design the system in such a way that it can withstand resonance, fatigue and other vibrations. Subsynchronous resonance which arises during line compensation by series capacitors increases oscillations in the turbine generator shaft system. The oscillations developed at low frequency causes physical damage to the shaft. There are several real time monitoring of the rotor shaft and turbine shaft misalignment by using laser technologies. The aim of this research paper is to use frequency response and modal analysis technique to detect the stress in the shaft and improve the design of it. A viscous damper is designed in the 3D model at the point of highly stressed area to control the resonance effect caused by series capacitors. 2020, Levrotto and Bella. All rights reserved. -
Determination of stress on turbine generator shaft due to subsynchronous resonance using finite element method
Power Capacitors plays a vital role in reactive power compensation. When the capacitors are connected to the transmission line, it improves the reactive power. Although the reactive power is improved, there is a possibility for sub synchronous resonance created by this capacitors in the transmission line which can impact the generator frequency. The sub synchronous resonance causes electro-mechanical stress in the generator shaft which ultimately leads to malfunction of the entire power generating unit. It is necessary to find out operating modes of the generator and turbine when the line is compensated with capacitors. Once the operating modes are clear, it is possible to damp the sub synchronous resonance. In this paper, three phase generator is coupled with a prime mover and capacitors are connected before the load. The stress on the turbine is analysed based on the torque of two rotating machines. Finite element method is used to estimate the stress in the turbine generator shaft system. 2006-2019 Asian Research Publishing Network (ARPN).