The current research aimed at designing mesoporous silica nanoparticles (MSNs) for a controlled coadministration of salicylic acid (SA) and ketoconazole (KCZ) to effectively treat highly resistant fungal infections. The sol-gel method was used to formulate MSNs, which were further optimized using central composite rotatable design (CCRD) by investigating mathematical impact of independent formulation variables such as pH, stirring time, and stirring speed on dependent variables entrapment efficiency (EE) and drug release. The selected optimized MSNs and pure drugs were subjected to comparative in vitro/in vivo antifungal studies, skin irritation, cytotoxicity, and histopathological evaluations. The obtained negatively charged (-23.1), free flowing spherical, highly porous structured MSNs having a size distribution of 300-500 nm were suggestive of high storage stability and improved cell proliferation due to enhanced oxygen supply to cells. The physico-chemical evaluation of SA/KCZ-loaded MSNs performed through powder X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and thermal gravimetric analysis (TGA) indicates absolute lack of any interaction between formulation components and successful encapsulation of both drugs in MSNs. The EESA, EEKCZ, SA release, and KCZ release varied significantly from 34 to 89%, 36 to 85%, 39 to 88%, and 43 to 90%, respectively, indicating the quadratic impact of formulation variables on obtained MSNs. For MSNs, the skin tolerability and cell viability percentage rate were also having an extraordinary advantage over suspension of pure drugs. The optimized SA/KCZ-loaded MSNs demonstrated comparatively enhanced in vitro/in vivo antifungal activities and rapid wound healing efficacy in histopathological evaluation without any skin irritation impact, suggesting the MSNs potential for the simultaneous codelivery of antifungal and keratolyic agents in sustained release fashion.
The growing awareness regarding environmental issues has encouraged stakeholders’ broader participation in green management and production. The article aims to investigate the role of green human resource management (GHRM) and eco-innovation (GI) in firm performance. Drawing upon the quantitative data collected through a structured questionnaire, the present study investigated how GHRM influences firms’ financial performance through the mediation of eco-innovation. The study findings suggested the significance of GHRM in influencing financial performance through the mediating role of GI. Despite the rising scholarly interest in studying GHRM, very few studies examined its influence on organizational performance in general and financial performance in particular. The present study intends to bridge the literary gaps by examining both the direct relationship between GHRM and firms’ financial performance and the indirect mechanism linking GHRM with a firm’s financial performance through GI, adding a unique contribution to literature and practice
The main objective of this manuscript is to derive the new class of black hole solutions exhibiting exotic matter properties in the framework of f(Q,T) gravity, where Q is non-metricity and T the trace of the energy-momentum tensor. Using the extended gravitational decoupling approach, we separate the field equations into two sets, one for a seed source and another for an additional anisotropic source that introduces violations of the energy conditions. Three different analytical configurations emerge when a specific equation of state is implemented that relates the constituent components of the source. The solutions obtained show a variety of rich physical behaviors governed by a decoupling parameter. For the positive decoupling parameter values, the energy density throughout the entire configuration is positive, while in two of the three models the radial pressure becomes negative, a crucial characteristic that is usually found in the interiors of black holes. All extended solutions violate the energy conditions, verifying the existence of exotic matter interior to the spacetime geometry. The metric potentials of any configuration show no singularities of any sort at the event horizon (r = 2M), while the central curvature singularity at r = 0 is enclosed, maintaining the causal structure. Moreover, asymptotic analysis demonstrates that as r -> infinity, all extended geometries gradually approach the condition of flat spacetime, confirming asymptotic flatness and providing a definitive closure to the analysis. This work establishes that f(Q,T) theory supports stable, asymptotically flat exotic compact objects, providing a new theoretical framework for horizonless alternatives to black holes.
Our analysis is particularly motivated by its relevance to understanding compact object instabilities, gravitational collapse thresholds, and the formation of dense structures under the influence of modified gravity theories. The interplay of anisotropic pressures, perturbative dynamics, and modified gravity contributions offers insight into both the stable configuration of dense fluids and the mechanisms leading to dynamical instability. Such considerations directly contribute to the aims of high energy density profiles, particularly in modeling physical systems where extreme pressure, curvature, and matter interactions co-exist. We consider an axially symmetric, dense structure with anisotropic matter content and employ a specific equation of state (EoS) to examine the interplay between static and dynamic quantities via the adiabatic index. To address the complex dynamics of the collapse process, a perturbative scheme is utilized under Newtonian and post-Newtonian approximations, enabling a detailed examination of the stability and structural evolution of the system under the influence of the considered minimally coupled gravity. Our results demonstrate that hydrostatic equilibrium is maintained when effective pressure, gravitational, and anti-gravitational forces are balanced, while deviations from this balance initiate dynamical instability. Graphical representations of stable and unstable regimes are presented, revealing how the choice of gravity functions significantly affects the outcome. This work provides insight into the behavior of dense, self-gravitating configurations under modified gravity, offering broader implications for the modeling of compact astrophysical objects and contributing to the understanding of gravitational collapse in energy density regimes.
Microgrids offer a promising paradigm for sustainable and decentralized energy management; however, they face operational challenges due to fluctuating load profiles and the intermittency of renewable energy sources. This paper proposes a two-phase framework to address these challenges through accurate short-term load forecasting (STLF) and an advanced energy management system (EMS) for grid-connected multi-microgrids. In Phase I, STLF was performed using residential metering infrastructure data from the PRECON dataset. A hybrid deep learning model, Prophet-Long Short-Term Memory (PLSTM), was developed and outperformed benchmarks, including LSTM, XGBoost, SARIMA, and Prophet, reducing the error by 12%-18%. In Phase II, an AI-enhanced EMS is introduced, integrating PLSTM-based load forecasting, ANN-based photovoltaic generation prediction, adaptive self-learning weights, and deep Q-learning for forecast margin tuning. This robust hierarchical model predictive control strategy eliminates reliance on demand-side management and preserves user comfort. The simulation results demonstrate that the proposed framework outperforms conventional baseline EMS methods in terms of energy efficiency, reducing grid imports by 28%, adaptability with average SoC tracking improvement of 15%, and resilience indicated by a 22% increase in battery cycle longevity under uncertainties in load consumption and solar energy generation, offering a scalable solution for microgrid deployment in dynamic environments.
