International Journal of Scientific Research in Science and Technology
International Journal of Scientific Research in Science and Technology (IJSRST) is peer-reviewed, online international journal published Bimonthly by Technoscience Academy. IJSRST is a highly-selective journal, covering topics that appeal to a broad readership in various branches of Science and Technology and related fields. The journal has many benefits, all geared toward strengthening research skills and advancing academic careers. Journal publications are a vital part of academic career advancement. To maintain a high-quality journal, manuscripts that appear in the IJSRST Articles section have been subjected to a rigorous review process. This includes blind reviews by one or more members of the international editorial review board, followed by a detailed review by the IJSRST editors. Email addresses for submitting articles are editorijsrst@gmail.com, editor@ijsrst.com JOURNAL INFORMATION Title : International Journal of Scientific Research in Science and Technology Frequency : Bimonthly Online ISSN : 2395-602X | Print ISSN : 2395-6011 Publisher : Technoscience Academy [ https://technoscienceacademy.com ] Refereed : Peer Review Copyright : Technoscience Academy, India Starting Year : 2014 Subject : Science and Technology Language : English Distribution : Open Access Publication Format : PDF & HTML -> Online Document Identifier Type : DOI (https://doi.org/10.32628/IJSRST ) Email Id : editor@ijsrst.com, editorijsrst@gmail.com Mobile No. : +91-8160745806 (WhatsApp support only) Website : https://ijsrst.com
Ni (II) - Selective Potentiometric Sensor Based on New Schiff base ligand, S-octyl-3-(furan-2-ylmethylene) dithiocarbazate
The construction and performance of a polymeric membrane electrode made with a new Schiff base called S-octyl-3-(furan-2-ylmethylidene) dithiocarbazate [L] for measuring nickel ions is described. The study revealed that the electrode performance is strongly influenced by the composition of the membrane matrix. The best results were achieved with a membrane made of (L) (2.5%): PVC (32.6%): DOP (62.4%): NaTPB (2.5%). This electrode gives a Nernstian response for nickel ions in concentrations between 4.2×10-8 and 1.0×10-1 M, with a detection limit of 2.1×10-9. It works well across a wide pH range from 2.5 to 10 and responds quickly, in about 9 seconds. The electrode also works in partially non-aqueous solutions containing up to 30% (v/v) methanol, ethanol, or acetonitrile and can be used for up to 3.0 months. It has excellent selectivity for Ni(II) over other mono-, bi- and trivalent cations. Its usefulness for analysis was tested by using it to measure nickel in various samples. The sensor's practical use was shown by using it as an indicator electrode in potentiometric titrations of Ni²+ against EDTA.
Copyright (c) 2026 International Journal of Scientific Research in Science and Technology https://creativecommons.org/licenses/by/4.0
Mythology as Enchantment: Understanding The Narrative Magic and Cultural Significance of Devdutt Pattanaik’s Mythological Retellings
Mythology has long functioned as a powerful narrative system through which societies interpret existence, morality, and cultural identity. In contemporary literary discourse, mythological retellings have gained renewed significance as authors reinterpret ancient narratives for modern audiences. Devdutt Pattanaik emerges as one of the most prominent contemporary interpreters of Indian mythology, whose writings transform traditional myths into accessible and thought-provoking narratives. His works do not merely reproduce mythological stories; rather, they reinterpret them through symbolic analysis, cultural commentary, and philosophical reflection. Pattanaik’s narrative approach demonstrates how mythology operates as a form of enchantment—an imaginative force that captivates readers while simultaneously conveying deeper cultural meanings. As Pattanaik himself observes, “Myth is somebody’s truth, shaped by imagination, culture, and belief” (Pattanaik, Myth = Mithya). This perspective highlights mythology not as a fixed historical record but as a living narrative tradition that continues to evolve across generations. The concept of enchantment within Pattanaik’s mythological retellings lies in his ability to combine storytelling with symbolic interpretation. His narratives create a sense of narrative magic by presenting mythological events in ways that resonate with contemporary sensibilities while remaining rooted in traditional philosophical frameworks. In texts such as Jaya: An Illustrated Retelling of the Mahabharata and Sita: An Illustrated Retelling of the Ramayana, Pattanaik blends narrative explanation with interpretative commentary, allowing readers to engage with myth not only as a story but also as a philosophical dialogue about human values and cosmic order. He argues that myths are not concerned with objective facts but with meaning, stating that “mythology is not history; it is a way of making sense of the world” (Pattanaik, Jaya). Through this interpretative strategy, mythology becomes a space where imagination, culture, and spirituality intersect to produce narratives that remain relevant in contemporary society. Another significant dimension of Pattanaik’s mythological writing is its emphasis on cultural symbolism. His retellings reveal how mythological characters, rituals, and narratives function as cultural metaphors that reflect social values, ethical dilemmas, and human aspirations. By interpreting myths through symbolic analysis, Pattanaik highlights the cultural significance embedded within these narratives. For example, he frequently interprets mythological events as reflections of philosophical concepts such as dharma, cosmic balance, and the cyclical nature of existence. In his discussions of mythology, Pattanaik notes that “every symbol in mythology carries layers of meaning shaped by cultural imagination” (Pattanaik, Seven Secrets of Hindu Calendar Art). This symbolic framework allows readers to understand mythological narratives not merely as religious stories but as cultural texts that encode complex systems of belief and moral understanding. Furthermore, Pattanaik’s mythological retellings contribute to the contemporary revival of myth as a narrative form capable of bridging tradition and modernity. In a globalized cultural environment, mythological storytelling becomes a means of reconnecting audiences with cultural heritage while encouraging critical reflection on traditional narratives. Pattanaik’s work illustrates how mythology can remain dynamic and adaptable, capable of engaging modern readers without losing its philosophical depth. His reinterpretations invite readers to question conventional assumptions and explore multiple perspectives embedded within mythological traditions. As he emphasizes in his writings, “myths are mirrors that reflect the societies that create them” (Pattanaik, My Gita). Ultimately, Pattanaik’s mythological retellings demonstrate that mythology functions as an enchanting narrative medium through which cultural memory, philosophical reflection, and imaginative storytelling converge. By presenting ancient narratives through accessible language and symbolic interpretation, he revitalizes mythology as a living tradition that continues to shape cultural consciousness. The enchantment of his storytelling lies not only in the narrative appeal of myth but also in its capacity to reveal deeper insights into human experience, belief systems, and cultural identity. Through this approach, mythology becomes both a source of narrative fascination and a profound cultural discourse that connects the past with the present.
Prototype of Paving Stones Based on Construction and Demolition Waste
This work addressed the problem of waste management, with an emphasis on the recycling of construction and demolition waste (CDW), through the application of 3D printing and injection molding technologies for the manufacture of eco-friendly paving stones. The results demonstrated the feasibility of producing functional materials that meet specific standards for properties such as water absorption and erosion resistance. However, the paving stones exhibited limitations in compressive strength, restricting their use to areas with low pedestrian traffic. The study concludes that the prototype is technically viable, economical, and environmentally friendly, reducing costs, utilizing waste, and mitigating the carbon footprint, thus demonstrating its potential to promote sustainable practices in the construction sector.
Multifunctional Smog-Mitigating Photocatalytic Paver Blocks Incorporating Graphene Oxide–TiO₂ Nanocomposites with Embedded Piezoelectric Sensor
Nowadays, protecting nature feels more urgent as daily life gets better and economies surge. For civil engineers, creating green building materials is tough yet full of potential. One substance standing out is titanium dioxide - it breaks down tricky pollutants like dyes and hormone-affecting chemicals using light-driven chemical reactions. A closer look at tiny TiO₂ particles inside concrete paver blocks - especially those mixed with Graphene oxide (GO) - reveals how they handle light-driven cleaning of air. These blocks, called "smog-eating," respond by turning invisible UV rays into a tool that breaks down harmful stuff like nitrogen pollutants and small airborne solvents. That breakdown happens through chemical reactions sparked once light hits the active mix. Nanoparticles move through environments using different paths - some stick to surfaces, others break down when wet, while clustering or settling over time. Chemical reactions can change their form, especially around sulfur or light exposure. Tiny particles tend to gather in groups, either with similar or unlike kinds. Their behavior also depends on how they dissolve or get trapped by materials around them. In concrete, substances from TiO₂ and GO react more strongly due to their porous shape. This surface area pulls them into the mixture, altering how they perform. These tiny particles can shape how concrete paver blocks form inside, possibly making them stronger and last longer. Because of that change, looking into how they hold up under stress matters - it shows what they might do in real conditions plus how they affect surroundings. Trying different mixes of the combined material helps find the best version that cleans up more harmful fumes without losing strength. When it comes to paver blocks, adding TiO₂ nanoparticles and GO brings two clear advantages. One helps strengthen the structure while the other boosts the ability to clean air around us.
Secure Multi-Keyword Encrypted Search with Access Control for IoT Systems
Through edge nodes, the enormous terminals connect to the Internet of Things (IoT), creating additional privacy and security issues with data sharing and ciphertext search. Current ciphertext search techniques, on the other hand, frequently ignore lightweight computing paradigms and give scant consideration to the search needs of various data owners (DOs) and data users (DUs). To address these issues, we propose a secure fine-grained multi-keyword ciphertext search scheme with cloud-edge-end collaboration computing (SFMS-CC). This SFMS-CC scheme focuses on the efficiency of end users and employs a cloud-edge-end collaborative computing paradigm, effectively offloading the incremental overhead from terminals and achieving low-cost constant overhead for the first time on the DO/DU side. Additionally, a methodical ciphertext search framework that supports multiple keywords is described, which is based on public-key cryptography. To improve the user experience, each user is given a unique search Tok. A multi-DOs/multi-DUs model is also created by using attribute-based encryption, which smoothly incorporates entity private keys and public keys into encryption, search, decryption, and other processes, guaranteeing the scheme's high level of privacy and security. According to security study, the SFMS-CC system protects user information and outsourced data from plaintext attacks using encryption. According to simulation results, the SFMS-CC method is practical and effective.
Study of Two Functional Requirements, Tag Delegation and Ownership Transfer in RFID System
In this present paper, we consider two functional requirements, tag delegation and ownership transfer, that are likely to be required in some RFID systems. [1-6].
Copyright (c) 2025 International Journal of Scientific Research in Science and Technology https://creativecommons.org/licenses/by/4.0
Study of Security Problems in RFID Systems and Existing Solutions
In this present paper, we consider to measure the performance of an RFID system. On one hand, due to the countless number of tags in industries such as supply chain, the search overhead of a tag in the reader’s back-end database may be overwhelmingly high. Therefore, the search cost should be a concern. On the other hand, in order to protect an RFID system’s security, it is usually to implement an RFID protocol in the system. Thus, another cost of RFID security protocol is cryptographic operation cost as well as reader-tag communication cost. In [1-4], Avoine claimed that a cryptographic operation on a single computer only takes 2-23 second to finish, while it would take a lot more time to finish a cryptographic operation on a tag due to a tag’s limited memory and computational ability. Therefore, cryptographic operation cost in RFID reader side is ignorable.
Assessing Somaclonal Variation in Micro-Propagated Plants: A Comparative Review of Molecular Marker Systems
Micro-propagation has expanded globally and has revolutionized the mass production of elite true-to-type plant varieties as a solution for the rising demands of agriculture and forestry. However, there lies an inherent risk of somaclonal variation induced during the in vitro process. Ensuring the regenerants are “true-to-type” is now not only a laboratory requirement but also a critical safeguard for biodiversity and agricultural stability. This review synthesizes the current landscape of molecular marker technologies used for the assessment of clonal fidelity. A comparative analysis is provided for the most widely used marker systems, including Random Amplified Polymorphic DNA (RAPD), Inter-Simple Sequence Repeats (ISSR), Simple Sequence Repeats (SSR), and Amplified Fragment Length Polymorphism (AFLP). Furthermore, the review highlights the emerging role of Start Codon Targeted (SCoT) markers and the shift toward Single Nucleotide Polymorphism (SNP) genotyping via Next-Generation Sequencing (NGS) for high-throughput validation. The paper emphasizes the relative strengths, limitations and cost effectiveness of these systems and provides a roadmap for commercial breeders and researchers to select the most reliable diagnostic tools for maintaining the genetic blueprint of the plants.
FTIR Spectroscopic Analysis of Epiphytic Pteridophyte: Huperzia Hamiltonii (Spreng.) Trevis. From Northern Western Ghats of Maharashtra
Epiphytic pteridophyte Huperzia hamiltonii (Spreng.) Trevis., belongs to family Lycopodiaceae a least concern (LC) species, The plant is rich in bioactive phytochemicals, including flavonoids, phenolics, and alkaloids, which contribute to its medicinal value. This study aims to identify and characterize the key bioactive compounds present in the fronds. through Fourier Transform Infrared Spectroscopy (FTIR). The FTIR Spectroscopic studies revealed different characteristic peak values with various functional compounds such as alkanes, carboxylic acid, esters, amines, nitro, alkyl halide and aromatic compounds. The FTIR method was performed on a spectrophotometer system, which is used to detect the characteristic peak values and their functional groups.
Efficient Synthesis of Rhodanine Conjugates Using Methyl-Imidazolium Based Ionic Liquid
The Methyl-imidazolium based ionic liquid-[BIL]-mediated Knoevenagel condensation pathway has been developed for the first time by a consecutive reaction of rhodanine and aldehydes to afford biologically active 5-arylidene-rhodanine derivatives in excellent to promising yields at ambient temperature. The main advantage of this protocol are the ability to permit a wide range of functional groups, easy workup, short reaction times, high yields, solvent-free conditions and recyclability of the catalyst due to these application this protocol is environmentally benign.
Policies for Ensuring Food Security at National and Household Level
In this present paper, we focused on policies for ensuring food security at national and household level. Food is the basic need for human beings. In the present time, non availability of sufficient food intake and its shortage is the matter of global issue and severely affect the multitude of weaker section of population. In the past, there were lots of famines and natural calamities which affected badly the food condition in and around the world. In the great Bengal famine of 1943, Bengal was short of land to feed its population of 60 million. Food production was not sufficient for increasing population of 1 milllion in a year. Moreover, Ethiopian famines of 1973-75, famines in the Sahel region of Africa during the early 1970s, and Bangladesh famine of 1974 are examples of such famines which were caused by sudden and sharp decline in food availability and affected the entitlements of the poor (Sen, 1981).
Growth Process of Bihar Economy (2005-2015) and Functions of Uttar Bihar Gramin Bank: An Overview
In this paper, we focused on the recent growth process of Bihar's economy, which has been a strong and sustained one, and its growth rate was one of the highest among all the Indian states. During 2005-06 to 2009-10, the GSDP at constant prices grew at an annual rate of 10.2 percent between 2010-11 and 2013-14, the growth rate was even higher at 10.4 percent. The GSDP of Bihar in 2004-05 was Rs. 0.78 lakh crore in current prices, yielding a per capita income of Rs. 8773. The estimated GSDP at current prices in 2013-14 is Rs 3.43 lakh crore, implying a per capita income of Rs. 33,954.
Modern Age Dementia: As A Multidimensional Neurodegenerative Disorder Affecting Cognition, Identity, and the Ageing Population
Dementia is a progressive neurodegenerative syndrome that affects daily functions like cognition, memory, and behaviour. Traditionally, it was just spoken in terms of ageing, but in modern research, it is being suggested that dementia is not just an ageing problem; it is a multidimensional condition that occurs due to biological, genetic, neurological, and lifestyle factors and their combination. This paper discusses dementia from a broad perspective, exploring it from brain structure and neuronal communication to memory, neuroplasticity, and genetic mutations. The first part of the study talks about the human brain and its structure, which discusses neurons, synapses, and neurotransmitters' roles. In dementia, neural communication is disrupted, which leads to a decline in memory, changes in behaviour, and cognitive impairment. Memory is being discussed as a core cognitive process in which the importance of neuroplasticity in dementia and its gradual decline is explained. The paper explains genes and proteins in detail, especially the amyloid precursor protein, amyloid plaques, and tau tangles, as a pathological mechanism that occurs based on neurodegenerations, with the major types of dementia, particularly Alzheimer's and frontotemporal dementia, their pathologies and clinical perspective is explained. This research focuses on dementia as an important challenge in the modern age. In today's time, dementia isn't just an age-related disorder; it is a lifestyle-influenced neurodegenerative condition from digital overload to chronic stress, incomplete sleep, and a multitasking culture, like modern factors are influencing it. This paper talks about the problem in differentiating cognitive burnout and early dementia; the overlapping symptoms are making the diagnosis complex, which leads to difficulty in early age detection. The paper even talks about genetic aspects like familial dementia, childhood dementia and genetic testing, which clarifies the difference between hereditary and sporadic dementias. Including it model clinical observation like digital dependency, behavioural shift and cognitive fatigue is presented as an emerging indicator. Social dimension is also highlighted, in which the structure of the nuclear family, a duo working household and reduced caregiving support in dementia management, which makes it challenging, is why the early planning, preventers, awareness, and neurological health are important and being emphasised. The paper also suggests that some dementia symptoms are even reversible if they are being treated with care and early. Overall, this paper talks about the holistic side of dementia, which presents a biological degeneration, genetic risk, modern lifestyle, and social changes, all of which are represented as interconnected factors. This study emphasises that in modern dementia, it isn't just a neurological disease, but it is necessary to understand it as a biopsychosocial challenge, where early detection, prevention, and awareness, as well as future management, are the key pillars.
An Intelligent Decision Support System for Tourists Management Via Global Tourism Analysis
One of the sectors that showed a positive growth following COVID-19 is tourism, which contributes the greatest part of the foreign exchange in developing nations, with foreign countries, particularly in Vietnam, starting to open up and the pandemic restriction of foreign travel. This paper suggests a CNN-LSTM deep learning model as the manager of tourists, relying on the global tourism analysis, with the structured tourism data being obtained at Kaggle. Similar data preprocessing methods as Standard Scaler normalization and label encoding were used. CNN module was employed to obtain useful feature extraction, whereas the LSTM component was used to obtain sequence dependencies in order to improve predictive capability. The hyperparameter tuning was conducted in order to get the best model configuration. The experimental findings indicate that the proposed model had a high generalization and low overfitting, where it had 99.5% accuracy (ACC), 99.8% precision (PRE), 99.7% recall (REC), and a 99.7% F1-score (F1) and low loss of 0.37. The comparative analysis also confirms that CNN-LSTM model is better than the conventional approaches like KNN, Bernoulli Naive Bayes, and Random Forest, and therefore it is a powerful model to use with intelligent tourism data analysis and management.
Copyright (c) 2024 International Journal of Scientific Research in Science and Technology https://creativecommons.org/licenses/by/4.0
Integrating Occupational Safety Management into Enterprise Risk Management (ERM) Frameworks
Organizations increasingly recognize that occupational health and safety (OHS) risks are not isolated operational concerns but systemic exposures with direct implications for enterprise volatility, financial performance, and long-term resilience. Yet, in practice, OHS management frequently remains siloed from Enterprise Risk Management (ERM) governance structures. This study advances the discourse by proposing the Integrated OHS–ERM Convergence Model (IOECM), a layered integration framework that structurally embeds OHS within enterprise risk governance, harmonized risk processes, integrated data intelligence, and safety culture dynamics. Grounded in systems theory and high-reliability organization principles, the study employs a qualitative critical review methodology synthesizing contemporary literature across healthcare, industrial, and financial sectors. The analysis introduces an OHS–ERM integration maturity model and demonstrates, through synthetic longitudinal validation metrics, how progressive integration can simultaneously reduce lagging indicators (Total Recordable Incident Rate, severity rates, and loss costs) while strengthening leading indicators (near-miss reporting, risk visibility, and employee safety engagement). Findings suggest that meaningful integration requires more than reporting alignment; it demands governance-level accountability, unified risk taxonomies, centralized risk registers, predictive analytics capability, and leadership-driven cultural transformation. Organizations adopting structurally embedded integration architectures are better positioned to mitigate volatility, protect human capital, optimize risk capital allocation, and enhance strategic decision-making. The IOECM contributes a replicable conceptual artifact for bridging OHS and ERM scholarship and offers a practical roadmap for enterprises seeking holistic risk governance in increasingly complex operating environments.
Deep Stroke Exploring Machine Learning and Deep Learning Techniques for Accurate Brain Stroke Classification
This work offers a complete brain stroke classification and prediction system based on the progressive machine learning and deep learning algorithms. To improve the performance of models the system includes preprocessing of extensive data such as cleaning, normalization, missing values, and feature engineering. Histograms, plots, and graph data visualization techniques are used to identify meaningful patterns and trends in the data retrieved on stroke to allow one to interpret intricate medical information. The Convolutional Neural Networks (CNNs) are paired up with machine learning algorithms to examine the data of brain imaging, identifying its spatial features and spotting the stroke-related anomalies, allowing to enhance the accuracy of the diagnosis. Deep learning interaction is a guarantee that a high-dimensional data and especially medical images are robustly handled. This entire solution is implemented on the Django web framework which offers an easy interface to interact in real time, input data, and also predictive analytics so that the healthcare personnel is able to make sound and timely decisions based on the predicted analysis and assist in improved stroke diagnosis and intervention.
An Intelligent QR Code–Enabled Framework for Digital Identification and Management of Zoological Specimens
In zoological labs and museums, precise biological specimen identification, preservation, and retrieval are essential criteria. Conventional specimen marking techniques are frequently vulnerable to human mistake, data loss, and physical deterioration. This study offers an interdisciplinary framework that uses artificial intelligence (AI) and QR code technology to combine computer science methods with zoological taxonomy in order to address these issues. The suggested system uses machine-readable QR codes and AI-assisted data processing to enable the digital identification, validation, storage, and retrieval of zoological specimen information. Each specimen is assigned a unique QR code that links to a validated digital record containing taxonomic, morphological, and collection-related information. The framework increases long-term specimen management, decreases manual errors, and improves accessibility. The method is especially well-suited for museums, biodiversity documentation centers, and college zoology labs.
Monitoring Spatio-Temporal Changes in Surface Water Bodies in Gombe State, Nigeria Using Landsat and Sentinel-2 Imagery
Surface water resources in semi-arid environments are highly sensitive to climatic fluctuations and human activities, making long-term monitoring essential for sustainable management. This study evaluated multi-decadal surface water dynamics in Gombe State using satellite-derived Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) for the years 1987, 2005, 2015, and 2025. Multi-temporal satellite imagery was analyzed to quantify variations in spectral water reflectance and assess temporal trends over 38 years. The results reveal a non-linear pattern of surface water change. In 1987, moderate water presence was observed (NDWI max = 0.36; MNDWI max = 0.48), establishing a baseline condition. A significant increase occurred in 2005 (NDWI = 0.57; MNDWI = 0.96), indicating strengthened water reflectance likely associated with improved rainfall and runoff conditions. In 2015, NDWI declined to 0.30 while MNDWI remained high (0.98), suggesting continued water presence but reduced spectral intensity, possibly due to vegetation interference, turbidity, or seasonal variability. The strongest signal was recorded in 2025 (NDWI = 0.89; MNDWI = 0.99), reflecting substantial enhancement of surface water presence, potentially linked to intense rainfall or flooding events. Across all years, MNDWI demonstrated greater stability and sensitivity than NDWI, confirming its suitability for surface water detection in semi-arid regions. The findings highlight the dynamic and climate-responsive nature of surface water systems and underscore the importance of continuous satellite-based monitoring to support adaptive water resource planning, flood risk management, and drought preparedness in northeastern Nigeria.
Harnessing Verticillium lecanii for Sustainable Biocontrol of Plant Diseases
Verticillium lecanii is a well-established entomopathogenic fungus with significant potential as a biological control agent for the management of insect pests. First described in 1861, this fungus infects host insects through direct contact with the cuticle, a protective outer layer composed of lipids, proteins, and chitin. Upon adhesion, fungal conidia germinate and penetrate the insect integument through the coordinated action of extracellular hydrolytic enzymes, particularly proteases and chitinases. Chitinase plays a pivotal role in degrading chitin, a major structural component of the insect exoskeleton, thereby facilitating fungal invasion, systemic colonization, and eventual host mortality. The enzymatic degradation of cuticular barriers enables V. lecanii to effectively control soft-bodied pests such as aphids and whiteflies. Due to its targeted mode of action and biological specificity, V. lecanii represents an eco-friendly alternative to conventional chemical pesticides. Its use minimizes environmental contamination, reduces the risk of pest resistance development, and limits adverse effects on non-target organisms. By integrating natural pathogenic mechanisms with sustainable crop protection strategies, V. lecanii contributes to environmentally responsible pest management. This study highlights the infection mechanisms of V. lecanii, emphasizing the role of chitinase-mediated cuticle degradation and its relevance in integrated pest management (IPM) programs aimed at promoting sustainable agriculture.
Efficient and Environmentally Sustainable Heterogeneous Polystyrene Divinylbenzene-Supported Sulphanilic Acid Catalyst for the Synthesis of Imidazopyridine Derivatives
We report a recyclable Brønsted-acid catalyst consisting of sulphanilic acid covalently immobilized on a cross-linked polystyrene–divinylbenzene matrix (PS–DVB–SA). The material promotes the solvent-free two-component creation of imidazo[1,2-a]pyridines from 2-aminopyridines, aldehydes, and isocyanides at 80 °C, delivering products in 81–93% isolated yields within 27–79 min. Comprehensive characterization (FT-IR, 1H NMR and 13C NMR) confirms functional groups and presence of attachment of H-atom and C-atom environment. The catalyst is magnet-free, easy to filter, and reusability of catalyst done for at least five cycles without considerable loss. This work unites the known pharmacological relevance of imidazo[1,2-a]pyridines and the powerful Groebke–Blackburn–Bienaymé (GBB) multicomponent logic with a robust, industry-familiar PS-DVB platform, offering a practical route to scalable, low-waste heterocycle synthesis.
Snail Diversity across Maharashtra Habitats: Comprehensive Review
Mollusca, the second-largest invertebrate phylum, encompasses Gastropoda (snails/slugs), Bivalvia, and Cephalopoda. Gastropods—soft-bodied organisms with calcified shells—dominate Maharashtra's malacofauna. This comprehensive literature review synthesizes 40+ studies documenting terrestrial and aquatic gastropod diversity across Maharashtra's districts, cataloging 142 species (48 genera, 23 families), new records, seasonal variations, species richness, relative abundance, and population dynamics. Raigad exhibits highest diversity (63 species), followed by Pune (49), Nashik (42), and Amravati (30+). Urbanization, pollution, and invasives (Achatina fulica) threaten native fauna. Traditional morphological identification limits cryptic species detection; DNA barcoding is recommended for comprehensive documentation. Findings establish baseline malacofauna knowledge, identify research hotspots / gaps, and inform conservation strategies. The review underscores ecological roles (bioindicators, nutrient cycling) and highlights urgent need for systematic molecular surveys to preserve Maharashtra's gastropod heritage amid anthropogenic pressures.
Eco-Compatible Green Synthesis of 1, 2-Disubstituted Benzimidazole Derivatives and Their In-Silico Studies in Designing of Anti-Malarial Potent Candidates
With the green approach, a novel and sustainable synthetic method for 1,2-disubstituted benzimidazole have been developed successfully using eco-compatible catalyst. In this report we have prepared 1, 2-disubstituted benzimidazole derivatives by double condensation between o-phenylenediamine (OPD) with various substituted benzaldehydes in presence of eco-compatible catalyst waste curd water under stirring at room temp. The employment of waste curd water for this reaction provides both as solvent as well as reaction medium with excellent yield of 81-90% within less reaction time and ease of workup process. In addition to eco-compatible green synthesis of benzimidazole derivatives, we extended their in-silico docking studies with PDB ID 1LDG using CB dock-2 web server. The green synthesized benzimidazole derivatives showed range of interactions with Gly27, Ser28, Gly29, Met 30, Asp53, Thr 97, Ala 98, Gly99, Phe 100, Thr 101, Lys102, Asn116, Val138, Thr139, Asn140 amino acids residues were predominately estimated with acceptable dock score. This exploration confirms the anti-malarial candidature of 1, 2-disubstituted benzimidazole derivatives.
A Review on Placement Prediction and Analysis Using Machine Learning
The rate at which the students are placed in jobs are considered an essential aspect of measuring the efficacy of a particular institution in imparting proper training to its students, which leads to placement in jobs. Many a learner takes due interest in studying the placement rate when deciding which institution to choose as a place to educate themselves at the collegiate level in colleges or universities. Enhancing the placement opportunities of the students in jobs is considered a major goal of almost all academic institutions, and this review paper is a study dedicated to laying a foundation in the aspect of campus placement prediction using machine learning as a predictive tool. By delving into the subject of machine learning as a predictive tool, this paper serves as a directional path that stimulates future research after pointing out the existing shortcomes in this type of prediction in raising awareness in a basic way regarding the accuracy of the efficiency of a machine learning-based campus placement prediction system.
Development and Validation of a Simultaneous HPLC Method for Quantification of Atenolol and Amlodipine Besylate in Tablet Form
A Reverse phase method has been developed for the quantitative estimation of Atenolol and Amlodipine Besylate in Tablets. The Quantification was carried out using RP stainless steel column ODS C18 250 x 4.6 x 5 μ L1 packing in Isocratic mode with mobile phase containing 0.03 M potassium buffer: Acetonitrile in the ratio of 50:50 Adjust pH3.5 with ortho-phosphoric acid. Degas this solution before use. Flow rate 1.0 ml/minute and the detection wavelength was set at 237 nm and the linearity was found to be in the range of 16-22 ug/ml for Atenolol and 8 to 12 ug/ml for Amlodipine Besylate. The proposed method was found to be simple, precise, accurate, reproducible for the Estimation of Atenolol and Amlodipine Besylate.
Atenolol and Amlodipine Besylate Method development Validation
LLM-Augmented IT Project Management : Intelligent Risk Assessment and Automated Documentation Systems
IT project management continues to experience high failure rates driven by inadequate risk visibility and documentation inefficiencies. While traditional frameworks provide structured processes, they struggle to manage the volume and velocity of modern project data. This study proposes the LLM-Augmented Risk and Documentation Integration (LARDI) Framework, a structured model embedding Large Language Models into formal IT risk and governance workflows. Through systematic literature synthesis and thematic analysis, the research identifies operational capabilities, governance safeguards, and measurable performance indicators for responsible deployment. A hybrid mathematical risk scoring model is introduced, integrating probabilistic exposure with contextual intelligence derived from unstructured artifacts. The findings position LLMs not as autonomous decision-makers but as augmented intelligence systems that enhance early risk detection, documentation accuracy, and compliance readiness. Ethical, security, and organizational change considerations are examined to ensure sustainable implementation. This research contributes a formalized integration architecture and evaluation metrics, establishing a foundation for empirical validation and advancing the discourse on AI-enabled project governance.
Investigation on RF Mems Switches: Designs, Fabrications and Measurements
The motivation for using radio frequency microelectromechanical systems (RF MEMS) technology for the control of microwave circuits and antennas is presented in this paper. A brief survey of currently used microelectronic RF switching technologies is presented. This is followed by an introduction to the fundamental characteristics of RF MEMS switches. The inherent advantages of these switches relative to semiconductor switches are discussed. Microwave circuit and system applications that could benefit from the use of RF MEMS switches are listed.
A Critical Review of Zinc Oxide Nanoparticles: Synthesis Strategies, Doping Chemistry, Structure–Property Correlations and Nanoscale Toxicological Considerations
Zinc oxide (ZnO) nanoparticles are technologically significant class of metal oxide nanomaterials, whose optical, electronic, and the surface properties are strongly governed by size, morphology, crystal defects, and the elemental doping. Controlled synthesis and dopant incorporation play a major role in shaping their performance at nanoscale. This critical review examines conventional chemical synthesis routes, like sol–gel, hydrothermal, solvothermal, precipitation along with green synthesis strategies using plant extracts, highlighting their effect on the crystallinity, particle size, morphology, and defect chemistry. Also focusing on transition and non-transition-metal doping, with comparative discussion on dopant-induced lattice distortion, bandgap modulation, oxygen vacancy formation, surface reactivity, and structure–property correlations. Moreover, nanoscale toxicological considerations are addressed that highlights the dependence of ZnO nanoparticle toxicity on physicochemical parameters, exposure pathways, and dose. Current challenges in reproducibility, dopant control, and safety assessment are identified and are outlined for rational design of ZnO nanoparticles for nanotechnology-driven applications.
Air Pollution Trend Analysis in Hangzhou during the Asian Games
This study examines the temporal dynamics of air pollution in Hangzhou, China, during 2023, with a particular focus on the Asian Games period (September-October 2023). Monthly average concentrations of six criteria pollutants (PM2.5, PM10, NO2, O3, SO2, and CO), together with four meteorological parameters, were used to evaluate the effectiveness of short-term regulatory interventions implemented for the mega-event. The results indicate substantial reductions in primary pollutants during the Games, especially NO2 (19 μg/m³ in September compared with an annual average of 30.1 μg/m³) and PM10 (40.5 μg/m³ during the Games versus 53.4 μg/m³ prior to the event), reflecting the effectiveness of traffic and industrial control measures. In contrast, ozone concentrations remained elevated (125.2 μg/m³), likely driven by favourable photochemical conditions, highlighting the challenges associated with managing secondary pollutants. A pronounced rebound effect was observed in November-December, with PM2.5 and NO2 increasing by 69.2 % and 76.5 %, respectively, relative to Games-period levels. Overall, the findings demonstrate that while temporary emission controls can deliver short-term air quality improvements, sustainable urban air quality management requires integrated, long-term strategies, and the study provides policy-relevant insights for future mega-events in rapidly developing urban environments.
Impact of Financial Literacy on Investment Decision-Making among Young Professionals in India
This paper studies how financial literacy affects the investment decisions of young professionals in India by using only secondary data sources. The research takes information from official reports published by RBI SEBI OECD and NCFE. It examines how awareness and understanding of financial terms influence personal investment behavior. The study shows that people who know more about finance make better decisions in choosing safe and profitable investment options. They plan long term and avoid emotional or unplanned spending. Young professionals form a major part of the Indian working population and they directly influence the growth of the financial market. But many still lack the knowledge needed to use modern investment products like mutual funds stock market and systematic investment plans. The paper explains how formal education and government awareness programs can change this situation. The analysis also points out that financial literacy is not only about earning and saving but also about knowing how to manage risk and build wealth for the future. The study highlights that continuous learning and digital awareness programs help young professionals become confident and responsible investors. In the end the paper suggests that strong financial education is the key for developing a financially secure and self-reliant youth in India.
Bacterial Consortia as Bioinoculants: Enhancing Soil Fertility and Crop Productivity through Synergistic Plant Growth-Promoting Mechanisms
The increasing reliance on chemical fertilisers has raised serious environmental and economic concerns, underscoring the need for sustainable alternatives in agriculture. Bacterial consortia-based bioinoculants represent a promising, eco-friendly strategy to enhance soil fertility and crop productivity. In this study, agriculturally beneficial bacteria were isolated from soil and screened for key plant growth-promoting traits, including mineral solubilization (phosphorus, potassium, and zinc), siderophore production, indole-3-acetic acid (IAA) production, extracellular enzymatic activity, and antimicrobial potential. Four efficient bacterial isolates were identified through 16S rRNA gene sequencing and were closely related to Bacillus subtilis, Pseudomonas fluorescens, and Azospirillum brasilense. Compatible isolates were combined to formulate a bacterial consortium and evaluated under pot conditions. The consortium significantly enhanced plant growth parameters, including shoot length, root length, and biomass, compared to uninoculated controls and individual isolates. The results demonstrate that bacterial consortia exhibit synergistic effects that improve nutrient availability, promote plant growth, and suppress potential pathogens. This study highlights the potential of bacterial consortium-based bioinoculants as sustainable alternatives to chemical fertilizers for improving soil health and crop productivity.