Background: The treatment of schizophrenia typically involves the use of olanzapine (OLZ), a typical antipsychotic drug that has poor oral bioavailability due to its low solubility and first-pass effect.  Objective: To prepare and optimize OLZ as nanoparticles for transdermal delivery to avoid problems with oral administration. Methods: The nanoprecipitation technique was applied for the preparation of eight OLZ nanoparticles by using different polymers with various ratios. Nanoparticles were evaluated using different methods, including particle size, polydispersity index (PDI), entrapment efficiency (EE%), zeta potential and an in vitro release study. The morphology was evaluated by a field emission scanning electron microscope (F

Prochloperazine maleate (PCM) is one of the most prescribed phenothiazine. The purpose of the present research was to develop fast dissolving tablets of PCM with β-cyclodextrin inclusion complex. Tablets prepared  by wet granulation with sublimation and by using  different superdisintegrants type [ low-hydroxypropylcellulose LH21 (L-HPC LH21), carboxymethylcellulose calcium (ECG505), crospovidone (CP)], and different type of subliming agents (urea and ammonium bicarbonate (AB)). Tablets evaluated for its % friability, disintegration time, wetting time, hardness, content uniformity, weight variation, in vitro dissolution studies. For further enhancement of disintegration and dissolution, PCM orodispersible tablet were formula

 The gas sensing properties of undoped Co₃O₄ and doped with Y₂O₃ nanostructures were investigated. The films were synthesized using the hydrothermal method on a seeded layer. The XRD, SEM analysis and gas sensing properties were investigated for the prepared thin films. XRD analysis showed that all films were polycrystalline, of a cubic structure with crystallite size of (12.6) nm for cobalt oxide and (12.3) nm for the Co₃O₄:6% Y₂O₃. The SEM analysis of thin films indicated that all films undoped Co₃O₄ and doped possessed a nanosphere-like structure.

The sensi

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

Among a variety of approaches introduced in the literature to establish duality theory, Fenchel duality was of great importance in convex analysis and optimization. In this paper we establish some conditions to obtain classical strong Fenchel duality for evenly convex optimization problems defined in infinite dimensional spaces. The objective function of the primal problem is a family of (possible) infinite even convex functions. The strong duality conditions we present are based on the consideration of the epigraphs of the c-conjugate of the dual objective functions and the ε-c-subdifferential of the primal objective functions.