IsoGeometric analysis using T-splines on two-patch geometries

We develop optimal approximation estimates for T-splines in the case of geometries obtained by gluing two standard tensor product patches. We derive results both for the T-spline space in the parametric domain and the mapped T-NURBS in the physical one. A set of numerical tests in complete accordance with the theoretical developments is also presented.     

Pocket extraction on proteins via the Voronoi diagram of spheres

Proteins consist of atoms. Given a protein, the automatic recognition of depressed regions, called pockets, on the surface of proteins is important for protein-ligand docking and facilitates fast development of new drugs. Recently, computational approaches have emerged for recognizing pockets from the geometrical point of view. Presented in this paper is a geometric method for the pocket recognition which is based on the Voronoi diagram for atoms. Given a Voronoi diagram, the proposed algorithm transforms the atomic structure to meshes which contain the information of the proximity among atoms, and then recognizes depressions on the surface of a protein using the meshes.     

An Evolutionary Algorithm Approach to Optimal Ensemble Classifiers for DNA Microarray Data Analysis

In general, the analysis of microarray data requires two steps: feature selection and classification. From a variety of feature selection methods and classifiers, it is difficult to find optimal ensembles composed of any feature-classifier pairs. This paper proposes a novel method based on the evolutionary algorithm (EA) to form sophisticated ensembles of features and classifiers that can be used to obtain high classification performance. In spite of the exponential number of possible ensembles of individual feature-classifier pairs, an EA can produce the best ensemble in a reasonable amount of time. The chromosome is encoded with real values to decide the weight for each feature-classifier pair in an ensemble. Experimental results with two well-known microarray datasets in terms of time and classification rate indicate that the proposed method produces ensembles that are superior to individual classifiers, as well as other ensembles optimized by random and greedy strategies.     

Dynamic planning model for determining cutting parameters using neural networks in feature-based process planning

Although feature-based computer-aided process planning plays a vital role in automating and integrating design and manufacturing for efficient production, its off-line properties prohibit the shop floor controllers from rapidly coping with unexpected production errors. The objective of the paper is to suggest a neural network-based dynamic planning model, by which the shop floor controllers determine cutting parameters in real-time based on shop floor status. At off-line is the dynamic planning model constructed as a neural network form, and then embedded into each removal feature. The dynamic planning model will be executed by the shop floor controllers to determine the cutting parameters. A prototype system is constructed to validate whether the dynamic planning model is capable of determining dynamically and efficiently the cutting parameters for a particular set of shop operating factors. Owing to the dynamic planning model, the shop floor controller will increase flexibility and robustness by rapidly and adaptively determining the cutting parameters in unexpected errors occurring.     

The discovery of biomarkers for type 2 diabetic nephropathy by serum proteome analysis

Diabetic nephropathy (DN) is a serious kidney complication of diabetes, and constitutes the leading cause of end-stage renal disease. The earliest clinical evidence of DN is microalbuminuria, a term which refers to the appearance of small but abnormal amounts of albumin in the urine. However, screening methods for DN, such as biomarker assays, are yet to be developed for type 2 DN. In the present study, in an attempt to identify the biomarkers for initial diagnoses of type 2 DN, the protein profiles of human sera collected from 30 microalbuminuric type 2 diabetic patients were compared with those collected from 30 normoalbuminuric type 2 diabetic patients, via 2-DE. As a result, a total of 18 spots were determined to have different protein levels in the microalbuminuric patients. Twelve spots had lower protein levels of approximately 50%, and the other six had higher levels of approximately 100-300% as compared to the spots of normoalbuminuric patients. These spots were identified with ESI-Q-TOF (ESI-quadrupole-TOF) MS. Among the identified proteins, vitamin D-binding protein (DBP) and pigment epithelium-derived factor (PEDF) were verified by Western blotting. The results of this study indicate that the DBP may be employed as diagnostic and monitoring biomarkers of type 2 DN, contingent on further study into the matter.     

Cholesterol is critical to the integrity of neuronal porosome/fusion pore

Secretion is one of the most fundamental cellular processes. Porosomes have been demonstrated as the universal secretory machinery in cells. Earlier studies determine the presence of a number of proteins in porosomes, among them the N- and P/Q-type calcium channels, actin, syntaxin-1, synaptotagmin-1, vimentin, the N-ethylmaleimide-sensitive factor (NSF), the chloride channel CLC-3, and the alpha subunit of the heterotrimeric GTP-binding protein G(o). Studies demonstrate that t-SNAREs localize at the base of porosomes, and directly interact with calcium channels. In the present study, we demonstrate that Syntaxin-1 co-localizes with cholesterol in solubilized synaptosomal membrane preparations. Depletion of cholesterol, results in the dissociation of both Syntaxin-1 and N-type calcium channel from neuronal porosomes. Thus, cholesterol participates as an integral component of the neuronal porosome complex, and is required for its stability.     

Phase-error-free quadrature sampling technique in the ultrasonic B-scan imaging system and its application to the synthetic focusing system

The quadrature sampling technique as a means of detecting the envelope of RF waveform in the baseband is well known. If this technique is applied to a focused ultrasound imaging system using an array transducer, whether it is a synthetic or nonsynthetic focusing system, unwanted phase terms appear in the expressions of the inphase and quadrature components of the baseband signal when an appropriate delay time is introduced to each channel signal for the purpose of focusing. The expressions of the inphase and quadrature components from the point of focusing are derived and analyzed in detail, and a scheme to eliminate the unwanted phase terms is proposed. The resulting phase-error-free quadrature sampling technique is applied to the synthetic focusing system; a system block diagram together with the simulation and experimental results are presented.     

Preparation of bao-pbo-nd2o3-tio2 powders by hydrothermal synthesis

Homogeneous and nano-sized BPNT [(Ba_1-xPb_x)Nd₂Ti₅O₁₄] powders were prepared under various hydrothermal conditions. Crystallinity and homogeneity of the synthetic powders were investigated. The microwave dielectric properties of the filters prepared with hydrothermal powders were compared with those of the filters prepared with conventional powders. The microwave dielectric properties of the filter prepared with the hydrothermal powders were also better than those of the filter manufactured with the conventional powders. The dielectric constant, quality constant and temperature coefficient of resonance frequency of hydrothermally prepared filter under optimum condition and measured at 3.5 GHz around were about 93, 6067 and 0 ppm/°C, respectively.     

Enhanced electrochemical properties of SnO2 anode by AlPO4 coating

A SnO₂ anode material undergoes severe capacity loss, which is mainly associated with cracking/crumbling of the material by the large volume change between the Li_xSn and Sn phases, and the intensive reactions with the electrolyte solution. However, AlPO₄ nanoparticle coating showed drastically improved electrochemical properties with decreased surface cracks. The AlPO₄-coated SnO₂ exhibited a capacity of 781 mAh/g, approaching its theoretical capacity at the first cycle, with 44% capacity retention after 15 cycles between 2.5 and 0 V at a relatively high C rate of 105 mA/g. In contrast, the bare SnO₂ showed an initial capacity of 680 mAh/g, with only 8% capacity retention after 15 cycles.