Central University of Jammu in Jammu, Jammu and Kashmir, has been established through an Act of Parliament: "The Central Universities Act, 2009" by Govt. of India. It started functioning from 2011. Dr. Sudhir Singh Bloeria was first Vice Chancellor of the university.
The biometrics-enabled human authentication has emerged as one of the viable solutions to mitigate the challenges of traditional mechanisms that employ methods such as identity cards, PINs, passwords, tokens, secret codes, ATM cards, etc. Among all palmprint biometrics is one of the popular human authentication traits, which is specifically useful for visually impaired individuals. However, the biometric-based authentication system is vulnerable to a variety of spoofing assaulters. In this case, the attacker creates an artifact of the legitimate user by replicating the original replicas of their palmprint. This study seeks to investigate various palmprint spoof attacks and interpret their countermeasures ranging from traditional hardware-based approaches to contemporary Artificial Intelligence (AI)-inspired vision transformers (ViTs)-based techniques. Besides, we propose a novel taxonomy for the classification of anti-spoofing mechanisms, and the entire study is organized accordingly. Moreover, the underlying conceptions of anti-spoofing methods, performance analysis, and evaluation protocols are thoroughly illustrated. A comparative analysis of various benchmark datasets along with the performance metrics, as well as overall analysis, is also discussed. The study identified various open research issues along with future perspectives that can be explored by the investigators in this active field of research.
A series of mercapto-1,2,4-triazole-quinoline hybrids (7a-7m) was designed, synthesized and evaluated for anticancer activity against DU-145 (prostate cancer) and MDA-MB-231 (breast cancer) cell lines. Compound 4-((5-benzyl-4H-1,2,4-triazol-3-yl)thio)-7-chloroquinoline (7c) showed notable potency with an IC50 value of 17.91 +/- 2.1 mu M against DU-145 cells highlighting the promise of these hybrids in developing innovative therapeutic strategies to combat cancer effectively. In-silico molecular docking studies further elucidated the binding interactions of the most active compound, supporting their potential as promising anticancer agents.
Enzyme cost is the one of the constraint in enzymatic hydrolysis of biomass for the production of bioethanol. Utilization of crude enzymes can be a viable alternative to make the bioethanol production process cost-effective, as their preparation requires minimal processing, thus cutting the expensive purification stages. So, to reduce the expense of the bioethanol production, the potential of the isolated strain Aspergillus flavus ITCC 11694.22 was investigated for enzyme production to hydrolyze wheat straw at optimized conditions under submerged fermentation. Several parameters including pH, temperature, inoculum size, incubation time, and carbon and nitrogen concentrations have been optimized utilizing a one variable at a time method and Response Surface Methodology (RSM). The optimum pH and temperature found for cellulase and xylanase activity were 6 and 35 °C. The highest CMCase, FPase and xylanase activity achieved were 29.7 U/g, 17.41 U/g and 403.84 U/g, respectively at optimum conditions of 84 h incubation time, 5
The even–even 94–100Mo isotopes have been studied using the Triaxial Projected Shell Model with zero triaxiality (ϵ ^'∼ 0) and with triaxiality incorporated (ϵ ^') to examine the evolution of triaxial deformation as we move from the shell closure at N = 50 towards the more deformed region approaching N ∼ 60. The calculated yrast and γ bands show excellent agreement with experimental data, with the inclusion of triaxiality providing substantial improvements particularly at higher spins. Band-diagram analysis, together with the corresponding wave-function composition, reveals the underlying quasiparticle structure and provides a microscopic explanation of key features such as band crossings and backbending. Backbending plots show a transition from rotational to vibrational behavior in heavier isotopes, indicating enhanced triaxiality. The evolution of B(E2) values, examined both as a function of spin and deformation, further supports the effect of triaxiality as one moves along the isotopic chain under study. An analysis of γ -band energy staggering demonstrates that the even–even 94–100Mo isotopes exhibit predominantly γ -soft behavior. These findings demonstrate a smooth transition from axial symmetry to triaxial shapes along the chosen Mo isotopic chain.
In the present situation, a lot of research has been directed towards the potency of plants. These natural resources contain characteristics valuable in combat against a number of diseases. But due to lack of familiarity of these plants among human beings, an appropriate advantage of their significance cannot be drawn away. Plants also shares the certain similar characteristics of leaves like color, texture, shape or size, making them hard to classify them among others. So, to eradicate this problem, a deep learning model has been used for the purpose for classification of different plants species captured in real-time using internet of things practice. Six different plants namely Ashwagandha, Black Pepper, Garlic, Ginger, Basil, and Turmeric has been selected for this purpose. Our proposed convolutional neural network (CNN) model achieved higher performance with an accuracy of 99
