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Implementation of biological fuel cells in treating pharmaceutical effluents
Mankind suffers from a wide variety of infections, diseases, and lifestyle problems. To overcome, several industries worldwide aim to achieve their main objective as the synthesis of an enormous number of diverse drugs that neutralize problems. With the production of tones-to-tones pharmaceutical products these industries also generate extreme good amount of waste, pharmaceutical waste which is now concerned as it contains massive quantity of high organic load of toxic and non-toxic elements. However, the industrial sector adopts anaerobic wastewater treatment strategies to overcome this. As pharmaceutical waste owes highly varied and complexed recalcitrant elements in their complex drug molecules it is not ideal to treat only with anaerobic treatment. Hence, several biotreatments are becoming popularized because they employ MFCs, which are known for the generation of electricity directly from biodegradable organic compounds. The new bio electrochemical technology promises to be inexpensive in comparison to conventional ones. MFC holds the process of both oxidation and reduction permitting the degradation of a wide range of compounds to easily degradable and generates concurrent renewable energy. 2022 by Nova Science Publishers, Inc. -
Growth and microindentation analysis of pure and doped Sb2 Se3 crystals
Pure and doped antimony selenide (Sb2 Se3, Sb 2 Se2.8 Te0.2, and Sb2 Se 2.6 Te0.4) crystals have been grown from melt by the Bridgman Stockbarger method. X-ray powder diffraction analysis was carried out to determine the lattice parameters of the grown samples. The morphology of cleavage planes was observed using SEM. Energy dispersive analysis by X-rays (EDAX) was done to find out the chemical composition of the grown samples. Correlation of microhardness with other mechanical characteristics such as toughness, brittleness, and yield strength, has been investigated. The effects of Te doping on the mechanical behaviour and energy gap were also studied on the cleavage faces. Ti?tak. -
Feminism in popular culture: A case study on justice league /
With popular culture stemming largely from the superhero comics it is difficult to ignore them nowadays. Marvel and DC have also been going at great lengths to ensure that for the next ten years, there exists a whole stock of such movies, comics and merchandise. This in turn means that there is a growing need to document and study the patterns of this growing culture. Within this, the evolution of female characters and feminist ideologies must be mapped. -
Exploring REITs in Indian Context: A Modern Avenue for Real Estate Investment
This paper explores how Real Estate Investment Trusts (REITs) are conceived and are poised for growth in Indias financial domain. REITs bring the opportunity for ordinary investors to invest in real estate based income generating assets with the added advantages of liquidity, transparency and control of SEBI regulation (2019). A closer look at how Indias listed REITs have performed to date, and what impact they have had on capital markets, investor preference and real estate development (Sharma and Iyer 2021). The results suggest that REITs may contribute in attracting additional capital to the real estate industry and The results indicate that REITs can significantly facilitate capital flow into the real estate industry and democratize property investment in India. The article emphasizes future prospects and policy concerns vital for the evolution of the REIT sector in India through worldwide benchmarking and empirical analysis (World Bank 2020). The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Impact of IFRS on the financial statements of select IT companies in India
Globalization of economies and shift in financial environment from the traditional bank based one to a market based one necessitated a uniform financial reporting language across countries to facilitate comparisons. This resulted in the establishment of International Accounting Standard Board (IASB) which issued International Financial Reporting Standards (IFRS), a global standard for company financial statements. More than 120 countries, including European Union, Australia, Canada have already adopted IFRS. India was expected to converge with IFRS from April 2016 for listed and unlisted companies with a net worth of more than rs 500 crores. However, few Indian companies listed internationally are voluntarily reporting IFRS. The present study aimed to understand the effect of this voluntary reporting of IFRS on key financial ratios of four selected IT sector companies. The study compared 12 major financial ratios under IFRS and Indian Generally Accepted Accounting Principles (IGAAP) as reported in their financial statements for a period of 5years from 2009-10 to 2013-14. For the purpose of the study, financial ratios representing four key dimensions of companies namely liquidity, leverage, profitability, and efficiency were considered. To understand the statistical significance of the difference between the ratios, Wilcoxon signed rank test, a non parametric test was used. Of the 12 ratios analyzed, 10 were found to be statistically significant. Further, the study explained the financial statement items which cause the difference in the ratios of these companies. The results indicated current liability and shareholder's equity to be significant at the 10% level, thus explaining the difference in financial statement items under IFRS. -
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An analysis on if presentation style attracts readers to read an article /
This study is to analyse if readers read an article due to the presentation style of an article (writing style, graphic designs, layout and topic) they come across. Readers pick a magazine based on their interest and the magazines may contain what they already know, something additional to the knowledge they already have and also from the areas that they are ignorant about. They may or may not read all the articles from that particular magazine and if at all they read there can be a solid reason behind it. I want to analyze if it is because of their interest or due to the presentation style. There have been studies done in this particular field but not on any particular point of view. They have also not stressed much on the contrast of presentations style and content. This study can be a means through which many magazines or other print media can reach up to the audience and make them read the articles. The researcher prefers qualitative study as analyze on why they read an article has to be done. It is by means of a questionnaire that I am going to do the qualitative study. -
TamilEnglish Machine Translation: A Comparative Analysis of Human and AI Renderings
This chapter explores the understudied challenges of TamilEnglish machine translation (MT), which is a field where most existing scholarship has focused on Western language pairs. It performs a comparative analysis of published translations of acclaimed Tamil authors such as Perumal Murugan, Ashokamitran, Jeyamohan, and Charu Nivedita with AI- generated translations produced by systems including ChatGPT, Grok, and AI Novel Translation. It explores issues of accuracy, fidelity, style, and cultural nuance. By examining how AI tools interpret and reproduce linguistic choices, syntax, and cultural particularities, it evaluates the extent to which AI can approximate human translation and highlights the role of post- editing in bridging gaps. The analysis not only identifies recurring errors but also suggests methods for refining human and AI translations for Tamil literary texts. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Detection of carbapenem resistance genes and cephalosporin, and quinolone resistance genes along with oqxAB gene in Escherichia coli in hospital wastewater: A matter of concern
Aims: This study was performed to detect the presence of Escherichia coli resistant to cephalosporins, carbapenems and quinolones in hospital wastewater. Methods and Results: Wastewaters from a rural (H1) and an urban (H2) hospital were tested for E.coli resistant to cephalosporins, carbapenem and quinolones. Genes coding for chromosomal and plasmid-mediated resistance and phylogenetic grouping was detected by multiplex polymerase chain reaction (PCR) and for genetic relatedness by rep-PCR. Of 190 (H1=94; H2=96) E.coli examined, 44% were resistant to both cephalosporins and quinolones and 3% to imipenem. ESBLs were detected phenotypically in 96% of the isolates, the gene blaCTX-M coding for 87% and blaTEM for 63%. Quinolone resistance was due to mutations in gyrA and parC genes in 97% and plasmid-coded aac-(6?)-Ib-cr in 89% of isolates. Only in one carbapenem-resistant E.coli, NDM-1 was detected. Nearly 67% of the isolates belonged to phylogenetic group B2. There was no genetic relatedness among the isolates. Conclusions: Hospital wastewater contains genetically diverse multidrug-resistant E.coli. Significance and Impact of the Study: This study stresses the need for efficient water treatment plants in healthcare settings as a public health measure to minimize spread of multidrug-resistant bacteria into the environment. 2014 The Society for Applied Microbiology. -
Biological treatment solutions using bioreactors for environmental contaminants from industrial waste water
Human needs have led to the development of various products which are produced in the industries. These industries in turn have become a source of various environmental concerns. As industries release regulated and unregulated contaminants into the water bodies, it has become a serious concern for all living organisms. Various emerging contaminates from industries like pesticides, pharmaceuticals drugs like hormones, antibiotics, dyes, etc., along with byproducts and new complexes contaminate the water bodies. Numerous traditional approaches have been utilized for the treatment of these pollutants; however, these technologies are not efficient in most cases as the contaminants are mixed with complex structures or as new substances. Advanced technologies such as bioreactor techniques, advanced oxidation processes, and so on have been used for the treatment of industrial wastewater and have served as an alternative way for wastewater treatment. Overall, biological treatment techniques based on bioreactors provide a long-term and ecologically useful solution to industrial wastewater contamination. They play an important role in saving water resources and encouraging a greener sustainable future for mankind. The current review outlines the industrial effluents that are released into water bodies, contaminating them, as well as the numerous traditional and novel treatment procedures used for industrial wastewater treatment. Graphical abstract: [Figure not available: see fulltext.] 2023, The Author(s). -
Co-Existence of Union and Management is Possible
ITIHAS The Journal of Indian Management, Vol-2 (4), pp. 100-101. ISSN-2249-7803 -
Intelligent Time Management Recommendations Using Bayesian Optimization
This paper focuses on the improvement of the intelligent time management system which employ Bayesian optimization for suggesting time management plans for each particular person. In this sense, through historical data of input-output patterns and users' preferences, the system aims at increasing productivity and user satisfaction. In the study, Gaussian Processes are used as the surrogate model in the Bayesian optimization so that the required evaluations by the algorithm to realize optimal scheduling methodologies are kept to a minimum. Implementation is done as a web application where users submit their tasks and get the recommended schedule instantly. Indicators like, the degree of task accomplishment, time, and scheduling compliance, and probably the users' satisfaction suggest that system helped enhance time management results. Lack of feedback from the users is removed through questionnaire that reveals the simplicity of the system and the quality of its recommended times, thereby supporting the idea of Bayesian optimization as a game changer in the management of time. This research significance points to the need for maintaining efficient and individualized approaches to time management strategies and agrees with others' findings, which suggest that this is an area ample fiction research needs to acknowledge and pursue. 2024 IEEE. -
A robust explainable machine learning pipeline for transformer health index prediction addressing data pathologies and redundancy
Power transformers are critical infrastructure assets where unexpected failures incur severe technical and economic penalties. This study proposes a robust, explainable machine-learning (ML) pipeline for predicting the transformer Health Index (HI) using routinely collected dissolved gas analysis (DGA) and dielectric measurements. To ensure model reliability, the pipeline specifically addresses data pathologiesnamely extreme skewness and heavy tailsusing YeoJohnson transformations, while mitigating multicollinearity through hierarchical correlation clustering (|r| ? 0.85) followed by a Variance Inflation Factor (VIF) screening (VIF ? 5). Four high-performance ensemblesRandom Forest, XGBoost, LightGBM, and CatBoostwere optimized via randomized cross-validation. Experimental results on a dataset of 470 records demonstrate consistent generalization across all models (RMSE ? 0.022), with Random Forest providing superior accuracy (MAPE ? 1.24%). A Taylor diagram confirmed consistent generalization (correlation ? 0.730.78 and matched variance), while residual analysis showed minimal bias. SHAP explanations indicated that dibenzyl disulfide (DBDS) and interfacial tension (Interfacial V) were the most influential positive drivers of HI; water content tended to depress HI; and several gases (e.g., methane, hydrogen, acetylene, CO) contributed positively at higher concentrations. The proposed workflow was robust to skew/heavy tails and multicollinearity, required no feature scaling, and produced transparent, practitioner-ready insights that support condition-based maintenance at fleet scale. 2026 Elsevier B.V. -
Advanced Materials for Next-Generation Energy Storage Devices: A Focus on Efficiency and Cost Reduction
The increasing demand for efficient and cost-effective energy storage systems has pushed extensive research into improved materials for next-generation energy storage devices. This study discusses the crucial significance of material advances in boosting the performance and reducing the costs of storage technologies such as batteries and supercapacitors. Conventional energy storage systems face limits in energy density, charge or discharge rates, and scalability, which impede their broad implementation. Advanced materials, including nanomaterials, solid-state electrolytes, and innovative electrode compounds, offer solutions to these difficulties by enhancing energy efficiency, power output, and overall longevity. Additionally, the use of plentiful and low-cost materials, such as sodium-ion and aluminium-based compounds, presents prospects for significant cost savings. This research analyzes current trends, issues in material manufacturing, and future perspectives for energy storage systems, concentrating on balancing efficiency improvements with cost-effectiveness to enable the rising integration of renewable energy sources. The development of these materials is important to creating sustainable, scalable, and economical energy storage systems for the future. The Authors, published by EDP Sciences. -
A Design of Agricultural Robotics for the use of Sowing and Planting
Agricultural robots is always getting better to deal with problems like population growth, fast urbanization, fierce competition for high-quality goods, worries about protecting the environment, and a lack of skilled workers. This in-depth study looks at the main uses of farming robotic systems, covering jobs like preparing the land, sowing, planting, treating plants, gathering, estimating yields, and phenotyping. Each robot is judged on how it moves, what it will be used for, whether it has sensors, a robotic arm, or a computer vision program, as well as its development stage and where it came from. The study finds trends, possible problems, and things that stop business growth by looking at these shared traits. It also shows which countries are putting money into studying and developing (R&D) for these products. The study points out four important areas - movement systems as a whole sensor, computer vision computer programs, and communication technologies - that need more research to make smart agriculture better. The results make it clear that spending money on farming robotic systems can pay off in the long run by helping with things like accurate yield estimates and short-term benefits like keeping an eye on the harvest. 2024 IEEE. -
Women's contributions to business growth and innovation in startups: Agile business
This chapter delineates the significance of women in innovation and growth as founders and leaders in the startup ecosystem. Agile environments require female entrepreneurship and leadership, offering distinct views, a spirit of cooperation, and flexibility; therefore, these are desirable attributes for business success during its highest uncertainty and optimal high-growth periods. Case studies of womenled startups have been analyzed in consideration of their inabilities to innovate, diversify, and lead through inclusive leadership to face market uncertainties and scale effectively. It shares some of the challenges women meet while trying to access venture capital and networks and gives strategies to overcome such pitfalls. This chapter gives an account of how gender, innovation, and agile methodologies intersect, thus underpinning empowerment of women in startups to cultivate competitive advantage and sustainable growth, thus developing a diverse and resilient entrepreneurial landscape. 2025, IGI Global Scientific Publishing. All rights reserved. -
Brahma Nirupan of Kabir: A Search for Ultimate Reality
Kabir Das was a fifteenth-century Indian mystic. Saint Kabir's philosophical tenets were extremely simple. He was known as the guiding spirit of the Bhakti movement. According to Kabir, Braham Nirupan is the ultimate reality called Ni-Akshar, which is only possible through Sar Shabda. Charlotte Vaudeville stated in her book named Kabir that Kabir is a weaver, the best-known and the most revered name in Indian tradition(Vaudeville, 1993). By performing service with full loving devotion, one can achieve Sar Shabda and become a Hansa. The liberated soul is blessed and can enjoy the pleasurable experience of Sar Shabda. The iconoclastic Saint Kabir is a symbol of the syncretic culture of India. Kabir refused to say if he was a Hindu or a Muslim. In today's polarized culture, Kabir's vision and love are desperately needed. Caste and religious divisions have exacerbated the fault line in our society. This paper focuses on the concept of Brahma Nirupan and the philosophy of Kabir Das and how in this materialistic world one can seek the ultimate truth while being a part of this world yet not being attached to it. Indian Council of Philosophical Research 2025. -
Applications and future directions in multimodal large language model: opportunities and challenges
Multimodal large language models (MLLMs) are an application of artificial intelligence that is rapidly growing by integrating numerous use cases. MLLMs have the capability to process data from several sources, including structured and unstructured. It enables large language models (LLMs) to give insights to the user by analyzing data from various formats. The traditional way of analyzing the data was done with a single data format. While using MLLMs, multiple data modalities are handled to manage complicated multimodal tasks, like generating content, multimodal perception, and augmenting human-computer interaction. This chapter discusses in detail the insights from data from multiple modalities and domains of the use cases of MLLMs. We also discuss the advantages of MLLMs and explain the transformative benefits from unimodal systems to multimodal systems in different sectors. We also focus on the ethical usage of MLLMs by addressing the challenges related to privacy, operational limits, bias, computational difficulties, and data scarcity. The scarce assessment metrics and trials in accomplishing robust explainability are also discussed. To train these MLLMs, acquiring and training the data utilizes more computation and power consumption, along with addressing the data security and privacy concerns. The chapter also discusses the sensible usage of AI through different problems and practices. Detailed analysis and strategies for addressing global challenges and promoting novelty in model development, outlining how these MLLMs shape the upcoming technological innovation focusing on ethical application of technology with an advantage on society. 2026 Elsevier Inc. All rights reserved. -
Impact of fine-tuning large language model in society: a comprehensive study
The fine-tuned large language models (LLMs) have revolutionized artificial intelligence (AI) and natural language processing (NLP) with key innovations in neural architectures, particularly with the transformer. The recent advancements of LLM have witnessed that models like bidirectional encoder representations from transformer (BERT), generative pretrained transformer (GPT)-2, GPT-3, and text-to-text transfer transformer (T5) show outstanding performance in understanding and generating human-like text at scale. Researchers use fine-tuned models to excel in their responses to specific tasks or domains. The purpose of fine-tuning the LLM models is to improve the performance of LLM in special fields such as education, research, literature summarization, contract analysis, and creative content generation. Fine-tuning LLM models also has issues like amplifying biases, ethical issues, and regulatory implications, remarkably when LLMs are fine-tuned for emerging domains that may hold harmful stereotypes or misinformation. Fine-tuned LLMs also provide substantial societal benefits, including expert-level knowledge to underserved regions and personalizing educational resources for self-directed learning. The study also discusses the technical aspects of fine-tuning LLMs by examining how general-purpose models are transformed into efficient models. The impact on society and the need for a framework that can shape the deployment of models, with ethical guardrails, transparency, and public engagement to ensure responsible development and use of fine-tuned LLMs. The current work explores the various steps that can be taken for bias mitigation and transparent documentation for different stakeholder engagements. The purpose of the chapter is to analyse the perspectives from technical foundations with ethical, cultural, and policy considerations and provides an integral view of the societal impact of fine-tuned LLMs. 2026 Elsevier Inc. All rights reserved.