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Harnessing Machine Learning for Mental Health: A Study on Classifying Depression-Related Social Media Posts
This study is of particular relevance in the way it identifies depression-related content on social media using a machine learning model to classify posts and comments. This dataset, encompassing around 6500 entries from various platforms including Facebook, was rigorously annotated by four proficient English-speaking undergraduate students together with the final label which is established via majority voting. Data Preprocessing, initial cleaning, normalization and TF-IDF feature creation through vectorization for the output of POS tags. The different machine learning models that were trained and tested are Logistic Regression, Random Forest, SVM (Support Vector Machine), Naive Bayes Gradient Boosting Algorithm K-NN (K nearest Neighbors) AdaBoost Decision Tree. Authors evaluated the models and measured their accuracy, precision score, recall rate (also known as sensitivity) in addition to F1-score. Gradient Boost, Random Forest, and SVM were top performers among which Gradient boosting was found to be an overall best one with almost 98.5%. They show that machine learning model can successfully predict the label of social media posts, as a way for accurately identifying depression from text data. This detailed model performance evaluation is useful in understanding what each approach does well and poorly, shedding light into whether they are / would be actually suitable for real-world applications. This study not only developed discriminative classifiers, but also included detailed analysis of their performance which should hopefully guide future work and help in practical implementations for real-time mental health monitoring. Through this work, this study aim to facilitate timely identification of depression-related posts, ultimately supporting mental health awareness and intervention efforts on social media platforms. 2024 IEEE. -
Harnessing Machine Learning toOptimize Social Media Marketing
Machine learning (ML) has transformed the way digital advertising is done and analyzed by social media data. This paper explores ML in targeted advertising, including techniques such as supervised learning, neural networks, and NLP. While ML improves campaign precision and consumer engagement, it also presents challenges such as algorithmic bias, data privacy concerns, and computational scalability. This study is a synthesis of existing research and explores real-world applications, providing a critical analysis of MLs capacity to optimize social media advertising. It argues that while ML may provide exceptional possibilities for customization and engagement, its success can only be ensured through appropriate ethical practices, transparency, and innovation in technology. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Harnessing Medical Databases and Data Mining in the Big Data Era: Advancements and Applications in Healthcare
In the contemporary period of Big Data, the healthcare industry is witnessing a transformative paradigm shift, propelled by the convergence of medical databases and data mining technology. This research paper delves into the multifaceted application of this synergy, offering a comprehensive overview of its implications and opportunities. With the exponential growth of healthcare data, the utilisation of medical databases serves as the bedrock for data mining techniques, fostering critical advancements in diagnosis, treatment, and patient care. Through this research, we explore the integration of electronic health records, genomic data, and clinical databases, unveiling new dimensions of predictive analytics, patient profiling, and disease monitoring. Moreover, we assess the ethical and privacy concerns entailed in this data-rich landscape, emphasising the need for robust governance and security measures. Our paper encapsulates the evolving landscape of health care, demonstrating the immense potential and the ethical responsibilities accompanying this groundbreaking merger of technology and medicine in the period of Big Data. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Harnessing MnMoO4 nanoparticles for eco-conscious effluent degradation and catalytic applications
The increasing need for green technology solutions to reduce water pollution and enhance sustainable catalysis has prompted the research for efficient photocatalysts. In this research, a green synthesis method was adopted to synthesize MnMoO4 NPs using solution combustion route followed by calcination. Synthesized MnMoO4 showed superior photocatalytic performance under visible light, with 91% degradation of Rose Bengal dye in aqueous medium indicates its potentiality for wastewater treatment. The material also showed catalytic efficiency in the coupling reaction of aniline and dimedone as model substrates for the synthesis of ?-enaminone derivatives, displaying its usability in organic catalysis. The work highlights the dual functional ability of MnMoO4 both an organic catalyst and a photo-catalyst, providing a green path for synthetic and environmental applications. The dual functionality combined with green fabrication process exemplifies the novelty and applicability of this article. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Harnessing mobile multimedia for entrepreneurial innovation and sustainable business growth
This research investigates the role of mobile multimedia platforms and artificial intelligence (AI) in driving innovation and ensuring the sustainability of entrepreneurial businesses, focusing particularly on technology acquisition, integration, and infrastructure. For data collection, the study employed a quantitative research design and surveyed 150 Indian technology firms that had adopted mobile multimedia applications. Structural equation modeling was used to analyze the data, supported by descriptive statistics, correlation, regression analysis, and mixed methods to understand the adoption and use of digital technologies for innovation activities. The results show that AI-driven applications, when combined with multimedia content and real-time analytics, significantly enhance entrepreneurial innovation by improving operational efficiency, increasing customer engagement, and facilitating expansion into new international markets. Companies utilizing mobile multimedia platforms gain a competitive advantage, translating into long-term business growth and sustainability. This research contributes to the literature on AI and entrepreneurship in the context of digital transformation, highlighting the need for startups to invest in AI-enabled mobile technologies. It equally serves policymakers by informing the regulation of an environment that promotes innovation and business sustainability through digital initiatives. This research addresses a significant gap in the literature by providing evidence on how AI acts as a driver of change and provides insight into the adoption of new technologies in the context of entrepreneurship, an area that remains largely underexplored. 2025, Society of Sytematic Innovation. All rights reserved. -
Harnessing MOF Derived Frustrated Lewis Pair-CeO2 Nano Catalyst for CO2-Activated Soft Oxidation of Furfural to Furoic Acid
CO2 as a soft oxidant is scarcely explored in literature for furfural oxidation to furoic acid, and where CeO2, capitalizes on the synergistic effect of FLPs for enhanced CO2 reduction and furfural oxidation. This study presents a comparative analysis by the synthesis method to produce hydrothermal and MOF-derived CeO2 nanocatalyst and their effect on the formation of oxygen vacancies and metastable Ce3+ ions. The normalized surface concentration derived from XPS At% and specific surface area effectively quantifies accessible Ce3+ sites and oxygen vacancies, capturing FLP sites. Oxygen vacancies near surface Ce3+ sites (FLPs) critically modulated the catalytic performance, and evidenced by high turnover number (TON). FTIR adsorption study revealed that CO2 forms bidentate carbonate species and furfural, bi-coordination via ?2- (C, O) mode on the catalyst surface. Further active site masking strategy helped to understand and validate the crucial role of FLPs. The Central Composite Design model was utilized to optimize the reaction conditions and obtained high furfural conversion (99%) and furoic acid selectivity (99%). The catalyst was resistant to active site leaching and exhibited excellent stability, recyclability, and robustness. The findings highlight a potential pathway for the catalytic soft oxidation of furfural to furoic acid by CO2 utilization. 2025 Wiley-VCH GmbH. -
Harnessing nanotechnology applications and solutions for environmental and climate protection-an overview
Nanotechnology is an emerging technology that has drawn considerable interest from environmentalists. Numerous nano techniques identify Nanotechnology applications as having the potential for imperative advantages and innovation. This work offers a wide-overview of the main beliefs that strengthen s nanotechnology. We focus on the potential applications of nanotechnology for environmental protection and management by thoroughly reviewing past literature. To our understanding, this is an academic, peer-reviewed work to deliver a systematic review of nano-activities in the areas of environmental and climate protection. Our study has been systematically arranged into two different groups (1) Potential applications of nanotechnology in r environmental protection and (2) The best part of Nanotechnology that combats Climate Change. For each of these cases, our contribution is twofold: First, in identifying the technical ways by which nanotechnology can solve environmental risks, and secondly, in briefly presenting its potential advantages. The paper ends with deliberation of challenges and operational barriers that technology needs to overcome to prove its commercial viability and for being adopted for commercial use. 2021 Author(s). -
Harnessing quorum sensing for disease management
Quorum sensing (QS) is a bacterial communication system that allows bacteria to coordinate their behavior based on their population size. Both Gram-positive and Gram-negative bacteria use QS, but they employ different chemical signals to communicate. As bacteria grow, they release these signals, and when the attention of these signals reaches a certain position, it triggers specific genes that help the bacteria acclimate to their terrain. 2026 Elsevier Inc. All rights reserved. -
Harnessing Salt-Tolerant Medicinal Plants: A Sustainable Approach to Agriculture and Herbal Medicine
Global agricultural productivity is significantly hampered by salt-affected soils, which calls for sustainable management techniques. The promise of salt-tolerant medicinal plants as a twofold answer for recovering saline lands and generating useful phytochemicals for therapeutic applications is highlighted in this review. Through a variety of adaptation processes, such as osmoprotection, ion compartmentalization, and antioxidant defense, certain medicinal species, such as Aloe vera, Catharanthus roseus, Plantago ovata, Capparis spp., and Salicornia, exhibit an innate tolerance to high salinity. Exogenous applications of plant biostimulants, beneficial microbes, and nanoparticles can further increase their resilience. Furthermore, the integration of omics approachesgenomics, transcriptomics, proteomics, and metabolomicshas advanced our understanding of the molecular basis of salt tolerance and secondary metabolite regulation in these plants. In addition to promoting their wider application in saline agriculture and herbal medicine, this review highlights the ecological and pharmacological importance of salt-tolerant medicinal plants, providing a viable route to soil regeneration and the synthesis of bioactive compounds. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Harnessing Technology for a Sustainable Future in Finance: The Role of Artificial Intelligence in Promoting Environmental Responsibility
The integration of artificial intelligence (AI) into sustainable finance has become a focal point in recent years, propelled by global concerns about the environment and the pressing need for sustainable development. AI technologies, equipped with advanced capabilities, offer significant opportunities to address challenges faced by financial institutions, investors, and policymakers, ushering in the prospect of a more sustainable and inclusive economy. AI's applications in sustainable finance cover diverse areas such as environmental risk assessment, green investment analysis, climate change modeling, and the integration of Environmental, Social, and Governance (ESG) factors. By leveraging advanced data analytics and machine learning algorithms, AI empowers financial institutions to assess environmental risks associated with investments and portfolios, identifying climate-related opportunities and seamlessly integrating ESG factors into decision-making processes. Furthermore, AI-driven technologies streamline the collection, processing, and analysis of extensive data from varied sources, facilitating precise and timely sustainability reporting. These technologies contribute to identifying sustainable investment trends and play a crucial role in monitoring the progress of sustainability initiatives. AI algorithms also aid in crafting predictive models for climate-related events, assisting investors and policymakers in evaluating the long-term financial implications of climate change and formulating effective mitigation strategies. While the adoption of AI in sustainable finance offers immense potential, it is not without challenges and risks. Ethical considerations, data quality and biases, transparency, and the interpretability of AI models are among the key concerns that require careful attention. Additionally, the establishment of regulatory frameworks and industry standards is essential to ensure the responsible and ethical use of AI technologies in finance. In spite of these challenges, the integration of AI in sustainable finance holds great promise for expediting the transition towards a greener and more sustainable future. It empowers stakeholders to make well-informed decisions, advocates for responsible investment practices, and contributes significantly to the attainment of global sustainability goals. By harnessing the capabilities of AI, financial institutions and policymakers can unlock new opportunities, mitigate risks, and cultivate a financial system that is not only sustainable but also resilient. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Harnessing technology for mitigating water woes in the city of Bengaluru
Industrialization has caused most of the world's environmental problems like climate change, water security issues, biodiversity issues among others. Water-related issues like water scarcity, lack of water quality, water sanitation issues, lack of proper water resources management are some of them. Urbanization, population increase, pollution has led to an increase in water demand. Water being the elixir of life, is essential for the day-to-day living of an individual. The Fourth Industrial Revolution technologies like AI, IoT, Blockchain, Machine Learning have the capability of bringing solutions to these issues. The current study focuses on the water woes of Bengaluru, a fast-growing urban city, due to its migrating population. The woes are also due to the irresponsible behaviour of builders converting lakes into real estate infrastructure leading to clogged drains, excess sewage creation and flooding. A huge mismatch between demand and supply of water is created due to these issues. Before the city hits the Day Zero - no water day, it is significant to set up water infrastructure along with technology implementation which will help resolve this burning issue at the earliest. Published under licence by IOP Publishing Ltd. -
Harnessing technology for mitigating water woes in the city of Bengaluru /
Journal of Physics: Conference Series, Vol.1427, pp.1-12, ISSN No: 1742-6596. -
Harnessing the Future: Emerging AI Trends Shaping SME Growth in Emerging Markets
With AI revolutionizing industries, SMEs in emerging markets can tap into its power for sustainable growth, operational efficiency, and enhanced customer experiences. This chapter explores AI- driven automation, predictive analytics, and personalized interactions, addressing challenges like technical skills, data availability, and cost. By adopting AI strategically, SMEs can overcome barriers, compete globally, and drive innovation, ensuring long- term success in the evolving digital economy. 2026 by IGI Global Scientific Publishing. -
Harnessing the Internet of Things for Sustainable Urbanization: A Framework for Resilient Smart Cities
The Internet of Things (IoT) represents a revolutionary technology, which facilitates the emergence of dynamic network of inter-connected devices that can flawlessly communicate and share information. It also merges various technologies, hardware systems, and software frameworks to form an all-embracive ecosystem, which comprises data, people, devices, and smart communication. In a country like India, which exhibits major regional differences in the degree of technology and IoT adoption, it can easily be considered that the idea of IoT has the enormous potential to transform the urban development process and introduce it into the paradigm of improvability, cost-efficient, and maintenance friendly solutions. The issues of smart cities are central to the development of a country and better life of citizens. In India, use of IoT in smart city projects makes it easier to provide core services to constituents, implement transparent governance strategies, and build sustainable urbanization. With the help of IoT, different systems may correlate effectively which will provide a reliable access to the data and the establishment of new opportunities in the form of innovative digital services that would meet the requirements of city residents. The present research paper explores the centrality of IoT in the development of smart cities in India. It discusses the policy framework of IoT in the country, outlines major drivers of and benefits of IoT-based smart city solutions, analyzes consumer preferences and demographics. With this comprehension, the paper would like to suggest practical insights concerning the use of IoT in creating inclusive and technology-driven cities of India. 2025 IEEE. -
Harnessing the Power of Big Data Analytics to Transform Supply Chain Management
The study aims to conduct a systematic literature review and bibliography analysis to explore the role of big data analytics in transforming supply chain management. The systematic literature review was conducted according to the PRISMA guidelines extended into a three-phase approach. The articles were reviewed from different databases like Scopus, Web of Science, and ABDC. 239 articles were reviewed through abstract screening, and 191 articles were finally selected after full-text screening. The results of the analysis reflected the publication trend from January 2011 to January 2024, keyword analysis, co-citation and network analysis, and theme identification from the domain. Moreover, the study theoretically contributes by suggesting growing trends in the field of supply chain management, and the managerial implications of the study suggest the benefits of implementing big data analytics in supply chain management. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Harnessing the Power of Climate Activism: Insights from Psychological Perspectives on Climate Change EngagementA Systematic Review
Scientific evidence has validated the inevitability of global warming and its effect in the form of climate change. There has been an increase in climate strikes and other forms of climate activism in recent years. It is important to understand the research landscape in psychological literature with regards to climate change and climate activism, to help guide future researchers. The databases of PubMed (Keywords: climate activism, climate change, psychology, n?=?1), Google Scholar (Keywords?=?climate activism, climate change, psychology, n?=?200) and Scopus database (Keywords: climate activism AND climate change AND psychology, n?=?160) were searched to create the pool of research documents. This was further filtered according to the inclusion and exclusion criteria. In the first section of this article, we have tried to explore the temporal and geographic growth trends of climate change research and collaborations using R (Bibliometric package). In the second section, we have used a text-mining approach to identify the research topics being explored in the climate change literature. R package tm along with associated packages were used to do the processing and subsequent grouping of the themes. In order to refine the classification the identified groupings were supervised by the authors. The final documents have been scoured to extract an overall understanding of the existing concepts explored so far and gauge their impact in the realm of climate change research. This systematic study casts light on the psychological views on climate activism and offers insightful information about the underlying causes that affect peoples involvement in the fight and struggle against climate change. The creation of more effective techniques for encouraging climate activism and utilizing its capacity to inspire significant action to address climate change can be influenced by an understanding of these elements. In order to address the complex issues of climate change, this chapter emphasizes the value of multidisciplinary collaboration amongst psychologists, policymakers, educators, and activists. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Harnessing the Power of Cloud Computing for Advanced Business and Economic Research
Cloud computing has surfaced as a significant influence in the domain of business and economic research. Its ability to deliver vast computational resources, scalable storage, and unparalleled accessibility has revolutionized the way researchers analyze complex datasets, conduct simulations, and collaborate on ground-breaking projects. This paper delves into the myriad ways cloud computing is empowering researchers to unlock unprecedented economic insights. This research article delves into the key dimensions of leveraging cloud computing for advanced business and economic research. It investigates the scalability and flexibility of cloud-based infrastructure, enabling researchers to process and analyze extensive datasets, conduct complex simulations, and implement machine learning algorithms for predictive modeling. Moreover, the cloud facilitates real-time collaboration and data sharing, fostering a global research community that transcends geographical boundaries. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Harnessing the power of digital transformation to promote sustainable growth enabling companies and societies to build a durable and inclusive future
This chapter explores the critical role of digital transformation in fostering sustainable development across various industries. It highlights how advanced technologies such as the Internet of Things, artificial intelligence, and big data analytics enhance environmental sustainability by improving operational efficiency and enabling informed decision-making. Key issues discussed include the connections between digital transformation and environmental sustainability, as well as the challenges organizations face during implementation. The chapter includes case studies demonstrating the successful use of digital technologies to address environmental challenges like air and water pollution and promote resource conservation. It emphasizes the importance of ethical leadership and stakeholder engagement in guiding digital initiatives toward genuine sustainability goals. Finally, the chapter presents a comprehensive framework for leveraging digital transformation to encourage sustainable behaviors and achieve global sustainability objectives. 2025, IGI Global Scientific Publishing. All rights reserved. -
Harnessing the Power of Simulation Games for Effective Teaching in Business Schools
This research delves into the effectiveness of simulation games, in business education specifically focusing on how they improve decision making skills, critical thinking, real world business applications, student engagement and problem-solving abilities. While simulation games are widely recognized as cutting edge tools that provide learning experiences beyond traditional methods there remains a gap in empirical research assessing their overall impact on educational outcomes. Using a combination of analysis and qualitative case studies this study seeks to address this gap by examining how simulation games influence factors in business education. The methodology involves using a one-way ANOVA to compare learning outcomes across business disciplines and conducting detailed case studies for context. The results reveal effects of integrating simulation games into curricula on the mentioned learning outcomes. These findings highlight the importance of incorporating simulation games into business education to enhance students learning experiences effectively. By offering insights on optimizing and tailoring the use of simulation games in education settings this study contributes to improving teaching practices in business schools and encourages research into the interaction, between educational technology and learning efficacy. 2024 IEEE. -
Harnessing the Transformative Potential of Blockchain Technology to Accelerate the Global Transition Toward a Scalable, Transparent, and Resilient Circular Economy Framework
Blockchain technology applied to circular economy has a world-changing potential to increase transparency, traceability, and the sustainability of the resources management. With the shift towards regenerative industries, it is of the essence to have the capacity to track the lifecycle of used products, used materials, and waste securely. A new method (Circular Blockchain-Resource Lifecycle Management (CB-RLM) algorithm) is proposed in this work that is supposed to maximize the monitoring and incentivization resource flow in the context of decentralized systems. Using a blockchain as a platform allows conducting real-time monitoring of materials backtracking, and the proposed approach will provide a way of materials following all stages of production, consumption, reuse, and recycling. The algorithm combines the information presented by the means of the IoT-enabled devices to guarantee permanent verification of product statuses and ownership, whereas smart contracts automatically sanction the policy compliance of reuse and returns. The system also creates digital tokens as rewards to sustainable behavior during processes, which gives the stakeholders incentive to engage in the circular economy. The mechanism will not only facilitate resource efficiency and accountability but it will promote trust among the members of the supply chain. The suggested CB-RLM algorithm also has the potential to solve such key design problems as data integrity, stakeholder cooperation and lifecycle openness, thus paving the way to the creation of scalable and smart circular systems. This model brings a more environmentally responsible and resilient industrial ecosystem by means of decentralized enforcement and automated incentives. The suggested CB-RLM technique achieves an overall accuracy of 99.4%. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.