Drug solubility and dissolution remain a significant challenge in pharmaceutical formulations. This study aimed to formulate and evaluate repanglinide (RPG) nanosuspension-based buccal fast-dissolving films (BDFs) for dissolution enhancement. RPG nanosuspension was prepared by the antisolvent-precipitation method using multiple hydrophilic polymers, including soluplus®, polyvinyl alcohol, polyvinyl pyrrolidine, poloxamers, and hydroxyl propyl methyl cellulose. The nanosuspension was then directly loaded into BDFs using the solvent casting technique. Twelve formulas were prepared with a particle size range of 81.6-1389 nm and PDI 0.002-1 for the different polymers. Nanosuspensions prepared with soluplus showed a favored mean particle size of 82.6 ± 3.2 nm. The particles were spherical and non-aggregating, as demonstrated by SEM imaging. FTIR showed no interaction between soluplus and RPG. Faster dissolution occurred for the nanosuspension in comparison with pure RPG (complete release vs 60% within 30 min). The nanosuspension was successfully incorporated into BDFs. The optimum film formula showed 28 s disintegration time, and 97.3% RPG released within 10 min. Ex-vivo permeation profiles revealed improved RPG nanosuspension permeation with the cumulative amount of RPG permeated is103.4% ± 10.1 and a flux of 0.00275 mg/cm2/min compared to 39.3% ± 9.57 and a flux of 0.001058 mg/cm2/min for pure RPG. RPG was successfully formulated into nanosuspension that boosted drug dissolution and permeation. The selection of the ultimate NP formula was driven by optimal particle size, distribution, and drug content. Soluplus NPs were shown to be the successful formulations, which were further incorporated into a buccal film. The film was evaluated for ex-vivo permeation, confirming successful RPG formulation with improved performance compared to pure drugs.
Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as
... Show MoreIn this work, the possibility of a multiwavelength mode-locked fiber laser generation based on Four-Wave Mixing (FWM) induced by Fe2O3-SiO2 nanocomposite material is investigated for the first time. A multiwavelength mode-locked pulses fiber laser are generated from Ytterbium–doped fiber laser (YDFL) due to the combined action of high nonlinear absorption and high refractive coefficients of Fe2O3-SiO2 nanocomposite incorporated inside YDFL ring cavity. Up to more than 20 lasing lines in the 1040–1070 nm band with an equally lines separation of ~0.6 nm have been observed by just simple variation of passive modulation of the state of the polarization and the pump power altogether. Moreover, a passively mode-locked operation of YDFL laser
... Show MoreThis work aims to investigate the tensile and compression strengths of heat- cured acrylic resin denture base material by adding styrene-butadiene (S- B) to polymethyl methacrylate (PMMA). The most well- known issue in prosthodontic practice is fracture of a denture base. All samples were a blend of (90%, 80%) PMMA and (10%, 20%) S- B powder melted in Oxolane (Tetra hydro furan). These samples were chopped down into specimens of dimensions 100x10x2.5mm to carry out the requirements of tensile tests. The compression strength test specimens were shaped into a cylinder with dimensions of 12.7mm in diameter and 20mm in length. The experimental results show a significant increase in both tensile and compression strengths when compared to cont
... Show MoreThe determination of captopril (CAP) using a new continuous flow injection analysis (CFIA) method was given in this work CAP in its pure state and some of its pharmaceutical preparations. The technique can be described as simple, fast, sensitive, easy to operate, and low-cost. The CAP reacted with ammonium ceric(IV) sulfate (ACS)2(NH4 )2SO4Ce(SO4)2. 3 H2O in an acidic medium and the reaction led to the formation of a white, slightly yellowish precipitate. The formed precipitate was studied using Ayah 6S×1-ST-2D Solar cell-CFI Analyzer, a through the reflection of accident light on the surfaces of the precipitate particles at (0-1800), expressed as the response
... Show MoreAdvances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship an
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