Terrain classification and identification of tree stems using ground‐based LiDAR

To operate autonomously in forested terrain, unmanned ground vehicles must be able to identify the load‐bearing surface of the terrain (i.e., the ground) and obstacles in the environment. To travel long distances, they must be able to track their position even when the forest canopy obstructs GPS signals, e.g., by tracking progress relative to tree stems. This paper presents a novel, robust approach for modeling the ground plane and tree stems in forests from a single viewpoint using a lightweight LiDAR scanner. Ground plane identification is implemented using a two‐stage approach. The first stage, a local height‐based filter, discards most nonground points. The second stage, based on a support vector machine classifier, identifies which of the remaining points belong to the ground. Main tree stems are modeled as cylinders or cones to estimate the diameter 130 cm above the ground plane. To fit these models, candidate main stem data are selected by finding points approximately 130 cm above the ground. These points are clustered into separate point clouds for each stem. Cylinders and cones are fit to each point cloud, and heuristic filters identify which fits correspond to tree stems. Experimental results from five forested environments demonstrate the effectiveness of this approach. For ground plane estimation, the overall classification accuracy was 86.28% with a mean error for the ground height of approximately 4.7 cm. For stem estimation, up to 50% of the main stems were accurately modeled using cones, with a root mean square diameter error of 13.2 cm.© 2012 Wiley Periodicals, Inc.     

Time dependence of mesoscopic strain distribution for triaxial woven carbon-fiber-reinforced polymer under creep loading measured by digital image correlation

This paper presents the time dependence of the mesoscopic strain of a triaxial woven carbon-fiber-reinforced polymer under creep loading measured using digital image correlation (DIC). Two types of DIC techniques were employed for the measurement: conventional subset DIC and mesh DIC. Static tensile and creep tests were carried out, and the time dependence of the mesoscopic strain distribution was investigated by applying these techniques. The ultimate failure of this material is dominated by inter-bundle decohesion caused by relative rigid rotation and relating shear stress. Therefore, these were focused on in the present study. During the creep tests, the fiber directional strain, shear strain, and rotation were monitored using the DIC, and the mechanism for the increase in the specimen’s macro-strain over time was investigated based on the results obtained by the DIC measurement.     

Abstract picture generation and zooming user interface for intuitive music browsing

Today many people store music media files in personal computers or portable audio players, thanks to recent evolution of multimedia technologies. The more music media files these devices store, the messier it is to search for tunes that users want to listen to. We propose MusCat, a music browser to interactively search for the tunes according to features, not according to metadata (e.g. title, artist name). The technique firstly calculates features of tunes, and then hierarchically clusters the tunes according to the features. It then automatically generates abstract pictures, so that users can recognize characteristics of tunes more instantly and intuitionally. It finally visualizes the tunes by using abstract pictures. MusCat enables intuitive music selection with the zooming user interface.     

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.     

Estimation of anisotropic properties of nano-structured arrays by modal vibration control at microscale

Nano-structured arrays are engineered to meet the requirements of a variety of applications such as microfilters, sensors, and structural interface due to their unique mechanical characteristics, which cannot be achieved by conventional solid materials. However, it is hard to evaluate the elastic properties of nano-structured arrays owing to the discrete structure, sample size, and availability of suitable techniques. To facilitate this, we develop an advanced three-dimensional microscale vibration testing process. In the test, a specially designed three-dimensional microspecimen with tuned mass is excited by a piezoelectric actuator, and the resonance frequencies are detected by a laser device successfully. The anisotropic elastic moduli of nano-structured array composed of helical nano-springs are identified from a single spectrum. This array shows so strong characteristic anisotropy that the solid one hardly can attain. The microscale testing technique can be extended to other materials and microstructures.     

Neuroprotection,Growth Factors and BDNF-TrkB Signalling in Retinal Degeneration

Neurotrophic factors play key roles in the development and survival of neurons. The potent neuroprotective effects of neurotrophic factors, including brain-derived neurotrophic factor (BDNF), ciliary neurotrophic factor (CNTF), glial cell-line derived neurotrophic factor (GDNF) and nerve growth factor (NGF), suggest that they are good therapeutic candidates for neurodegenerative diseases. Glaucoma is a neurodegenerative disease of the eye that causes irreversible blindness. It is characterized by damage to the optic nerve, usually due to high intraocular pressure (IOP), and progressive degeneration of retinal neurons called retinal ganglion cells (RGCs). Current therapy for glaucoma focuses on reduction of IOP, but neuroprotection may also be beneficial. BDNF is a powerful neuroprotective agent especially for RGCs. Exogenous application of BDNF to the retina and increased BDNF expression in retinal neurons using viral vector systems are both effective in protecting RGCs from damage. Furthermore, induction of BDNF expression by agents such as valproic acid has also been beneficial in promoting RGC survival. In this review, we discuss the therapeutic potential of neurotrophic factors in retinal diseases and focus on the differential roles of glial and neuronal TrkB in neuroprotection. We also discuss the role of neurotrophic factors in neuroregeneration.     

Cathodic pulse breakdown of anodic films on aluminium in alkaline silicate electrolyte – Understanding the role of cathodic half-cycle in AC plasma electrolytic oxidation

Sequential anodic and cathodic pulse voltages were applied on anodised Al micro-electrodes in alkaline silicate electrolyte to explore the role of cathodic pulse in AC or bipolar plasma electrolytic oxidation (PEO) process. SEM observation was carried out to observe the sites of anodic and cathodic breakdown and their morphologies. The prior anodic breakdown accelerated the cathodic breakdown at ?50 V, and the acceleration was associated with the preferential cathodic breakdown at the anodic breakdown sites. However, the succeeding anodic breakdown during applying anodic pulse of 420 V for 2 ms was highly suppressed at the cathodic breakdown sites. This would randomise the anodic breakdown sites. Such role may contribute to the formation of rather uniform coatings on aluminium in this electrolyte without large discharge channels when larger cathodic current is applied with respect to the anodic current in AC PEO.     

Pulverization mechanism of hydrogen storage alloys on microscale packing structure

In-situ and transient visualizations of the packing structure of a hydrogen storage alloy bed are carried out using an X-ray computed tomography (CT) system. The packing structure is clearly observed on the microscale using the CT system. When the alloy bed is subjected to hydrogen absorption–desorption cycles, the pulverization progresses from the lower to the upper regions of the bed. After several hydrogen absorption–desorption cycles, the packing structure in the lower region of the bed changes and the microstructural void decreases slightly. Based on these results, we propose a pulverization mechanism of the packed bed in which the friction between particles affects the pulverization process.