Single-mode fluorotellurite glass fiber

By multi-stage rod-in-tube fiber drawing process, a single-mode fluorotellurite glass fiber was fabricated and reported for the first time. Benefiting from chemical–physical dehydration process to remove water and OH⁻ groups, the propagation loss was decreased to 1.9 dB/m at 1550 nm and the infrared window is extended from 2.8 μm to 4.2 μm, i.e. a new kind of mid-infrared glass fiber. The fiber is with a small core of 3.52 μm in diameter to meet single-mode condition, and the effective nonlinear parameter γ was estimated to be 236.7 W⁻¹ km⁻¹ at 1550 nm by using continuous-wave self-phase modulation method. © 2015 Elsevier B.V. All rights reserved.     

Surface energy-mediated fibronectin adsorption and osteoblast responses on nanostructured diamond

Nanostructured diamond have potential applications in many biomedical related fields and demonstrated extraordinary capacity to influence cellular responses. Studying the surface property of nanodiamond and its influence to protein adsorption and subsequent cellular responses along with the mechanism behind such capacity becomes more important. Here the role of surface energy associated with nanostructured diamond in modulating fibronectin and osteoblast(OB, bone forming cells) responses was investigated. Nanocrystalline diamond(NCD) and submicron crystalline diamond(SMCD) films with controllable surface energy were prepared by microwave-enhanced plasma chemical vapor deposition(MPCVD) techniques. Fibronectin adsorption on the diamond films with varied surface energy values was measured via the enzyme-linked immunosorbent assay(ELISA) and the relationship between the surface energy and fibronectin adsorption was studied. The result indicated that fibronectin adsorption on nanostructured surfaces was closely related to both surface energy and material microstructures. The spreading and migration of OB aggregates(each containing 30–50 cells) on the NCD with varied surface energy values were also studied. The result indicates a correlation between the cell spreading and migration on nanodiamond and the surface energy of nanostructured surface.     

Embedding HMMs-based models in a Euclidean space: the topological hidden Markov models

Current extensions of hidden Markov models such as structural, hierarchical, coupled, and others have the power to classify complex and highly organized patterns. However, one of their major limitations is the inability to cope with topology: When applied to a visible observation (VO) sequence, the traditional HMM-based techniques have difficulty predicting the n-dimensional shape formed by the symbols of the VO sequence. To fulfill this need, we propose a novel paradigm named “topological hidden Markov models” (THMMs) that classifies VO sequences by embedding the nodes of an HMM state transition graph in a Euclidean space. This is achieved by modeling the noise embedded in the shape generated by the VO sequence. We cover the first and second level topological HMMs. We describe five basic problems that are assigned to a second level topological hidden Markov model: (1) sequence probability evaluation, (2) statistical decoding, (3) structural decoding, (4) topological decoding, and (5) learning. To show the significance of this research, we have applied the concept of THMMs to: (i) predict the ASCII class assigned to a handwritten numeral, and (ii) map protein primary structures to their 3D folds. The results show that the second level THMMs outperform the SHMMs and the multi-class SVM classifiers significantly.     

Monte Carlo simulations of systems with complex energy landscapes

Non-traditional Monte Carlo simulations are a powerful approach to the study of systems with complex energy landscapes. After reviewing several of these specialized algorithms we shall describe the behavior of typical systems including spin glasses, lattice proteins, and models for “real” proteins. In the Edwards-Anderson spin glass it is now possible to produce probability distributions in the canonical ensemble and thermodynamic results of high numerical quality. In the hydrophobic-polar (HP) lattice protein model Wang-Landau sampling with an improved move set (pull-moves) produces results of very high quality. These can be compared with the results of other methods of statistical physics. A more realistic membrane protein model for Glycophorin A is also examined. Wang-Landau sampling allows the study of the dimerization process including an elucidation of the nature of the process.     

A novel, electrically protein-manipulated microcantilever biosensor for enhancement of capture antibody immobilization

This study demonstrated a microcantilever biosensor for enhancement of capture antibody immobilization. The electrically protein-manipulated, microcantilever biosensor is featured with enhanced capture antibody immobilization, miniaturization, and high sensitivity. Thanks to the electric property of biological substances in a real environment, given charged proteins can be manipulated with attraction in solution under an electric field. It is evident that higher amount of capture antibody molecules immobilized onto sensing surfaces captures or detects specific molecules, indicating greater deflection and stresses as well. This however leads to significant cost in biosensors. With the merit of MEMS technique that allows highly fabrication-compatible integration into microcantilever biosensors, sparsely distributed antibody molecules in solution are attracted in focus onto a sensing solid surface under electric fields. As the sensing element of the gold-coated, V-shaped silicon nitride microcantilever also serves as an electrode, the electric fields are applied in a channel of flowing microfluidics by locally in-plane electrodes or by a top electrode arranged for three-dimensional fields. As expected, most charged proteins distributed in solution are effectively attracted onto the sensing area within the electric fields. This improves the efficiency of capture antibody immobilization and achieves an eight-fold reduction over the necessary amount of capture antibodies without applying electric fields. With such a successful manipulation of charged proteins, the novel microcantilever biosensor exhibits efficient use of capture antibodies in solution.     

A novel ACO–GA hybrid algorithm for feature selection in protein function prediction

Protein function prediction is an important problem in functional genomics. Typically, protein sequences are represented by feature vectors. A major problem of protein datasets that increase the complexity of classification models is their large number of features. Feature selection (FS) techniques are used to deal with this high dimensional space of features. In this paper, we propose a novel feature selection algorithm that combines genetic algorithms (GA) and ant colony optimization (ACO) for faster and better search capability. The hybrid algorithm makes use of advantages of both ACO and GA methods. Proposed algorithm is easily implemented and because of use of a simple classifier in that, its computational complexity is very low. The performance of proposed algorithm is compared to the performance of two prominent population-based algorithms, ACO and genetic algorithms. Experimentation is carried out using two challenging biological datasets, involving the hierarchical functional classification of GPCRs and enzymes. The criteria used for comparison are maximizing predictive accuracy, and finding the smallest subset of features. The results of experiments indicate the superiority of proposed algorithm.     

基于MPI和CUDA的蛋白质定量软件的设计和分析

介绍了蛋白质定量软件的设计及测试结果,分析结果表明:P-QuantWiz软件在曙光600。的Intel集群部分,测试规模达到2048核,在256核加速比仍在增加。相对P-QuantWiz软件在单CPU运行的结果,PG-QuantWiz软件在单CPU运行的加速比为8.1,在16个GPU上运行的加速比为14.18,并行效率为89%。     

光纤无线电系统中的新型探测法研究

光纤无线电系统利用光载波携带毫米波信号在中心站和基站之间构成上行和下行传输链路,能够满足宽带无线接入系统的需求.利用光外差的方法产生毫米波信号是光载毫米波最简单和直接的方式.分析了在光纤无线电系统中利用光纤布拉格光栅从可调谐激光器中反射出两束相位近似相等的相干光,采用平衡探测产生了毫米波信号,降低了相位噪声和强度噪声对产生的毫米波信号的影响.     

Tool path smoothing of a redundant machine: Application to Automated Fiber Placement

Automated Tape Laying and Fiber Placement of composite materials are the two principal automated processes used for fabrication of large composite structures in aeronautical industry. The aluminum parts produced by High Speed Machining tend to be replaced by carbon fiber composite parts realized with these processes. However, structural parts present reinforcement zones which disturb the tool path follow-up and generate an increase of the manufacturing time. Thus, this paper deals with the optimization of tool paths of a 7-axis machine tool of Fiber Placement with the objective of reducing the manufacturing time while ensuring the requested quality of the final part. In this paper, two complementary methods are detailed. The first method takes advantage of the degree of redundancy of the machine tool to decrease the kinematic loads of the control joints. The second method aims to smooth the orientation of the machine head along the tool path while ensuring quality constraints. These two methods are then applied on a test tool path and bring to a significant decrease of the manufacturing time (32.9%).     

Monte Carlo simulations of the HP model (the "Ising model" of protein folding)

Using Wang–Landau sampling with suitable Monte Carlo trial moves (pull moves and bond-rebridging moves combined) we have determined the density of states and thermodynamic properties for a short sequence of the HP protein model. For free chains these proteins are known to first undergo a collapse “transition” to a globule state followed by a second “transition” into a native state. When placed in the proximity of an attractive surface, there is a competition between surface adsorption and folding that leads to an intriguing sequence of “transitions”. These transitions depend upon the relative interaction strengths and are largely inaccessible to “standard” Monte Carlo methods.