Design, Characterization and In-vitro Evaluation of Favipiravir Orodispersible Films

Introduction: Orodispersible films (ODF) is a thin strip that is mostly transparent, biodegradable and it has hydrophilic polymers that disintegrate and dissolves immediately when getting in contact with saliva. Different disintegrants play a crucial role in film properties such as organoleptic properties, film thickness, and in particular disintegration time of the film. The main reason for the development of oral films is for their prominent role in increased patient compliance among pediatrics and geriatrics by disintegrating faster, releasing the drug rapidly, without the need for water, and mostly decreasing the risk of choking. Aim: To formulate orodispersible films of favipiravir and to study the effect of different superdisintegrants on various film properties. Methods: The method used to prepare the film is the solvent casting method. In this method, the solution is prepared using polymer, drug, and superdisintegrants. This solution is casted on a film-forming apparatus using a spreader an instrument to obtain a thin film. Results: The prepared oral films weights ranging from 148mg to 237mg based on the superdisintegrant concentration. The pH of the prepared films didn’t vary significantly and percent moisture absorption doesn’t have significant variation. However, the texture varied from smooth to rough and transparent to translucent. Disintegration time is varying from 28 to 42 seconds. The optimum batch formulation gave 98% of drug release.

Exactly sparse Gaussian variational inference with application to derivative-free batch nonlinear state estimation

We present a Gaussian variational inference (GVI) technique that can be applied to large-scale nonlinear batch state estimation problems. The main contribution is to show how to fit both the mean and (inverse) covariance of a Gaussian to the posterior efficiently, by exploiting factorization of the joint likelihood of the state and data, as is common in practical problems. This is different than maximum a posteriori (MAP) estimation, which seeks the point estimate for the state that maximizes the posterior (i.e., the mode). The proposed exactly sparse Gaussian variational inference (ESGVI) technique stores the inverse covariance matrix, which is typically very sparse (e.g., block-tridiagonal for classic state estimation). We show that the only blocks of the (dense) covariance matrix that are required during the calculations correspond to the non-zero blocks of the inverse covariance matrix, and further show how to calculate these blocks efficiently in the general GVI problem. ESGVI operates iteratively, and while we can use analytical derivatives at each iteration, Gaussian cubature can be substituted, thereby producing an efficient derivative-free batch formulation. ESGVI simplifies to precisely the Rauch–Tung–Striebel (RTS) smoother in the batch linear estimation case, but goes beyond the ‘extended’ RTS smoother in the nonlinear case because it finds the best-fit Gaussian (mean and covariance), not the MAP point estimate. We demonstrate the technique on controlled simulation problems and a batch nonlinear simultaneous localization and mapping problem with an experimental dataset.

Microfluidic Based Fabrication and Characterization of Highly Porous Polymeric Microspheres

Polymeric porous particles are currently used for various applications in biotechnology, tissue engineering and pharmaceutical science, e.g., floating drug delivery systems and inhaled formulations. Particle shape and size depend on variable parameters; among them, polymer type and concentration, stirring speed, pH and type of solvent. In this study, porous poly(lactic-co-glycolic) acid (PLGA) and poly(d,l-lactide) (PLA) microspheres (MPs), with varying sizes and morphologies, were synthesized and optimized using both batch formulation and a flow-focusing microfluidic device. A well-established method of preparation utilizing solvent evaporation and the double emulsion technique was performed. Similar to other batch encapsulation methods, this technique is time and reagent consuming and consists of several steps. Hence, although porous structures provide tremendous opportunity in the design of new applications for tissue engineering and as improved controlled-release carriers, the synthesis of these particles with predefined properties remains challenging. We demonstrated the fabrication of porous MPs using a simple microfluidic device, compared to batch synthesis fabrication; and the effect of solvent, polymer concentration and type, post-hydrolysis treatment, on porosity degree. Moreover, a kinetic release study of fluorescent molecule was conducted for non-porous in comparison to porous particles. An overview of future prospects and the potential of these porous beads in this scientific area are discussed.

Improvement of a Preparation Process of Chromite Raw Material Used for Ferroalloys and Pigments Manufacture

<p>The given article contains the research results of carbon-containing chromite pellets’ production from off-grade raw material with application of internal coal-mining overburden rocks as flux. Besides, for the purpose of improvement of ecological situation in industrial regions and expansion of a raw-material base for ferrochrome and pigments manufacture we suppose to use in a charge composition the dust of aspiration units and electrostatic precipitators, which is formed at the preparation of raw materials and production of chromite pellets. The production technology of chromite pellets with use of a slime formed at the concentration of chrome ores as a binding substance was developed. Testing the suggested technology has been carried out in laboratory and trial conditions. The data of a chemical composition of initial components of a charge and calcined carbon-containing chromite pellets have shown economic and ecological efficiency of the developed technological process. Research results lead to the conclusion that the proposed granulation feedstock mixture pellets with a moisture content of 11–12% are obtained crude granules have a compressive strength of 2.3–3.2 kg/splashed. Increasing the content of Cr₂O₃ in the pellets to 7.6% occurs due to the increase in the extraction of chromium oxide and due to the charge of chromium oxides contained in the sludge, as well as removal of the batch formulation was heat treated carbonates, and volatile organic substances. It was established that during this mode, the temperature in the lower layers is about 1200 °C, and a reduction in natural gas consumption achieves 50% and the residual carbon content in the pellets is about 1.5%, which leads to improvement of technical and economic indices of production chromite pellets and ferrochrome.</p>

Incremental and Decremental Exponential Discriminant Analysis for Face Recognition

Linear Discriminant Analysis (LDA) is widely used for feature extraction in face recognition but suffers from small sample size (SSS) problem in its original formulation. Exponential discriminant analysis (EDA) is one of the variants of LDA suggested recently to overcome this problem. For many real time systems, it may not be feasible to have all the data samples in advance before the actual model is developed. The new data samples may appear in chunks at different points of time. In this paper, the authors propose incremental formulation of EDA to avoid learning from scratch. The proposed incremental algorithm takes less computation time and memory. Experiments are performed on three publicly available face datasets. Experimental results demonstrate the effectiveness of the proposed incremental formulation in comparison to its batch formulation in terms of computation time and memory requirement. Also, the proposed incremental algorithms (IEDA, DEDA) outperform incremental formulation of LDA in terms of classification accuracy.