Category Archives: Uncategorized

Authors: Ajay Kumar Dash, Ipsita Pradhan

Abstract: Nano-enabled microbial bioreactors are emerging as an innovative approach for sustainable water purification, combining the catalytic versatility of microbes with the high surface area, reactivity, and functional properties of nanomaterials. These hybrid systems are designed to enhance the degradation, adsorption, and transformation of organic pollutants, heavy metals, and pathogens in contaminated water sources. Nanoparticles act as catalysts, redox mediators, or structural supports, accelerating microbial metabolic processes and facilitating electron transfer in bioreactors. This synergistic relationship significantly improves pollutant removal efficiency, reduces treatment time, and enhances system stability. As global freshwater resources face escalating pollution and scarcity, nano-enabled microbial bioreactors offer a scalable and eco-friendly solution that bridges the gap between advanced nanotechnology and traditional biological wastewater treatment. This article explores their working principles, applications, environmental benefits, and future prospects

DOI: https://doi.org/10.5281/zenodo.16842310

 

Published by: vikaspatanker

Authors: Moushami D, Rachna V, Srinidhi B

Abstract: The Student-Alumni Platform is an educational community designed to develop connections between students alumni of an esteemed institution. It involves the current students and passed out alumni of the institution. This platform is helpful to make the students network, seek mentorship and have access to development resources which help the student to grow and learn. The alumni can offer guidance,share job opportunities,and contribute to their institution and students.By using this platform, the gap between student and alumni is solved and provides a seamless and interactive interface. The necessary features that are included in the platform are creating user profile, login, student dashboard, alumni dashboard with sending connection requests and messages. The platform is built by using HTML,CSS and JavaScript.As the platform evolves, future enhancements will further enrich user engagement by using more enhanced features like advanced messaging and group chats, linkedin integration,mobile access,and more features to help make the application more dynamic and dependant to the users.It also helps in building life long relationships by promoting the connections between student and alumni.

 

 

Published by: vikaspatanker

Authors: Dhrisya S. Anil1, Dr Abhilash S. Vasu2

Abstract: Flexible antennas are key components in modern wireless systems, valued for their lightweight design, adaptability, and integration with non-planar surfaces. They are categorized into four main types: conformal antennas, which adapt to curved structures for aerodynamic and stealth uses; wearable or textile antennas, integrated into clothing or body-worn devices for healthcare, military, and sports; reconfigurable antennas, which dynamically adjust frequency, radiation pattern, or polarization; and fluidic or movable architectures, utilizing liquid metals or mechanical actuation for tunability and shape adaptability. Material selection significantly influences both mechanical flexibility and electromagnetic performance. Traditional conductors like copper and silver offer high conductivity but require special techniques for flexibility. Conductive polymers and composites combine electrical performance with mechanical compliance and environmental resistance. Textile-based conductors integrate antennas directly into fabrics for comfort and durability. Advanced flexible substrates such as polyimide, PDMS, LCP, and TPU provide low dielectric loss and resilience under stress. This review outlines classification, materials, and fabrication advances, emphasizing their role in enabling next-generation communication technologies like 5G/6G, IoT devices, aerospace systems, and wearable healthcare solutions. Flexible antennas promise compact, unobtrusive, and high-performance wireless connectivity for future applications.

DOI: https://doi.org/10.5281/zenodo.16869714

 

Published by: vikaspatanker

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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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

 

Published by: vikaspatanker

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