Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

An advanced evenly-spaced streamline placement algorithm

This paper presents an advanced evenly-spaced streamline placement algorithm for fast, high-quality, and robust layout of flow lines. A fourth-order Runge-Kutta integrator with adaptive step size and error control is employed for rapid accurate streamline advection. Cubic Hermite polynomial interpolation with large sample-spacing is adopted to create fewer evenly-spaced samples along each streamline to reduce the amount of distance checking. We propose two methods to enhance placement quality. Double queues are used to prioritize topological seeding and to favor long streamlines to minimize discontinuities. Adaptive distance control based on the local flow variance is explored to reduce cavities. Furthermore, we propose a universal, effective, fast, and robust loop detection strategy to address closed and spiraling streamlines. Our algorithm is an order-of-magnitude faster than Jobard and Lefer's algorithm with better placement quality and over 5 times faster than Mebarki et al.'s algorithm with comparable placement quality, but with a more robust solution to loop detection.     

Noise of He-Cd laser and its suppression

Linear relations have been observed between the reciprocal of the noise ratio and the reciprocal of the output power of the He-Cd laser as well as between the noise ratio and the net gain within the laser cavity. By a feedback method with an acoustooptic modulator in the laser cavity at the Brewster angle for low optical loss, a stable laser with high power output and low noise has been obtained. The noise ratio and the output power are 0.8% and 33 mW, respectively, at 4416 A     

Study on shop floor control system in semiconductor fabrication by self-organizing map-based intelligent multi-controller

To confirm semiconductor wafer fabrication (FAB) operating characteristics, the scheduling decisions of shop floor control systems (SFCS) must develop a multiple scheduling rules (MSRs) approach in FABs. However, if a classical machine learning approach is used, an SFCS in FABs knowledge base (KB) can be developed by using the appropriate MSR strategy (this method is called an intelligent multi-controller in this study) as obtained from training examples. A classical machine learning approach main disadvantage is that the classes (scheduling decision variables) to which training examples are assigned must be pre-defined. This process becomes an intolerably time-consuming task. In addition, although the best decision rule can be determined for each scheduling decision variable, the combination of all the decision rules may not simultaneously satisfy the global objective function. To address these issues, this study proposes an intelligent multi-controller that incorporates three main mechanisms: (1) a simulation-based training example generation mechanism, (2) a data preprocessing mechanism, and (3) a self-organizing map (SOM)-based MSRs selection mechanism. These mechanisms can overcome the long training time problem of the classical machine learning approach in the training examples generation phase. Under various production performance criteria over a long period, the proposed intelligent multi-controller approach yields better system performance than fixed decision scheduling rules for each of the decision variables at the start of each production interval.     

A platform for the development of patient applications in the domain of personalized health

Personalized health (p-health) systems can contribute significantly to the sustainability of healthcare systems, though their feasibility is yet to be proven. One of the problems related to their development is the lack of well-established development tools for this domain. As the p-health paradigm is focused on patient self-management, big challenges arise around the design and implementation of patient systems. This paper presents a reference platform created for the development of these applications, and shows the advantages of its adoption in a complex project dealing with cardio-vascular diseases.     

Deformation Behavior of Duplex Zircaloy-4-Oxygen Alloys

The mechanical properties of two-phase Zircaloy-4-oxygen alloys at thermal equilibrium have been determined. The strength of these alloys depends to a large extent on their microstructure. The strengthening behavior for alloys having isolateda grains in the softer β matrix is similar to the dispersed particle strengthening. The yield strength of these alloys is found to obey the Petch relationship, (MPa), whereλ _β is the mean free path of β phase inμm. As the volume fraction ofa phase increases, its aspect ratio also increases. This allows more effective load transfer from the matrix to the hardera phase. It has been shown that the strength of these alloys obeys a modified rule of mixtures. The alloys having equiaxeda grains in the β matrix show large strain rate sensitivities at low strain rate. The deformation behavior is interpreted in terms of dislocation slip in the β matrix and diffusion assisted climb near the interphase boundary.     

Polymeric carbon nanocomposites from multiwalled carbon nanotubes functionalized with segmented polyurethane

Multiwalled carbon nanotubes (MWNT) were functionalized with segmented polyurethanes (PU) by the “grafting to” approach. Raman and X‐ray photoelectron spectroscopy (XPS) spectra show that the sidewalls of MWNTs have been functionalized with acid treatment, and the amount of COOH increases with increasing acid treatment time. FTIR and X‐ray diffraction (XRD) spectra confirm that PU is covalently attached to the sidewalls of MWNTs by esterification reaction. Similar to the parent PU, the functionalized carbon nanotube samples are soluble in highly polar solvents, such as dimethyl sulfoxide (DMSO) and N,N‐dimethylformamide (DMF). The functionalized acid amount and the grafted PU amount were determined by thermogravimetric analyses (TGA). Comparative studies, based on SEM images between the PU‐functionalized and chemically defunctionalized MWNT samples, also reveal the covalent coating character. Dynamic mechanical analysis (DMA) of nanocomposite films prepared from PU and PU‐functionalized MWNTs show enhanced mechanical properties and increased soft segment T_g. Tensile properties indicate that PU‐functionalized MWNTs are effective reinforcing fillers for the polyurethane matrix. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Lane Detection With Moving Vehicles in the Traffic Scenes

A lane-detection method aimed at handling moving vehicles in the traffic scenes is proposed in this brief. First, lane marks are extracted based on color information. The extraction of lane-mark colors is designed in a way that is not affected by illumination changes and the proportion of space that vehicles on the road occupy. Next, for vehicles that have the same colors as the lane marks, we utilize size, shape, and motion information to distinguish them from the real lane marks. The mechanism effectively eliminates the influence of passing vehicles when performing lane detection. Finally, pixels in the extracted lane-mark mask are accumulated to find the boundary lines of the lane. The proposed algorithm is able to robustly find the left and right boundary lines of the lane and is not affected by the passing traffic. Experimental results show that the proposed method works well on marked roads in various lighting conditions     

4.9-GHz low-phase-noise transformer-based superharmonic-coupled GaInP/GaAs HBT QVCO

The low-phase-noise GaInP/GaAs heterojunction bipolar transistor (HBT) quadrature voltage controlled oscillator (QVCO) using transformer-based superharmonic coupling topology is demonstrated for the first time. The fully integrated QVCO at 4.87GHz has phase noise of -131dBc/Hz at 1-MHz offset frequency, output power of -4dBm and the figure of merit (FOM) -198dBc/Hz. The state-of-the-art phase noise FOM is attributed to the superior GaInP/GaAs HBT low-frequency device noise and the high quality transformer formed on the GaAs semi-insulating substrate.