27 research outputs found
The application prospects and development trends of orally disintegrating tablets to dogs
Powder Compaction: Compression Properties of Cellulose Ethers
Effective development of matrix tablets requires a comprehensive understanding of different raw material attributes and their impact on process parameters. Cellulose ethers (CE) are the most commonly used pharmaceutical excipients in the fabrication of hydrophilic matrices. The innate good compression and binding properties of CE enable matrices to be prepared using economical direct compression (DC) techniques. However, DC is sensitive to raw material attributes, thus, impacting the compaction process. This article critically reviews prior knowledge on the mechanism of powder compaction and the compression properties of cellulose ethers, giving timely insight into new developments in this field
Inverse solution for parameter estimation of a dynamic volume spline based forehead skin model
Quantitative determination of p-aminosalicylic acid and its degradation product m-aminophenol in pellets by ion-pair high-performance liquid chromatography applying the monolithic Chromolith Speedrod RP-18e column
Simulation of deformable models with the Poisson equation.
In this paper, we present a new methodology for the deformation of soft objects by drawing an analogy between the Poisson equation and elastic deformation from the viewpoint of energy propagation. The potential energy stored due to a deformation caused by an external force is calculated and treated as the source injected into the Poisson system, as described by the law of conservation of energy. An improved Poisson model is developed for propagating the energy generated by the external force in a natural manner. An autonomous cellular neural network (CNN) model is established by using the analogy between the Poisson equation and CNN to solve the Poisson model for the real-time requirement of soft object deformation. A method is presented to derive the internal forces from the potential energy distribution. The proposed methodology models non-linear materials with the non-linear Poisson equation and thus non-linear CNN, rather than geometric non-linearity. It not only deals with large-range deformations, but also accommodates isotropic, anisotropic and inhomogeneous materials by simply modifying constitutive coefficients. A haptic virtual reality system has been developed for deformation simulation with force feedback. Examples are presented to demonstrate the efficiency of the proposed methodology