Solid Lipid Nanoparticles: A Potential Approach for Dermal Drug Delivery

Solid lipid nanoparticles (SLNs) have attracted increasing attention during recent years. Due to their unique size dependent properties, lipid nanoparticles offer possibilities to develop new therapeutics. The ability to incorporate drugs into nanoparticles offers a new prototype in drug delivery thus realizing the dual goal of both controlled release and site-specific drug delivery. Drug delivery to the skin is widely used for local and systemic delivery and has potential to be improved by application of nanoparticulate formulations. If investigated appropriately, solid lipid nanoparticles may open new opportunities in therapy of complex diseases which is difficult to treat

Employee Attrition Prediction based on Grey Wolf Optimization and Deep Neural Networks

Despite the constructive application of promising technologies such as Neural Networks, their potential for predicting human resource management outcomes still needs to be explored. Therefore, the primary aim of this paper is to utilize neural networks and meta-heuristic technologies to predict employee attrition, thereby enhancing prediction model performance. The conventional Grey Wolf optimization optimization (GWO) has gained substantial attention notice because of its attributes of robust convergence, minimal parameters, and simple implementaton. However, it encounter problems with slow convergence rates and susceptibility to local optima in practical optimization scenarios. To address these problems, this paper introduces an enhanced Grey Wolf Optimization algorithm incorporating the utilization of Cauchy-Gaussian mutation, which contributes to enhancing diversity within the leader wolf population and enhances the algorithm's global search capabilities. Additionally, this work preserves exceptional grey wolf individuals through a greedy selection of 2 mechanisms to ensure accelerated convergence. Moreover, an enhanced exploration strategy is suggested to expand the optimization possibilities of the algorithm and improve its convergence speed. The results shows that the proposed model achieved the accuarcy of 97.85%, precision of  98.45%, recall of 98.14%, and f1-score of 97.11%. Nevertheless, this paper extends its scope beyond merely predicting employee attrition probability and activities to enhance the precision of such predictions by constructing an improved model employing a Deep Neural Network (DNN).

DESIGN AND EVALUATION OF FAST DISSOLVING TABLETS OF ERGOTAMINE TARTARATE

Objective: The main objective of this study was to formulate and evaluate the fast dissolving tablets of ergotamine tartarate with synthetic superdisintegrants. Methods: Various formulations were prepared by direct compression method using different concentrations of crospovidone (12.5%-62.5%) and croscarmallose sodium (12.5%-62.5%) as superdisintegrants. Formulations were evaluated for precompressional parameters and postcompressional parameters like uniformity of weight, thickness, hardness, friability, drug content, wetting time, the water absorption ratio, in vitro disintegration time and in vitro dissolution study. Results: Results revealed that among the 10 formulations, the formulation F5 containing 62.5% of crospovidone and formulation F10 containing 62.5% of croscarmallose sodium was found to be promising formulations. F5 shown disintegration time of 12 seconds and the drug release was up to 96% in 30 minutes and F10 shown disintegration time of 18 seconds and the drug release was up to 89% in 30 minutes. Conclusion: From the result obtained, it can be concluded that formulation of fast dissolving tablet using crospovidone as a superdisintegrant showed improved disintegration and solubility and hence better patient complianc

Closed-Range Composition Operators on A2 and the Bloch Space

For any analytic self-map φ of {z : |z| \u3c 1} we give four separate conditions, each of which is necessary and sufficient for the composition operator Cφ to be closed-range on the Bloch space B . Among these conditions are some that appear in the literature, where we provide new proofs. We further show that if Cφ is closed-range on the Bergman space A2 , then it is closed-range on B , but that the converse of this fails with a vengeance. Our analysis involves an extension of the Julia-Carathéodory Theorem

Closed-Range Composition Operators on A2 and the Bloch Space

For any analytic self-map φ of {z : |z| \u3c 1} we give four separate conditions, each of which is necessary and sufficient for the composition operator Cφ to be closed-range on the Bloch space B . Among these conditions are some that appear in the literature, where we provide new proofs. We further show that if Cφ is closed-range on the Bergman space A2 , then it is closed-range on B , but that the converse of this fails with a vengeance. Our analysis involves an extension of the Julia-Carathéodory Theorem

Photocatalytic activity of mixed-phase of TiO2 synthesized by non-aqueous methodology

768-774A mix-phase (anatase-rutile) nanocrystalline titania particles were successfully synthesized in a non-aqueous solvent medium using a novel approach of controlled hydrolysis of titanium isopropoxide. The hydrolysis was carried out by the controlled release of water molecules from simple Schiff base formation reaction of anisaldehyde employing aniline as an amine component in isopropanol solvent medium. The excess aniline used, and the imine formed acts as directing agents. The photocatalytic activities of the catalysts prepared were compared with Degussa P25 for methylene blue degradation in direct sunlight. The photocatalytic activity was found to increase with decreasing availability of water molecules formed during the Schiff base formation (imination) reaction. Also, it was found to affect the phase and shape selection. TEM images show sphere-like to hexagonal to a rod-shaped formation of particulates