Sensitivity of Viscosity on Molten Ti Infusion into a B4C-Packed Bed at the Microscale

Metallurgical and Materials Transactions B - The effect of the surface tension–viscosity dissipation driving liquid Ti flow into a B4C packed bed was analyzed at 1941 K and 2573 K. The model...     

In vivo evaluation of a mucoadhesive polymeric caplet for intravaginal anti-HIV-1 delivery and development of a molecular mechanistic model for thermochemical characterization

Context and objective: The aim of this study was to develop, characterize and evaluate a mucoadhesive caplet resulting from a polymeric blend (polymeric caplet) for intravaginal anti-HIV-1 delivery.

Materials and methods: Poly(lactic-co-glycolic) acid, ethylcellulose, poly(vinylalcohol), polyacrylic acid and modified polyamide 6, 10 polymers were blended and compressed to a caplet-shaped device, with and without two model drugs 3′-azido-3′-deoxythymidine (AZT) and polystyrene sulfonate (PSS). Thermal analysis, infrared spectroscopy and microscopic analysis were carried out on the caplets employing temperature-modulated DSC (TMDSC), Fourier transform infra-red (FTIR) spectrometer and scanning electron microscope, respectively. In vitro and in vivo drug release analyses as well as the histopathological toxicity studies were carried out on the drug-loaded caplets. Furthermore, molecular mechanics (MM) simulations were carried out on the drug-loaded caplets to corroborate the experimental findings.

Results and discussion: There was a big deviation between the T_g of the polymeric caplet from the T_g's of the constituent polymers indicating a strong interaction between constituent polymers. FTIR spectroscopy confirmed the presence of specific ionic and non-ionic interactions within the caplet. A controlled near zero-order drug release was obtained for AZT (20 d) and PSS (28 d). In vivo results, i.e. the drug concentration in plasma ranged between 0.012–0.332?mg/mL and 0.009–0.256?mg/mL for AZT and PSS over 1–28 d.

Conclusion: The obtained results, which were corroborated by MM simulations, attested that the developed system has the potential for effective delivery of anti-HIV-agents.     

Deep autoencoders for feature learning with embeddings for recommendations: a novel recommender system solution

Neural Computing and Applications - We propose “Deep Autoencoders for Feature Learning in Recommender Systems,” a novel discriminative model based on the incorporation of features from...     

Identifying crop water stress using deep learning models

Neural Computing and Applications - The identification of water stress is a major challenge for timely and effective irrigation to ensure global food security and sustainable agriculture. Several...     

Analytical Modeling of Surface Potential and Drain Current of Hetero-Dielectric DG TFET and Its Analog and Radio-Frequency Performance Evaluation

Semiconductors - In the present paper, analytical modeling of surface potential and drain current for hetero-dielectric double gate tunnel FET (HDG-TFET) has been done. The two dimensional (2D)...     

Detailed study on fusion characteristics of rigid poly(vinyl chloride) nanocomposites: The comparison of using multiple regression analysis and artificial neural network

Fusion behavior of poly(vinyl chloride) (PVC) compounds plays an important role in the development of physical properties of processed material. The fusion characteristics in PVC processing are governed by material variables that affect the fusion with some interactions. In this research, the aim was to characterize the effects of formulation ingredients on fusion characteristics of PVC. Four material parameters, including the contents of nanoclay (NC), azodicarbonamide, calcium stearate, and processing aid, are proposed as affecting variables. The fusion time (FT) as well as fusion factor (FF) are considered fusion indicators and are experimentally determined in some different levels of affecting parameters. The multivariable regression analysis (MRA) and the Artificial Neural Network (ANN) modeling are considered as two analytical methods. The regression analysis result for the FT denotes, in part, significant linear and quadratic effects of NC and also its significant interactions with azodicarbonamide and calcium stearate, whereas that of FF indicates only a linear effect of NC. ANN modeling is performed with a three‐layer (input, hidden, and output) neural network. The results of the comparison of the MRA and ANN predictions with experimental values are reported as the correlation coefficient (R²), mean‐square error, and mean absolute percentage error for both FF and FT parameters. The obtained values clearly denote that the ANN results are more precise and especially more general than those of MRA. However, in the case of FT, improvement of the ANN modeling is much greater than that of FF. J. VINYL ADDIT. TECHNOL., 21:147–155, 2015. © 2014 Society of Plastics Engineers     

Analytical Modeling of a Triple Material Double Gate TFET with Hetero-Dielectric Gate Stack

Silicon - In this paper, we propose and develop an analytical model of a Triple material double gate Tunnel Field Effect Transistor (TM-DG TFET) with hetero-dielectric gate oxide stack comprising...     

High‐performance thermosets with tailored properties derived from methacrylated eugenol and epoxy‐based vinyl ester

A renewable chemical, eugenol, is methacrylated to produce methacrylated eugenol (ME) employing the Steglich esterification reaction without any solvent. The resulting ME is used as a low‐viscosity co‐monomer to replace styrene in a commercial epoxy‐based vinyl ester resin (VE). The volatility and viscosity of ME and styrene are compared. The effect of ME loading and temperature on the viscosity of the VE–ME resin is investigated. Moreover, the thermomechanical properties, curing extent and thermal stability of the fully cured VE–ME thermosets are systematically examined. The results indicate that ME is a monomer with low volatility and low viscosity, and therefore the incorporation of ME monomer in VE resins allows significant reduction of viscosity. Moreover, the viscosity of the VE–ME resin can be tailored by adjusting the ME loadings and processing temperature to meet commercial liquid molding technology requirements. The glass transition temperatures of VE–ME thermosets range from 139 to 199 °C. In addition, more than 95% of the monomer is incorporated and fixed in the crosslinked network structure of VE–ME thermosets. Overall, the developed ME monomer exhibits promising potential for replacing styrene as an effective low‐viscosity co‐monomer. The VE–ME resins show great advantages for use in polymer matrices for high‐performance fiber‐reinforced composites. This work is of great significance to the vinyl ester industry by providing detailed experimental support. © 2018 Society of Chemical Industry