Veer Kunwar Singh University was established on 22 October 1992 with its headquarters at Arrah, under the Bihar University Act 1976 [as amendment Act 9 of 1992]. It is named after Kunwar Singh, the well known national hero and distinguished freedom fighter of 1857.It is in the list of recognized universities under section 2(f) of the U.G.C. Act. All of its 17 constituent colleges and one affiliated college receive financial assistance from U.G.C. by virtue of being constituent/affiliated colleges of the erstwhile Magadh University in Bodh-Gaya, Bihar.C.C.C.
The rapid expansion of Internet of Things (IoT) devices has transformed industry and everyday lives by facilitating widespread connection and data interchange. This increase in connection has generated significant security weaknesses, rendering IoT systems more vulnerable to advanced cyber-attacks. This research introduces a novel ensemble learning architecture focused on at improving the detection of IoT attacks. The proposed approach utilizes advanced machine learning methods, namely the extra trees classifier, and implements intensive preprocessing and hyperparameter optimization to examine datasets including CICIoT-2023, IoTID20, BotNeTIoT-L01, ToN_IoT, N-BaIoT, and BoT-IoT. The findings demonstrate remarkable performance, with the model attaining near-optimal metrics, including recall, accuracy, and precision, while maintaining incredibly low error rates. These findings demonstrate the model's efficiency above existing techniques, offering an effective choice for securing IoT environments. This research establishes a new benchmark for IoT security, providing a robust basis for future progress in protecting networked devices from emerging cyber threats.
Herein, two-dimensional alpha-SnWO4 nanoflake-like particles are synthesized to investigate the cooperative redox participation of the dual metal sites during the electrocatalytic nitrate reduction reaction (eNO(3)RR). Cyclic voltammetric studies reveal the reduction of the tungstate sites of alpha-SnWO4 at a more anodic potential compared with that observed for the iso-stoichiometric ZnWO4, which leads to significantly higher eNO(3)RR activity of alpha-SnWO4, enabling 90 +/- 4% faradaic efficiency (FE) for NH3 at a low potential of -0.2 V (vs. RHE) in an acetate buffer of pH 2.8. A high yield and NH3 selectivity under a low operating potential on alpha-SnWO4 arise due to the ease of nitrate activation through the cooperation of redox-active Sn-II and tungstate sites, whereas it happens at a more cathodic potential on ZnWO4 due to a distinct lattice arrangement and higher reduction potential of Zn-II sites. The drop in NH3 yield on increasing pH and the enhancement of Tafel slope are the primary indications of [NO3](-) adsorption and a proton-assisted activation pathway. Brunauer-Emmett-Teller analysis, contact angle measurement and electrochemically determined surface area suggest a high active surface area of 30 m(2) g(-1) (ECSA: 5 cm(2)) for alpha-SnWO4, maximizing the surface accessibility for the eNO(3)RR. 15-N labelling studies confirm the nitrate as the source of nitrogen in NH3, and rotating disk electrode (RDE) analysis confirms an similar to 8e(-) transfer process for the eNO(3)RR. A variable-temperature voltammetric study indicates a low activation barrier for [NO3](-) reduction right after the reduction of tungstate sites. Use of D2O or t-BuOH and the concomitant suppression of NH3 yield, together with in situ EPR analysis in the presence of 5,5-dimethyl-1-pyrroline N-oxide (DMPO), confirms that the first 2e(-)-reduction of the adsorbed [NO3](-) is the rate-limiting and a proton-coupled electron transfer (PCET) step. Detection of [NO2](-) and NH2OH intermediates through in situ IR spectroscopy further validates the NO3RR pathway. The n-type semiconducting nature of the alpha-SnWO4 with an accessible band gap leads to the photoelectrochemical NO3RR with enhanced NH3 yield under visible-light illumination. Consistent photocurrent switching during light-on/off studies and enhanced surface potential after photo-irradiation during in situ Kelvin probe atomic force microscopy (KPFM) corroborate the photon-induced charge-separation. Furthermore, the alpha-SnWO4 is shown to be an effective electrode material for nitrate remediation, producing similar to 7.7 mg L-1 NH3 from tap water itself. This study establishes alpha-SnWO4 as a potential photo(electro)catalyst for nitrate-to-ammonia conversion, offering insights into the NO3RR mechanism and its potential practical applications.
Diabetes mellitus is a progression involves worsening insulin resistance and beta-cell dysfunction, culminating in severe metabolic complications. In this work, chalcone-based aryloxyethylamines were synthesized and evaluated for their antihyperglycemic activity using glucose tolerance test (GTT) and STZ-induced DM rat models. Compounds 12, 10, 8, 7, 5, and 3 exhibited moderate to good anti-DM activity ranging from 18.5% to 39.8% in GTT and 11.6% to 28.3% in STZ in vivo models. The most promising compounds 10 and 12 exhibited 31.1% and 39.8% glucose lowering in GTT and 28.3% and 22.9% in STZ-induced DM rat model, respectively. Molecular docking for beta 3-AR revealed strong binding affinity of the identified compounds to beta 3-AR, with docking scores in the range of -7.8 to -8.9 kcal/mol and comparable to co-crystallized ligand carazolol. Key interactions included hydrogen bonds with Asn312 and hydrophobic contacts with Val118, Val121, and Phe309. The most promising compound 10 and 12 displayed the binding score of -8.9 and -8.1 kcal/mol, respectively. The binding mode analysis showed that carbonyl oxygen of 10 and 12 displayed hydrogen bond with Asn312, in addition to hydrogen bond with Ser209 in 10. Further, ring A of 10 and 12 occupied the aromatic hydrophobic core created by residues Phe308, Phe309, Val118, and Val121. The ethylamine side chain on ring B of 10 displayed hydrophobic interactions with Val205, Ala316, and Arg315, while ring B itself engages in a carbon hydrogen bond with Tyr204. The ethylamine side chain of 12 displayed carbon hydrogen bond with Asn332. Overall, the work resulted in the identification of 10 and 12 as potential beta 3-AR binders.
The growing threat of emerging infectious diseases emphasizes the need for proactive health monitoring, particularly in underserved rural areas. This chapter explores the innovative integration of artificial intelligence (AI) and predictive genomics to enhance pandemic prevention and rural healthcare. Genomic surveillance, powered by next-generation sequencing (NGS), provides real-time insights into pathogen evolution and variant emergence. AI-driven models transform vast genomic data into actionable insights, enabling precise public health interventions. Portable, cost-effective sequencing tools with edge computing extend these capabilities to remote regions. Case studies reveal AI's impact in recent health crises, highlighting lessons in governance, collaboration, and ethical considerations like privacy and equity. The chapter advocates predictive health strategies and global cooperation to build resilient rural healthcare systems, reduce disease burdens, and strengthen global health security.
Tapered optical fiber surface plasmon resonance sensor has attracted great attention due to their high sensitivity to refractive index variations. In this article, a rigorous theoretical analysis of tapered optical fiber SPR sensor having sinusoidal, raised Sin, hyperbolic tangent and gaussian smooth curve taper profile. By the ray model approach, the plasmonic resonance wavelength shift is calculated at various taper ratio at five distinct taper section (0, L/4, L/2, 3L/4 and L) along the taper length. The achieved maximum sensitivity is evaluated and compared for each taper profile at different tapered section. It is observed that to decrease taper ratio leads to increased sensor sensitivity for all taper profile and attaining a maximum at the particular taper ratio. The results demonstrate that taper ratio, taper profile and taper section significantly influence of the sensitivity of surface plasmon resonance sensor.
