PPSU hollow fiber nanofiltration membranes are prepared by applying two concentrations and various extrusion pressures according to the phase inversion method. Cross-sectional area and outer structures were characterized by using scanning electron microscope (SEM) and atomic force microscopy (AFM). In additional to the pore size distribution, either the mean roughness or the mean pore size of the PPSU hollow fiber surfaces was evaluated by AFM. It was found that the morphology of the PPSU fibers had both sponge-like and finger-like structures through different extrusion pressures and PPSU concentrations. The mean pore size and mean roughness for inner and outer surfaces were seen to be decreased with the increase of extrusion pressure at two different PPSU concentrations. Moreover, the lead ion rejection was significantly improved from 19 to 78 % with increasing the extrusion pressure from 2.5 to 3 bar at 25 wt.% PPSU concentration.
in this paper the notion of threshold relations by using resemblance relation are introduced to get a similarity relation from a resemnblance relation R
The purpose of this paper is applying the robustness in Linear programming(LP) to get rid of uncertainty problem in constraint parameters, and find the robust optimal solution, to maximize the profits of the general productive company of vegetable oils for the year 2019, through the modify on a mathematical model of linear programming when some parameters of the model have uncertain values, and being processed it using robust counterpart of linear programming to get robust results from the random changes that happen in uncertain values of the problem, assuming these values belong to the uncertainty set and selecting the values that cause the worst results and to depend buil
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In this research study Hardness (shore D), Water absorption,
Flexural, Impact Test, and Fracture Toughness of polymer nano
composites. The polymer nano composites based on unsaturated
polyester resin reinforced with Kevlar fibers (K.F). The samples are
attended by hand lay – up method according to (Rule mixture) for
various volume fractions of unsaturated polyester resin, fiber and
carbon nanotube. The polyester resin was matrix strengthened with
3% volume fraction from Kevlar fiber and (0.5%, 1%, 1.5%, 2%)
volume fractions of carbon nanotube. The water absorption, hardness
(shore D), flexural test, impact test and toughness fracture properties
were studied. Results showed that the water absorption increas
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia
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Titanium dioxide nanorods have been prepared by sol-gel template
method. The structural and surface morphology of the TiO2 nanorods was
investigated by X-ray diffraction (XRD) and atomic force microscopy
(AFM), it was found that the nanorods produced were anatase TiO2 phase.
The photocatalytic activity of the TiO2 nanorods was evaluated by the
photo degradation of methyl orange (MO). The relatively higher
degradation efficiency for MO (D%=78.2) was obtained after 6h of exposed
to UV irradiation.
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This study aimed to develop an oral drug delivery system for gastro-retentive sustained drug release of baclofen by using a 3D printed capsular device since baclofen has a short half-life of 2.5 to 4 hours and has a narrow absorption window. Firstly sustained-release tablets of baclofen were formulated through the hot-melt extrusion of various thermoplastic polymers and direct compression of the extrudate, then a capsular device was designed and 3D printed to contain two air pockets to enable floating of the device and has four windows for drug release.
3D printing of the capsular device was done by an FDM printer using biodegradable PLA filament, and the sustained release tablets were inserted into the device to allow the medici
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Background: This study evaluated the influence of different fiber formulations incorporation in resin composite on cuspal deflection (CD) of endodontically-treated teeth with mesio-occluso-distal (MOD) cavities. Materials and Methods: Thirty-two freshly extracted maxillary premolar teeth received MOD cavity preparation followed by endodontic treatment using single cone obturation technique, and divided into: Group I: direct composite resin only using a centripetal technique, Group II: direct composite resin with short fiber-reinforced composite (everX Flow), Group III: direct composite resin with leno wave ultra-high molecular weight polyethylene (LWUHMWPE) fibers placed on the cavity floor, and Group IV: direct composite resin with LWUHMWP
... Show MoreDenture bases are fabricated routinely using Poly(methyl methacrylate) (PMMA) acrylic resin. Yet, it is commonly known for its major drawbacks such as insufficient strength and ductility. The purpose of this study was to improve the performance of PMMA acrylic resin as a denture base material by reinforcement with surface treated lithium disilicate glass ceramic powder. The ceramic powder was prepared by grinding and sieving IPS e.max CAD MT blocks. Then, the powder was surface treated with an organosilane coupling agent (TMSPM) and added to PMMA in amount of 1%, 3%, 5% and 7% by weight. Characterizations of the powder was done by particle size analysis, XRD and FTIR. Transverse strength, Impact strength, Shore D hardness and surface roughn
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat
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