Search

Interference usually occurs between two non-orthogonally polarized light beams. Hence, metasurface enabled polarization multiplexing is generally conducted under two orthogonal polarization states to realize independent intensity and/or phase modulations. Herein, we show that polarization multiplexed metasurfaces can work under three non-orthogonal polarization states to realize tri-channel image displays with independent information encoding. Specifically, enabled by orientation degeneracy, each nanostructure of the metasurface operates with triple-manipulations of light, i.e., two channels for independent intensity manipulation under π/4 and 3π/8 linearly polarized (LP) light, respectively, and one channel for phase manipulation without polarization control. We experimentally demonstrate this concept by recording one continuous-brightness polychromatic image and one binary-brightness polychromatic image right at the metasurface plane, while a continuous-brightness polychromatic image is reconstructed in the far field, corresponding to three independent channels, respectively. More interestingly, in another design strategy with separated image encoding of two wavelengths, up to six independent image-display channels can be established and information delivery becomes safer by utilizing encryption algorithms. With the features of high information capacity and high security, the proposed meta-devices can empower advanced research and applications in multi-channel image displays, orbital angular momentum multiplexing communication, information encryption, anti-counterfeiting, multifunctional integrated nano-optoelectronics, etc.

Designing a color hologram with conventional metasurfaces usually resorts to a supercell strategy or single-sized approach with different incident angles. However, these designs still have their own drawbacks that need to be further solved. Herein, we show a new, to the best of our knowledge, single-sized strategy to design full-color geometric meta-holograms by utilizing the conjugation property of two circularly polarized lights with opposite handedness and diffraction dispersion. The experimentally captured holographic color images are reconstructed with high quality and without cross talk, which agrees well with our theoretical prediction. Moreover, only with an appropriate combination of wavelength and polarization state can color images be observed accurately. Our strategy provides a simple and effective approach for full-color meta-holography and offers significant potential in image display, information storage, etc.

Metasurfaces have shown their unique capabilities to manipulate the phase and/or amplitude properties of incident light at the subwavelength scale, which provides an effective approach for constructing amplitude-only, phase-only or even complexed amplitude meta-devices with high resolution. Most of meta-devices control the amplitude and/or phase of the incident light with the same polarization state; however, separately controlling of amplitude and phase of the incident light with different polarization states can provide a new degree of freedom for improving the information capacity of metasurfaces and designing multifunctional meta-devices. Herein, we combine the amplitude manipulation and geometric phase manipulation by only reconfiguring the orientation angle of the nanostructure and present a single-sized design strategy for a multiplexing meta-hologram which plays the dual roles: a continuous amplitude-only meta-device and a two-step phase-only meta-device. Two different modulation types can be readily switched merely by polarization controls. Our approach opens up the possibilities for separately and independently controlling of amplitude and phase of light to construct a multiplexing meta-hologram with a single-sized metasurface, which can contribute to the advanced research and applications in multi-folded optical anti-counterfeiting, optical information hiding and optical information encoding.

Geometric metasurfaces, governed by PB phase, have shown their strong polarization sensitivity and can generate opposite phase delay when the handedness of incident circularly-polarized (CP) light is opposite. Here, we show this interesting characteristic can be employed to generate asymmetric forward and backward propagation with the same incident left- or right-handed CP light, which is hard to achieve with conventional optical elements and devices. Specifically, with the modified holographic design algorithm to consider both forward and backward CP light, an asymmetric meta-hologram is designed, which can project two different holographic images in the forward and backward directions, respectively. We demonstrate this concept by fabricating an asymmetric hologram with a single-size nanostructured metasurface, and the experimentally obtained holographic images in both directions have shown their advantages of high fidelity, broadband response and low crosstalk. The proposed asymmetric metasurface can play an important role in data storages, anti-counterfeitings, optical communications, displays and many other related fields.

Though already being one of the standard modules of SCADA for years, the fault diagnosis software still exists the problem of high misrecognition rate. To mitigate the issue, this paper proposed a new fault diagnosis model and algorithm based on logistic regression deep neural network (LRDNN) to improve the diagnosis accuracy. The basic process of the proposed method is as follows: 1) construct a deep fully connected neural network for each power equipment. The input of the neural network is the vector of the fault signals of equipment, including switching signal, protection signal and etc., and the output is the failure probability; 2) train the LRDNN based on RMSprop method. Since the proposed method can dig out the complicated relationship between the fault signals and the fault probability, it owns high diagnosis accuracy. Moreover, this paper designed a sample expansion method based on random sampling strategy to successfully realize the training of the LRDNN, skillfully overcoming the defect of the lack of sample. The basic process of which is: 1) extend the historical fault records of equipment by including the fault records of equipment at nearby areas, whose type is the same as the one to be diagnosed; 2) generate adequate number of samples by probability statistics and random sampling operation. A comprehensive comparison of the proposed method and the method based on expert system was performed on practical power systems, which shows that the proposed method reduces the misrecognition rate from 31.25% to 0 compared with the one based on expert system.

Precise identity recognition is a pre-condition for robots to enter the human living environment. Most of the existed face identification methods cannot work on the non-frontal face since the severe texture loss. In this paper, we propose a novel system to deal with multi-angle face identification in video sequence based on frontal face generation, which replaces the process of detection, alignment in the typical face identification system. To solve the problem of face texture loss in large pose variation, we creatively combine generative adversarial networks (GAN) with the state-of-the-art facial landmark localization method. The proposed system was tested on video database containing multi-angle faces, and the experimental results indicate that our system can recognize more faces in the frames, and improve the accuracy of identification for multi-angle face by 130%.

Enabled with both magnetic resonance and geometric phase, dielectric nanobrick based metasurfaces have shown their unusual abilities to produce high-definition and high-efficiency holographic images. Herein, we further show that such a metasurface can not only project a holographic image in far field but also record a grayscale image right at the metasurface plane simultaneously, merely with a single-celled nanostructure design approach. Specifically, each nanobrick in a unit-cell of the metasurface acts as a half-wave plate and it can continuously rotate the polarization direction of incident linearly polarized light. Governed by Malus law, light intensity modulation is available with the help of a bulk-optic analyzer and a continuous grayscale image appears right at the metasurface plane. At the same time, the concept of orientation degeneracy of nanostructures can be utilized to generate a 4-step geometric phase, with which a holographic image is reconstructed in far field. We experimentally demonstrate this multifunctional meta-device by employing the widely used silicon-on-insulator (SOI) material and all results agree well with our theoretical prediction. With the novel features of easiness in design, high efficiency, broadband spectrum response, strong robustness, high security and high information density, the proposed SOI-based metasurfaces will have extensive applications in optical information security and multiplexing.

Metasurfaces, acting as arrays of perfect nano-polarizers, provide a promising approach to manipulate the amplitude of an incident light at the sub-wavelength scale. In this Letter, we design and demonstrate continuous amplitude-modulated meta-fork gratings to generate optical vortex beams. More importantly, benefiting from the unique negative amplitude modulation, the unavoidable zero-order light that conventional amplitude-only elements always suffer disappears by carefully adjusting the orientation of each nanobrick. The dramatically dropped zero-order light with only 3% leakage energy verifies our design. With the advantages of continuous amplitude modulation, zero-order extinction, and super-high resolution, the proposed meta-fork grating will have a widespread application in integrated optical vortex manipulation and promote the emergence of many other amplitude-modulated nano-optical devices.

The yearly amount of waste getting disposed of in Singapore is rising, which poses a waste management issue to be tackled and overcome. The practice of upcycling increases the value of objects and materials and hence, can divert these materials from landfills. This study investigated individuals' and businesses' motivation, interest and participation in upcycling in Singapore. Firstly an overview of the relatively nascent upcycling studies was conducted. The design thinking approach was then employed, which helped to uncover stakeholders’ needs and frustrations. Through the implementation of the design thinking approach, this study chose and prototyped a mobile app-aided waste marketplace platform that aimed to reduce the barriers of upcycling by aggregating the materials available in the market and crowdsourcing upcycling know-how. Generally, the results found from the user testing of the platform were positive and encouraging. Feedbacks from individuals showed that the platform can help to improve key factors including raising the awareness of the upcycling issues, and also enable such practices by providing better usability and promoting the upcycling culture. Evaluations from business also corroborate these aspects. The results indicated the potential feasibility and impact of such a solution to promote upcycling in Singapore.

Power grid dispatching is a complex system engineering, and its working pattern and operation principle are implicit in the operation behavior of the dispatcher's daily work. This paper proposes a method which applies the big data technology to mine the operation patterns of grid dispatching. Firstly, data preprocessing is performed on a large number of historical operational records through session division, routine distinguishing and page hierarchy division, where a method of dynamically determining session division threshold and routine distinguishing reference value based on statistical indicators is proposed. Then, the clustering model based on session similarity and affinity propagation algorithm is adopted. This algorithm clusters the operation records after data preprocessing to find the daily operation behavior pattern of the dispatcher. The operation log data of a regional dispatching center in China is taken as an example to verify the algorithm. The results show that the method can effectively identify the operational behavior pattern in power grid dispatching, which provides strong support for the application of auxiliary decision based on the operating mode.

Lane detection plays an important role in improving autopilot&rsquo, s safety. In this paper, a novel lane-division-lines detection method is proposed, which exhibits good performances in abnormal illumination and lane occlusion. It includes three major components: First, the captured image is converted to aerial view to make full use of parallel lanes&rsquo, characteristics. Second, a ridge detector is proposed to extract each lane&rsquo, s feature points and remove noise points with an adaptable neural network (ANN). Last, the lane-division-lines are accurately fitted by an improved random sample consensus (RANSAC), termed the (regional) gaussian distribution random sample consensus (G-RANSAC). To test the performances of this novel lane detection method, we proposed a new index named the lane departure index (LDI) describing the departure degree between true lane and predicted lane. Experimental results verified the superior performances of the proposed method over others in different testing scenarios, respectively achieving 99.02%, 96.92%, 96.65% and 91.61% true-positive rates (TPR), and 66.16, 54.85, 55.98 and 52.61 LDIs in four different types of testing scenarios.

Climbing stairs is an important ability for humanoid robots. This paper proposes a target location and gait planning method for humanoid robot climbing stairs. Target location enables the humanoid robot to accurately locate the stair position, and the gait planning algorithm makes the humanoid robot to climb the stairs. In order to enable the humanoid robot to climb multiple stairs, this paper proposes control strategy of motion for humanoid robot. The effectiveness of our proposed method was confirmed by experiments. The experimental results show that this method improves the accuracy of target location, and enables the humanoid robot Nao to climb a staircase with 2.928 cm steps.

Background Lung adenocarcinoma (LUAD) patients experiencing lymph node metastasis (LNM) always exhibit poor clinical outcomes. A biomarker or gene signature that could predict survival in these patients would have a substantial clinical impact, allowing for earlier detection of mortality risk and for individualized therapy. Methods With the aim to identify a novel mRNA signature associated with overall survival, we analysed LUAD patients with LNM extracted from The Cancer Genome Atlas (TCGA). LASSO Cox regression was applied to build the prediction model. An external cohort was applied to validate the prediction model. Results We identified a 4-gene signature that could effectively stratify a high-risk subset of these patients, and time-dependent receiver operating characteristic (tROC) analysis indicated that the signature had a powerful predictive ability. Gene Set Enrichment Analysis (GSEA) showed that the high-risk subset was mainly associated with important cancer-related hallmarks. Moreover, a predictive nomogram was established based on the signature integrated with clinicopathological features. Lastly, the signature was validated by an external cohort from Gene Expression Omnibus (GEO). Conclusion In summary, we developed a robust mRNA signature as an independent factor to effectively classify LUAD patients with LNM into low- and high-risk groups, which might provide a basis for personalized treatments for these patients.

Introduction. Gliomas are infiltrative neoplasms of a highly invasive nature. Different stages of gliomas feature distinct genomic, genetic, and epigenetic changes. The long noncoding RNA Growth Arrest Specific Transcript 5 (GAS5) is an identified tumour suppressor involved in several cancers. However, the underlying roles of the GAS5 gene in lower-grade glioma (LGG) patients are not clear. Methods. Via bioinformatic analysis based on TCGA-LGG and TCGA-GBM data, we explored the mechanisms of GAS5 expression in LGG (grades II and III) and high-grade glioma (glioblastoma multiforme, grade IV). The log-rank test and multivariate Cox analysis were performed to find the association between GAS5 and overall survival (OS) in LGG patients. Weighted gene coexpression network analysis (WGCNA) and RNA-Seq analysis were applied to find the key gene network associated with GAS5. Results. We found that GAS5 expression was downregulated in both LGG and glioblastoma multiforme (GBM) compared with normal brain tissue. Low methylation in the GAS5 promoter region was detected in both LGG and GBM tissues. The amplification type was the predominant type of GAS5 gene alteration in both LGG and GBM. High GAS5 expression was more associated with long overall survival (OS) in LGG patients than in GBM patients. The multivariate survival analysis of GAS5 and clinical and molecular characteristics in LGG patients further confirmed the association between GAS5 and OS in LGG patients. We then developed a nomogram for clinical use. WGCNA and RNA-Seq analysis indicated that ribosomal biogenesis and translation initiation were the predominant events regulated by GAS5 in LGG patients. Conclusion. Taken together, these results demonstrate that GAS5 expression is associated with OS in LGG patients and that its underlying roles involve the regulation of ribosomal biogenesis and translation initiation, which may aid in identifying a new target for the treatment of LGG.

The compressed tracking algorithm (CT tracker) is a well-known visual tracking method that models a target object's appearance through sparse random projection. However, the tracking results are not stable and robust due to the randomness of random projection. To solve this problem, a more stable and robust approach is proposed for visual tracking based on maximally stable extremal regions (MSERs), sparse random projection and online least squares SVM classifier (LS-SVM) learning. To obtain a relatively stable appearance model, the stable connected components of an object based on MSERs in image feature space are extracted. With the fusion of MSERs and sparse random projection, we model adaptive object appearance to adapt the variation of appearance. Additionally, an online closed-form LS-SVM is employed to quickly and robustly predict the target object location in a tracking by detection framework. Experimental results on benchmark sequences show the stability and robustness of the proposed algorithm compared with the existing CT-based trackers and other state-of-the-art trackers. HighlightsA more stable and robust approach is proposed for visual tracking relying on Maximally Stable Extremal Regions (MSERs), sparse random projection and online Least Squares SVM classifier (LS-SVM) learning.With the fusion of MSERs and sparse random projection, the stable adaptive object appearance is modeled to adapt the variation of appearance.An online closed-form LS-SVM is employed to quickly and robustly predict the target object location.

AIM: The aim of this study was to investigate the alterations of pulmonary function tests (PFTs) and their relationship with disease activity in inflammatory bowel diseases (IBDs). METHODS: Sixty-four IBD patients (31 Crohn's disease [CD] and 33 ulcerative colitis [UC]) and thirty healthy individuals (controls) were studied with regard to the following parameters of PFTs: Forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), their ratio, mid-forced expiratory flow of 25–75% (FEF 25–75), residual volume, total lung capacity, and diffusing capacity of the lung for carbon monoxide (DLCO). The disease activity was calculated using the Crohn's Disease Activity Index for CD and Mayo Clinic Score for UC. Correlation analysis was performed between disease activity and sputum cytology and PFTs. RESULTS: Nineteen of the 31 CD patients (61.29%) and 17 of the 33 UC patients (51.52%) but none of the controls showed at least one abnormal PFTs (P < 0.05). Compared with controls, both CD and UC patients exhibited a significant reduction in FEV1 (P < 0.05), FVC (P < 0.05), FEF 25–75 (P < 0.05), and DLCO (P < 0.05). The majority with decreased measurements of PFTs were in the active phase of diseases (P < 0.05). IBD activity scores correlated negatively with some parameters of PFTs and positively with lymphocytosis and eosinophilia of sputum (P < 0.05). CONCLUSIONS: Pulmonary function disorders are significantly common in IBD patients. The impairment in active disease is significantly greater than in remission.

Background. The prevalence of overweight/obesity in adults is raised to 39%, which is nearly tripled more than 1975. The alteration of the gut microbiome has been widely accepted as one of the main causal factors. To find an effective strategy for the prevention and treatment of overweight/obesity, a systematic review and meta-analysis were designed. Methods. In this study, we systematically reviewed the article published from January 2008 to July 2018 and conducted a meta-analysis to examine the effects of probiotics on body weight control, lipid profile, and glycemic control in healthy adults with overweight or obesity. The primary outcomes were body weight, body mass index (BMI), waist circumference, fat mass, fat percentages, plasma lipid profiles, and glucose metabolic parameters. Results. We systematically searched PubMed, Embase, and the Web of Science and identified 1248 articles, and 7 articles which were manually searched by the references of included studies and previously systematic reviews. Twelve randomized controlled trials (RCTs), including 821 participants, were included in the meta-analysis via full-text screening. Probiotics supplementation resulted in a statistical reduction in body weight (WMD [95% CI]; -0.55 [-0.91, -0.19] kg), BMI (WMD [95% CI]; -0.30 [-0.43, -0.18] kg m−2), waist circumference (WMD [95% CI]; -1.20 [-2.21, -0.19] cm), fat mass (WMD [95% CI]; -0.91 [-1.19, -0.63] kg), and fat percentage (WMD [95% CI]; -0.92 [-1.27, -0.56] %) compared with control groups. As expected, the metabolic parameters were improved significantly, with a pooled standardized mean difference in TC (SMD [95% CI]; -0.43 [-0.80, -0.07]), LDL-C (SMD [95% CI]; -0.41 [-0.77, -0.04]), FPG (SMD [95% CI]; -0.35 [-0.67, -0.02]), insulin (SMD [95% CI]; -0.44 [-0.84, -0.03]), and HOMA-IR (SMD [95% CI]; -0.51 [-0.96, -0.05]), respectively. The changes in TG (SMD [95% CI]; 0.14 [-0.23, 0.50]), HDL-C (SMD [95% CI]; -0.31 [-0.70, 0.07]), and HbA1c (SMD [95% CI]; -0.23 [-0.46, 0.01]) were not significant. Conclusion. This study suggests that the probiotics supplementation could potentially reduce the weight gain and improve some of the associated metabolic parameters, which may become an effective strategy for the prevention and treatment of obesity in adult individuals.

The traditional lane detection methods based on the RANSAC algorithm used to cause many false detection and unable to accurately detect the lanes in complex road environment, because of the existence of interferential noise points in the set of sampling points. Aiming at these issues, this paper presents a new lane detection method combined fuzzy control with RANSAC algorithm. The first process of the new lane detection method is pretreatment, the purpose of which is to denoise the image preliminarily through filtering and binarization. And then it selects the region of interest (ROI) that contains lanes in the input image and extract the initial boundary candidate points of the lanes in ROI. So far, there are still a lot of irrelevant noise points in the set of lane boundary candidate points. It would analyze the relationship between the interferential noise points and the boundary points of the lane, and then remove the interferential noise points from the set of lane boundary candidate points by using the fuzzy control. After that, fit the lane model by using RANSAC algorithm in the set of effective lane boundary points. The experiment shows that the method proposed in this paper has high robustness and effectiveness which can accurately detect the lanes in complicated city road.

Active distribution network is a development mode of future distribution network and a new power distribution system adapting to the active control and management development trend of distribution network. Therefore, this network can effectively cope with large-scale and high-permeability grid connection of distributed energy resource. The Comprehensive Demonstration Project of Active Distribution Network in Suzhou is an engineering practice of active distribution network technology application. This paper describes overview and implementation plan of the demonstration project and explains with emphasis the key technologies for coordinated control of the active distribution network from such aspects as situation awareness, flexible DC, and coordinated control of power grid, power source and load. Through construction of the demonstration project, it is able to realize flexible absorption of high proportional and distributed energy resource in the demonstration zone, intelligent allocation of high-quality electric energy, coordinated and optimized control of multiple resources from power grid, power source, load and stored energy. In addition, a new DC power supply mode has been explored and developed for the distribution network, providing a reference and example for in-depth development and engineering practice of the active distribution network.

UHVDC commutation failure and DC block need to be studied in detail, for they will evidently affect the safety and stability of AC power grid. Firstly, the main circuit and control system are studied and analyzed in depth. Then, the simulation model is established in PSCAD software. After that, the curves of commutation failure and DC block in different cases are obtained. Finally, the correctness of this simulation platform is verified by comparison of some recording curves.

With the rapid construction of UHV AC/DC power grid, the integration characteristics of power grid are becoming more and more prominent, and real-time operation control of dispatching is significantly becoming more and more difficult. The existing monitoring and control model based on the system model data cannot meet the requirements for the development of UHV power grid. Based on the existing achievements of dispatching automation system, the general goal and framework of the trans-regional cooperative disposal of UHV interconnected power grid are put forward, and the key technologies are analyzed in four aspects: situation awareness, fault location, joint disposal and cooperative control to provide reference and example for follow-up construction for real-time control and support system for the dispatching of UHV power grid.

With the rapid development of society and remarkable improvement of the power distribution automation of our country, users put forward higher requirements to power quality and reliability of power supply. According to the distribution network structure and operation mode, combining large-scale blackouts of Hangzhou distribution grid, this paper did a depth study on rapid restoration technology, under the existence of the bottleneck, it proposed the key technology to improve the reliability of distribution blackout automation and completed the development of recovery software. Through the Hangzhou actual test, software finish restoration less than 10 minutes, the distribution of large area blackouts rapid recovery become practical.

BACKGROUND Current expert consensus recommends the use of bare metal stent (BMS) for patients with an indication for oral anticoagulation (OAC) undergoing coronary stenting. The use of drug-eluting stents (DES) should be limited. However, there is a lack of evidence to support these recommendations. We performed a meta-analysis to compare the efficacy and safety of DES to BMS in these patients. METHODS We searched PubMed, Embase, the Cochrane library, and relevant journals. Studies comparing the efficacy and safety of DES to BMS in patients with an indication for OAC undergoing coronary stenting were included. End points included major adverse cardiac events (MACE), death, bleeding complications, and stroke. The outcome assessments were measured by hazard ratio (HR) and its 95% confidence interval. RESULTS We yielded 453 studies by primary searching. According to the inclusion criteria, four studies enrolling 1,522 patients were finally included. A pooled estimate of HR for MACE, all-cause mortality, myocardial infarction, and bleeding complications showed no significant differences between patients treated with DES and BMS. The risk of target vessel revascularization (TVR) was significantly decreased in the DES implanted patients in comparison with patients with a BMS implantation. CONCLUSION For patients with an indication for OAC undergoing coronary stenting, DES might a DES can be as safely used as a BMS, and is superior in reducing the risk of TVR.

The time–intensity curve (TIC) from contrast-enhanced ultrasound (CEUS) image sequence of uterine fibroids provides important parameter information for qualitative and quantitative evaluation of efficacy of treatment such as high-intensity focused ultrasound surgery. However, respiration and other physiological movements inevitably affect the process of CEUS imaging, and this reduces the accuracy of TIC calculation. In this study, a method of TIC calculation for vascular perfusion of uterine fibroids based on subtraction imaging with motion correction is proposed. First, the fibroid CEUS recording video was decoded into frame images based on the record frame rate. Next, the Brox optical flow algorithm was used to estimate the displacement field and correct the motion between two frames based on warp technique. Then, subtraction imaging was performed to extract the positional distribution of vascular perfusion (PDOVP). Finally, the average gray of all pixels in the PDOVP from each image was determined, and this was considered the TIC of CEUS image sequence. Both the correlation coefficient and mutual information of the results with proposed method were larger than those determined using the original method. PDOVP extraction results have been improved significantly after motion correction. The variance reduction rates were all positive, indicating that the fluctuations of TIC had become less pronounced, and the calculation accuracy has been improved after motion correction. This proposed method can effectively overcome the influence of motion mainly caused by respiration and allows precise calculation of TIC.

Background Reperfusion therapy is widely utilized for acute myocardial infarction (AMI), so ischemia/reperfusion (I/R) of the heart is frequently encountered in clinical practice. The curative effects of reperfusion therapy for AMI are favourable in most cases, but reperfusion can also cause harmful effect to cardiomyocytes. Hydroxysafflor yellow A (HSYA) is an effective therapeutic agent to alleviate I/R injury, but the mechanisms underlying this therapeutic effect are unknown. Methods and results The H9c2 cardiomyocyte cell line was incubated with or without HSYA during hypoxia, then it was reoxygenated. In the presence of HSYA, reoxygenation resulted in the upregulated expression and activity of heme oxygenase-1 (HO-1), phosphorylation of Akt, translocation of nuclear factor Nrf2, and most importantly, a reduction in A/R-induced apoptosis. An HO-1 inhibitor completely suppressed HO-1 enzymatic activity upregulated by HSYA and notably diminished the anti-apoptotic effect of HSYA. An inhibitor of PI3K, completely blocked Akt phosphorylation induced by HSYA and partly negated HSYA-induced upregulation of HO-1, translocation of nuclear factor Nrf2 and suppression of apoptosis in the H9c2 cardiomyocytes. Conclusions Our study suggests that HSYA can provide protection to H9c2 cardiomyocytes against A/R-induced apoptosis. This protective effect largely depends on the upregulation of HO-1 expression through the PI3K/Akt/Nrf2 signaling pathway.

Considering the influence of the limited measurement data on the effectiveness of the image reconstruction algorithms in industrial multiphase flow tomography, an iterative filtering reconstruction algorithm is proposed by redefining inverse problem in this article. In order to improve the image quality in iterative reconstruction algorithm, Wiener filter and soft-threshold algorithm are employed as constraints for the reconstructed image. The developed algorithm is applied to gamma-CT based two-phase flow measurements, both simulated and experimental. The results demonstrate that the proposed method cannot only realize the flow regime identification on horizontal pipe, but also improve the iterative reconstruction process, i.e., the reconstructed image quality is enhanced and the iteration number is reduced.

In order to complete the auto-segmentation of cardiac dual-source CT image and extract the structure of heart accurately, this paper proposes a hybrid segmentation method based on k clustering and Graph-Cuts. This method identifies the initial label of pixels, on the basis of it, then creates the energy function on the label with the knowledge of anatomic construction of heart and constructs the network diagram, finally minimizes the energy function by the method of max-flow/min-cut theorem and picks up region of interest. The experiment results indicate that the robust, accurate segmentation of the cardiac DSCT image can be realized by combining Graph-Cut and k clustering algorithm

Wireless sensor network can eliminate the high cost of wired network. However, in wireless sensor networks, an important but critical problem is the energy consumption of sensor nodes greatly limits the working life. The paper combining the application of genetic algorithm for wireless sensor networks in multi-objective optimization, taking into account the needs of specific application, a sensor network in the open pit slope detection example is introduced. Fitness function is designed according to the application of open-pit mine slope detection system. In the same conditions, using serial genetic algorithm, parallel genetic algorithm and quantum genetic algorithm for network energy optimization. Simulation results show that: genetic algorithm optimize the energy consumption, achieve the longest life cycle of the network. By comparing these three kinds of genetic algorithms, the quantum genetic algorithm is much better than the other two genetic algorithms in optimizing the energy consumption.

Increasingly importance has been taken seriously for high frame rate CMOS camera to optical communication acquisition pointing and tacking (APT) system, with its compact structure, easy to developed and adapted to beacon light spot detection in atmospheric channel. As spot position accuracy directly determines the performance of space optical communication, it is very important to design a high precision spot center algorithm. Usually spot location algorithm uses gravity algorithm, shape center capturing algorithm or self-adaption threshold algorithm. In experiments we analyzed the characteristics of the spots which transmitted through atmospheric turbulence and studied light transmission characteristics in turbulent channel. We carried out a beacon light detection experiments in a distance of 3.4km, collected the beacon spots on CMOS camera and signal light power. We calculated spot position with two different algorithm and compared the calculation accuracy between field dispersive spot and ideal Gaussian laser spot. Experiment research show that, gravity center algorithm should be more suitable for beacon beam spot which accuracy can be improved about 1.3 pixels for a Gaussian spot. But the shape center algorithm has higher precision. The reasons were analyzed which made an important preparation for subsequent testing.

Communication experiments of free space optical system which was laid on the vibration platform were implemented. In the communication experiments, the transmitting terminal is static and the receiving terminal is laid on the vibration platform. The vibration platform was used to validate the performance of the APT (acquiring, pointing and tracking) system. The analytic results of experimental data prove that the APT system can effective restrain the destabilization of laser beam caused by the vibration platform. The communication distance is 3.4 km and the communication rate is 2.5 Gbps.

Objective: Realize the accurate segmentation and tridimensional visualization of cardiac medical image and finish the design of cardiac aided diagnosis. Methods: Combine clinical experts diagnosis experience, CT image prior feature and graph cut algorithm model, adopt GPUs parallel data processing to realize the segmentation of cardiac struction and tridimensional visualization. Result: Finish the accruate, quick and robust segmentaion and visualization of CT image sequence, initially realize the visualized cardiac aided diagnosis system based on GPUs. Conclusion: The study makes full use of the powerful parallel comouting capacity of computer graphics processing unit, solves the problems in medical image processing and segmentaiton, and improves the operating efficiency of the program and the uer experience.

Based on the visualization platform of the dispatching technical support system of smart grid, an overall scheme design and application implementation of the visualization for power system dynamic monitoring is presented. The overall visualization process framework, the overall interface design and the application visual effects of power system dynamic monitoring based on the wide area measurement system (WAMS) are described in detail. It is indicated from its application in smart grid dispatching system of Jiangsu province in China that the visualization functions for the applications of WAMS can realize an efficient, accurate monitoring and alarming for the dynamic operation status of electric power system and allow operators to grasp important system information quickly and intuitively.

Fault Processing is the most important part of dispatchers routine monitoring work, which is significant to improving processing efficiency, shorten the processing time and prevent further deterioration of the accident when enhance its intelligent level. From the features of dispatchers fault processing, this paper presents a general framework of large grid online decision-making support for accident treatment, and research on the five aspects of integrated information platform, risk awareness of beforehand, online fault diagnosis, auxiliary decision-making of afterward and visualization.

Computed tomography angiography (CTA) is widely used to assess heart disease, like coronary artery disease. In order to complete the auto-segmentation of cardiac image of dual-source CT (DSCT) and extract the structure of heart accurately, this paper proposes a hybrid segmentation method based on k clustering and Graph-Cuts (GC). It identifies the initial label of pixels by this method. Based on this, it creates the energy function of the label with the knowledge of anatomic construction of heart and constructs the network diagram. Finally, it minimizes the energy function by the method of max-flow/min-cut theorem and picks up region of interest. The experiment results indicate that the robust, accurate segmentation of the cardiac DSCT image can be realized by combining Graph-Cut and k clustering algorithm.

One of the most crucial issues, during the operation of power system, is to deal with the power failures timely and rapidly in case the accident grows bigger, which calls for our operators and controllers to judge the fault facilities correctly. Based on the development of science and information technology aimed at automatic control upon power grid, we put for-ward a method of online fault diagnosis which comprehensive use three-state data (steady, dynamic, transient state), co-processes on the time, space and information dimensions of data sources together, to improve real-time, reliability and practicality of power fault diagnosis. It also incorporates the visualization technology to achieve hierarchical and intelligent linkage visualization of power fault information,which improve intelligent level of Fault Disposal.

Realization of real-time on-line fault diagnosis has great significance to determine fault device as soon as possible, reduce power losses, and help dispatchers process fault. In this paper, based on previous theories of fault diagnosis, the practicable on-line intelligent fault diagnosis system is developed with unified model of information description and multi-source information fusion technology. This information includes information of switch, protection and recorder, which are on the foundation of EMS/protection information system. The diagnosis system is proved to be effective in practice after being applied to the real power system.

This paper describes the application of a low-energy γ-ray computed tomography (CT) system to two-phase flow measurement. A 241A m (59.5 KeV) γ-ray source is used to penetrate a 82 mm i.d. pipe, an array of 17 detector elements is utilized to measure the projection data, and a rotating mechanism is employed to get 3 to 11 projections with the single source. Because this system offers only 3 to 11 projections, and the detector elements are sparsely arranged, conventional reconstruction algorithms are ineffective, thus improvement based on matrix completion algorithm has been developed to improve the imaging quality. Reconstructed results from measurement data demonstrate the effectiveness of this technique. Dynamic experiment result of a horizontally moving Perspex model are also presented, which clearly show the shape and size of the model.

For multi-phase flow in pipelines, the distributions of the individual phases are of significant importance. For this reason a low-energy gamma-ray tomography system has been designed. The set-up uses a 241Am source along with a CdZnTe array to acquire gamma ray attenuation data in different positions of a cross-section plane around a test pipe. A charge sensitive amplifier (CSA) and a fourth-order Gaussian pulse shaper have been designed. The voltage pulses generated by CSA are filtered inside the Gaussian pulse shaper to obtain maximum output signal-to-noise rate (SNR) before being fed to a digital spectrum analyzer. In this paper, CSA and the pulse shaper will be considered first, and some output waveforms of the real circuit will be given. Meanwhile, some details of the spectrum analyzer unit based on FPGA are also described. Raw data from the set-up will be used as the input of PC for image reconstruction.

Electrical capacitance tomography (ECT) is gaining acceptance as a laboratory and industry tool to analyze gas/liquid two phase flow. To overcome the shortcomings of the existing analogue ECT system, a new 16-electrode digital electrical capacitance tomography system based on FPGA and DSP is designed. The new scheme can easily realize single frequency and multi-frequency excitation and demodulation. Furthermore, two kinds of methods for multi-frequency demodulation, DFT demodulation and digital quadrature demodulation, are discussed deeply. Static and dynamic experiments under condition of single frequency are carried out to verify the performance of the digital ECT system. Experimental results show that this system is of high precision and stability.