The University of Allahabad is a collegiate central university located in Allahbad, Uttar Pradesh, India. It was established on 23 September 1887 by an Act of Parliament and is recognised as an Institute of National Importance (INI). It is one of the oldest modern universities in India. Its origins lie in the Muir Central College, named after Lt. Governor of North-Western Provinces, Sir William Muir in 1876, who suggested the idea of a Central University at Allahabad, which later evolved to the present university. it was known as the "Oxford of the East". Its Central University status was re-established through the University of Allahabad Act 2005 by the Parliament of India.
Electric vehicles’ (EVs’) accelerated expansion is changing transportation systems and making managing the charging infrastructure and power grid much more difficult. In order to handle issues like demand variations, charging congestion, grid instability, intermittent renewable energy, and cybersecurity risks, intelligent coordination techniques are needed. Through data-driven forecasting, predictive control, and automated decision-making, artificial intelligence (AI) has become a crucial enabling technology for optimizing EV charging networks. An organized and thorough analysis of AI methods used in intelligent infrastructure for EV charging is presented in this research. System architecture, operational difficulties, optimization techniques, deployment obstacles, and new research avenues are all methodically examined in this paper. To guarantee openness and repeatability, a PRISMA-based approach for choosing literature is used. The scalability and practical viability of major AI technologies are compared, including deep learning for predictive maintenance, optimization-based scheduling, machine learning for demand forecasting, and reinforcement learning in order for real-time charging control. Additionally, this assessment highlights important implementation gaps in the areas of economic modeling, cybersecurity integration, distributed intelligence, and standards. Future research avenues for secure, self-optimizing, and autonomous charging ecosystems are explored. Academics, system operators, and politicians working toward the widespread implementation of AI-enabled EV infrastructure can use the findings as technical assistance.
We develop a thermodynamically consistent nonperturbative framework for equilibrium criticality in QCD matter by unifying Dyson-Schwinger quark propagation, functional renormalization-group (FRG) evolution of the effective action, and Polyakov- Nambu-Jona-Lasinio (PNJL) thermodynamics for the coupled chiral and deconfinement order parameters. A holographic Maxwell-Chern-Simons sector supplies the topological response, and its topological susceptibility is fed into the FRG flow of the determinantal ('t Hooft) interaction to encode the evolution of the axial anomaly across the phase diagram. At mu(B) = 0, the construction is anchored to continuum-extrapolated lattice thermodynamics and conserved-charge susceptibilities through a lattice-calibrated Polyakov sector, while exact thermodynamic identities are enforced by evaluating all derivatives at the stationary solution of the grand potential at each RG scale. Solving the coupled DSE, FRG, and holographic system yields, within this framework and at the present level of approximation, an equilibrium critical end point (CEP) at T-CEP similar or equal to 130 to 135 MeV and mu(B,CEP) similar or equal to 600 MeV together with an internally quantified sensitivity to regulator, Polyakov-sector, and holographicnormalization variations. The critical region is organized by a nonperturbative mapping to universal 3D Ising scaling variables with anomalous-dimension effects absorbed into nonuniversal metric factors, leading to equilibrium predictionsfor the hierarchy, nonmonotonicity, and sign structure of higher-order net-baryon cumulant ratios along the smooth freeze-out trajectories, as well as equilibrium softening of the speed of sound. Comparisons to RHIC beam energy scan fluctuation measurements are presented as qualitative consistency checks on correlated equilibrium trends and sign patterns, because finite size and lifetime, critical slowing down, baryon number conservation, acceptance and efficiency corrections, the net-proton to net-baryon conversion, and baryon-transport dynamics can round or reshape cumulants in the experimental system. The results, therefore, provide a unified equilibrium baseline and a set of controlled inputs for finite-size scaling and dynamical embeddings of heavy-ion data.
Reproductive phenology provides insights into plant adaptation strategies under changing climates, and thus requires extensive studies on intraspecific variations across climate gradients. In this study, we examined the reproductive phenology of the Himalayan wild cherry (Prunus cerasoides Buch. -Ham. Ex D. Don) at two climatically contrasting sites – the tropical Mizoram, part of the Indo-Burma region, and the temperate Uttarakhand, part of the western Himalayas, between 2019 and 2023. Monthly climatic variations in temperature, rainfall, humidity, and wind speed, as well as the reproductive phenological observations of the flowering and the fruiting phases, were recorded. Comparative analyses revealed an earlier and shorter flowering period in Uttarakhand compared to Mizoram, suggesting site-specific adaptive responses of the Himalayan wild cherry. We developed and implemented a staggered machine learning pipeline using regularised regression models (Lasso, Elastic Net and Ridge) to predict four key events: first flowering day, peak flowering day, last flowering day and the fruit drop day, using site-specific monthly climatic data. Temperature, rainfall, and their interaction were the major determinants of reproductive timing, contributing to nearly 90
Emerging evidence confirms the expression of functional growth hormone (GH) receptors in the male and female reproductive systems, and suggests that the GH signaling might influence gonadal function by acting at different levels of the hypothalamic-pituitary-gonadal (HPG) axis in animals and mammals. Despite this, the role of GH in the modulation of the gonadal cycle in seasonal breeders has been less explored. This study focused on a free-living passerine, Amandava amandava (Red Munia), a distinct seasonal breeder. It aimed at elucidating the plasticity in pituitary expression of the GH, and alteration in the plasma hormone profile across life-history stages parallel to the testicular cycle (histomorphometry and plasma levels of testosterone). The pituitary expression and plasma GH levels remained elevated during the breeding cycle, where the energy-demanding process of testicular recrudescence occurs. The study correlated the plasma GH level with various parameters of the testis and suggests that physiological GH, in association with pituitary gonadotropins, may facilitate the growth and functionality of the testis. The extrapituitary localization of GH in the hypothalamus, optic chiasma, and cerebral cortex during the breeding cycle suggests its paracrine role in the modulation of the gonadotropin-releasing hormone secretion. GH may help meet energy requirements and achieve reproductive status during the transition from the non-breeding to breeding life-history stage, interacting with hormones from other endocrine axes related to reproduction.
The present research evaluates in vivo antihyperglycemic together with antioxidant vigor of wheatgrass on streptozotocin-induced hyperglycemic rats. The previous research on in vitro activity of wheatgrass documented its immense potentiality so the current research was inspired to explore its in vivo efficacy. Subsequently, the experimental rats were arbitrarily segregated comprising of four groups of three animals each. A single intraperitoneal injection of streptozotocin was administered to the rats to induce hyperglycemia. Freshly prepared 0.1 M ice-cold citrate buffer was used at a dosage of 55 mg/kg body mass. However, administering wheatgrass extract to hyperglycemic rats caused a drop in glycemia which indicates antidiabetic potentials of wheatgrass. Evaluation of antioxidant activity in all the rat groups by DPPH and FRAP assay revealed that wheatgrass extract improved the antioxidant activities in hyperglycemic rats, but the antioxidant activities considerably declined in streptozotocin-treated rats versus normal control rats. Further, administration of STZ significantly reduced GSH levels in hyperglycemic rats in comparison with control rats but subsequently the supplementation with wheatgrass extract considerably elevated GSH content in hyperglycemic rats. Moreover, MDA content considerably declined in hyperglycemic rats when treated with wheatgrass extract in contrast to hyperglycemic control rats. The supplementation of wheatgrass extract in hyperglycemic rats restored MDA content near to normal control rats. A considerable elevation in sialic acid of plasma was recorded in STZ-induced hyperglycemic rats versus control. However, supplementing extract of wheatgrass to diabetic rats restored the content of sialic acid. Subsequently, administration of wheatgrass extract to hyperglycemic rats showed a considerable decline in lipid profile, viz., total cholesterol, triglycerides, LDL, and VLDL levels, and a rise in HDL level. Furthermore, wheatgrass extract supplementation to hyperglycemic rats documented a significant decline in liver function parameters such as SGOT, SGPT, and alkaline phosphatase levels, as well as kidney function parameters such as urea and creatinine levels. Finally, the HPLC of wheatgrass extract revealed the presence of chlorophyllin and rutin conferring antidiabetic and antioxidant efficacy.
