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TraditionalIn this study, we propose an improved NIPS method, which calculates the SD in theA total of 3,219 pregnant samples have been used for validating the proposed method on detecting fetal trisomy syndromes (T13, T18, and T21), in which eight false negative (FN) samples have been corrected as true positive (TP) and eight false positive (FP) samples have been fixed as true negative (TN) with our proposed adaptive-SD method. Another 6592 samples were used to compare the two methods on detecting five recurrent fetal copy number variation (CNV) syndromes, in which the FP samples have decreased from 99 to 39.Our adaptive-SD NIPS method shows more power on detecting both trisomy syndromes and five recurrent CNVs in the pregnant samples with diverse read counts. Besides, our proposed method contributes to lower FP and FN samples than the traditional

Reflectors are very critical space elements and can be used not only as solar collectors/reflectors, telecommunication radio antennas and telescopes but also for dual-usage such as solar sails and solar concentrators to probe and sublimate materials from asteroids when actively controlling the surface shape. In this paper, the surface shape of a slack reflector with negligible elastic deformations will be controlled to be a paraboloid by actively modulating the solar radiation pressure (SRP) force using reflectivity control devices (RCDs) across the reflector. Nonlinear static equilibrium equations for an arbitrary infinitesimal within the reflector along the radial, circumferential and transverse directions are established considering the external modulated SRP force and internal tensions respectively. The coupled radial stress differential governing equation and reflectivity algebraic equation are obtained for the paraboloid reflector by the help of the formulation of an inverse problem based on equilibrium equations previously established. Some analytical and numerical analysis for reflectors with ideal and non-perfect SRP force models are performed respectively. The conclusions concerning about how to control the reflector’s surface shape successfully using allowed reflectivity, resulting in reasonable stress range, moreover, how to get the feasible solutions influenced by the reflector’s size parameters, are all based on the presented analytical and numerical analysis.

Immunotherapy, an attractive option for cancer treatment, necessitates the direct stimulation of immune cells in vivo and the simultaneous effective inhibition of immunosuppressive tumor microenvironments. Methods: In the present study, we developed an injectable PEG-b-poly(L-alanine) hydrogel for co-delivery of a tumor vaccine and dual immune checkpoint inhibitors to increase tumor immunotherapy efficacy. Tumor cell lysates, granulocyte-macrophage colony stimulating factor (GM-CSF), and immune checkpoint inhibitors (anti-CTLA-4/PD-1 antibody) were readily encapsulated in the porous hydrogel during the spontaneous self-assembly of polypeptide in aqueous solution. Results: Sustained release of tumor antigens and GM-CSF persistently recruited and activated dendritic cells (DCs) and induced a strong T-cell response in vivo, which was further enhanced by the immune checkpoint therapy. The hydrogel vaccine also upregulated the production of IgG and the secretion of cytokines including IFN-γ, IL-4, and TNF-α. Importantly, the hydrogel-based combination therapy had superior immunotherapy effects against melanoma and 4T-1 tumor in comparison with the vaccine alone or in addition with a single immune checkpoint blockade. In studying the underlying mechanism, we found that the hydrogel-based combinatorial immunotherapy not only significantly increased the activated effector CD8+ T cells within the spleens and tumors of vaccinated mice, but also reduced the ratio of Tregs. Conclusion: Our findings indicate that the polypeptide hydrogel can be used as an effective sustained delivery platform for vaccines and immune checkpoint inhibitors, providing an advanced combinatorial immunotherapy approach for cancer treatment.

Decision tree method is one of the most popular data mining technologies, which is mainly used for classification and prediction. Decision tree method is a sample-based inductive classification and decision-making method. It has many advantages, such as small amount of calculation, fast speed, high classification accuracy and easy understanding of classification rules. With the rise of various Internet consumer loans, customer credit overdue risk prediction has become an important research direction in the e-commerce finance industry. Under the background of big data, it is of practical significance for credit loan decision-making to establish a comprehensive and unified data platform to integrate multi-dimensional data information, to model data in multi-dimension, to predict customer credit risk, and to construct a prediction model of credit overdue risk. This paper takes the customer credit risk of e-commerce financial platform as the research object, and constructs a decision tree to determine the decision-making scheme of customer credit rating in order to maximize the expected return.

With the development of deep neural networks in pattern classification for recognizing handwritten digits on cheques, object classification for the automated surveillance, and autonomous vehicles, the problem of DNNs confront malicious inputs has been a hot topic. In this paper, we introduced a security-enhanced framework for DNNs to conduct classification based on moving target defense (MTDNNF). Also, we presented three pivotal characteristics to realize the framework, heterogeneity, selectivity, and adaptability, which enabled MTDNNF and guaranteed security and veracity. Also, we analyzed the security and performance of MTDNNF. Those analyses show that the MTDNNF can provide significant security improvements against malicious inputs, and extra cost in performance is inessential under both massive and minimum scenarios.

In the heterogeneous interference and target-rich environment, the clutter-plus-noise covariance matrix (CCM) estimate with a good match for the cell under test is significant for space–time adaptive processing. In this paper, an intelligent sample selection method is proposed to estimate the CCM and, thus, to suppress the clutter in the heterogeneous background. First, the proposed method applies the sample amplitude and the spatial relationship between the sample and the antenna beam center to describe the characteristics of samples, which preliminarily selects the crucial homogeneous and heterogeneous samples based on the joint histogram property. Then, the generalized inner product value and the spatial included angle are used to work as two representative features for the training samples as well as the testing samples. Based on the feature vector, the multi-dimensional feature projection based on the kernel function is carried out to achieve the offline training classifier, and the testing samples are classified with intelligence in the multi-dimensional feature space by utilizing the trained support vector machine. Due to the utilization of space–time property in representative feature extraction and intelligent strategy for the decision-making process, the proposed method acquires more reliable and efficient sample selection results compared with most of conventional sample selection methods. The experimental results based on the simulated and measured data show the effectiveness of the proposed method.

Objective: To explore the microstructural damage of extrapyramidal system gray matter nuclei in Parkinson disease (PD) using diffusion kurtosis imaging (DKI). Materials and Methods: We enrolled 35 clinically confirmed PD patients and 23 healthy volunteers. All patients underwent MR examination with conventional MRI scan sequences and an additional DKI sequence. We subsequently reconstructed the DKI raw images and analyzed the data. A radiologist in our hospital collected the Mini-Mental State Examination (MMSE) score of all subjects. Results: In the PD group, the mean kurtosis and axial kurtosis level decreased in the red nucleus (RN) and thalamus; the radial kurtosis increased in the substantia nigra (SN) and globus pallidus (GP). Fractional anisotropy decreased in the putamen. The largest area under the ROC curve of mean diffusion in GP was 0.811. Most kurtosis parameters demonstrated a positive correlation with the MMSE score, while several diffusion parameters showed a negative correlation with the same. Conclusion: DKI can qualitatively distinguish PD from healthy controls; furthermore, DKI-derived parameters can quantitatively evaluate the modifications of microstructures in extrapyramidal system gray matter nucleus in PD.

The aim of this paper is to explore a novel bumper system consisting of a negative Poisson's ratio (NPR) beam and a NPR absorber. The NPR beam is designed to improve the frontal crashworthiness of the vehicle, which is composed of a large number of inner hexagonal cellular structures through periodic arrangement. Meanwhile, the NPR absorber, filled in the space between the bumper beam and the skin, is contrived to protect the pedestrian's lower leg in the collision accident. Based on this, an optimization model is constructed and the multi-objective optimization algorithms are used to search the optimal structural parameters. The simulation results show that the comprehensive performance index of the NPR bumper system optimized by electronic-search algorithm (ESA) algorithm has been effectively improved, and it performs excellent performances in both pedestrian protection and vehicle crashworthiness.

The bumper system always directly causes the injury of the pedestrian leg in the car–pedestrian accidents. Therefore, it is of practical significance to optimize the bumper structure to enhance the protective effect of the pedestrian leg. Based on the original bumper system, this work proposes a novel negative Poisson’s ratio energy-absorbing forepart with inner hexagonal cellular structure, which is designed at the lower leg impact zone between the bumper beam and the cover. The parametric model of the negative Poisson’s ratio forepart, the lower legform impactor model, and the car–pedestrian collision model are firstly established. Then, through integrating the response surface method, second-order reliability method, and archive-based micro genetic algorithm, a reliability optimization design is further conducted for the negative Poisson’s ratio forepart based on the deterministic optimization results. Simulation results show that the optimized negative Poisson’s ratio forepart not only can significantly enhance the reliability and robustness, but also improve the protective effect of the pedestrian leg.

ABO-incompatible (ABO-i) living-donor liver transplantation (LDLT) is performed if an ABO-compatible graft cannot be obtained. However, a perfect desensitization protocol has not been established worldwide, especially for simultaneous ABO-i LDLT and splenectomy. We herein report two cases of ABO-i LDLT. To the best of our knowledge, this is the first case report of ABO-i LDLT in an adult patient in China. Splenectomy and T-cell-targeted immunosuppression (basiliximab) was used to overcome the blood group barrier in these recipients. The patients had good graft function without signs of antibody-mediated rejection throughout the 12-month follow-up. Thus, ABO-i LDLT with splenectomy is undoubtedly life-saving when an ABO-compatible graft cannot be obtained for patients in critical condition.

In order to realize dimension reduction detection of satellite-borne GPS receivers, the working mode and on-orbit historical fault mode of GPS receivers are analyzed, and a dimension reduction detection method of satellite-borne GPS receivers based on principal component analysis is proposed. The main components of the fault alarm variables are extracted from the on-orbit fault data samples of a satellite GPS receiver, and the fault features are effectively reduced in dimension, which is verified by historical fault simulation. The dimension reduction detection of satellite-borne GPS receivers is of great significance for ensuring the safe and stable operation of satellites in orbit and effectively realizing their mission.

Lung squamous cell carcinoma (LUSC) progression is accompanied by changes in protein levels that may be reflected in body fluids, such as plasma, bronchoalveolar lavage fluid (BALF) and urine. Certain proteins present in these biofluids can facilitate lung cancer diagnosis. Kininogen 1 (KNG1), osteopontin (OPN) and α-1-antitrypsin (AAT) are associated with tumorigenesis. The present study aimed to explore the combined monitoring of plasma, urine and BALF to gain insight into LUSC by monitoring the levels of the above three protein using ELISA. LUSC (n=31) and healthy controls with benign lung diseases (n=20) were enrolled in the study. KNG1 levels in plasma, BALF and urine were significantly higher in patients with LUSC patients than in controls (P

Lubricant filling into a closed fluid domain of a transmission component has always been a challenge, for it is limited by a number of factors, like structural characteristics of a transmission component, load characteristics, and oil temperature of during an operation. This paper proposes a lubricant volume optimization model that takes into account the effect of temperature and heat, with an electronically controlled limited slip differential (ELSD) for an automobile taken as the study object. In the paper, an ELSD simulation model was firstly constructed, based on a CFD numerical simulation method. After model simplification and assumption, the probes were established for fluid speed and temperature parameters during gear rotation. The influence law of lubricant volume in the ELSD on convective heat transfer was then determined by analyzing the working conditions, including different rotational speeds and different oil immersion depths. Finally, the optimization model was constructed, with the numerical values after the steady-state temperature fluctuation and the time required for the fluctuation taken as evaluation indexes. In the study, by taking specific parameters for examples and based on the proposed optimization model, quadratic response surface method was used for equation fitting of multiple results obtained from the simulation, and the lubricant volume of 37.21% of the total volume was found to be optimal, which verified the feasibility of the model. The method provides a new approach for determining the lubricant volume for a transmission component.

The heat load of the car compartment is complex and difficult to express with mathematical models. Therefore, this paper establishes a compartment physical model of an electric car through Amesim and simulates the heating process of the heat pump air conditioning system. Because the load of the passenger compartment of the car is complex and changeable, and the heat pump air-conditioning is a large inertia, hysteretic system. This study designs fuzzy rules and uses fuzzy PID to control the temperature of the passenger compartment. Fuzzy PID control has 1.6% less overshoot than PID control and 39 seconds less setting time. At the same time, this paper establishes a thermal comfort model of cabin temperature and humidity. It uses PMV (predicted average vote) and PDD (dissatisfied percentage) thermal comfort index to evaluate the passenger cabin’s thermal comfort. The PMV index controlled by fuzzy PID is more stable than the PMV controlled by PID.

Anti-collision beam of front door has significant influence on occupant protection and side crashworthiness. In order to improve the comprehensive side impact performance of vehicle, this work proposes a novel negative Poisson's ratio (NPR) door anti-collision beam based on star-shaped cellular structural material, and optimizes it by a reliability-based optimization scheme. First, the parametric model of NPR anti-collision beam, vehicle model assembling NPR beam, occupant restraint system model and side collision model are established. Then, the basic mechanical properties of the NPR structure are investigated under considering the axial normal force, transverse shear force and bending moment of each rod, and the macro performance of NPR beam are analyzed. Next, a deterministic optimization integrating optimal Latin hypercube sampling (OLHS) method, response surface model (RSM) and NSGA-II algorithm is conducted to improve the performance of novel NPR beam. Finally, considering the uncertainties of design variables, a reliability-based optimization is further executed to enhance the robustness of the deterministic optimization by using Design for Six Sigma (DFSS) method. Simulation results show that the ultimate optimized NPR anti-collision beam can not only ameliorate driver's protection and side crashworthiness, but also ensure the reliability and lightweight effect.

The huge AC power girds of China have been all connected by dozens of HVDC links now. To understand the behavior of the complicated network and mechanism of interaction between AC and DC, there is a demand for a more precise simulation technology. Traditional power system analysis tools, such as electromechanical transient program and off-line electromagnetic transient program, the models of DC control and protections are simplified to some degree. Sometimes the simplification may not reflect the same act that grid may do as in the field. In order to get a detailed, panoramic view, it is believed that simulating the large-scale network model by electromagnetic transient software in real-time with actual DC control and protection devices linked will give a better performance. In this way, the simulation time step should be small enough so that the physical DC controllers can be connected to realize hybrid simulation. Normally, microsecond level is applied. However, running a tremendous AC/DC grid model of thousands of buses with a time step of microseconds is the precondition of digital-analog hybrid simulation, and also a great challenge to all experts in the field of power system real-time simulation of the world. Based on task mapping and parallel computing technology, power system real-time simulator HYPERSIM and supercomputer SGI UV300 are used in this paper to achieve the goal. Considering of the processor’s computational capability, on account of naturally decoupling by long distributed parameter lines, this paper optimizes the method of large-scale grid decoupling, splits the sophisticated region grid model into distributed tasks reasonably. Exploring the automatic task mapping function in HYPERSIM, a synthetic method about multiple auto-assigned parameters optimization is proposed. Eventually, an electromagnetic transient network model of 17746 single phase buses can be operated in real-time, which is a breakthrough on scale expanding of real-time simulation. The precision of AC/DC grid simulation makes a step further. The realization of massive grid model real-time operation gives a new technical means for characteristic cognition, system planning, operating, decision-making and failure reproduction of Chinese future power system.

Fetal fraction (FF) is the percent of cell-free DNA (cfDNA) in the mother's peripheral blood that is of fetal origin, which plays a pivotal role in noninvasive prenatal screening (NIPS). We present a method that can reliably estimate FFs by examining autosome single-nucleotide polymorphisms (SNPs).Even at a very low sequencing depth, there are plenty of SNPs covered by more than one read. At those SNPs, we define read heterozygosity and demonstrate that the percent of read heterozygosity is a function of FF, which allows FF to be inferred.We first demonstrated the effectiveness of our method in inferring FF. Then we used the inferred FF as an informative alternative prior to computing Bayes factors to test for aneuploidy, and observed better power than the Z-test. In analysis of clinical samples, we were able to identify female-male twins thanks to the accurate FF inference.Knowing FF improves efficacy of NIPS. It brings a powerful Bayesian method, allows "no call" for samples with small FFs, renders screening for XXY syndrome simpler, and permits an adaptive design to sequence at a higher depth for samples with small FFs.

This paper proposes an electric equipment image recognition algorithm based on decision fusion of multiple classifiers. Considering the drawbacks of a single classifier, three classifiers, i.e., K-nearest neighbor (KNN), support vector machine (SVM), and sparse representation-based classification (SRC) are jointly used in the classification stage. The decision values from the three classifiers are linearly combined using a weighting strategy. So, the merits of different classifiers can be fused to enhance the recognition performance. Finally, based on the fused decision values, the object label of the test sample can be decided. To validate the effectiveness of the proposed method, images of three electrical equipments (insulators, power transformers, and breakers) are classified and compared with some other methods.

The acoustic field of a linear compressor serves to deliver the compression work to the load, such as the connected cold head of a cryocooler; it plays an equivalently important role as the electrical and mechanical parts, especially in the impedance match issue. This paper studies the acoustic impedance characteristics of a linear compressor. The parameters including the current, the piston displacement, the pressure amplitude, the electrical power dissipation, the power factor, the pressure-volumetric (PV) power delivered, and the efficiency are theoretically and experimentally investigated. Different from previous theoretical studies, optimization for the operations away from the resonance is also included. More general optimization results imply relevance between thermoacoustic engines and linear compressors. The predicted results are validated by the experiments performed on a linear compressor with an adjustable resistive-capacitive (RC) acoustic load. The comparisons between the calculations and the measurements are presented and analyzed. The results provide deeper insight into the mechanism of the linear compressor and the impedance match in a cryocooler system.

// Weiwei Wang 1, * , Shanshan Wang 1, * and Man Zhang 2, 3 1 Department of Pulmonary and Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China 2 Clinical Laboratory Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China 3 Beijing Key Laboratory of Urinary Cellular Molecular Diagnostics, Beijing, China * These authors have contributed equally to this work Correspondence to: Man Zhang, email: mzhang99@aliyun.com Keywords: urine peptides, lung adenocarcinoma, MALDI-TOF MS, immunohistochemistry, biomarker Received: November 30, 2016 Accepted: January 24, 2017 Published: March 03, 2017 ABSTRACT Lung adenocarcinoma (LAC) progression is accompanied by changes in protein levels that may be reflected in body fluids, such as urine. Urine collected from LAC patients ( n =34) and healthy controls ( n =36) was analyzed via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. The results revealed 76 urinary polypeptides significantly different between LAC patients and normal controls ( P 600. Twelve of these 13 peptides were successfully identified using nano-liquid chromatography-tandem MS. Receiver operating characteristic analyses identified seven peptides with superior LAC diagnostic performances. Immunohistochemical staining in 20 paired LAC and adjacent normal tissues showed that IGKC, AAT, SH3BGRL3, osteopontin and gelsolin levels were higher in LAC tissues than in adjacent tissuesand were closely associated with LAC. Urinary peptides assessments may thus provide a novel, noninvasive, repeatable method for detecting and monitoring LAC. New, low-cost detection methods and bioinformatics tools are therefore urgently needed for the analysis of low abundance proteins and peptides in body fluids.

A 43-year-old man with a history of rheumatoid heart disease developed endocarditis. Blood culture showed endocarditis was caused by Kodamaea ohmeri and the susceptibility test showed the yeast species were susceptible to itraconazole, amphotericin B, and voriconazole, but susceptible-dose dependent to fluconazole, and resistant to 5-flucytosine. Treated with surgery and anti-fungi agents, the patient recovered from endocarditis. This is the first case of K. ohmeri fungemia found in Chinese from mainland. More and more evidence indicate that K. ohmeri is an important opportunistic pathogen for human beings.

An efficient optical image amplification scheme has been proposed and demonstrated using the quasi-phase-matched optical parametric amplifier. Pumped with the 152 μJ per pulse pump laser at 532 nm, the input weak infrared image at 1064 nm with 3.5 pJ energy is amplified with a 55 dB optical gain using only a 3 mm long MgO-doped periodically poled lithium niobate (MgO:PPLN) crystal. A spatial resolution of 17 lines/mm on the surface of the PPLN crystal is obtained. Further numerical simulation indicates that our scheme enables efficient image enhancement with a long pulsed pumping source, such as nanosecond lasers.

Magnetorheological (MR) dampers have promising applications for providing instantaneous and controllable damping to attenuate vibrations in various dynamic systems. Currently, the mechanical energy along with motion of the MR damper is mostly transferred into heat energy and is finally dissipated into environments. In view of recycling usage of such dissipated energy in MR damper systems, the MR damper with power generation is consequently needed in practical applications. In this paper, a MR damper with compact power generation mechanism in parallel is proposed, which can provide both damping effect and recycling energy from mechanical vibration. The physical modeling of the MR damper with power generation in a non-dimensional parametric analysis is developed to give a clear and quantitative insight of performance influences from parameter design. The analytical modeling was validated by comparison results with finite element analysis of this prototype. Then, a performance-oriented parameter optimization design of this prototype is proposed, which could achieve a maximum damping force with fairly large dynamic range for the MR damper and a maximum resulting energy for the power generator subject to physical structure limitation under various external excitations in applications.

The disadvantage of the generalized learning vector quantization (GLVQ) and fuzzy generalization learning vector quantization (FGLVQ) algorithms is discussed in this paper. And a revised generalized learning vector quantization (RGLVQ) algorithm is proposed to overcome the disadvantage of GLVQ and FGLVQ. Furthermore, by introducing a stimulating coefficient in completing step, a new competing technique to improve the performance of the LVQ neural network is proposed also. The proposed algorithms are tested and evaluated using the IRIS data set. And the efficiency of the proposed algorithms is also illustrated by their use in codebook design for image compression based on vector quantization, and the training time for RGLVQ algorithm is reduced by 10% as compared with FGLVQ while the performance is similar. The new competing technique is also used to generate codebook and PSNR is improved in experiments.

With the increase of the swath width and imaging resolution, the resulting enormous amount of sampling raw data aggravates storage and transmission load for Multi-channel synthetic aperture radar (SAR) system. Considering the fact that the correlation among the multi-channel SAR images is high, we propose a compressive sensing (CS)-based ground moving target indication framework with sparse sampled raw data. In the proposed framework, the SAR imaging of one channel is utilized as prior-knowledge, the clutter of other channels is suppressed with only small amount of raw data. Thus the moving targets can be accurately recovered by compressive sensing after clutter suppression. Experiment results demonstrate the proposed method performs well with a very limited number of samples, even if clutter scattering centers are non-sparse.

The wind power integration in northwest grid will produce great influence on the operation of power grid which is particularly different from conventional power network. The problem of security and stability of the power grid has been prominent, which may intensify with the increase of wind power integration scale and capacity. In this paper, the digital-analog hybrid simulation model of Northwest China grid is built based on the data of summer-peak load in 2015 level year. Based on the model, the security and stability of the northwest power grid is studied by simulating different types of the serious faults on the the wind farm interconnection point and the 750kV transmission lines at the Hexi corridor. Study shows that the different low voltage ride through (LVRT) capability characteristic may cause different impacts on the stability of Northwest China grid with large scale wind power. The voltage index of wind turbines' LVRT capability and proportion requirements of wind turbines with LVRT capability are put forward to make sure the stability of power system after N-1 faults. Hierarchical control strategy for wind turbine is promoted to prevent system instability after serious faults. It is of great guiding significance on the planning and construction of Northwest China grid, as well as the safety and stability operation of power grid with largescale wind power.

In the ESP (Electronic Stability Program), the pressure limiting valve is used to control the max pressure in the brake system. Although the traditional relief valve can meet this requirement, the max pressure that can control is a certain value which can't change due to the circumstance of the vehicle. In this paper, the high speed on/off valve under control of high-frequency PWM (Pulse Width Modulation) is used to control the max pressure in the brake system by changing the duty cycle of PWM. Nevertheless, this paper establish a high-speed on/off valve simulation model which is under control of PWM of 2k ȼ 4k Hz modulation frequency in MATLAB-Simulink, and analysis the function of pressure limiting valve in different duty cycle of the control of PWM. Through this research, the application of the high-speed on/off valve is extended, and it is helpful to control the brake pressure precisely.

Low quality and small size of X-ray images causes difficulties for doctors to diagnose comprehensively. This paper presents a panorama system for x-ray medical images with low quality and small size based on SURF. The main steps of this system are: first to enhance the low quality images by MSR; secondly, to match separated images by SURF; lastly to blend the images by multiband blending method. Experiments showed that the presented system can not only enhance the contrast and clearness of the medical image with low quality but also observe it synthetically.

Coriolis mass flowmeter (CMF) is significant in many industrial and commercial areas. The two-phase flow, external vibration or flow pulsation in a Coriolis mass flowmeter can cause errors in the meter's measurements of density and mass flow rate. Some errors may be due to the closed-loop control system. In this paper, they are investigated from analog and digital closed-loop control system by experiment study. And also the advantage and disadvantage ware tested between analog and digital closed-loop control system by using the oil-water two-phase flow. It was found that the relative precise error of mass flowrate was relatively small for oil-water two-phase flow, not changed with the quantity of oil. Experimentally-derived data was used to illustrate that the digital closed-loop control system has more precise than the analog, and provide stable oscillation and selection of a sustainable setpoint for amplitude of oscillation, even during situations such as a highly-damped operation of the flowtube, vibration or beginning/ending operation of the flowtube.

A new time series prediction method based on support vector machine (SVM) and genetic algorithm (GA) is proposed. At first, SVM is used to partition the whole input space into several disjointed regions. Secondly, GA is adopted to determine the parameter combination of the SVM corresponding to the partitioned region obtained above. At last, the different SVM in the different input-output spaces is constructed and used to predict time series. The simulation result shows that the multiple SVM achieve significant improvement in the generalization performance in comparison with the single SVM model.

This paper describes a domain-specialized natural language generation system-Intelligent Scenes Inquiring System (ISIS), which automatically produce Chinese text with information of a park and the scenes in it when the user asks a question in Chinese. One feature of ISIS is the discourse focusing strategy in text planning, another is the use of a dynamic knowledge base that includes a map of a park and some forms filled by the user. This feature makes the use of ISIS common to all parks.

An image-feature based second generation watermarking scheme is proposed in this paper. A host image is firstly transformed into wavelet coefficients and features are extracted from the lowest approximation. Then a watermark sequence is inserted in all high frequency coefficients corresponding to the extracted featured approximation coefficients. Original host image is not needed in watermarking detection, but the featured approximation coefficients position is necessary for robust detection. The correlation between the embedded watermark and all high frequency coefficients of a possibly corrupted watermarked image corresponding to the approximate coefficients at the same position as the original featured approximation coefficients is calculated and compared to a predefined threshold to see if the watermark is present. Experimental results show the watermark is very robust to common image processing, lossy compression in particular.

Background and objectives Circumferential pulmonary vein isolation (CPVI) has become a major treatment of atrial fibrillation (Af). However, the postprocedural early recurrence rate is still high, which may be related to postoperative inflammatory reaction. With pleiotropic effects, statins are expected to inhibit the inflammatory response and thus reduce the Af recurrence after catheter ablation. The authors sought to clarify the efficacy of a large dose of atorvastatin therapy for preventing early Af recurrence after CPVI. Methods A total of 40 patients with paroxysmal Af and with hypercholesterolemia were randomly divided into two groups: control group (n=20) and high-dose atorvastatin intervention group (intervention group, n=20). Both groups received routine clinical medical treatment, and control group only received atorvastatin of £20 mg/day if indicated. Intervention group was given atorvastatin 80 mg 24 h and 40 mg 2 h before CPVI, and then atorvastatin 40 mg/day for 1 month. Blood samples were collected 24 h before and immediately after, 3 days and 1, 2 and 3 months after CPVI. The inflammatory markers including high-sensitivity C reactive protein (hs-CRP), interleukin 6 (IL-6) and tumour necrosis factor α (TNFα), and myocardial injury markers CK-MB and cTn-T were measured. The Af early recurrence was monitored clinically and by 72 h Holter monitoring. Results At a mean follow-up period of 3 months, as compared with the control group, AF burden was significantly reduced in the intervention group (p 0.05). The level of inflammatory markers including hs-CRP, IL-6, TNFα were increased immediately and 3 days after ablation in both groups. However, compared with those of the control group, the levels of hs-CRP, IL-6 and TNFα were significantly reduced in intervention group (p 0.05, each). Conclusions The pilot study showed that high-dose atorvastatin pretreatment and short-term enhanced intervention can reduce the peri-procedural inflammatory response and atrial fibrillation burden after catheter ablation, but does not decrease the early recurrence of atrial fibrillation.