Category Archives: Uncategorized

Authors: Pradeep Kumar Netam, Meena Porte

Abstract: Soil health is an integral determinant of agricultural productivity, ecosystem balance, and environmental sustainability. Microbial biosensors, leveraging genetically engineered microbial strains, offer a novel approach to real-time, in situ monitoring of soil contaminants and nutrient dynamics. These biosensors are designed to detect specific chemical signals—ranging from heavy metals and pesticides to changes in pH and nitrogen content—by producing measurable outputs such as fluorescence, bioluminescence, or electrochemical signals. This article reviews the development and deployment of microbial biosensors as tools for assessing soil health. It explores their underlying biological principles, integration into environmental monitoring frameworks, and potential to overcome the limitations of conventional soil assessment techniques. The paper emphasizes the importance of synthetic biology and CRISPR-based modulation in enhancing biosensor specificity and stability. Furthermore, it highlights successful case studies from agriculture, bioremediation, and land reclamation projects. Finally, the article discusses current challenges—such as environmental variability and regulatory hurdles—and future directions, including field-deployable biosensor platforms and wireless data integration. The findings underscore microbial biosensors’ transformative potential in advancing precision agriculture and soil restoration practices through continuous and targeted ecological surveillance.

DOI: https://doi.org/10.5281/zenodo.16834975

 

Published by: vikaspatanker

Authors: Harish Kumar Rathore, Monika Gupta

Abstract: The microbial communities inhabiting agroecosystems play critical roles in soil health, nutrient cycling, and crop productivity. With advancements in high-throughput sequencing technologies, comparative genomics has emerged as a powerful tool to analyze the diversity and functional capabilities of these microbial populations. This study explores how comparative genomics can illuminate the evolutionary relationships, functional gene repertoire, and adaptive traits among microbial taxa in various agricultural environments. By analyzing metagenomic datasets from different soil types and farming practices, we identify patterns of gene distribution related to nitrogen fixation, phosphorus solubilization, and pathogen resistance. The study also examines how horizontal gene transfer contributes to microbial resilience in disturbed agroecosystems. Insights from comparative genomic studies enhance our understanding of the impact of agricultural practices—such as crop rotation, fertilization, and pesticide use—on microbial diversity and ecosystem function. Case studies from organic and conventional farms reveal significant differences in microbial gene expression and evolutionary adaptation. This article underscores the importance of integrating genomic data into sustainable agriculture strategies and offers future directions for using microbial genomics in crop management and soil restoration efforts.

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Published by: vikaspatanker

Authors: Arun Kumar Patidar, Bhavana Chauhan

Abstract: Microbial life in soil-water systems operates at a scale far more intricate than previously understood. With the emergence of nanoscale imaging and molecular tools, researchers have begun to uncover a new paradigm in microbial ecology—one where microbial interactions, community behavior, and environmental feedbacks occur at the nanometer level. These interactions encompass molecular exchanges, quorum sensing, and nanostructure-based adhesion mechanisms that shape the functionality and resilience of soil ecosystems. At these scales, microbial dynamics dictate nutrient flux, pollutant transformation, and plant-microbe symbiosis in ways not observable through conventional microbiological techniques. This article provides a comprehensive exploration of these nanoscale phenomena, examining how environmental pressures and nanoscale physical forces drive microbial behavior. The implications for sustainable land use, biogeochemical cycling, and soil rehabilitation are profound, as understanding microbial processes at this resolution can lead to breakthroughs in bioremediation, precision agriculture, and climate-resilient farming. The review also presents advances in methodologies such as atomic force microscopy, nanoSIMS, and cryo-electron tomography that have facilitated the visualization and quantification of microbial interactions at the nanoscale. Overall, this paradigm shift emphasizes the importance of considering nanoscale microbial interactions as fundamental units in soil-water system functioning.

DOI: https://doi.org/10.5281/zenodo.16835268

 

Published by: vikaspatanker

Authors: Basant Kumar Sahu, Lata Pradhan

Abstract: The increasing use of engineered nanoparticles (NPs) across consumer products, medicine, and industrial applications has led to their unintended release into natural ecosystems, sparking ecotoxicological concerns. Due to their small size, high surface area, and reactivity, nanoparticles interact uniquely with microorganisms in soil, water, and sediment ecosystems. These environmental microbiomes—complex networks of bacteria, archaea, fungi, and protozoa—play essential roles in nutrient cycling, decomposition, and pollutant degradation. However, exposure to nanoparticles often results in oxidative stress, disruption of cellular membranes, genotoxicity, and changes in metabolic functions. Such stress responses can reduce microbial diversity, impair ecosystem processes, and destabilize trophic networks. Despite these critical risks, traditional environmental risk assessments fail to incorporate microbial endpoints, focusing instead on higher organisms. This review explores the pathways through which nanoparticles induce stress in microbiomes, the ecological consequences of such interactions, and the current limitations in detection and regulation. Emphasis is placed on using omics tools and community-level bioindicators to assess sub-lethal effects. Addressing nanoparticle impacts at the microbial level is vital for maintaining ecological balance and sustainability. The paper concludes by recommending policy frameworks and green nanotechnologies that prioritize microbiome integrity in environmental safety assessments.

DOI: https://doi.org/10.5281/zenodo.16835383

 

Published by: vikaspatanker

Authors: Satish Kumar Lodhi, Shikha Gupta

Abstract: Microbial nanowires represent a transformative advancement in bioenergy science, offering a novel mechanism for extracellular electron transport (EET) that can be harnessed for sustainable energy generation. These protein-based conductive filaments, produced by certain electroactive bacteria such as Geobacter and Shewanella species, enable microbes to transfer electrons across cell membranes to external electron acceptors such as metal oxides or electrodes. This unique capability has immense implications for microbial fuel cells (MFCs), bioremediation, and electro-fermentation. Unlike traditional conductive materials, microbial nanowires are biodegradable, self-assembling, and functionally dynamic under ambient environmental conditions. Recent discoveries have revealed the complex structure of nanowires, often comprising multi-heme cytochromes or type IV pili modified with aromatic amino acids, which contribute to long-range electron conductivity. Their integration into bioelectrochemical systems significantly enhances current output and efficiency. This review synthesizes current knowledge of microbial nanowire biology, electrochemical behavior, and engineering strategies to optimize their conductive properties. It also highlights future directions in synthetic biology and materials science for scalable bioenergy solutions. As global energy demands grow, microbial nanowires stand at the forefront of next-generation, eco-friendly energy technologies, bridging the gap between living systems and electrical networks.

DOI: https://doi.org/10.5281/zenodo.16835489

 

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Authors: Nitish Sharma, Dr Komal Garg

Abstract: The rising demand for food worldwide and declining freshwater resources have intensified the need for efficient agricultural practices. Smart irrigation, powered by the integration of the Internet of Things (IoT) and Artificial Intelligence (AI), offers a transformative solution for precise and sustainable water management. This review examines current advancements in smart irrigation technologies, concentrating on IoT-enabled sensor networks, real-time environmental monitoring, and AI-powered judgment models such as machine learning and predictive analytics. It examines the evolution among these technologies, their application in farming with accuracy, and the synergetic benefits of combining IoT and AI. Moreover, the review highlights implementation challenges, including high costs, energy constraints, data security, and region-specific limitations. The paper concludes with future research directions aimed at enhancing system efficiency, adaptability, and accessibility, especially in water-scarce and developing regions.

DOI: http://doi.org/10.5281/zenodo.16810519

 

 

Published by: vikaspatanker

Authors: Mr. Kartik, Dr. Bijendra Singh, Dr. Kavita

Abstract: This research aims to analyze and design an effective ransomware detection technique using machine learning algorithms. The study explores various ML approaches—such as classification, anomaly detection, and clustering—and evaluates their performance in identifying ransomware from normal and benign system behavior. Key features, such as file access patterns, process activities, and network communication, are extracted and analyzed to train and test ML models capable of early detection with high accuracy and low false positives. The primary aims of this study are to understand the behavioral characteristics of ransomware attacks; Identify and select relevant features for effective detection; Evaluate different machine learning models based on precision, recall, F1-score, and accuracy; and Propose a novel or improved ML-based detection framework tailored for real-time ransomware threat identification. This research contributes to the ongoing efforts to fortify cybersecurity by presenting a data-driven, machine learning-powered methodology that enhances early detection capabilities, thereby reducing potential damage and enabling quicker incident response.

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Published by: vikaspatanker

Authors: Moslem Mousavi khademi

Abstract: In this paper, the dissimilar welding microstructure of the duplex stainless steel SFA 2205 with the high strength low alloy A378 Gr.11 was studied.The microstructure investigations indicated that the weld obtained has a two-phase structure, including dendritic and interdendritic areas. A high hardness transition area was detected in the interface of the A378 low alloy steel and ER 309L metal filler. An unmixed area was observable at the melting boundary of SFA2205 duplex steel and both austenitic and duplex filler metals. The results showed that for joining the two-phase stainless steel SFA2205 with the high strength low alloy A378 Gr.11, using the metal filler ER2209 is more appropriate as a result of forming a more suitable properties microstructure.

Published by: vikaspatanker

Authors: Ms. Shruti Rawat, Manasvee Jain

Abstract: – In today's fast-paced and digitally driven work environment, organizations are increasingly relying on e-learning platforms for employee training and development. While digital training offers flexibility, scalability, and cost-efficiency, its actual impact on employee performance remains a critical area of inquiry. This study explores the relationship between e-learning effectiveness and employee performance metrics, aiming to bridge the gap between training delivery and measurable workplace outcomes. By analyzing data from employees across multiple departments in a mid-sized technology company, the research examines how engagement with online training modules correlates with key performance indicators such as task accuracy, productivity levels, customer satisfaction scores, and overall goal completion rates. A combination of pre-training and post-training performance data, user feedback, and system usage logs were used to assess the tangible benefits of e-learning initiatives. The findings suggest a positive link between well-structured e-learning programs and improved employee performance, particularly when courses are interactive, aligned with job roles, and supported by timely feedback. However, the study also highlights that the effectiveness of digital training is influenced by factors such as learner motivation, management support, and course design quality. This research underscores the importance of integrating performance metrics into e-learning evaluations to ensure learning investments translate into real-world results. The insights provided can help HR professionals, training managers, and organizational leaders refine their digital learning strategies for maximum impact.

DOI: http://doi.org/10.5281/zenodo.16792612

 

 

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Authors: Avdesh Kumar Ahirwar, Murlidhar Chourasia, Rahul Kumar Satbhaiya

Abstract: Gravity dams are essential infrastructural elements used for water storage, flood control, and hydropower generation. Their structural safety and performance under varying loading and reservoir conditions are critical due to the potential risks associated with failure. This paper presents a comprehensive review of structural analysis techniques for gravity dams, with a specific focus on modeling through STAAD.Pro software. The study highlights the application of finite element methods (FEM) in simulating dam behavior under different forces, including hydrostatic pressure, uplift pressure, seismic effects, and self-weight. The role of STAAD.Pro as a versatile tool capable of handling complex geometries and material properties is explored in detail. Emphasis is placed on its ability to model solid elements and perform static and dynamic analyses in accordance with IS 6512:1984 and IS 875 standards. The review synthesizes results from multiple case studies and simulations, examining factors such as stress distribution, displacement, sliding resistance, overturning moments, and shear friction parameters. Findings indicate that STAAD.Pro provides accurate and reliable predictions for assessing dam safety under full and partial reservoir conditions. Furthermore, the study identifies common stress concentration zones—particularly at the heel—and discusses reinforcement strategies to mitigate structural vulnerability. It also evaluates the factor of safety under various loading combinations and confirms compliance with national safety codes. This paper contributes to the evolving methodology of dam design and evaluation, offering valuable insights for engineers, researchers, and policymakers aiming to enhance the resilience of gravity dams through advanced numerical modeling.

DOI: http://doi.org/10.5281/zenodo.16875326

Published by: vikaspatanker