5 research outputs found
On the Dynamic Stability of Block Sliding on Rock Slopes
This paper deals with the dynamic analysis of block sliding on rock slope along plane surfaces, such as joints, bedding planes and faults. According to the results obtained in the shaking tests the dynamic friction along a sliding surface is dependent on the velocity of relative motion, and can be determined by using the proposed method of test. On the basis of conducted experiments a differential equation was established. The integration of the dynamics equation by numerical method provides a basis for evaluation of slope stability in terms of critical displacement and dynamic instability
Formulation and evaluation of transdermal drug-delivery system of isosorbide dinitrate
The purpose of this study was to develop a reservoir-type transdermal delivery system for isosorbide dinitrate (ISDN). The developed patch consisted of five layers from bottom to top, namely, a temporary liner, an adhesive layer, a rate-controlling membrane, a reservoir and a backing. The effects of chemical penetration enhancers, reservoir materials and rate-controlling membranes on the release behaviour of ISDN from the transdermal patch were studied, and the; in vitro; release of ISDN from the developed patch was studied and compared with the commercially available ISDN patch. The results showed that there was no significant difference in permeation rates between the developed reservoir-type patch and the commercially available ISDN patch (;p;>; 0.05). Moreover, the cumulative release ratio of the commercially available ISDN patch in 48 h was up to 89.8%, whereas the developed patch was only 34.9%, which meant the sustained release time of the developed patch was much longer than the commercially available ISDN patch, and would promote the satisfaction of the patient.;O objetivo do presente estudo foi desenvolver um sistema de liberação transdérmico do tipo reservatório para o dinitrato de isossorbida (ISDN, abrevitura em Inglês). A formulação transdérmica desenvolvida constou de cinco camadas de baixo para cima, ou seja, um revestimento temporário, uma camada adesiva, uma membrana controladora da taxa de liberação, um reservatório e um reforço. Estudaram-se os efeitos dos potenciadores de penetração química, materiais do reservatório e membranas de controle da taxa de liberação no comportamento da formulação transdérmica de dinitrato de isossorbida. A liberação; in vitro; da formulação transdérmica de dinitrato de isossorbida desenvolvida foi estudada em comparação com a formulação de dinitrato de isossorbida disponível comercialmente. Os resultados mostraram que não existem diferenças significativa nas taxas de permeação entre o tipo de reservatório desenvolvido e o de dinitrato de isossorbida desenvolvido comercialmente (;p;>;0,05). Ademais, a taxa de liberação cumulativa da formulação de dinitrato de isossorbida disponível comercialmente em 48 horas foi de até 89,8% e a da formulação desenvolvida, de apenas de 34,9%, o que provou que a liberação sustentada da formulação desenvolvida foi muito maior do que a de dinitrato de isossorbida desenvolvida comercialmente, o que promoveria a satisfação do paciente.
PCDNF: Revisiting Learning-based Point Cloud Denoising via Joint Normal Filtering
Recovering high quality surfaces from noisy point clouds, known as point
cloud denoising, is a fundamental yet challenging problem in geometry
processing. Most of the existing methods either directly denoise the noisy
input or filter raw normals followed by updating point positions. Motivated by
the essential interplay between point cloud denoising and normal filtering, we
revisit point cloud denoising from a multitask perspective, and propose an
end-to-end network, named PCDNF, to denoise point clouds via joint normal
filtering. In particular, we introduce an auxiliary normal filtering task to
help the overall network remove noise more effectively while preserving
geometric features more accurately. In addition to the overall architecture,
our network has two novel modules. On one hand, to improve noise removal
performance, we design a shape-aware selector to construct the latent tangent
space representation of the specific point by comprehensively considering the
learned point and normal features and geometry priors. On the other hand, point
features are more suitable for describing geometric details, and normal
features are more conducive for representing geometric structures (e.g., sharp
edges and corners). Combining point and normal features allows us to overcome
their weaknesses. Thus, we design a feature refinement module to fuse point and
normal features for better recovering geometric information. Extensive
evaluations, comparisons, and ablation studies demonstrate that the proposed
method outperforms state-of-the-arts for both point cloud denoising and normal
filtering