A Mechanistic Approach To Model the Compression Cycle of Different Toolings Based on Compression Roller Interactions.

The aim of the current work was to model and understand the mechanical interactions of tooling heads with compression rollers during tableting. Binary direct compression blends of Prosolv® SMCC with 0.5% w/w magnesium stearate and ternary blends with 30% w/w acetaminophen were used.

Influence of punch geometry (head-flat diameter) and tooling type ('B' or 'D') on the physical-mechanical properties of formulation tablets.

The presented study assessed the influence of punch geometry (head-flat [HF] diameter) and tooling type ('B' or 'D') on the physical-mechanical properties of tablets prepared by direct-compression of two guaifenesin (25% or 40% w/w) formulations. Tablets of both formulations were prepared on instrumented, single-layer, rotary tablet press using 10 mm, flat-faced, 'B' or 'D'-type tooling with different HF diameters, and compression forces (CF) ranging from 5 to 25 kN with 5 kN increments. The tablets were evaluated for dimensions, weight variation, tensile strength (TS), friability, and capping index.

Comparison of the impedance cardiogram with continuous wave radar using body-contact antennas.

This paper describes a continuous wave (CW) radar system with body-contact antennas and basic signal processing. The goal is to assess the signals' reproducibility across different subjects as well as a respiration cycle. Radar signals using body-contact antennas with a carrier frequency of 868 MHz are used to acquire the cardiac activity at the sternum.

Fusion Method for Solubility and Dissolution Rate Enhancement of Ibuprofen Using Block Copolymer Poloxamer 407.

Aim of current research was to prepare ibuprofen-poloxamer 407 binary mixtures using fusion method and characterize them for their physicochemical and performance properties. Binary mixtures of ibuprofen and poloxamer were prepared in three different ratios (1:0.25, 1:0.

High-order neural networks and kernel methods for peptide-MHC binding prediction.

Motivation: Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between different amino acid positions. As a result, they often produce low-quality rankings of strong binding peptides.