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This paper presents an interesting nanosecond (ns) laser-induced plasma deburring (LPD) effect (from microchannel sidewalls) discovered by the authors, which has been rarely reported before in the literature. Fast imagining study has been performed on plasma produced by ns laser ablation of the bottom of microchannels. It has been found that the plasma can effectively remove burrs from the sidewall of the channels, while on the other hand microscopic images taken in this study did not show any obvious size or shape change of the channel sidewall after LPD. LPD using a sacrifice plate has also been studied, where the plasma for deburring is generated by laser ablation of the sacrifice plate instead of the workpiece. The observed laser-induced plasma deburring effect has several potential advantages in practical micromanufacturing applications, such as high spatial resolution, noncontact and no tool wear, and less possibility of damaging or overmachining useful microfeatures when removing burrs from them. The fundamental mechanisms for the observed laser-induced plasma deburring effect still require lots of further work to completely understand, which may include mechanical breaking of burrs due to high kinetic energies carried by plasma and the associated shock wave, and/or thermal transport from plasma to burrs that may cause their heating and phase change, or other mechanisms. [ABSTRACT FROM AUTHOR]

Ultrasonic cavitation peening is a peening process utilizing the high pressure induced by ultrasonic cavitation in liquids (typically water). In this paper, ultrasonic cavitation peening on stainless steel and nickel alloy has been studied. The workpiece surface microhardness, the microhardness variation at different depths, the workpiece surface profile, roughness, and morphology have been measured or observed. It has been found that for the studied situations, ultrasonic cavitation peening (at a sufficiently high horn vibration amplitude) can obviously enhance the workpiece surface hardness without significantly increasing the surface roughness. Under the investigated conditions, a surface layer of more than around 50 pm has been hardened under a horn vibra-tion amplitude of~20 pm. [ABSTRACT FROM AUTHOR]

Prompt and accurate diagnosis of acute ischemic stroke is critical to seek acute therapy. In traditional Chinese medicine (TCM) science, there is a comprehensive system of diagnosis and medical care of acute ischemic stroke. Here we introduce a two-level model for the analysis of TCM syndrome of acute ischemic stroke. Owing to the limitation of sample size and imbalance, we focused on the analysis of wind-phlegm collateral obstruction syndrome (Feng Tan Yu Zu Zheng). Firstly, a Support-Vector-Machine-(SVM-) based diagnostic model was set up through selection of core symptoms. After pairwise undersampling, we improved the performance of prediction and generated the core symptoms-based diagnostic model of wind-phlegm collateral obstruction syndrome. Next, Pathway Pattern-based method and MetaDrug platform were used to shed light on the molecular basis of the significance of core symptoms in three complementary aspects: symptom-gene-pathway multilayer correlation network, enriched pathways, and most relevant interaction network. The integration of diagnostic model and molecular mechanism analysis creates an interesting perspective for better understanding the syndrome. The two-level model would provide a new opportunity for the study of TCM syndromes. [ABSTRACT FROM AUTHOR]

At the molecular level, it is acknowledged that a TCM formula is often a complex system, which challenges researchers to fully understand its underlying pharmacological action. However, module detection technique developed from complex network provides new insight into systematic investigation of the mode of action of a TCM formula from the molecule perspective. We here proposed a computational approach integrating the module detection technique into a 2-class heterogeneous network (2-HN) which models the complex pharmacological system of a TCM formula. This approach takes three steps: construction of a 2-HN, identification of primary pharmacological units, and pathway analysis. We employed this approach to study Shu-feng-jiedu (SHU) formula, which aimed at discovering its molecular mechanism in defending against influenza infection. Actually, four primary pharmacological units were identified from the 2-HN for SHU formula and further analysis revealed numbers of biological pathways modulated by the four pharmacological units. 24 out of 40 enriched pathways that were ranked in top 10 corresponding to each of the four pharmacological units were found to be involved in the process of influenza infection. Therefore, this approach is capable of uncovering the mode of action underlying a TCM formula via module analysis. [ABSTRACT FROM AUTHOR]

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TC M. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SV M feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique.We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM. [ABSTRACT FROM AUTHOR]

Silicon carbide, due to its unique properties, has many promising applications in optics, electronics, and other areas. However, it is difficult to micromachine using mechanical approaches due to its brittleness and high hardness. Laser ablation can potentially provide a good solution for silicon carbide micromachining. However, previous studies of silicon carbide ablation by nanosecond laser pulses at infrared wavelengths are very limited on material removal mechanism, and the mechanism has not been well understood. In this paper, experimental study is performed for silicon carbide ablation by 1064 nm and 200 ns laser pulses through both nanosecond time-resolved in situ observation and laser-ablated workpiece characterization. This study shows that the material removal mechanism is surface vaporization, followed by liquid ejection (which becomes clearly observable at around 1 μs after the laser pulse starts). It has been found that the liquid ejection is very unlikely due to phase explosion. This study also shows that the radiation intensity of laser-induced plasma during silicon carbide ablation does not have a uniform spatial distribution, and the distribution also changes very obviously when the laser pulse ends. [ABSTRACT FROM AUTHOR]

A novel electrochemical sensor has been constructed by using a glassy carbon electrode (GCE) coated with nafion/sodium dodecylbenzenesulfonate (SDBS). Differential pulse voltammetry (DPV) was used to study the electrochemical behaviors of dopamine (DA) and uric acid (UA). An optimum of 5 mM SDBS together with 0.05 wt% of nafion was used to improve the resolution and the determination sensitivity successfully. In 0.1 M phosphate buffer solution (pH 6.5), the modified electrode exhibited high electrocatalytical activity toward the oxidation of DA and UA with obvious reduction of overpotential. Compared with bare GCE, the modified electrode resolved the voltammetric response of DA and UA into two well-defined voltammetric peaks by DPV, which can be used for simultaneous determination of these species in mixture. The peak currents obtained from DPV were linearly related to the concentrations of DA and UA in the ranges of 4.0 × 10−7–8.0 × 10−5 M and 4.0 × 10−6–8.0 × 10−4 M, respectively. The detection limit of DA and UA (signal-to-noise ration was 3) were 5.0 × 10−8 and 4.0 × 10−7 M, respectively. [ABSTRACT FROM AUTHOR]

The effect of the chain length of polyvinyl pyrrolidone (PVP) on the structures of silver nanowires (AgNWs) is explored in this study. It was found in the experiments that PVP, when serving as a capping agent, has a great impact on the morphology and structure of AgNWs. By means of a series of experiments and the inquiry of the growth mechanism, the critical minimum PVP chain length for the successful formation of uniform nanowires was discovered, below which only nanoparticles or short nanorods can be obtained. Surprisingly, a core–shell structure of a nanowire with a polycrystal was observed when PVP with a very long chain length was employed in the processing. [ABSTRACT FROM AUTHOR]