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Variational mode decomposition (VMD), a recently introduced method for adaptive data analysis, has aroused much attention in various fields. However, the VMD is formulated based on the assumption of narrow-band property of the signal model. To analyze wide-band nonlinear chirp signals (NCSs), we present an alternative method called variational nonlinear chirp mode decomposition (VNCMD). The VNCMD is developed from the fact that a wideband NCS can be transformed to a narrow-band signal by using demodulation techniques. Our decomposition problem is, thus, formulated as an optimal demodulation problem, which is efficiently solved by the alternating direction method of multipliers. Our method can be viewed as a time–frequency filter bank, which concurrently extracts all the signal modes. Some simulated and real data examples are provided showing the effectiveness of the VNCMD in analyzing NCSs containing close or even crossed modes.

Utilizing Doppler radar to conduct noncontact vital sign detection has attracted growing interest in recent years. Aiming to extract the vital sign information from the baseband signal effectively and accurately, a novel signal processing method based on parameterized demodulation (PD) is proposed. To effectively characterize the baseband signal whose phase consists of two oscillating components (i.e., the respiration and heartbeat components), the proposed algorithm defines a demodulation operator with sine kernel functions and formulates the phase demodulation as a parameter optimization problem. To increase the computational efficiency of the algorithm, the parameters corresponding to the respiration and heartbeat components are estimated sequentially. Specifically, the respiration component is first estimated and removed from the phase of the baseband signal, and then, the heartbeat component is extracted from the residual signal. Compared with the existing methods, the proposed algorithm is free of the resolution problem in fast Fourier transform-based methods with a limited data length and can obtain accurate rate tracking in a noisy environment. Both simulated and experimental results are provided to demonstrate the advantages and effectiveness of the proposed method for accurate noncontact vital sign detection.

In some applications, it is necessary to analyze multi-component non-stationary signals whose components severely overlap in the time-frequency (T-F) domain. Separating those signal components is desired but very challenging for existing methods. To address this issue, we propose a novel non-parametric algorithm called ridge path regrouping (RPRG) to extract the instantaneous frequencies (IFs) of the overlapped components from a T-F representation (TFR). The RPRG first detects the ridges of a multi-component signal from a TFR and then extracts the desired IFs by regrouping the ridge curves according to their variation rates at the intersections. After the IFs are obtained, component separation is achieved by using the intrinsic chirp component decomposition (ICCD) method. Different from traditional T-F filter-based methods, the ICCD can accurately reconstruct overlapped components by using a joint-estimation scheme. Finally, applications of separating some simulated and experimental micro-Doppler signals are presented to show the effectiveness of the method.

We introduce a general model to characterize multi-component chirp signals.The model represents instantaneous frequencies and instantaneous amplitudes of the intrinsic chirp components as Fourier series.We propose a novel chirp component decomposition method based on the model.The method is able to decompose multi-component chirp signals with intersecting IFs. In this paper, we consider the decomposition problem for multi-component chirp signals (MCCSs). We develop a general model to characterize MCCSs, where instantaneous frequencies (IFs) and instantaneous amplitudes (IAs) of the intrinsic chirp components (ICCs) are modeled as Fourier series. The decomposition problem thus boils down to identifying the developed model. The IF estimation is addressed using the framework of the general parameterized time-frequency transform and then the signal can be easily reconstructed by solving a linear system. For the practical implementation of our method, we present a two-step algorithm, which is initiated by an iterative scheme to achieve preliminary separation of the ICCs, followed by a joint-refinement step to get high-resolution ICC reconstructions. Our method acts as a time-varying band-pass filter and can even separate ICCs that cross in the time-frequency domain. The method is applied to analyze several simulated and real signals, which indicates its usefulness in various applications.

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time–frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

We propose a novel method, called chirplet path fusion, to analyze nonstationary signals with time-varying frequencies. As opposed to many existing methods that assume the signal persists throughout the whole time, the proposed method can be applied in cases where the signals are only present in short time frames. A demodulation-operator-based method is introduced to estimate the locally matched chirplet atoms which can form a chirplet path in the time–frequency domain. According to the density of the multiple chirplet paths obtained under different scales, the effective time support and the instantaneous frequency (IF) of the target signal can be estimated. Our method is effective in analyzing the nonstationary signal with discontinuous IF curve and works well under heavy noise. Several simulated signals and the vibration signal of a rotor test rig are considered to verify the effectiveness of the proposed method.

The users often have many product-related questions before they make a purchase decision in E-commerce. However, it is often time-consuming to examine each user review to identify the desired information. In this paper, we propose a novel review-driven framework for answer generation for product-related questions in E-commerce, named RAGE. We develope RAGE on the basis of the multi-layer convolutional architecture to facilitate speed-up of answer generation with the parallel computation. For each question, RAGE first extracts the relevant review snippets from the reviews of the corresponding product. Then, we devise a mechanism to identify the relevant information from the noise-prone review snippets and incorporate this information to guide the answer generation. The experiments on two real-world E-Commerce datasets show that the proposed RAGE significantly outperforms the existing alternatives in producing more accurate and informative answers in natural language. Moreover, RAGE takes much less time for both model training and answer generation than the existing RNN based generation models.

Flexible and high energy density supercapacitors have been received extensive attention due to their suitability as the power supply for wearable and portable electrical devices. However, it is still a great challenge to fabricate devices with simultaneously flexibility, high energy density and voltage window in a neutral electrolyte. Herein, we demonstrated a high-efficiency supercapacitor with dense NiCo2O4 nanosheets in Na2SO4 neutral electrolyte, achieving 1.2 V voltage window based on a single electrode, and 2.4 V for an assembled asymmetric system. The device shows an impressive capacitance of 120 F g‐1 at current density of 1 A g‐1, as well as an excellent cycling performance of 79.4% capacitance retention after 10,000 cycles. Meanwhile, the flexible ASC shows highly mechanical flexibility and impressive energy density, suggesting the great potential of the applications in flexible energy storage devices.

Wheel flat, as a common defect of railway vehicles, can cause large impact forces on both the vehicle and infrastructure components and thus seriously hinder the vehicle running stability and safety. Considering the complex track irregularities and variable-speed conditions, the vehicle vibration responses often contain strong interference signal components and exhibit time-varying frequency contents, which poses severe challenges to wheel flat detection. In this paper, a vehicle-track coupled model considering wheel flats under variable-speed conditions is employed to calculate and analyze the vehicle vibration accelerations at first. Then, according to the vibration characteristics, a two-level adaptive chirp mode decomposition (ACMD) approach is developed for the wheel flat detection. Specifically, in Level 1 of the approach, the ACMD is integrated with a Gini index-based mode selection and regrouping scheme to separate different fault signal modes under strong interferences. Based on the separated signal modes, the high-resolution ACMD-based time-frequency analysis method is applied to accurately extracting the time-varying fault characteristic frequencies and thus achieving the fault detection in Level 2. Both the dynamics simulation and experiment results indicate that the proposed approach can accurately detect wheel flats of small sizes under strong interferences for a variable-speed railway vehicle.

Intra-wave modulation effects with oscillating time-varying frequencies have been observed in physical systems including mechanical, ocean, power, and even biological ones. Such phenomena correspond to actual physical processes with which the underlying dynamics of these systems can be understood. In this work, we study intra-wave modulation effects in milling processes with the aid of iterative nonlinear chirp mode decomposition (INCMD), a recently proposed technique for analyzing complex dynamic responses. A nonlinear non-stationary template signal is provided to model milling vibration responses, and an INCMD-based strategy is developed to extract embedded modulation features. Through dynamic simulations and experimental verification, it has been demonstrated that distinct intra-wave modulation frequencies that are exactly equal to theoretical chatter frequencies calculated based on the Floquet theory exist to indicate different cutting states, and milling instability is accompanied by the variation of such a characteristic quantity. Bessel functions can mathematically relate explicit modulation patterns with intricate spectral distributions of milling responses. Moreover, the switch of the modulation pattern, which remains noticeable in the presence of noise, emerges far earlier than visible chatter marks do, indicating the superiority of the chatter detection and even prediction utilizing intra-wave modulation features.

Dispersive signals known for frequency-dependent characteristics have been frequently encountered in various fields like nondestructive testing, underwater acoustics, etc. Such signals often exhibit frequency-varying group delays (GDs) and consist of multiple modes overlapped in the time-frequency (TF) domain, which brings challenges to existing signal processing methods. In this paper, a generalized dispersive mode decomposition (GDMD) method is proposed to accurately estimate GDs and fully separate overlapped modes of dispersive signals. Specifically, a generalized dispersive signal model is defined in the frequency domain at first. Then, based on the defined model, the mode decomposition issue is formulated as an optimal dispersion compensation problem where the method simultaneously searches for the optimal modes and their GDs, with which the dispersion effects of all the modes can be fully eliminated. In addition, according to the output results of the GDMD, a high-quality TF distribution can be constructed to clearly reveal the TF pattern of a multimodal dispersive signal. Simulated examples and real-life applications to railway wheel fault diagnosis and Lamb wave analysis are carried out to show the effectiveness of the GDMD.

A new type of track inspection wagons (TIWs) for damage detection in urban rail transit systems is proposed to overcome the problems existing in traditional track inspection and ensure efficient and safe detection. Research on the dynamic testing and evaluation of TIWs is inadequate, which is not conducive to the design and improvement of similar products. Considering this, extensive dynamic performance tests and safety assessments under different running speeds were carried out on a new intelligent TIW. In this study, the rail misalignment and harmonic defects were designed to simulate the local irregularities in actual track lines. The accelerations of the axle-box, frames, vision modules, and wheel–rail forces were measured and analysed. Since the vision modules are the most critical components in the inspection system, the experiments focused on the evaluation of the safety of the visual module subjected to various track impacts. The experimental results indicate that the new intelligent TIW shows outstanding dynamic performance in the lab tests. Within the normal working range of the vision module, the vision modules of the wagon can withstand certain impacts from local rail local irregularities owing to its suspension design. Rail harmonic irregularity has a higher impact on wagon vibration than rail misalignment irregularity.

To analyze the valuable frequency component for time-varying frequency-modulated (FM) signals, component extraction is necessary in most applications. Considering the advantage of parameterized demodulation (PD) in transforming FM signals to be stationary, a novel component extraction method based on PD and singular value decomposition (PD-SVD) for both monocomponent and multicomponent signals is proposed. By extending the idea of PD, the time-varying term of the continuous phase function for the interested FM component can be removed, thus resulting in a highly self-correlated component with constant phase. Then, the extraction of the target component from noise or other components can be realized by SVD. Compared with the existing methods, the proposed algorithm is able to analyze the multicomponent signal with crossed instantaneous frequency trajectories and effectively improve the signal-to-noise ratio of the extracted component. The effectiveness of the proposed method is demonstrated by applying it on several numerical signals and the radial vibration signal of a hydroturbine rotor, indicating the potential of analyzing many practical FM signals.

The displacement measurement with frequency-modulated continuous-wave radar based on radar interferometry technique has attracted growing interest in recent years. One of the main challenging issues is the static clutter interference in the same range bin, which results in amplitude shrinkage. A novel approach from signal processing side is proposed, i.e. implementing a post-processing procedure based on phasor offset compensation, which can be formulated as a circle fitting problem regarding phasor representation. Both simulated and experimental results are provided to validate the effectiveness and superiority of the proposed technique.

Intra-wave modulations are a class of inherent nonlinear characteristics, exhibiting a fast oscillating instantaneous frequency and/or amplitude of responses. With the aid of the well-known Hilbert-Huang transform (HHT), such phenomena have been observed and utilized in many practical nonlinear systems including mechanical, power, ocean and even human biological systems. However, the empirical nature of the HHT makes the results physically uninterpretable and sensitive to perturbations of noise. Variational nonlinear chirp mode decomposition (VNCMD) is a recently proposed tool for analyzing wideband multicomponent signals, including intra-wave modulated responses. On the other hand, the VNCMD has strict requirements on the priori information of the signal. In this paper, we combine the framework of the VNCMD with that of the HHT, by replacing the joint-optimization scheme of the VNCMD with a recursive procedure adopted in the HHT. In this way, the new method becomes more adaptive without losing the rigorous mathematical foundation. This construction leads to a descendant of VNCMD, named the iterative nonlinear chirp mode decomposition (INCMD). Through dynamic simulations and applications to real data, it is demonstrated that the INCMD considerably outperforms state-of-the-art techniques of the same class. Using the INCMD, intra-wave modulations can be captured with high accuracy and strong noise-robustness. Extracted modulation features by the INCMD greatly help to detect and identify nonlinear systems.

Hierarchical porous precious metal-based nanosheets with ultrathin structures and highly exposed active surfaces are desirable in energy conversion technology, while robust synthetic strategies remain challenging. Here, we report a facile 1-hydroxyethylidene-1,1-diphosphonic acid (HEDP)-mediated approach to synthesize hierarchical porous Rh nanosheets (HP-Rh NSs), following the formation mechanism of emulsion-induced soft template. When HP-Rh NSs are applied to the methanol oxidation reaction (MOR), abundant edge/grain-boundary atoms and the ultrathin porous structure endow HP-Rh NSs with a mass activity of 333 A g−1 at 0.63 V, which are 5.8-fold enhancements compared with traditional commercial Pt black (57.4 A g−1). Meanwhile, the peak potential of MOR on HP-Rh NSs is 0.2 V lower than that on commercial Pt black. With the aid of theoretical calculations, larger methanol adsorption energy and the lower energy barrier reaction path are responsible for superior MOR activity on Rh HP-Rh NSs than commercial Pt black.

Fault diagnosis of planetary gearboxes under variable-speed conditions is a challenging task since the vibration signals are non-stationary and have more complicated characteristic components due to the complex gearbox configuration. Effectively identifying and extracting these non-stationary characteristic components are important for fault diagnosis. This paper achieves the goal by exploiting an improved adaptive chirp mode decomposition (I-ACMD) method. The I-ACMD mainly includes two ingredients. Firstly, the algorithm framework of the original ACMD is modified for joint component estimation, which can effectively deal with very close signal components. Secondly, to address the issue of the instantaneous frequency (IF) initialization for I-ACMD, we combine a parameterized demodulation (PD) method with a signal resampling technique to extract multiple IF curves simultaneously. Compared with traditional time-frequency ridge detection methods, the proposed PD-based IF initialization method shows much better interference robustness and thus is more effective to analyze complicated vibration signals of planetary gearboxes. Moreover, with the output results of the I-ACMD, we construct a high-resolution time-frequency representation which can clearly reveal the time-varying gear characteristic frequencies. Both our simulated and experimental studies have shown that the proposed method can effectively indentify very close and weak vibration characteristic components, and thus successfully detect different kinds of gear faults.

One important necessity is to filter out the irrelevant information and organize the relevant information into meaningful categories. However, developing text classifiers often requires a large number of labeled documents as training examples. Manually labeling documents is costly and time-consuming. More importantly, it becomes unrealistic to know all the categories covered by the documents beforehand. Recently, a few methods have been proposed to label documents by using a small set of relevant keywords for each category, known as dataless text classification . In this article, we propose a seed-guided topic model for the dataless text filtering and classification (named DFC). Given a collection of unlabeled documents, and for each specified category a small set of seed words that are relevant to the semantic meaning of the category, DFC filters out the irrelevant documents and classifies the relevant documents into the corresponding categories through topic influence. DFC models two kinds of topics: category-topics and general-topics . Also, there are two kinds of category-topics: relevant-topics and irrelevant-topics. Each relevant-topic is associated with one specific category, representing its semantic meaning. The irrelevant-topics represent the semantics of the unknown categories covered by the document collection. And the general-topics capture the global semantic information. DFC assumes that each document is associated with a single category-topic and a mixture of general-topics. A novelty of the model is that DFC learns the topics by exploiting the explicit word co-occurrence patterns between the seed words and regular words (i.e., non-seed words) in the document collection. A document is then filtered, or classified, based on its posterior category-topic assignment. Experiments on two widely used datasets show that DFC consistently outperforms the state-of-the-art dataless text classifiers for both classification with filtering and classification without filtering. In many tasks, DFC can also achieve comparable or even better classification accuracy than the state-of-the-art supervised learning solutions. Our experimental results further show that DFC is insensitive to the tuning parameters. Moreover, we conduct a thorough study about the impact of seed words for existing dataless text classification techniques. The results reveal that it is not using more seed words but the document coverage of the seed words for the corresponding category that affects the dataless classification performance.

Automated trust negotiation (ATN) is an approach to regulating the gradual exchange of sensitive resources, which are protected by access control policies, between two strangers to establish mutual trust in open distributed systems. Policy compliance checkers of ATN determine which credentials satisfy an access control policy and whether a particular set of credentials satisfies the relevant policy. We propose a description logic-based approach to policy compliance checking, in which the description logic (DL) $\mathcal {SHOIN(D)}$ is exploited to formalize credentials and policies of ATN, and the state-of-the-art DL reasoners are leveraged for policy compliance checking. By exploring the semantics of credentials and policies defined by DL, our approach can promote the success of a negotiation whenever it is semantically possible. As long as a policy can be satisfied, our approach can find the credentials satisfying the policy. These credentials can be either syntactically defined in the policy or semantically imply those defined. In addition, benefiting from DL reasoning, attribute delegations that are modeled as semantic relations among attributes can be retrieved by our approach as the evidence of a negotiator’s satisfaction of an access control policy. This evidence is quite necessary in the ATN environment where negotiators are usually strangers belonging to different domains without a common knowledge of delegations.

A simple and novel method for measuring four-degree-of-freedom geometric errors of a linear stage was put forward. A single-mode fiber-coupled laser module was used. Only a cube corner retro-reflector and a beam splitter were adopted in the moving target in order to sense the straightness errors and angular errors, respectively. In this way, the horizontal and vertical straightness errors as well as yaw and pitch errors can be measured simultaneously. Theoretic error separation has been analyzed in detail and the straightness-compensated method was given. The system based on the above method was developed. In comparison with an API five-dimensional laser measurement system, the accuracy of the measuring straightness error is about ±2.5 μm within the measuring range of ±500 μm, and the angular errors are about ±3 arcsec within the range of ±400 arcsec. In addition, there is no cable connection in the moving target, which is a great convenience for the workshop measurements.

A heterodyne temporal speckle pattern interferometer that measures the in-plane displacement dynamically has been built. The object is displaced in its plane continuously and the frequency-modulated output signals with a carrier frequency are recorded by a CCD camera. The displacement information is extracted with wavelet transform technique. Preliminary experiments have been performed with such interferometer. The respective measurement results recovered from wavelet transform and Fourier transform are compared.

This study was aimed to investigate the changes of hemodynamic parameters, pathology and c kit mRNA expression in myocardium after acute myocardial infarctionin (AMI) in rats, and to elucidate the relationship between these three kinds of changes. Sixty six adult male SD rats were randomly divided into normal group, Sham groups and ligation groups. The rat model of AMI was set up by ligating the left anterior descending artery. Hemodynamic parameters, pathological changes and c kit mRNA expression in myocardiam were examined. The results revealed that there were no statistically significant differences in hemodynamic parameters between normal group and Sham groups. Compared with the normal group, all ligation groups exhibited significantly decreased left ventricular systolic pressure (LVSP) and +/-dp/dtmax (P0.01), and increased left ventricular end diastolic pressure (LVEDP, P0.01). In the other ligation groups, compared with 6th hour group after ligation, there appeared striking increase of LVSP, LVEDP and +/-dp/dtmax (P0.05). HE staining in myocardiam showed that there are necrosis and derangement at 24th hour group after ligation ,and a great number of inflammatory cells infiltration around the infarct zone at 3rd day group after ligation, and granulation tissue infiltrated into the infarct zone at 14th day group after ligation. In all five time points groups after ligation, the levels of c-kit mRNA expression were 0.99 fold, 1.06 fold, 1.46 fold, 1.91 fold and 2.67 fold, respectively, compared with Sham groups. The results suggest that cardiac stem cells in myocardium might contribute to the role of regenerating myocardium via self proliferation after acute myocardial infarction, but further investigation is still needed.

This study was aimed at observing the effects of ovariectomy and estradiol on the microarchitecture of cancellous bone and exploring the influence of microarchitectural change on the biomechanical properties. Thirty 6-month-old unmated female SD rats were randomly divided into 3 groups (10 rat each): sham-operated control group (Sham), ovariectomized group (OVX)and Estradiol Benzoate treated group (EBT). All rats were housed in standard environmental conditions. Five months after operation, the rats were sacrificed. The biomechanical properties of the third lumbar vertebras (L3) were measured with compression testing in vitro. Micro-CT scanning was performed on the fourth lumbar vertebras (L4) in vitro. In comparison with the corresponding variables of Sham, the bone volume fraction (BV/TV) and the trabecular number (Tb. N) of OVX were reduced remarkably, and the trabecular separation (Tb. Sp) and the structural model index (SMI) of OVX were enhanced obviously. These facts implicated that the bone trabecular plate-like structure of OVX were decreased. BV/TV, Tb. N and the trabecular thickness (Tb. Th) of EBT were greater than those of OVX. Tb. Sp and SMI of EBT were much smaller than those of OVX. The results of mechanical test showed that the maximum forioe (Fmax), the maximum stress (sigmamax) and the elastic modeulus (E) of the lumbar vertebral cancellous bone of OVX were declined sharply, while the aforesaid biomechanical index of EBT was improved distinctly. The performance of three-dimensional micro-CT and the mechanical testing to assess microarchitecture of cancellous bone are useful for evaluating the state of osteoporosis and the antiosteoporotic effect of agents.

This paper presents the analysis and compensation of the errors crosstalk in our developed simultaneous measuring system for five-degree-of-freedom geometric error. The errors crosstalk, including the yaw crosstalk to the horizontal straightness, the pitch crosstalk to the vertical straightness, the roll crosstalk to the horizontal and vertical straightness, and the roll real value crosstalk to the roll measured value, can all be eliminated with the compensation. A series of experiments is conducted, and the results verify the compensation effect. For a linear stage, compared with an electronic level and a laser interferometer, the residuals are less than 2′′ when the roll errors are compensated, and the largest residuals for the compensated horizontal and vertical straightness are 1.9 and 3.5 μm, respectively.

This report describes a method for patterning multiple types of adherent cells on the same substrate by electrochemical desorption of self-assembled monolayers (SAMs) in localized areas defined by a microfluidic system. Several groups have previously reported techniques that allow the patterning of two different types of cells. None of these reported techniques, however, could both confine two or more types of cells to specific locations on surfaces without the presence of physical constraints and control the motility of these different types of cells. 4, 5] The technique presented herein will be useful for a number of biological systems, such as in the studies of neuronal development and in the control of tumor growth. Our method employs a commercially available thiol (HS(CH2)11(OCH2CH2)6OH, abbreviated as “EG6”) to form a SAM on the gold surface, which resists adsorption of proteins and adhesion of cells (for convenience, we call this surface the “inert surface”). A poly(dimethylsiloxane) (PDMS) stamp with embedded microfluidic channels is used to carry out selective electrochemical desorption of EG6 from the gold substrate (Figure 1). [7] This procedure allows parts of the inert surface to promote the adsorption of proteins and the adhesion of cells (we call this transformation “activation of the inert surface”). Each of these individually addressable microchannels can deliver one type of cell to activated regions of the surface, resulting in a pattern of multiple types of cells on the surface. Because an electrochemical reaction can take place only in areas exposed to microfluidic channels, patterned cells are confined to activated regions, which are defined by these channels upon removal of the stamp that carries the fluidic system. As there is no physical barrier between these cells, there is a free exchange of substances between these different types of cells through the liquid medium. This exchange allows the studies of cell–cell interactions when different types of cells are confined to separate locations on the surface. A second step of electrochemical desorption can “turn on” motility of cells and allow them to move under the influence of each other. We illustrate this approach by patterning two types of cells (NIH 3T3 and Hela cells) in stripes. Fabrication of an inert surface is accomplished by coating a gold-covered glass substrate with EG6. To selectively activate the inert surface, we first coated the inert substrate with a PDMS stamp with embedded microfeatures (see the Supporting Information for its fabrication) to form enclosed microchannels. The features embedded in the PDMS stamp formed the ceilings and vertical walls and the gold substrate formed the floors of the channels; the channels were reversibly sealed. We filled the channels with solutions of the extracellular matrix (ECM) protein fibronectin (100 mgmL 1 in a phosphate-buffered Figure 1. Strategy for patterning different types of cells. a) To obtain “inert” surfaces, we formed SAMs on gold-coated coverslips with EG6. b) A PDMS stamp with an embedded microfluidic system was brought into contact with the substrate, and the channels were filled with solutions of fibronectin. Application of a cathodic potential on the gold substrates desorbed SAMs inside the channels. c)–f) Magnified views of the main functional locations of the channel system. c) Adsorption of proteins inside the microchannels after electrochemical activation of the surface. d) Adhesion of cells on the floors of the channels. e) After the PDMS stamp was peeled off, a pattern of different types of cells was formed. f) A second step of electrochemical desorption enabled cells that were previously confined in patterns to spread across the previously inert surface.

A novel method to measure the roll angle using a quarter wave plate and a Wollaston prism is presented in this paper. The setup and principle of the measurement system are introduced. According to the optical structure, the mathematical model was established by Jones matrix method. The output voltage from an optical detector located after the Wollaston prism can be used to determine the roll angle. Theoretical analysis and experimental results show that the sensitivity of roll measurement can reach arc-second. The chief advantages of the sensor are simply, stable and compact. This system can be applied to dynamic roll angle measurement. Experimental results have shown that the angular resolution is 0.04 arc-minute in a ±40 are-minute range.

The effect of chitosan with different molecular weight and deacetylation degree on blood hemostasis was tested. The experiments found evident alteration of red blood cell morphology and unusual coagglutination between erythrocytes in the anticoagulant blood which was treated by chitosan acetic acid solution. The red blood cells clot formation experiments showed that chitosan with low deacetylation degree (60%-70%) caused more red blood cells to assemble when compared versus chitosan with other deacetylation degrees. The effect of molecular weight between 10(5)-10(6) was not obvious. The thrombin time (TT), prothrombin time (PT), activated partial thromboplastin time (APTT), and concentration of fibrinogen (FIB) of blood treated by chitosan acetic acid solution were measured. The results proved that the hemostasis property of chitosan acetic acid solution was independent of the platelets and the normal "Cascade-like" coagulation pathway.

Rail track geometric parameters, such as gage, level, twist, longitudinal irregularity, alignment irregularity, etc., have much influence on the operation safety of train vehicles. With the development of railway, the demand for measuring track geometric parameters precisely and efficiently has become a common concern, and to date this problem has not been properly solved. In this work, a new measurement method and a system for track geometric parameters are presented. Through analyzing advantages and disadvantages of existing measurement methods of track geometric parameters, a fiber-optic gyro is adopted for the straightness measurement. It greatly eliminates the measurement errors caused by existing methods. The feasibility of this track parameter measurement trolley is proven by practical experiments.