Material That Talks:Material Use of Architectural Surface in Semiotic Implications

According to the language of post-modern architecture which Charles Jencks proposed in the 1980s,form has been very crucial for architectural language expression.However,many suggestions also imply that the material which is deployed for building is also significant in the linguistic expression of architecture.Based on this consideration,the material use of architecture will also contain semiotic implications,whether for architects or for social consensus.How the material talks and what it says are two questions that need to be clarified.To answer these two questions,some empirical works in architecture will be examined to reveal the messages which could be delivered in architectural materials.Before this,semiotic debates in architecture will be reviewed.Then,two empirical works,one in the West and one in the East,will be considered particularly for their material deployments on the surface(façade).Since the architectural surface is the most tangible part of architecture in terms of material use,the surfaces of both projects will be discussed in detail with their implications and the atmospheres which the materials formulated and created.This paper will conclude with a consideration of the possible implications from these projects and also the different expressions of material use,which will help us to rethink the expression of the material use of architectural surface.

Gill surface architecture of mullet, Mugil soiuy (Basilewsky) : A scanning electron microscope study

Specimens of Mugil soiuy were collected from the coastal waters of Bohai Sea in Tianjin. The gillfilaments were cut with fine scissors and soaked for 24h in a fixative consisting of 2.5% glutaralde-hyde in 0.1 mol lphosporic acid buffer. After three washes in a buffer solution the tissue was fixedin a mixture of 1% osmium tetraoxide at 4℃ for 1h. The tissue was dehydrated in graded ethandethanols and dried. The tissue was examined and photographed with an SEM at an accelerating voltage

Mechanobiology of the cell surface:Probing its remodeling dynamics using membrane tether pulling assays with optical tweezers

Mammalian cell surfaces consist of the plasma membrane supported by an underneath cortical cytoskeleton.Together,these structures can control not only the shape of cells but also a series of cellular functions ranging from migration and division to exocytosis,endocytosis and differentiation.Furthermore,the cell surface is capable of exerting and reacting to mechanical forces.Its viscoelastic properties,especially membrane tension and bending modulus,are fundamental parameters involved in these responses.This viewpoint summarizes our current knowledge on how to measure the viscoelastic properties of cell surfaces employing optical tweezers-based tether assays,paving the way for a better understanding of how cells react to external mechanical forces,with a glance on their remodeling dynamics and possible consequences on downstream cellular processes.

Implementation of the moving particle semi-implicit method on GPU

The Moving Particle Semi-implicit (MPS) method performs well in simulating violent free surface flow and hence becomes popular in the area of fluid flow simulation. However, the implementations of searching neighbouring particles and solving the large sparse matrix equations (Poisson-type equation) are very time-consuming. In order to utilize the tremendous power of parallel computation of Graphics Processing Units (GPU), this study has developed a GPU-based MPS model employing the Compute Unified Device Architecture (CUDA) on NVIDIA GTX 280. The efficient neighbourhood particle searching is done through an indirect method and the Poisson-type pressure equation is solved by the Bi-Conjugate Gradient (BiCG) method. Four different optimization levels for the present general parallel GPU-based MPS model are demonstrated. In addition, the elaborate optimization of GPU code is also discussed. A benchmark problem of dam-breaking flow is simulated using both codes of the present GPU-based MPS and the original CPU-based MPS. The comparisons between them show that the GPU-based MPS model outperforms 26 times the traditional CPU model.