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Efficient one-pot green synthesis of carboxymethyl cellulose/folic acid embedded ultrafine CeO2 nanocomposite and its superior multi-drug resistant antibacterial activity and anticancer activity
Due to the prevalence of drug-resistant bacteria and the ongoing shortage of novel antibiotics as well as the challenge of treating breast cancer, the therapeutic and clinical sectors are consistently seeking effective nanomedicines. The incorporation of metal oxide nanoparticles with biological macromolecules and an organic compound emerges as a promising strategy to enhance breast cancer treatment and antibacterial activity against drug-resistant bacteria in various biomedical applications. This study aims to synthesize a unique nanocomposite consisting of CeO2 embedded with folic acid and carboxymethyl cellulose (CFC NC) via a green precipitation method using Moringa oleifera. Various spectroscopic and microscopic analyses are utilized to decipher the physicochemical characteristics of CFC NC and active phytocompounds of Moringa oleifera. Antibacterial study against MRSA (Methicillin-resistant Staphylococcus aureus) demonstrated a higher activity (95.6%) for CFC NC compared to its counterparts. The impact is attributed to reactive oxygen species (ROS), which induces a strong photo-oxidative stress, leading to the destruction of bacteria. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of CFC NC are determined as 600g/mL and 1000g/mL, respectively. The anticancer activity against breast cancer cell resulted in the IC50 concentration of 10.8?g/mL and 8.2?g/mL for CeO2 and CFC NC respectively.The biocompatibility test was conducted against fibroblast cells and found 85% of the cells viable, with less toxicity. Therefore, the newly synthesized CFC NC has potential applications in healthcare and industry, enhancing human health conditions. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Psidium guajava-mediated green synthesis of Fe-doped ZnO and Co-doped ZnO nanoparticles: a comprehensive study on characterization and biological applications
The efficacy of nanoparticles (NPs) in healthcare applications hinges on their biocidal activity and biocompatibility. This research is dedicated to green-synthesized NPs with potent biocidal properties, aiming for high inhibition rates in bacterial infections and offering a multifunctional application, including potential use in anticancer therapy, in comparison to traditional antibiotics. The present study focuses on synthesis of zinc oxide (ZnO) nanoparticles (NPs), including iron-doped ZnO (GZF) and cobalt-doped ZnO (GZC), using the green co-precipitation method involving Psidium guajava (P. guajava) leaf extract. The physicochemical properties of the synthesized NPs were analyzed using various characterization techniques. The antibacterial and anticancer activity depends on the generation of reactive oxygen species (ROS), particle size, surface area, oxygen vacancy, Zn2+ release, and diffusion ability. The antibacterial activity of the synthesized NPs was tested against various Gram-positive (Streptococcus pneumoniae (S. pneumoniae), Bacillus subtilis (B. subtilis) and Gram-negative (Klebsiella pneumoniae (K. pneumoniae), and Pseudomonas aeruginosa (P. aeruginosa) bacterial strains. The zone of inhibition showed higher activity of GZC (1820mm) compared to GZF (1619mm) and GZO (1115mm) NPs. Moreover, anticancer studies against blood cancer cell line (MOLT-4) showed half-maximal inhibitory concentration of 11.3?g/mL for GZC compared to GZF and GZO NPs with 12.1?g/mL and 12.5?g/mL, respectively. Cytotoxicity assessments carried out on the fibroblast L929 cell line indicated that GZO, GZF, and GZC NPs demonstrated cell viabilities of 85.43%, 86.66%, and 88.14%, respectively. Thus, green-synthesized GZC NPs hold promise as multifunctional agents in the biomedical sector. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Contradictions in conservation: Indias forest (Conservation) Amendment Bill, 2023
[No abstract available] -
The SDG conundrum in India: navigating economic development and environmental preservation
The paper explores the complex interplay between economic development and environmental sustainability in the context of Indias pursuit of the Sustainable Development Goals (SDGs). It examines the inherent contradictions and trade-offs involved, particularly in agriculture, industrialisation, and infrastructure sectors. The paper highlights how economic growth, essential for improving living standards, often conflicts with environmental objectives. The paper underscores the importance of integrating economic, environmental, and social objectives to achieve a sustainable and inclusive future for India. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Media Framing of Indian Green Fiscal Policy: A Survey of Environmental Policies Across Online News Portals
This research undertakes a framing analysis of news coverage from five leading Indian news portals, focusing on the environmental provisions of India's fiscal budgets for 2022-23 and 2023-24. These budgets marked a significant shift, being the first to prioritize "Energy Transition and Climate Action" and "Green Growth" as central themes. The analysis uncovers a spectrum of portrayals: from highlighting government initiatives and the potential economic windfalls of green policies to critical evaluations and concerns about their real-world implications. Specifically, the Times of India, with its 27 stories, leans heavily towards business and economic perspectives. The Hindu, through its five stories, both praises the government's green initiatives and critiques certain infrastructure projects. Hindustan Times offers a balanced view in its nine stories, juxtaposing government action plans against critiques of infrastructure spending. In contrast, The Scroll and The Wire, each with three stories, delve deeper, providing incisive, critical analyses of the government's environmental commitments. The study underscores that while independent news portals present nuanced insights, their narratives often stand in the shadow of mainstream portals that echo the government's perspective. Given the escalating global importance of environmental challenges, the findings strongly advocate for media outlets to establish dedicated environmental news sections. Such focused coverage could enhance public awareness and pressurize effective governmental action in the domain of green fiscal policies. 2023 by authors, all rights reserved. -
Indias environmental policy paradox: dissecting Indias budgetary allocations for environment
This paper examines Indias environmental policies and budget allocations from 20162024, revealing a focus on infrastructure that may overshadow environmental conservation. Significant discrepancies between policy rhetoric and budgetary commitments suggest that there is a need for realignment. Advocating an environment-centric approach, the study calls for increased budgetary commitments to environmental protection, a strategic shift away from fossil fuels, and stringent regulatory oversight, all essential to ensure sustainable development in India. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Spatio-temporal crime analysis using KDE and ARIMA models in the Indian context
In developing countries like India, crime plays a detrimental role in economic growth and prosperity. With the increase in delinquencies, law enforcement needs to deploy limited resources optimally to protect citizens. Data mining and predictive analytics provide the best options for the same. This paper examines the news feed data collected from various sources regarding crime in India and Bangalore city. The crimes are then classified on the geographic density and the crime patterns such as time of day to identify and visualize the distribution of national and regional crime such as theft, murder, alcoholism, assault, etc. In total, 68 types of crime-related dictionary keywords are classified into six classes based on the news feed data collected for one year. Kernel density estimation method is used to identify the hotspots of crime. With the help of the ARIMA model, time series prediction is performed on the data. The diversity of crime patterns is visualized in a customizable way with the help of a data mining platform. Copyright 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. -
Geo-spatial crime analysis using newsfeed data in indian context
Social media is the platforms where users communicate, interact, share ideas, career interest, pictures, video, etc. Social media gives an opportunity to analyze the human behavior. Crime analysis using data from social media such as Newsfeeds, Facebook, Twitter, etc., is becoming one of the emerging areas of research for law enforcement organizations across the world. The intelligence gathered through data is used for identifying future attacks and plan for reinforcements. This article focuses on the implementation of textual data analytics by collecting the data from different newsfeeds and provides an optimized visualization. This article establishes a framework for better prediction of 16 types of crime in India and the Bangalore area by providing the coordinates of the crime area, along with the crime which might happen there. 2019, IGI Global. -
Student engagement and learning during COVID-19: an empirical analysis
COVID-19 pandemic brought along with it a widespread disruption of education system around the world. Schools, colleges and universities were shut all over the world. In order to maintain the continuity of education, educators and students alike adopted the online mode of teaching and learning. While mainstream education was mostly face-to-face; a sudden shift to the online mode of teaching and learning required teachers and students to get acquainted with the platform and tools. This study attempts to test a model to understand the impact of online education on students engagement levels in the context of higher education and the COVID-19 pandemic. Results indicate that access to digital resources and teacher effectiveness has positive impact on engagement and student engagement in turn has positive impact on learning outcomes. Stress has negative impact on student learning. The paper also discusses implications of the study and future direction for research. Copyright 2022 Inderscience Enterprises Ltd. -
Breeding Potential of Crosses Derived from Parents Differing in Overall GCA Status for Productivity per se Traits and Powdery Mildew Disease Response in Blackgram [Vigna mungo (L.) Hepper]
Background: Predicting the breeding potential of crosses in terms traits means, genetic variability and frequency of desirable transgressive segregants in early segregating generations is crucial in breeding programme. Therefore, an experiment was carried out to assess breeding potential of crosses involved parents with varying overall GCA status and contrasting responses to powdery mildew disease (PMD) in blackgram. Methods: Total of 40 F1 s developed by following Line Tester design; among, nine crosses were selected based on gca status of parents and responses to PMD. F1, F2 and F3 along with parents of six and three crosses were evaluated for 10 productivity per se traits and responses to PMD separately during kharif, 2016 and rabi, 2016-17 respectively. The traits means, absolute and standardized range, PCV and frequency of transgressive segregants in F2 and F3 were compared to assess the breeding potential of the crosses. Result: F2 and F3 generations derived from six crosses (for productivity traits) and three crosses (for PDI) were differed for means, absolute and standardized range, PCV and the frequency of transgressive segregants. This is may be due to the contribution of diverse genes from female and male parent. Though considerable number of transgressive segregants were also identified in F2 and F3 of all the crosses, high frequency of desirable transgressive segregants was observed in crosses involved parents with overall high GCA status. 2024, Agricultural Research Communication Centre. All rights reserved. -
Emprical Study of Crypto Currency and its Adoption Among Indians
This paper investigates many factors that impact cryptocurrency awareness and acceptance in the Indian market. Data were obtained from 376 volunteers of various ages across India. The following paper presented a framework based on EFA (Exploratory Factor Analysis), CFA (Confirmatory Factor Analysis), and SEM (Structural Equation Model). Technology awareness, recommendations to others, attitude, social influence, and openness to technical education were all responsible for bitcoin adoption. Meanwhile, trust and perceived risk were not accountable for the adoption of crypto currency. No significant factors directly responsible for the adoption or abandonment of crypto currencies were mentioned in the papers that were read. The Indian market is still not thoroughly studied regarding crypto currency and the population using it. It would create a massive opportunity for crypto currency to operate in the Indian market once the factors responsible for crypto currency adoption are known 2024 IEEE. -
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Application of Hydrogel in Paddy Field for Soil Moisture Retention and Yield Optimization
Agricultural sustainability is essential to enhance food and water security, particularly in the context of climate change. To ensure food security and to protect water resources, agricultural and irrigation practices need to be amended with innovative technology that conserves water and increases productivity. In the recent past, applications of hydrogels in agriculture have received substantial attention among researchers as well as among farmers. Paddy is the core crop for the vast newlineparts of the world. The present study elaborates on various aspects of hydrogels such as classifications, ideal properties for agricultural application, analysis of soil characteristic changes for pre and post crop newlineseason, irrigation water quality analysis for crop season. BPT 5204 and NDLR 07 varities of paddy had been experimented in this study. newlineVerification of hydrogel degradation was conducted using Fourier transform infrared (ft-ir) spectroscopy. The experimental methods for determining hydrogel properties were given specific attention to properties such as swelling, retention, slow release, and degradation which are vital for agricultural sustainability. Hydrogel experiments have demonstrate significant improvement in water consumption, water use newlineefficiency, crop growth and yield parameters. The reduction in water footprint in major crops such as paddy and wheat through hydrogel might establish a shift towards sustainable irrigation practices if adopted on a large scale. Integrating innovative solutions with environmental-friendly newlinehydrogels in the coming decades will contribute to the pursuit of achieving newlinesustainable development goals. The application of hydrogel as soil conditioners was identified as a possible solution. to increase water use efficiency in irrigation and optimization of crop yield. The study points towards developing a framework for the evaluation of the suitability of hydrogel for agricultural applications when get scaled up to regional level. -
Eco-friendly synthesized nanoparticles as antimicrobial agents: an updated review
Green synthesis of NPs has gained extensive acceptance as they are reliable, eco-friendly, sustainable, and stable. Chemically synthesized NPs cause lung inflammation, heart problems, liver dysfunction, immune suppression, organ accumulation, and altered metabolism, leading to organ-specific toxicity. NPs synthesized from plants and microbes are biologically safe and cost-effective. These microbes and plant sources can consume and accumulate inorganic metal ions from their adjacent niches, thus synthesizing extracellular and intracellular NPs. These inherent characteristics of biological cells to process and modify inorganic metal ions into NPs have helped explore an area of biochemical analysis. Biological entities or their extracts used in NPs include algae, bacteria, fungi, actinomycetes, viruses, yeasts, and plants, with varying capabilities through the bioreduction of metallic NPs. These biosynthesized NPs have a wide range of pharmaceutical applications, such as tissue engineering, detection of pathogens or proteins, antimicrobial agents, anticancer mediators, vehicles for drug delivery, formulations for functional foods, and identification of pathogens, which can contribute to translational research in medical applications. NPs have various applications in the food and drug packaging industry, agriculture, and environmental remediation. Copyright 2023 Borehalli Mayegowda, Roy, N. G., Pandit, Alghamdi, Almehmadi, Allahyani, Awwad and Sharma. -
Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review
Wheeled mobile robots (WMRs) have been a focus of research for several decades, particularly concerning navigation strategies in static and dynamic environments. This review article carefully examines the extensive academic efforts spanning several decades addressing navigational complexities in the context of WMR route analysis. Several approaches have been explored by various researchers, with a notable emphasis on the inclusion of stability and intelligent capabilities in WMR controllers attracting the attention of the academic community. This study traces historical and contemporary WMR research, including the establishment of kinetic stability and the construction of intelligent WMR controllers. WMRs have gained prominence in various applications, with precise navigation and efficient control forming the basic prerequisites for their effective performance. The review presents a comprehensive overview of stability analysis and navigation techniques tailored for WMRs. Initially, the exposition covers the basic principles of WMR dynamics and kinematics, explaining the different wheel types and their associated constraints. Subsequently, various stability analysis approaches, such as Lyapunov stability analysis and passivation-based control, are discussed in depth in the context of WMRs. Starting an exploration of navigation techniques, the review highlights important aspects including path planning and obstacle avoidance, localization and mapping, and trajectory tracking. These techniques are carefully examined in both indoor and outdoor settings, revealing their benefits and limitations. Finally, the review ends with a comprehensive discussion of the current challenges and possible routes in the field of WMR. The discourse includes the fusion of advanced sensors and state-of-the-art control algorithms, the cultivation of more robust and reliable navigation strategies, and the continued exploration of novel WMR applications. This article also looks at the progress of mobile robotics during the previous three decades. Motion planning and path analysis techniques that work with single and multiple mobile robots have been discussed extensively. One common theme in this research is the use of soft computing methods to give mobile robot controllers cognitive behaviors, such as artificial neural networks (ANNs), fuzzy logic control (FLC), and genetic algorithms (GAs). Nevertheless, there is still a dearth of applications for mobile robot navigation that leverage nature-inspired algorithms, such as firefly and ant colony algorithms. Remarkably, most studies have focused on kinematics analysis, with a small number also addressing dynamics analysis. 2023 by the authors. -
Optimizing Drug Discovery for Breast Cancer in a Laboratory Environment Using Machine Learning
Breast cancer therapy can be greatly enhanced by the proposed method that combines experimental and computational techniques. Employing a state-of-the-art in vitro system, we evaluated biopsy tissues at different cancer stages, monitoring them for 48 hours. Later on, our investigation involved the application of machine learning models including nae Bayes (NB), artificial neural networks (ANN), random forest (RF), and decision trees (DT). Surprisingly, these models reached high test accuracies - ANN 93.2%, NB 90.4%, DT 87.8%, and RF 85.9%. The dataset's impedance dynamics data provide evidence for treatment efficacy. Therapeutic strategies need to be adjusted for particular patients and their stage of cancer since the results underscore the usefulness of personalized breast cancer therapy. This study will significantly contribute to new tailored treatment options available for breast cancer patients. 2024 IEEE. -
Role of medicinal plants against lung cancer
Nowadays for treatment of various diseases, scientific studies are conducted using the medicinal plants of both domestic and wild for curing purpose. Every plant contain compounds that have medicinal properties and can be isolated from the plants parts. Due to plants diversity in India and use in Ayurveda, Unani and Siddha, India is known as medicinal hub. Lung cancer is the third most common cancer, that develops in lung tissue and are of two type's non-small cell lung cancer and small cell lung cancer. Many factors cause lung cancer; tobacco smoking is the prominent cause of lung cancer. The individuals who smoke have 20-30% more chance of developing lung cancer than non-smokers. The conventional treatment of lung cancer, are chemotherapy, stem cell therapy, and electrochemical treatments. Plants and the compounds present can be used for treating lung cancer. So in this chapter will focus on plants Acalypha indica, Solanum trilobatum, Justicia adhatoda, Coleus amboinicus and Piper nigrum in lung cancer treatment and on the medicinal properties. 2024, IGI Global. -
Artistic Representation of Gender Nonconforming Female Bodies in Social Media: A Study of Select Indian Graphic Artists on Instagram
The study critically examines gender nonconforming female identities via their sex-ualized representations through artistic imagination on Instagram. Instagram representation becomes a political act where this visual subversion allows the queer to reclaim their non-binary identity and thus articulate their choices through their body. The digital graphic art taken under study is select images from the Instagram pages of Indian artists artwhoring, aorists, and sayartic. The research study examines the question of an ideal hegemonic femininity perpetuated by the rhetoric of Indian heteronormative patriarchal assertions. It analyses select images that defy hegemonic femininity and gender binary by embodying an amalgamation of masculinity and femininity and lesbian desire which forms an act of subversion. The methodology of critical discourse analysis is employed to study Instagram art and the critical frameworks of the fantasy female body, and the notion of hetero-patriarchal femininity. In conclusion, the study discusses the treatment of female gender non-conforming bodies, their appearance, lesbian desire, and body image. Such transgressive depiction of bodies successfully situates the female body beyond the dichotomy of masculinity and femininity. 2023 The Author(s). All rights reserved. -
A Comparative Study of Machine Learning Techniques for Credit Card Customer Churn Prediction
A customer is a churner when a customer moves from one service provider to another. Nowadays, with an increasing number of severe competition with inside the market, essential banks pay extra interest on customer courting management. A robust and real-time credit card holders churn evaluation is vital and valuable for bankers to preserve credit cardholders. Much research has been observed that retaining an old customer is more than five times easier compared to gaining a new customer. Hence, this paper proposes a method to predict churns based on a bank dataset. In this work, Synthetic Minority Oversampling Technique (SMOTE) has been used for handling the imbalanced dataset. Credit card customer churn is predicted using random forest, k-nearest neighbor, and two boosting algorithms, XGBoost and CatBoost. Hyperparameter tuning using grid search has been used to increase the accuracy. The experimental result shows Catboost has achieved an accuracy of 97.85% and tends to do better than the other models. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Machine learning insights into mental health risk factors associated with climate change: Impact on schoolchildren's cognitive abilities
In this chapter, we use machine learning techniques to investigate how the effects of climate change and certain risk factors for mental health affect students' cognitive skills in the classroom. The mental health of at-risk populations, especially students, must be considered in light of the fact that the world's environment is changing significantly. Using state-of-the-art machine learning algorithms, we analyze large datasets that include environmental variables, socio-economic characteristics, and markers of mental health among school-aged persons. We are primarily interested in identifying key relationships and trends that might help us understand the complex relationship between climate change and cognitive health in this population. In order to uncover complex insights, the chapter takes a holistic approach by combining feature selection, model training, and interpretability analysis. The cognitive capacities of school-aged children may be significantly impacted by some climate- related stresses, according to preliminary results. The findings add to our knowledge of the interconnected webs of environmental shifts, psychological susceptibilities, and cognitive consequences. Educators, legislators, and healthcare providers can benefit from this study's use of machine learning insights into the possible effects of climate change on students' mental health. It also paves the way for the creation of tailored treatments and adaptive techniques to deal with the highlighted dangers, fostering resilience and prosperity in the face of a changing environment. 2024, IGI Global. All rights reserved.