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Harnessing ZnO Nanoparticles for Sustainable River Water Treatment: Efficiency, Mechanisms, and Environmental Implications
Get PDFIt has been revealed after through scientific research that ZnO nanoparticles (ZnO-NPs) are among one of the most if not the most studied nanomaterials brought to use for environmental and specifically wastewater remediation. Its key physicochemical traits are unique and play a key role in the remediation process. These nanoparticles are not only low cost in nature but also possess strong antimicrobial properties with a wide range of direct bandgap from 3.2 to 3.37 Ev and a very high excitation binding energy. When it comes to treatment of river water, the have a dual functionality, they cause photocatalytic degradation of organic pollutants alongside the act of disinfecting the microbial contaminants present in a given sample of river water. This research paper focuses in key areas such as the generation of the reactive oxygen species, chemistry of photocatalysis , mechanism of antimicrobial action of these nanoparticles and their real life applications in the river water matrices. The following are the various parameters of assessment, catalytic stability, leaching behaviour of zinc ion, the matrix effect on the activity, photocatalytic and disinfection performance, the evaluation of its ecotoxicity. However thye entire process also is accompanied by certain identified challenges such as the photocorrosion reducing and the poor utilization of the visible light as it is restricted to specifically the UV region. There are also concerns about the environmental impact. This paper also discusses the strategies for the improvement of the nanoparticles such as elemental doping, catalyst immobilization , formation of heterojunctions and the green synthesis routes which is a more eco-friendly approach. This aims to achieve a promising ZnO NP based solution to wastewater treatment, one which is sustainable and has a high rate of efficacy to bridge the gap between the lab and on field gap
Digital twin in pharma manufacturing enhancing QMS with virtual simulations
Get PDFDigital twin technology is swiftly becoming a groundbreaking advancement in pharmaceutical manufacturing, propelling the sector toward Pharma 4.0. A digital twin serves as a dynamic, digital replica of physical systems, facilitating continuous surveillance, modelling, and optimization of intricate processes. This technology tackles essential challenges in the medicinal products sector, including the preservation of data integrity, the assurance of product quality, the enhancement of process oversight, and the fulfilment of rigorous regulatory standards. Utilizing IoT, the use of AI, and big data statistical analysis, digital twins improve decision-making, facilitate predictive maintenance, and reduce variability in production.Digital twins provide many advantages, as shown in several case studies from different industries. In the midst of the COVID-19 pandemic, Pfizer used digital twin models to speed up vaccine production, while Novartis and GSK used facility-wide digital replicas to enhance quality assurance, decrease failures, and increase batch uniformity. These achievements prove that digital twins may improve efficiency, follow regulations, and ultimately benefit patients.There are obstacles to adoption, notwithstanding its advantages. Problems with data harmonization, cybersecurity, and the intricacy of complying with rules like FDA 21 CFR Part 11 persist as major obstacles. To get around this, pharmaceutical firms need to beef up their cybersecurity, establish consistent data governance practices, and establish a scalable IT infrastructure. If digital transformation is to be a success, it is equally critical to encourage a culture of constant improvement and cooperation across departments.In the future, digital twins will be much more powerful when combined with blockchain technology to provide supply chain visibility, internet of things (IoT) to track metrics in real-time, and deep learning to boost quality continuously. The establishment of uniform standards and best practices will need close cooperation between pharmaceutical companies, technology suppliers, and regulatory bodies. In the end, digital twin technology might completely change the way pharmaceuticals are made. It could lead to better healthcare solutions that are safer, more effective, and focused on the patient. Plus, it could assure conformance and operational excellence
SYNERGISTIC EFFECT OF DIFFERENT MICRONUTRIENTS ON THE GROWTH OF FUSARIUM OXYSPORUM F.SP. CUBENSE CAUSING PANAMA WILT OF BANANA
Get PDFPanama wilt, caused by Fusarium oxysporum f. sp. cubense (Foc), is one of the most devastating diseases affecting banana production worldwide. Micronutrients in soil are significant factors in plant health and disease resistance, as they affect both host-pathogen interactions and fungal growth dynamics. This study investigates the effect of some key micronutrients, such as Manganese, magnesium and boron, on the growth and pathogenicity of Foc. The paper would gain strength, for example by detailing concentrations of micronutrients studied and application methods. This means that it may be made reproducible or comparable to other studies. The inclusion of potential mechanisms on how this micronutrient is affecting growth of fungi and increased resistance by the plant makes the outcome more meaningful. In essence, therefore, this work presents a relevant contribution to the comprehension of relationships between micronutrient-pathogens and provides real practical insights into managing Panama wilt among banana cultivators
An IoT-Enabled Real-Time System for Detection and Analysis of Toluene using Machine Learning
Get PDFBackground / Objective: According to World Health Organization (WHO) reports, Toluene is one of the volatile organic compounds (VOCs) that is released by industries and vehicles causing serious health concerns, including brain damage and respiratory problems. To reduce health risks, maintain regulatory compliance and help the regulatory agencies to frame the future policies, toluene concentrations must be accurately and consistently monitored. However, traditional detection methods, including gas chromatography-mass spectrometry (GC-MS), lack real-time monitoring capabilities and are very expensive from installation and maintenance point of view. Methodology: The presented work suggests a portable, low-cost, real-time toluene detection system that integrates inexpensive sensors with IoT architecture for real-time data Collection and monitoring on the Amazon Web Service (AWS) cloud platform. The system deals with Machine learning (ML) based analysis for trend identification and interpretation. Findings: The strong correlation between VOC grade and Toluene concentration (0.98) shows that the developed device is highly capable of detecting the toluene concentration. The dataset can be useful to the external agencies for the pollution audit in industrial settings. Novelty / Improvement: The device is developed using the low cost and portable sensors, collects the real time data using the AWS cloud. Therefore, this device can be easily installed in industrial settings that can ensure increased workplace safety and regulatory compliance by providing an affordable and scalable environmental monitoring solution
EFFECTIVENESS OF GROUP COUNSELING ON INTERNET ADDICTION AMONG COLLEGE STUDENTS IN SELECTED COLLEGES IN CHENNAI
Get PDFBackground: The term “internet addiction” is mentioned, it refers to the internet usage of an individual, to the extent that it becomes compulsive and makes it impossible for the individual to carry out his/her routine life, work and social function. Methodology: A quasi-experimental research design using pretest, post-test design was used. The study was designed for a total time of four months, which include two months for intervention and two months for post evaluation. The study was conducted in selected colleges in Chennai, colleges and students meeting the inclusion criteria were purposively sampled.Results: The result showed that after the intervention, the study shows a significant reduction in internet addiction indicated by the mean score falling from 56.4 (SD = 10.1) to 43.2 (SD = 8.7), t = 7.53, p = 0.000. The effectiveness of group counseling is proved by moderate addiction drop down (45.7%) and severe addiction (31.4%) while the mild addiction went up to 51.4% and the severe addiction went down to 14.3%. There were significant associations between educational level (p = 0.043), stream of study (p = 0.001), and internet usage (p = 0.000) and internet addiction. They were also related to education (p = 0.002) and marital status (p = 0.02), but age, gender, socio-economic status, and having a mental health history were not associated with the degree of change in symptoms. Conclusion: The study concludes that group counseling successfully decreases the level of internet addiction in college students. The numbers of people in addiction decreased dramatically after the targeted interventions were implemented
TOXICOLOGICAL ASSESSMENT OF FOOD ADDITIVE: "YODAZIN"
Get PDFThe increasing use of food additives in the food industry necessitates rigorous toxicological evaluation to ensure consumer safety. This study aimed to assess the potential toxicity of Yodazin, a commonly used food additive, through a series of in vitro and in vivo experiments. Acute and sub-chronic toxicity studies were conducted using rodent models to evaluate the effects of Yodazin on physiological, biochemical, and histopathological parameters. Additionally, genotoxicity assays, including the Ames test and micronucleus assay, were performed to determine its mutagenic potential. The results indicated that Yodazin exhibited low acute toxicity, with an LD₅₀ value exceeding 5000 mg/kg body weight. However, sub-chronic exposure at high doses led to mild hepatic and renal alterations, suggesting a need for dose regulation. No significant genotoxic effects were observed in the tested models. These findings suggest that while Yodazin is relatively safe at recommended levels, prolonged excessive consumption may pose health risks. Further long-term studies are recommended to establish its safety profile comprehensively
Effect of nutrient management practices on crop growth and yield of maize (Zea mays L.)
Get PDFThe field experiment was conducted at the agronomy research farm of Acharya Narendra Deva University of Agriculture & Technology, Kumarganj, Ayodhya, Uttar Pradesh to access the effect of optimization of nutrient management practices on growth and yield of maize during kharif season of 2023 and 2024. The experiment was laid out in factorial randomized block design (FRBD) with 3 replications and consists three RDF Levels 50% RDF (NPK), 75% RDF (NPK) and 100% RDF (NPK)) and five Bio-agent enriched FYM and micronutrient (Zn @ 5 kg ha-1 + B @ 1kg ha-1, Enriched FYM @ 5 t ha-1, Enriched FYM @ 10 t ha-1, Zn @ 5 kg ha-1 + B @ 1kg ha-1 + Enriched FYM @ 5 t ha-1, Zn @ 5 kg ha-1 + B @ 1kg ha-1 + Enriched FYM @ 10 t ha-1). Results indicate that among the RDF levels crop fertilized with 100% RDF (NPK) recorded significantly highest plant height (96.76 & 99.36 cm, 176.24 & 180.98 cm and 205.88 & 211.38 cm), highest leaf area index (2.88 & 2.91, 4.18 & 4.23 and 3.34 & 3.38) at knee-high, tasseling and harvest stage of crop growth during 2023 and 2024, respectively. Similarly, maximum grain yield (43.20 & 44.94 q ha-1) was recorded under 100% RDF. Among the bio-agent enriched FYM and micronutrient application of Zn @ 5 kg ha-1 + B @ 1kg ha-1 + Enriched FYM @ 10 t ha-1) recorded significantly the highest plant height (95.93 & 98.50cm, 174.73 & 179.40 cm and 204.13 & 209.60 cm), highest leaf area index (2.84 & 2.87, 4.11 & 4.16 and 3.29 & 3.33) at knee-high, tasseling and harvest stage of crop growth during both the years of investigation. Similarly, maximum grain yield (47.12 & 49.02 q ha-1) was reported with same treatment
Influence of neem cake on composting of food waste
Get PDFThis study aimed to evaluate the effect of neem cake as the additive with food waste (FW) and sawdust on improving the compost quality and composting. The food waste (FW), sawdust (SD) and neem cake (NC) was mixed at 1:1:0.2, w/w, dry basis (FW+SD+NC) while food waste + sawdust mix (FW+SD, 1:1 w/w dry basis) served as control. The mixtures were composted in 20-L bench scale composters for 42 days. The results revealed that addition of neem cake resulted in thermophilic peak temperature of 63oC while the thermophilic period prevailed for nearly three weeks which were significantly higher than the control. The nitrogen content of the FW+SD+NC treatment (2.20 %) was higher when compared with FW+SD treatment (1.94 %). The physicochemical properties of the FW+SD and FW+SD+NC composts were within the recommended compost standard range. Addition of 20% neem cake proved to be one of the most effective strategies for improving the composting process, enhancing compost quality, and reducing nitrogen loss during food waste composting
QUANTITATIVE ASSESSMENT OF AIRBORNE MICROBIAL LOAD IN CLINICAL AND ADJACENT ENVIRONMENTS
Get PDFAirborne microbial contamination in hospital environments poses a significant risk to infection control, especially in operating rooms. This study evaluates airborne microbial loads in six different hospital and adjacent locations through passive sampling using nutrient agar plates. Samples were exposed to air for 10 minutes and incubated for 48 hours to quantify colony-forming units (cfus). The highest microbial counts were observed near the bike stand outside the lab, while the immunology lab recorded the lowest counts. The findings underscore the importance of air quality monitoring and control strategies in healthcare settings
Advanced Spatio-Temporal Assessment of PM₂.₅ Variability and Health Risks Using Multi-Scale Mapping in a Tier-2 Indian City
Get PDFAir pollution driven by rapid urbanization poses significant environmental and public health challenges. This study conducts a comprehensive spatiotemporal analysis of fine particulate matter (PM₂.₅) concentrations in Nashik, Maharashtra, a representative Tier-2 Indian city, by integrating low-cost sensor monitoring with advanced GIS mapping, machine learning models, and epidemiological risk assessment. Fifteen monitoring locations across urban, commercial, and industrial zones recorded daily PM₂.₅ levels from July 2021 to April 2022, enabling capture of both seasonal and monthly trends. PM₂.₅ concentrations ranged from 11.46 ± 2.96 μg/m³ in July (monsoon, lowest) to 104.46 ± 28.25 μg/m³ in December (winter, highest), with winter months exhibiting the most severe pollution. Spatial interpolation using the Inverse Distance Weighting (IDW) method in ArcGIS produced detailed pollution maps, with cross-validation indicating higher predictive accuracy (R²) and lower error (RMSE) during the monsoon season and reduced accuracy in the spring months due to greater concentration variability. Pathardi, a densely populated industrial neighbourhood, consistently showed the highest PM₂.₅ levels across all seasons. Statistical analysis revealed moderate correlations between PM₂.₅ and meteorological variables, underscoring that lower temperature and higher humidity tend to suppress PM₂.₅ concentrations in certain seasons. A Random Forest regression identified ambient temperature as the dominant predictor of PM₂.₅ variability (~60% relative importance), followed by humidity (~40%), confirming meteorology’s influence on particulate levels. Furthermore, a Support Vector Machine (SVM) classifier categorized air quality index (AQI) levels with high accuracy (~88%), demonstrating the efficacy of machine learning for real-time air quality classification. An epidemiological assessment using the World Health Organization (WHO) dose-response model estimated a significant increase in mortality risk during winter peaks – each 10 μg/m³ rise in PM₂.₅ associated with ~1.07% higher mortality which is highlighting severe health implications. These results underscore an urgent need for targeted air quality management in Nashik and similar mid-tier cities, including stricter emissions control, expansion of green infrastructure, and public awareness initiatives during high-risk periods. The integrated framework presented is scalable and can support evidence-based policymaking for urban air quality mitigation