Cyclic behaviour of connecting beams in reinforced concrete slit shear walls

The connecting beams in slit shear walls are generally much shorter than those in ordinary coupled shear walls and may therefore behave quite differently. In order to investigate the shear behaviour of such short connecting beams, two series of shear tests, one on monotonic behaviour and the other on cyclic behaviour, were carried out. Altogether, 24 specimens were tested. The results of the monotonic shear tests have been reported in an earlier paper. This Paper presents some additional information on the ductility of the beams as revealed by the monotonic shear tests, and the results of the cyclic shear tests. From the cyclic shear tests, the cracking and failure characteristics, reinforcement stress distribution, stiffness and strength degradations, ductility and damping capacity, etc., of the connecting beams are studied. The results are useful for evaluating the seismic performance of reinforced concrete slit shear walls.published_or_final_versio

Visibility-based coverage of mobile sensors in non-convex domains

The area coverage problem of mobile sensor networks has attracted much attention recently, as mobile sensors find many important applications in remote and hostile environments. However, the deployment of mobile sensors in a non-convex domain is nontrivial due to the more general shape of the domain and the attenuation of sensing capabilities caused by the boundary walls or obstacles. We consider the problem of exploration and coverage by mobile sensors in an unknown non-convex domain. We propose the definition of 'visibility-based Voronoi diagram' and extend the continuous-time Lloyd's method, which only works for convex domains, to deploy the mobile sensors in the unknown environments in a distributed manner. Our simulations show the effectiveness of the proposed algorithms. © 2011 IEEE.published_or_final_versionThe 8th International Symposium on Voronoi Diagrams in Science and Engineering (ISVD2011), Qingdao, China, 28-30 June 2011. In Proceedings of the 8th ISVD, 2011, p. 105-11

Rod-like trabeculae extraction from cancellous bone microstructure using topological analysis

The study of the microstructure in cancellous bone is important in osteoporosis research. In this paper, we focus in the extraction of rod-like trabeculae in cancellous hone, whose topological and geometrical properties are known to be strongly related to bone strength. Three dimensional (3D) cancellous bone volume data obtained from micro Computed Tomography (micro-CT) scans is used in our analysis. Because of the complexity of the cancellous bone microstructure, the mere use of existing 3D digital topology method's is unable to yield satisfactory results for trabeculae extraction. We devise several enhancements which are specific to the identification of rod-like trabeculae. Experimental results show that the accuracy of trabeculae extraction is greatly improved. This application study may help clinicians to solve problems in future. © 2005 IEEE.published_or_final_versio

Multimodal fuzzy fusion for enhancing the motor-imagery-based brain computer interface

© 2005-2012 IEEE. Brain-computer interface technologies, such as steady-state visually evoked potential, P300, and motor imagery are methods of communication between the human brain and the external devices. Motor imagery-based brain-computer interfaces are popular because they avoid unnecessary external stimuli. Although feature extraction methods have been illustrated in several machine intelligent systems in motor imagery-based brain-computer interface studies, the performance remains unsatisfactory. There is increasing interest in the use of the fuzzy integrals, the Choquet and Sugeno integrals, that are appropriate for use in applications in which fusion of data must consider possible data interactions. To enhance the classification accuracy of brain-computer interfaces, we adopted fuzzy integrals, after employing the classification method of traditional brain-computer interfaces, to consider possible links between the data. Subsequently, we proposed a novel classification framework called the multimodal fuzzy fusion-based brain-computer interface system. Ten volunteers performed a motor imagery-based brain-computer interface experiment, and we acquired electroencephalography signals simultaneously. The multimodal fuzzy fusion-based brain-computer interface system enhanced performance compared with traditional brain-computer interface systems. Furthermore, when using the motor imagery-relevant electroencephalography frequency alpha and beta bands for the input features, the system achieved the highest accuracy, up to 78.81% and 78.45% with the Choquet and Sugeno integrals, respectively. Herein, we present a novel concept for enhancing brain-computer interface systems that adopts fuzzy integrals, especially in the fusion for classifying brain-computer interface commands

Ultra-strong Adhesion of Graphene Membranes

As mechanical structures enter the nanoscale regime, the influence of van der Waals forces increases. Graphene is attractive for nanomechanical systems because its Young's modulus and strength are both intrinsically high, but the mechanical behavior of graphene is also strongly influenced by the van der Waals force. For example, this force clamps graphene samples to substrates, and also holds together the individual graphene sheets in multilayer samples. Here we use a pressurized blister test to directly measure the adhesion energy of graphene sheets with a silicon oxide substrate. We find an adhesion energy of 0.45 \pm 0.02 J/m2 for monolayer graphene and 0.31 \pm 0.03 J/m2 for samples containing 2-5 graphene sheets. These values are larger than the adhesion energies measured in typical micromechanical structures and are comparable to solid/liquid adhesion energies. We attribute this to the extreme flexibility of graphene, which allows it to conform to the topography of even the smoothest substrates, thus making its interaction with the substrate more liquid-like than solid-like.Comment: to appear in Nature Nanotechnolog

The involvement of tau in nucleolar transcription and the stress response

Tau is known for its pathological role in neurodegenerative diseases, including Alzheimer’s disease (AD) and other tauopathies. Tau is found in many subcellular compartments such as the cytosol and the nucleus. Although its normal role in microtubule binding is well established, its nuclear role is still unclear. Here, we reveal that tau localises to the nucleolus in undifferentiated and differentiated neuroblastoma cells (SHSY5Y), where it associates with TIP5, a key player in heterochromatin stability and ribosomal DNA (rDNA) transcriptional repression. Immunogold labelling on human brain sample confirms the physiological relevance of this finding by showing tau within the nucleolus colocalises with TIP5. Depletion of tau results in an increase in rDNA transcription with an associated decrease in heterochromatin and DNA methylation, suggesting that under normal conditions tau is involved in silencing of the rDNA. Cellular stress induced by glutamate causes nucleolar stress associated with the redistribution of nucleolar non-phosphorylated tau, in a similar manner to fibrillarin, and nuclear upsurge of phosphorylated tau (Thr231) which doesn’t colocalise with fibrillarin or nucleolar tau. This suggests that stress may impact on different nuclear tau species. In addition to involvement in rDNA transcription, nucleolar non-phosphorylated tau also undergoes stress-induced redistribution similar to many nucleolar protein

Confined conversion of CuS nanowires to CuO nanotubes by annealing-induced diffusion in nanochannels

Copper oxide (CuO) nanotubes were successfully converted from CuS nanowires embedded in anodic aluminum oxide (AAO) template by annealing-induced diffusion in a confined tube-type space. The spreading of CuO and formation of CuO layer on the nanochannel surface of AAO, and the confinement offered by AAO nanochannels play a key role in the formation of CuO nanotubes