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"Kumar, Vineet"
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Omics for environmental engineering and microbiology systems
\"Bioremediation using microbes is a sustainable technology for biodegradation of target compounds and OMICS approach gives more clarity on these microbial communities. This book provides insights into the complex behavior of microbial communities and identifies enzymes/metabolites and their degradation pathways. It describes the application of microbes and their derivatives for bioremediation of potentially toxic and novel compounds. It highlights existing technologies along with industrial practices and real-life case studies. Features: Includes recent research and development in the areas of OMICS and microbial bioremediation. Covers the broad environmental pollution control approach such as metagenomics, metabolomics, fluxomics, bioremediation, and biodegradation of industrial wastes. Reviews metagenomics and waste management, and recycling for environmental cleanup. Describes the metagenomic methodologies and best practices, from sample collection to data analysis for taxonomies. Explores various microbial degradation pathways and detoxification mechanisms for organic and inorganic contaminants of wastewater with their gene expression. This book aims at Graduate students and researchers in environmental engineering, soil remediation, hazardous waste management, environmental modeling, and wastewater treatment\"-- Provided by publisher.
Book
Enhancing home IoT network security
The Internet of Things (IoT) has reshaped modern digital ecosystems by enabling seamless communication between devices across various sectors. While this interconnectedness supports innovation in areas such as healthcare, commerce, and domestic automation, it also exposes critical security vulnerabilities. These risks often stem from inadequate design practices and insufficient security protocols, making IoT devices susceptible to exploitation, including denial-of-service attacks and data breaches. This study provides a comprehensive analysis of device-level vulnerabilities within IoT ecosystems, highlighting the pressing need for robust, domain-specific security interventions. We examine common attack vectors in home, healthcare, and commercial contexts, leveraging data from publicly disclosed vulnerabilities to uncover trends and weaknesses. Based on these findings, the paper proposes actionable strategies to strengthen IoT resilience and mitigate the likelihood of successful cyberattacks.Article HighlightsExploration of prevalent security threats in IoT systems and practical mitigation techniquesSector-specific analysis of vulnerability patterns in home, healthcare, and commercial IoT environments.Use of CVE database insights to assess and classify real-world attack surfaces.
Journal Article
Hybrid grey Wolf–Cuckoo search optimized linear quadratic regulator for robust quadrotor control
Accurate position and altitude control of quadrotor Unmanned Aerial Vehicles (UAVs) is essential for mission-critical applications such as surveillance, defense, and autonomous delivery. This study introduces an innovative control framework that integrates a Linear Quadratic Regulator (LQR) with a hybrid Grey Wolf Optimizer–Cuckoo Search (GWO–CS) algorithm for optimal gain tuning. The innovation lies in combining GWO’s global exploration with CS’s local exploitation, ensuring faster convergence and higher-quality tuning of LQR weighting matrices. A comprehensive nonlinear dynamic model of the quadrotor was developed using the Newton–Euler formalism, and the LQR–GWO–CS controller was implemented in a simulated environment. Comparative analysis reveals that the proposed controller achieves significant improvements. For the X-axis, the settling time is reduced from 4.08 s (LQR) and 7.36 s (LQR–GWO) to 1.70 s with zero overshoot, while the Integral Absolute Error (IAE) improves by approximately 39% compared to the conventional LQR. For the Y-axis, the proposed method reduced the IAE from 1.16 (LQR) to 0.70 with a settling time of 1.64 s and zero overshoot, outperforming LQR-WOA, which exhibited 4.2% overshoot. In altitude (Z-axis) control, the proposed controller limited overshoot to 2.0% while reducing settling time from 4.27 s (LQR) to 1.96 s, with lower IAE than both LQR and LQR-WOA. Robustness was further demonstrated under external disturbances and validated through real-time Hardware-in-the-Loop testing on OPAL-RT (Operational and Automation Platform for Real-Time applications), confirming feasibility for practical UAV missions. Overall, the LQR–GWO–CS framework outperforms state-of-the-art controllers, offering a quantitatively validated, robust, and efficient solution for UAV operation in dynamic and uncertain environments.
Journal Article
Voltage and frequency regulation in wind penetrated deregulated power system using an electric vehicle and IPFC assisted model predictive controller
This paper presents a coordinated voltage and frequency control strategy for a wind-integrated deregulated dual-area power system comprising three Generation Companies (GENCOs), diesel, thermal, and wind—and three Distribution Companies (DISCOs) in each area. A Harris Hawks Optimization-based Model Predictive Controller (MPC-HHO) is proposed to enhance system performance under three distinct market scenarios: poolco, bilateral, and contract violation modes. The proposed controller is benchmarked against conventional PID, fractional-order PI
λ
DF, and MPC schemes optimized via Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA). Simulation results show that the MPC-HHO controller achieves the lowest figure of demerit (FOD = 385.75), with up to 54.07% improvement over MPC-PSO and faster settling time under various test cases. Further, integration of Interline Power Flow Controller (IPFC) and Electric Vehicles (EVs) demonstrates significant improvement in frequency regulation, with marginal enhancements in voltage response. Robustness of the proposed approach is validated through eigenvalue analysis, sensitivity to DISCO Participation Matrix (DPM), contract violations, time-delay effects, and random load variations, confirming its applicability in complex and dynamic smart grid environments.
Journal Article
A Review on X-ray Excited Emission Decay Dynamics in Inorganic Scintillator Materials
Scintillator materials convert high-energy radiation into photons in the ultraviolet to visible light region for radiation detection. In this review, advances in X-ray emission dynamics of inorganic scintillators are presented, including inorganic halides (alkali-metal halides, alkaline-earth halides, rare-earth halides, oxy-halides, rare-earth oxyorthosilicates, halide perovskites), oxides (binary oxides, complex oxides, post-transition metal oxides), sulfides, rare-earth doped scintillators, and organic-inorganic hybrid scintillators. The origin of scintillation is strongly correlated to the host material and dopants. Current models are presented describing the scintillation decay lifetime of inorganic materials, with the emphasis on the short-lived scintillation decay component. The whole charge generation and the de-excitation process are analyzed in general, and an essential role of the decay kinetics is the de-excitation process. We highlighted three decay mechanisms in cross luminescence emission, exitonic emission, and dopant-activated emission, respectively. Factors regulating the origin of different luminescence centers controlling the decay process are discussed.
Journal Article
Estimation of Number of Graphene Layers Using Different Methods: A Focused Review
Graphene, a two-dimensional nanosheet, is composed of carbon species (sp2 hybridized carbon atoms) and is the center of attention for researchers due to its extraordinary physicochemical (e.g., optical transparency, electrical, thermal conductivity, and mechanical) properties. Graphene can be synthesized using top-down or bottom-up approaches and is used in the electronics and medical (e.g., drug delivery, tissue engineering, biosensors) fields as well as in photovoltaic systems. However, the mass production of graphene and the means of transferring monolayer graphene for commercial purposes are still under investigation. When graphene layers are stacked as flakes, they have substantial impacts on the properties of graphene-based materials, and the layering of graphene obtained using different approaches varies. The determination of number of graphene layers is very important since the properties exhibited by monolayer graphene decrease as the number of graphene layer per flake increases to 5 as few-layer graphene, 10 as multilayer graphene, and more than 10 layers, when it behaves like bulk graphite. Thus, this review summarizes graphene developments and production. In addition, the efficacies of determining the number of graphene layers using various characterization methods (e.g., transmission electron microscopy (TEM), atomic force microscopy (AFM), scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectra and mapping, and spin hall effect-based methods) are compared. Among these methods, TEM and Raman spectra were found to be most promising to determine number of graphene layers and their stacking order.
Journal Article
Optimal voltage and frequency control strategy for renewable-dominated deregulated power network
Maintaining stable voltage and frequency regulation is critical for modern power systems, particularly with the integration of renewable energy sources. This study proposes a coordinated control strategy for voltage and frequency in a deregulated power system comprising six Generation Companies (GENCOs) and six Distribution Companies (DISCOs). The system integrates thermal, diesel, wind, solar photovoltaic (PV), and hydroelectric sources. Two stochastic modeling techniques are used to characterize wind and solar generation, accounting for their variability within the control loops. A novel Leader Harris Hawks Optimization-based Model Predictive Controller (MPC-LHHO) is implemented, achieving a reduction in frequency deviation undershoot by 67.45% and voltage settling time by 91.11% compared to conventional controllers under poolco and bilateral transactions. Auxiliary devices, including the Unified Power Flow Controller (UPFC) and grid-connected electric vehicles (EVs), further enhance performance, reducing frequency deviations by 52.18% under stochastic scenarios. Rigorous evaluation under contract violations, random load variations, and renewable intermittency demonstrates the strategy’s robustness and efficacy.
Journal Article
Enhancing load frequency control and automatic voltage regulation in Interconnected power systems using the Walrus optimization algorithm
This paper introduces the Walrus Optimization Algorithm (WaOA) to address load frequency control and automatic voltage regulation in a two-area interconnected power systems. The load frequency control and automatic voltage regulation are critical for maintaining power quality by ensuring stable frequency and voltage levels. The parameters of fractional order Proportional-Integral-Derivative (FO-PID) controller are optimized using WaOA, inspired by the social and foraging behaviors of walruses, which inhabit the arctic and sub-arctic regions. The proposed method demonstrates faster convergence in frequency and voltage regulation and improved tie-line power stabilization compared to recent optimization algorithms such as salp swarm, whale optimization, crayfish optimization, secretary bird optimization, hippopotamus optimization, brown bear optimization, teaching learning optimization, artificial gorilla troop optimization, and wild horse optimization. MATLAB simulations show that the WaOA-tuned FO-PID controller improves frequency regulation by approximately 25%, and exhibits a considerable faster settling time. Bode plot analyses confirm the stability with gain margins of 5.83 dB and 9.61 dB, and phase margins of 10.8 degrees and 28.6 degrees for the two areas respectively. The system modeling and validation in MATLAB showcases the superior performance and reliability of the WaOA-tuned FO-PID controller in enhancing power system stability and quality under step, random step load disturbance, with nonlinearities like GDC and GDB, and system parameter variations.
Journal Article
Insights into the functionality of endophytic actinobacteria with a focus on their biosynthetic potential and secondary metabolites production
Endophytic actinobacteria play an important role in growth promotion and development of host plant by producing enormous quantities of novel bioactive natural products. In the present investigation, 169 endophytic actinobacteria were isolated from endospheric tissues of
Rhynchotoechum ellipticum
. Based on their antimicrobial potential, 81 strains were identified by 16rRNA gene analysis, which were taxonomically grouped into 15 genera. All identified strains were screened for their plant growth promoting attributes and, for the presence of modular polyketide synthases (PKSI, PKSII and nonribosomal peptide synthetase (NRPS) gene clusters to correlate the biosynthetic genes with their functional properties. Expression studies and antioxidant potential for four representative strains were evaluated using qRT-PCR and DPPH assay respectively. Additionally, six antibiotics (erythromycin, ketoconazole, fluconazole, chloramphenicol, rifampicin and miconazole) and nine phenolic compounds (catechin, kaempferol, chebulagic acid, chlorogenic acid, Asiatic acid, ferulic acid, arjunic acid, gallic acid and boswellic acid) were detected and quantified using UHPLC-QqQ
LIT
-MS/MS. Furthermore, three strains (BPSAC77, 121 and 101) showed the presence of the anticancerous compound paclitaxel which was reported for the first time from endophytic actinobacteria. This study provides a holistic picture, that endophytic actinobacteria are rich bacterial resource for bioactive natural products, which has a great prospective in agriculture and pharmaceutical industries.
Journal Article
Emerging Trends in Nanomedicine: Carbon-Based Nanomaterials for Healthcare
Carbon-based nanomaterials, such as carbon quantum dots (CQDs) and carbon 2D nanosheets (graphene, graphene oxide, and graphdiyne), have shown remarkable potential in various biological applications. CQDs offer tunable photoluminescence and excellent biocompatibility, making them suitable for bioimaging, drug delivery, biosensing, and photodynamic therapy. Additionally, CQDs’ unique properties enable bioimaging-guided therapy and targeted imaging of biomolecules. On the other hand, carbon 2D nanosheets exhibit exceptional physicochemical attributes, with graphene excelling in biosensing and bioimaging, also in drug delivery and antimicrobial applications, and graphdiyne in tissue engineering. Their properties, such as tunable porosity and high surface area, contribute to controlled drug release and enhanced tissue regeneration. However, challenges, including long-term biocompatibility and large-scale synthesis, necessitate further research. Potential future directions encompass theranostics, immunomodulation, neural interfaces, bioelectronic medicine, and expanding bioimaging capabilities. In summary, both CQDs and carbon 2D nanosheets hold promise to revolutionize biomedical sciences, offering innovative solutions and improved therapies in diverse biological contexts. Addressing current challenges will unlock their full potential and can shape the future of medicine and biotechnology.
Journal Article