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The vortex-induced vibration of the aqueduct girder may excite the parametric sloshing of the contained water which will have substantial impacts on the normal running and structural safety of the ...

Objectives As the largest organ of the human body, the skin is the major exposure route of NO2. However, the evidence for a relationship between NO2 exposure and dermatologic diseases (DMs) is limited. This time-series study was conducted to assess the short-term effect of nitrogen dioxide (NO2) exposure on DMs outpatient visits in Xinxiang, China. Methods Daily recordings of NO2 concentrations, meteorological data, and the outpatient visits data for DMs were collected in Xinxiang from January 1st, 2015, to December 31st, 2018. The analysis method used was based on the generalized additive model (GAM) with quasi-Poisson regression to investigate the relationship between NO2 exposure and DMs outpatient visits. Several covariates, such as long-term trends, seasonality, and weather conditions were controlled. Results A total of 164,270 DMs outpatients were recorded. A 10 μg/m3 increase in NO2 concentrations during the period was associated with a 1.86% increase in DMs outpatient visits (95% confidence intervals [Cl]: 1.06–2.66%). The effect was stronger (around 6 times) in the cool seasons than in warmer seasons and younger patients (

As the global warming crisis becomes increasingly serious, decarbonized integrated electricity-gas system (IEGS) which can reduce CO2 emissions are gradually developed. However, with high proportion of renewable energy access, the inherent randomness and volatility bring great difficulties to energy scheduling optimization of decarbonized IEGS. In this article, for reducing CO2 emissions, meanwhile improving the utilization efficiency of wind power, a novel IEGS architecture with collaborative operation of power-to-gas (P2G), carbon capture system (CCS) and electric vehicles (EVs) is constructed. P2G is operated in a refined model combined with H2 storage and captured CO2 by CCS can be further consumed in reaction of P2G. Besides, EVs are innovatively adopted in IEGS as flexible energy resource to reduce the impact of wind power fluctuations. Additionally, a multi-step day ahead-intraday collaborative optimization framework is proposed to handle with the uncertainty of wind power, more accurate predicted wind power can be adopted under this framework. The objective function of constructed IEGS is minimize the total operating costs, which takes the CO2 processing costs and penalty costs of wind power deviations into consideration. Numerical studies are conducted with different cases, with the constructed structure and proposed multi-step optimization framework, the emissions of CO2 can be efficiently reduced and wind power utilization can be significantly improved, the total operating costs of IEGS can be reduced more than 20% compared with other cases, which demonstrates that the research of this article has better economic benefits and environmental friendliness.

In this paper, we focus on human pose transfer in different videos, i.e., transferring the dance pose of a person in given video to a target person in the other video. Our methods can be summed up in three stages to tackle this challenging scenario. Firstly, we extract the frames and pose masks from the source video and target video. Secondly, we use our model to synthesize the frames of target person with the given dance pose. Thirdly, we refine the generated frames to improve the quality of outputs. Our model is built on three stages: 1) human pose extraction and normalization. 2) a GAN based on cross-domain correspondence mechanism to synthesize dance-guided person image in target video by consecutive frames and pose stick images. 3) coarse-to-fine generation strategy which includes two GANs: a GAN used to reconstruct human face in target video, the other generates smoothing frame sequences. Finally, we compress the sequential frames generated from our model into video format. Compared with previous works, our model manifests better person appearance consistency and time coherence in video-to-video synthesis for human motion transfer, which makes the generated video look more realistic. The qualitative and quantitative comparisons represent our approach performs significant improvements over the state-of-the-art methods. Experiments on synthetic frames and ground truth validate the effectiveness of the proposed method.

A two-stage denoising algorithm based on local similarity is proposed to process lowly and moderate corrupted images with random-valued impulse noise in this paper. In the noise detection stage, the pixel to be detected is centered and the local similarity between the pixel and each pixel in its neighborhood is calculated, which can be used as the probability that the pixel is noise. By obtaining the local similarity of each pixel in the image and setting an appropriate threshold, the noise pixels and clean pixels in the damaged image can be detected. In the image restoration stage, an improved bilateral filter based on local similarity and geometric distance is designed. The pixel detected as noise in the first stage is filtered and the new intensity value is the weighted average of all pixel intensities in its neighborhood. A large number of experiments have been conducted on different test images and the results show that compared with the mainstream denoising algorithms, the proposed method can detect and filter out the random-value impulse noise in the image more effectively and faster, while better retaining the edges and other details of the image.

Prostate cancer is the second-deadliest cancer in men in the United States, seriously affecting people's life and health. The Gleason grading system is one of the most reliable methods to quantify the invasiveness of prostate cancer, which is of great significance for risk assessment and treatment planning for patients. However, the task of automating Gleason grading is difficult because of the complexity of pathological images of prostate cancer. This paper presents an automated Gleason grading and Gleason pattern region segmentation method based on deep learning for pathological images of prostate cancer. An architecture combining the atrous spatial pyramid pooling and the multiscale standard convolution is proposed for the segmentation of the Gleason pattern region to get accurate Gleason grading. In addition, the postprocessing procedure based on conditional random fields is applied to the prediction. The quantitative experiments on 1211 prostate cancer tissue microarrays demonstrate that our results have a high correlation with the manual segmentations. The mean intersection over union and the overall pixel accuracy for the Gleason pattern region are 77.29% and 89.51%, respectively. Furthermore, the results of the automatic Gleason grading were comparable to the results of experienced pathologists. The inter-annotator agreements between the model and the pathologists, quantified via Cohen's quadratic kappa statistic, was 0.77 on average. Our study shows that the method of combining different deep neural network architectures is suitable for more objective and reproducible Gleason grading of prostate cancer.

Background The immunomodulatory abnormalities of silicosis are related to the lymphocyte oxidative stress state. The potential effect of antioxidant therapy on silicosis may depend on the variation in nuclear factor erythroid 2-related factor 2 (NRF2)-regulated antioxidant genes in peripheral blood mononuclear cells (PBMCs). As NRF2 is a redox-sensitive transcription factor, its possible roles and underlying mechanism in the treatment of silicosis need to be clarified. Methods Ninety-two male patients with silicosis and 87 male healthy volunteers were randomly selected. PBMCs were isolated from fresh blood from patients with silicosis and healthy controls. The lymphocyte oxidative stress state was investigated by evaluating NRF2 expression and NRF2-dependent antioxidative genes in PBMCs from patients with silicosis. Key differentially expressed genes (DEGs) and signaling pathways were identified utilizing RNA sequencing (RNA-Seq) and bioinformatics technology. Gene set enrichment analysis was used to identify the differences in NRF2 signaling networks between patients with silicosis and healthy controls. Results The number of monocytes was significantly higher in patients with silicosis than that of healthy controls. Furthermore, RNA-Seq findings were confirmed using quantitative polymerase chain reaction and revealed that NRF2-regulated DEGs were associated with glutathione metabolism, transforming growth factor-β, and the extracellular matrix receptor interaction signaling pathway in PBMCs from patients with silicosis. The top 10 hub genes were identified by PPI analysis: SMAD2, MAPK3, THBS1, SMAD3, ITGB3, integrin alpha-V (ITGAV), von Willebrand factor (VWF), BMP4, CD44, and SMAD7. Conclusions These findings suggest that NRF2 signaling regulates the lymphocyte oxidative stress state and may contribute to fibrogenic responses in human PBMCs. Therefore, NRF2 might serve as a novel preventive and therapeutic candidate for silicosis.

Remote sensing images have been widely applied in various industries; nevertheless, the resolution of such images is relatively low. Panchromatic sharpening (pan-sharpening) is a research focus in the image fusion domain of remote sensing. Pan-sharpening is used to generate high-resolution multispectral (HRMS) images making full use of low-resolution multispectral (LRMS) images and panchromatic (PAN) images. Traditional pan-sharpening has the problems of spectral distortion, ringing effect, and low resolution. The convolutional neural network (CNN) is gradually applied to pan-sharpening. Aiming at the aforementioned problems, we propose a distributed fusion framework based on residual CNN (RCNN), namely, RDFNet, which realizes the data fusion of three channels. It can make the most of the spectral information and spatial information of LRMS and PAN images. The proposed fusion network employs a distributed fusion architecture to make the best of the fusion outcome of the previous step in the fusion channel, so that the subsequent fusion acquires much more spectral and spatial information. Moreover, two feature extraction channels are used to extract the features of MS and PAN images respectively, using the residual module, and features of different scales are used for the fusion channel. In this way, spectral distortion and spatial information loss are reduced. Employing data from four different satellites to compare the proposed RDFNet, the results of the experiment show that the proposed RDFNet has superior performance in improving spatial resolution and preserving spectral information, and has good robustness and generalization in improving the fusion quality.

Background Averrhoa carambola L. is a traditional medicinal herb that has long been used to treat diabetes. Our previous studies found that 2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione (DMDD) isolated from A. carambola L. roots could ameliorate diabetic nephropathy (DN), but its exact mechanism remains unclear. Methods A DN model was established by streptozotocin (STZ, 100 mg/kg body weight) in TLR4 knockout (TLR4-/-, KO) mice and wild-type (WT) mice. Body weight and blood glucose were evaluated after oral administration of DMDD (12.5, 25, 50 mg/kg body weight/d) in diabetic mice. The levels of serum lipids, including TC, TG, HDL, and LDL and kidney function indexes Scr and BUN, were detected by biochemical equipment. The levels of inflammatory cytokines including IL-6 and TNF-α, were determined by ELISA kits. Furthermore, changes in renal ultrastructure were observed by electron microscopy. Western blot analysis and RT-PCR were used to assess the protein expression and mRNA levels of TLR4, MyD88 and NF-κB. Results DMDD treatment attenuated diabetic nephropathy, as a result of a decline in blood glucose, serum creatinine, and blood urine nitrogen levels and an increase in the quantity and density of podocytes, combined with improved dyslipidaemia. DMDD treatment inhibited the inflammatory response and downregulated the expression of the TLR4/MyD88/NF-κB pathway in diabetic mice, and these changes were significantly different in TLR4-/- mice. Conclusion DMDD alleviates diabetic nephropathy by mitigating kidney damage and inflammation via the inhibition of the TLR4/MyD88/NF-κB signalling pathway.

While increasing evidence suggests that ozone (O3) exposure is associated with adverse birth outcomes, only one study has focused on its impact on the premature rupture of membranes (PROM). Therefore, we thus examined the effect of O3 on PROM in Xinxiang, China, using an over-dispersed Poisson generalized additive model. Several confounding factors, including meteorological factors, temporal trends, the day of the week, and public holidays, were considered in the model. We identified a total of 3255 instances of PROM from January 1, 2015 to December 31, 2017, and there was a significant association between the daily maximum 8-h mean concentrations (O3–8h) and PROM. Each 10 μg/m3 increase in the 3-day average concentration (lag02) of O3–8h corresponded to an increment in PROM of 5.42% (95% CI: 1.45–9.39%). Although the results of the stratified analyses were insignificant, a few trending results were observed: stronger associations between O3 and PROM would occur in women with advanced age (≥35) or during the warm season than those in younger women (

Yulangsan polysaccharide (YLSPS) is derived from the root of Millettia pulchra (Benth.) Kurz var. Recent studies have postulated YLSPS as a regimen for cancer treatment. However, the underlying mechanism anti-breast cancer is still poorly unknown. The aim of this study was to examine the suppressive and apoptosis effect of YLSPS on the growth of breast cancer cell 4T1 and its possible underlying mechanism. In this study, breast cancer cell 4T1 viability and apoptosis were assessed by CCK-8 and flow cytometry, relative quantitative real-time PCR and western blot after treated with drug-serum of YLSPS. Furthermore, therapy experiments were conducted using a Balb/c mouse transplanted tumor model of breast cancer. The number of apoptotic cells and microvascular density (MVD) in the tumor tissues were assessed by TUNEL and CD34 immunostaining. Immunohistochemical assays and ELISA were used to detect the expression of VEGF, Bcl-2, Bax and Caspase-3 in the tissues. The in vitro studies showed that the drug-serum of YLSPS significantly inhibition of proliferation and effectively induced apoptosis of 4T1 cells. Oral administration of YLSPS in the breast cancer models significantly reduced the tumor volume and weight. The enhanced antitumor efficacy was associated with decreased angiogenesis, an enhanced antioxidant capacity, an increased induction of apoptosis and an inhibition of lung metastasis. These findings indicate that YLSPS significantly inhibited mouse breast cancer growth in vitro and in vivo. These data suggest that YLSPS may serve as a potential therapeutic agent for breast cancer.

Nowadays, intelligent surveillance has received extensive attention from academia, business, and industry. Deep learning algorithms are widely used in the field of intelligent surveillance. Recently, most deep learning models are limited to a short-term behavior recognition in the entire video. In order to better identify human behavior in the video, we combined a Two-stream network and a Temporal Relation network (TRN) and added a time pyramid pooling operation. In this way, the Two-Stream Temporal Relation-Time Pyramid Pooling Network (TTR-TPPN) can be constructed. The relational pyramid pool network integrated the frame-level features in the video into video-level features. We applied the TTR-TPPN to the Internet public standard data set UCF101 and the self-made DW20 data set. It is found through experiments that this network has a higher recognition rate than other behavior recognition methods on both data sets, and it has better performance in long-term behavior recognition. Therefore, the TTR-TPPN enables it to recognize long-time sequence behavior and improves the accuracy of human behavior recognition.

In the process of image generation or transmission, the image quality is often degraded due to the interference and influence of speckle noise, which will adversely affect the subsequent image processing. However, most of the existing Optical Coherence Tomography (OCT) image denoising methods usually only use part of the prior information of the OCT image, and ignore the changes in the texture and structure of the OCT image. There is often a problem that the network is too deep and the calculation complexity is too large. Aiming at this shortcoming, this paper proposes an improved deep convolutional neural network image denoising algorithm based on the original DenseNet algorithm idea. First, by constructing a speckle noise image data set, a series of preprocessing is performed on the input image data set, then the visual statistical feature map of the image is extracted, and finally the DenseNet network structure is improved for network training. The experimental results show that the improved DenseNet has better performance no matter compared with BM3D, which is recognized as the best denoising algorithm in the field of image denoising, or compared with DnCNN, an advanced image denoising algorithm in the field of deep learning.

The heating furnace is an essential oilfield facility for surface gathering, treatment, and transportation, so the energy consumption level of an oilfield is directly affected by its operational efficiency. In this paper, the thermal efficiency, exhaust gas temperature, external surface temperature, excess air coefficient, and load rate of a heating furnace are taken as energy efficiency evaluation indexes. By improving game theory, the objective and subjective weights are combined to determine the final weights of each index. On this basis, the grey TOPSIS method is used to establish the energy efficiency evaluation model of an oilfield heating furnace, which is to comprehensively evaluate the energy consumption of the heating furnace by calculating the closeness degree between its actual and ideal operational states. Finally, the effectiveness of the energy efficiency evaluation model is verified by taking an actual oilfield as an example, the results show that the weight sequence of the indexes is thermal efficiency, exhaust gas temperature, external surface temperature, load rate, and excess air coefficient. In addition, the relative closeness of the heating furnace is mostly concentrated between 0.5 and 0.7, which shows that the efficiency is low. The weak link of energy consumption is analyzed, and the corresponding improvement measures are put forward.

Background Associations between ambient air pollution and child health outcomes have been well documented in developed countries such as the United States; however, only a limited number of studies have been conducted in developing countries. This study aimed to explore the acute effects of five ambient air pollutants (inhalable particles [PM10], fine particles [PM2.5], sulfur dioxide [SO2], nitrogen dioxide [NO2] and 0zone [O3]) on children hospital outpatients with respiratory diseases in Shijiazhuang, China. Methods Three years (2013–2015) of daily data, including cause-specific respiratory outpatient records and the concentrations of five air pollutants, were collected to examine the short-term association between air pollution and children’s respiratory diseases; using a quasi-Poisson regression generalized additive model. Stratified analyses by season and age were also performed. Results From 2013 to 2015, a total of 551,678 hospital outpatient records for children with respiratory diseases were collected in Shijiazhuang, China. A 10 μg/m3 increase in a two-day average concentration (lag01) of NO2, PM2.5, and SO2 corresponded to an increase of 0.66% (95% confidence interval [CI]: 0.30–1.03%), 0.13% (95% CI: 0.02–0.24%), and 0.33% (95% CI: 0.10–0.56%) in daily hospital outpatient visits for children with respiratory diseases, respectively. The effects were stronger in the transition season (April, May, September and October) than in other seasons (the hot season [June to August] and the cool season [November to March]). Furthermore, results indicated a generally stronger association in older (7–14 years of age) than younger children (

Background Bone mineral density (BMD) has been positively associated with lung function in patients diagnosed with respiratory diseases such as chronic obstructive pulmonary disease (COPD) and cystic fibrosis. However, the relationship between BMD and lung function is inconsistent in the general population. Methods To investigate the association between BMD and lung function in a Chinese general population, a total of 1024 adults aged 40–70 years old from Qiliying (an industrial polluted exposure area) and Langgongmiao (the reference area with non-industrial pollution) were recruited and underwent BMD and spirometry tests. Results Both BMD and lung function levels were lower in the exposed area compared to the reference area. In addition, BMD and lung function levels were also lower in females compared to males. Both Spearman and partial correlation analyses showed that BMD was positively correlated with FVC and FEV1. After adjusting linear regression analyses for potential confounding factors, every 0.1 g/cm2 drop in BMD was associated with 53.0 mL decrease in FVC and 33.5 mL decrease in FEV1. Conclusions A reduction of BMD is associated with lower lung function in a general population from China.

Flow mixing has always been of particular interest for chemical engineering, combustion, and energy industries as well as other related engineering applications. Mixing always plays a crucial role because of its ability to uniformly distribute the passive scalar in the flow field without dynamic influences to the flow field itself. This paper reviews studies which quantitatively evaluated passive scalar mixing in various engineering applications. On the one hand, passive scalar mixing in turbulence has been reviewed from the aspect of energy spectrum cascades and small temporal-spatial scale analysis, mixing time, unmixedness, mixing time-scale ratio, and relative mixing intensity ratio using DNS. Secondly, several different concepts (percentage mixing, mixing intensity and degree of mixing) to quantify the flow mixing in microfluidic systems were introduced and compared thoroughly, and it is believed that these methods can be extended to other macro fluid engineering systems. Furthermore, a CFD-based approach using the statistics of temporal and spatial distribution of fluid particles was reviewed, but cannot be extended to engineering applications with special requirements of mixing time.

A tube-core sandwich panel was designed to serve as anti-blast panel of blast resistant walls. Steel tubes are non-expensive and strong for anti-blast walls, and can be easily connected with face sheets through welding. Static three-point bending experiments, close-in explosion experiments and contact explosion experiments were performed to explore its anti-blast ability. The tough interface and shear-resistant tube-core endow the panel with high bending rigidity. In close-in explosion, the front face mitigates the shock wave corrugations through corrugated plastic deformation and the panel is rigid enough to resist the shock wave. In contact explosion, the panel attenuates the shock wave through tube-crushing and skin-tearing. Appropriate thicknesses of the front face and the tube wall promote energy absorption. The experiments indicate that spaced tube-core panel is the better choice for close-in explosions while connected tube-core panel has advantages under contact explosions.

Under the background of global energy crisis and environmental pollution, the concept of Energy Internet (EI) has attracted widespread attentions from both industry and academia. Energy hub (EH) is the critical component in EI, which can act as a dual-port network node coupling electricity, natural gas and heating in an integrated energy system. This paper presents a model for an EH to couple the electricity and natural gas network. The proposed EH system consists of the distributed combined heat and power (CHP), gas furnace, energy storage device and wind turbine (WT). The corresponding model and operational constraint of these elements are fully established, in particular the energy loss and degradation cost of electrical and heat energy storages are modeled in detail. Besides, the optimal management of the developed EH system with considering the demand response programs (DRP) is formulated as a Mixed Integer Nonlinear Programming (MINLP) problem, which is addressed by CPLEX solver under YALMIP. The results verify the capability of the proposed model under different scenarios.

Objective: Diabetic kidney disease (DKD) is the leading cause of death and disability of diabetes mellitus. However, there is still a lack of specific drugs for the treatment of DKD. Objective: The chief aim of this research is to investigate the role and mechanism of DMDD for DKD. Methods: Wild type and TLR4 knockout mice were induced to diabetes. After 4-week treatment with DMDD, blood sugar, renal function, blood lipid and pathological changes were assessed. Real-time PCR, western blotting, and immunohistochemistry were employed to detect the expressions of TLR4, TGFβ1 and Smad2/3 in the renal tissue. Results: DMDD improved the serum lipid and decreased fasting blood glucose levels in diabetic mice. CysC and urinary albumin levels increased markedly in the diabetic group, and they were obviously decreased after 4 weeks of DMDD treatment. Compared with the WT diabetic mice, the urinary albumin and CysC in the TLR4-/- mice were expressed at lower levels. HE and Masson's staining revealed that DMDD clearly ameliorated pathological changes and renal fibrosis. When TLR4 gene was knock out, the pathological was improved. Mechanistically, TLR4, TGF-β1 and Smad2/3 were obvious up-regulation in the renal tissues of diabetic mice. The expressions of these proteins were significantly down-regulated after DMDD treatment (p< 0.05). In the TLR4-/- mice, mRNA and protein levels of TGF-β1 and Smad2/3 were obviously lower than those in the WT mice. In addition, IHC revealed that a strong in situ expressions of TLR4, TGF-β1 and Smad2/3 were seen in the kidney tissues of diabetic mice, which were distinctly weakened in the DMDD-treated mice. In the TLR4-/- mice, however, expressions of TGF-β1 and Smad2/3 were not remarkable increase in the diabetic mice compared with normal mice. Conclusions: These results strongly indicate that TLR4 is essential for DMDD protection against renal dysfunction in diabetic mice. Its hypoglycemic and anti-fibrosis effects were likely mediated by inhibiting of the TLR4/TGFβ signaling pathway, and the downregulation of Smads in the renal interstitium. Funding Statement: This research was supported by the National Natural Science Foundation of China (No. 81760665, 81460205), and Guangxi Natural Science Foundation under Grant No. 2017GXNSFBA198177. In addition, this project was financially supported by the project of improving the basic ability of young teachers in colleges and universities in Guangxi (KY2016YB098). Declaration of Interests: The authors declare no conflicts of interest in this work. Ethics Approval Statement: All experimental procedures were approved by the Institutional Animal Care and Use Committee of Guangxi Medical University.

Demand response (DR) has become an effective and critical method for obtaining better savings on energy consumption and cost. Buildings are the potential demand response resource since they contribute nearly 50% of the electricity usage. Currently, more DR applications for buildings were rule-based or utilized a simplified physical model. These methods may not fully embody the interaction among various features in the building. Based on the tree model, this paper presents a novel model based control with a random forest (MBCRF) learning algorithm for the demand response of commercial buildings. The baseline load of demand response and optimal control strategies are solved to respond to the DR request signals during peak load periods. Energy cost saving of the building is achieved and occupant’s thermal comfort is guaranteed simultaneously. A linguistic if-then rules-based optimal feature selection framework is also utilized to redefine the training and test set. Numerical testing results of the Pennsylvania-Jersey-Maryland (PJM) electricity market and Research and Support Facility (RSF) building show that the load forecasting error is as low as 1.28%. The peak load reduction is up to 40 kW, which achieves a 15% curtailment and outperforms rule-based DR by 5.6%.

Coordinating integrated energy system and clean energy sources, particularly wind energy, is deemed as a desirable means to alleviate the energy and environmental crisis. However, the nature of uncertainty and intermittency of wind energy is imperative to be considered for the stable operation of the system. The gas-fired generation units with fast start-up and high ramp-rate can deepen the coupling of multiple energy sources and increase system flexibility to deal with uncertainties. This paper proposes a novel day-ahead scheduling for the district integrated natural gas and power system (DIGPS) at the presence of severe uncertainty caused by high wind power penetration. A linear and flexible energy flow equation is presented to build the energy conversion and coupling of the proposed DIGPS. Moreover, information gap decision theory (IGDT) is employed to better depict the inherent uncertainty of wind power output. Two different decisions including risk averse and opportunity seeker strategies are formulated to implement the co-optimization operation of the DIGPS. Also, compressed air energy storage (CAES) and demand response program (DRP) are introduced to reduce system operation costs and the impact of wind power uncertainty. An illustrative example and a modified IEEE 33-bus distribution system are tested to demonstrate the performance of the proposed model. Numerical testing results show that the total cost has reduced 3.63% with considering DRP. Besides, compared with stochastic programming and error-based interval forecasting method, the proposed IGDT approach can obtain cost reductions of 3% and 14%, respectively. The calculation time has been reduced by 91% in comparison with stochastic programming.

The application of smart substation technology has brought many opportunities to the power industry, but also caused many new problems and challenges. At present, with the large-scale promotion of intelligent substation based on IEC61850, there are many engineering problems which will not appear in IEC61850 protocol and are closely related to practical application. A device for online detection of electrical error is designed in the paper for the measurement deviation problem of “IEC61850-9-2 input digital power meter” in the new generation of intelligent substation. The characteristic of the device is that once the meter measurement error is detected within the set time interval, it will record the voltage and current waveform data within the interval in real time for error analysis and problem finding.

Choroidal neovascularization (CNV), caused by new blood vessels in the choroid growing through the Bruch’s membrane, is an important manifestation of terminal age-related macular degeneration (AMD). Automated CNV detection in three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) images is still a huge challenge. This paper presents an automated CNV detection method based on object tracking strategy for time series SD-OCT volumetric images. In our proposed scheme, experts only need to manually calibrate CNV lesion area for the first moment of each patient, and then the CNV of the following moments will be automatically detected. In order to fully represent space consistency of CNV, a 3D-histogram of oriented gradient (3D-HOG) feature is constructed for the generation of random forest model. Finally, the similarity between training and testing samples is measured for model updating. The experiments on 258 SD-OCT cubes from 12 eyes in 12 patients with CNV demonstrate that our results have a high correlation with the manual segmentations. The average of correlation coefficients and overlap ratio for CNV projection area are 0.907 and 83.96%, respectively.

Geographic atrophy (GA), mainly characterized by atrophy of the retinal pigment epithelium (RPE), is an advanced form of age-related macular degeneration (AMD) which will lead to vision loss. Automated and robust GA segmentation in three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) images is still an enormous challenge. This paper presents an automated and robust GA segmentation method based on object tracking strategy for time series SD-OCT volumetric images. Considering the sheer volume of data, it is unrealistic for experts to segment GA lesion region manually. However, in our proposed scenario, experts only need to manually calibrate GA lesion area for the first moment of each patient, and then the GA of the following moments will be automatically detected. In order to fully embody the outstanding features of GA, a new sample construction method is proposed for more effectively extracting histogram of oriented gradient (HOG) features to generate random forest models. The experiments on SD-OCT cubes from 10 eyes in 7 patients with GA demonstrate that our results have a high correlation with the manual segmentations. The average of correlation coefficients and overlap ratio for GA projection area are 0.9881 and 82.62%, respectively.

Blood oxygen saturation is an important physiological parameter involved in respiration and circulation, which is also a critical indicator in the area of medical and health monitoring. Wearable non-invasive blood oxygen saturation monitoring approaches overcomes the shortcomings of the traditional approaches, and reflects the tendency to change of breathing function in real time, which has great advantages for monitoring at home. Thanks to the Internet of Things and advanced signal processing algorithms, we have developed wearable pulse oximeters. These devices are able to detect users' physiological data such as blood oxygen saturation (SpO2), pulse rate (PR), and perfusion index (PI). These data can then be transmitted to an APP for intelligent mobile devices. Then, the data could be uploaded to a server to generate a report. Accordingly medical personnel will know patients' medical condition. Finally, the accuracy of the device has been verified by the experiment conducted on the simulator.

Pyronaridine and artesunate have been shown to be effective in falciparum malaria treatment. However, pyronaridine is rarely used in Hainan Island clinically, and artesunate is not widely used as a therapeutic agent. Instead, conventional antimalarial drugs, chloroquine and piperaquine, are used, explaining the emergence of chloroquine-resistant Plasmodium falciparum. In this article, we investigated the sensitivity of P. falciparum to antimalarial drugs used in Hainan Island for rational drug therapy. We performed in vivo (28 days) and in vitro tests to determine the sensitivity of P. falciparum to antimalarial drugs. Total 46 patients with falciparum malaria were treated with dihydroartemisinin/piperaquine phosphate (DUO-COTECXIN) and followed up for 28 day. The cure rate was 97.8%. The mean fever clearance time (22.5±10.6 hr) and the mean parasite clearance time (27.3±12.2 hr) showed no statistical significance with different genders, ages, temperatures, or parasite density (P>0.05). The resistance rates of chloroquine, piperaquine, pyronarididine, and artesunate detected in vitro were 71.9%, 40.6%, 12.5%, and 0%, respectively (P piperaquine>pyronarididine>artesunate. The inhibitory dose 50 (IC50) was 3.77×10-6 mol/L, 2.09×10-6 mol/L, 0.09×10-6 mol/L, and 0.05×10-6 mol/L, and the mean concentrations for complete inhibition (CIMC) of schizont formation were 5.60×10-6 mol/L, 9.26×10-6 mol/L, 0.55×10-6 mol/L, and 0.07×10-6 mol/L, respectively. Dihydroartemisinin showed a strong therapeutic effect against falciparum malaria with a low toxicity.

The aim of the present study was to explore the associations of genetic variants in the ADAM33 and TGF-β1 genes with the risk of childhood asthma. A total of 299 asthmatic children and 311 healthy controls were recruited in the hospital-based case-control study. The asthmatic subjects were further divided into mild and severe groups according to disease severity. Single-nucleotide polymorphisms (SNP) at ADAM33 V4, T2, S2 and T1, and TGF-β1 C-509T and T869C were selected and detected with PCR-RFLP. The associations of the SNPs with asthma risk and severity were analyzed. The associations between the haplotypes of ADAM33 and TGF-β1 were also evaluated. Compared with the GG genotype, the GC and CC genotypes at V4 were associated with an increased asthma risk in children and the ORs were 2.92 and 10.56, respectively. Compared with the CC genotype, the CT/TT genotype at C-509T was associated with an increased asthma risk and the OR was 2.26. Subsequent to stratification by asthma severity, compared with the V4 GG genotype, it was found that the CG and CC genotypes were associated with a mild asthma risk and the ORs were 3.00 and 5.99, respectively. The SNP at C-509T (CT/TT vs. CC) was associated with mild asthma (OR=2.34), whereas a marginally significant association was detected between the SNP (CT/TT vs. CC) and severe asthma risk (OR=2.19). The haplotype analysis revealed that, compared with the GGCA haplotype of ADAM33, significant associations of the haplotypes of CGCG, CGGA, GACA, GACG and GAGA with asthma risk were observed, and the ORs were 31.12, 12.24, 4.73, 30.85 and 4.83, respectively. No significant association was detected between the TGF-β1 haplotypes and asthma risk. The genetic variants at V4 and C-509T had the potential to modify the childhood asthma risk and the associations showed no notable difference with the disease severity. Thus, ADAM33 haplotypes provided more useful information in the prediction of asthma risk.

CIP2A is a human oncoprotein that inhibits PP2A and stabilizes c-myc in human malignancies. Autoantibodies to CIP2A protein have been reported to be present in higher levels in sera from patients with hepatocellular carcinoma (HCC) than in sera of healthy individuals. The CIP2A gene has been demonstrated as a potential cancer susceptibility gene. To elucidate whether common CIP2A variants are associated with HCC susceptibility, we conducted a case-control study comprising 233 cases of HCC and 280 controls matched on age, gender and ethnicity in the Chinese Han population. Two haplotype-tagging single nucleotide polymorphisms (htSNPs) (rs2278911 and rs4855656) from the HapMap database were analyzed, which provide an almost complete coverage of the genetic variations in the CIP2A gene. We found that neither of these htSNPs and haplotypes were associated with the risk of HCC. However, an interaction was observed between hepatitis virus B and C infection (HBV and HCV) and the C carriers (TC or CC) of rs2278911 on HCC risk (OR=12.35; 95% CI, 4.93–19.87). No such association was found for rs4855656. Our study also demonstrated that two htSNPs (rs2278911 and rs4855656) in the CIP2A gene are not associated with the risk of HCC. HBV and HCV infection was found to exert a synergistic effect on the risk of HCC in individuals with the C carriers (TC or CC) of rs2278911 in the Chinese Han population.

In this paper and based on the linear potential theory of a fluid and an analogical approach, a supplementary, (complete) exact solution of an equivalent model is developed for a sloshing fluid in a rectangular tank and is compared with the existing solutions given by Graham and Rodriguez, Housner and a semi-analytical/numerical method. The results indicate that Graham and Rodriguez did not provide the correct location expressions for the convective masses. The expressions for the impulsive mass and its position given by Housner are not completely satisfactory approximations of the exact solutions. The solution in this paper can be an exact formulation to supplement the famous, traditional formulations given by Graham and Rodriguez as well as Housner.

In this paper, a full-scale 3-D finite element model of the Jundushan cable-stayed aqueduct bridge is established with ANSYS Code. The shell, fluid, tension-only spar and beam elements are used for modeling the aqueduct deck, filled water, cables and support towers, respectively. A multi-element cable formulation is introduced to simulate the cable vibration. The dry (without water) and wet (with water) modes of the aqueduct bridge are both extracted and investigated in detail. The dry modes of the aqueduct bridge are basically similar to those of highway cable-stayed bridges. A dry mode may correspond to two types of wet modes, which are called the in-phase (with lower frequency) and out-of-phase (with higher frequency) modes. When the water-structure system vibrates in the in-phase/out-of-phase modes, the aqueduct deck moves and water sloshes in the same/opposite phase-angle, and the sloshing water may take different surface-wave modes. The wet modes of the system reflect the properties of interaction among the deck, towers, cables and water. The in-phase wet frequency generally decreases as the water depth increases, and the out-of-phase wet frequency may increase or decrease as the water depth increases.

SUMMARY This paper reports on a semi-analytical/numerical method to model sloshing water in an arbitrarily shaped aqueduct. The water motion is assumed to be inviscid, compressible, and linear (small displacement). The transverse sloshing fluid in an aqueduct is equivalently simplified as a fixed rigid mass M0 and a mass–spring system (M1, K1). According to a rule that the actual fluid (computed with finite element model) and its equivalent mechanical model have the same first sloshing frequency and acting effects on the aqueduct, the analytical solutions of the fixed (impulsive) mass M0, sloshing (convective) massM1, spring stiffness K1, and their locations in the aqueduct body are acquired by the least squares (curve fitting) algorithm. Applying this equivalent principle, the equivalent mechanical models are respectively obtained for the sloshing water in rectangular, semicircular, U-shaped, and trapezoid aqueducts. The equivalent principle and fluid models are validated through comparison investigations involving rectangular and U-shaped aqueducts. The dynamic properties and seismic responses of the original and equivalent systems are simulated, compared, and discussed for a U-shaped aqueduct bridge. The main purpose of this paper is to provide a simplified model of sloshing fluid for the seismic/wind-resistant computation of the support structures of the aqueduct bridge. Copyright © 2011 John Wiley & Sons, Ltd.

Considering the development of cooperative design and internet-based manufacturing and in order to manage the manufacturing process more efficiently, a unit of remote intelligent fault-diagnosis based on Bayesian Networks was designed and a software based on internet was realized. The establishment of such system will enable efficient cooperation between CNC machine tools and users as well as maintainers.

By the theories of potential flow and structural vibration, the formulae for evaluating the ‘wet’ (with water) frequencies and mode shapes of the beam-supported aqueduct are derived through a simplified fluid-structure interaction analysis. The time-history formulae of structural responses to the vertical seismic excitation are obtained. Applying the response-spectrum principle, the equivalent vertical earthquake load exerted on the beam and the corresponding effects are also derived. Several illustrative examples are conducted. The analytical results show that: (i) The ‘wet’ frequencies of the structure are lower than the corresponding ‘dry’ (without water) frequencies due to the participating water mass, but the ‘wet’ mode shapes are identical to the corresponding ‘dry’ ones. (ii) The water mass plays an important role in the vertical seismic response, which varies with the different geological sites. For the different seismic inputs, the deeper the water is, the greater are the structural responses. (iii) The vertical seismic effects on the beam are generally not too small to be neglected and should be considered in the structural designs of a beam-supported aqueduct. Copyright © 2002 John Wiley & Sons, Ltd.

Supplemental Digital Content is available in the text, Background: Accumulating studies have reported inconsistent association between ErbB4 single nucleotide polymorphisms (SNPs) and predisposition to schizophrenia. To better interpret this issue, here we conducted a meta-analysis using published case-control studies. Methods: We conducted a systematic search of MEDLINE (Pubmed), Embase (Ovid), Web of Science (Thomson-Reuters) to identify relevant references. The association between ErbB4 SNPs and schizophrenia was assessed by odds ratios (ORs) and 95% confidence intervals (CIs). Between-study heterogeneity was evaluated by I squared (I2) statistics and Cochran's Q test. To appraise the stability of results, we employed sensitivity analysis by omitting 1 single study each time. To assess the potential publication bias, we conducted trim and fill analysis. Results: Seven studies published in English comprising 3162 cases and 4264 controls were included in this meta-analysis. Meta-analyses showed that rs707284 is statistically significantly associated with schizophrenia susceptibility among Asian and Caucasian populations under the allelic model (OR = 0.91, 95% CI: 0.83–0.99, P = 0.035). Additionally, a marginal association (P

Curcumin has been proven to effectively inhibit tumor growth by both targeting tumor cells and angiogenesis; however, poor water solubility limits further clinical application. In the present study, we prepared water-soluble liposomal curcumin to investigate its anti-tumor effects and the underlying mechanism. The MTT assay was used to test the anti-proliferative activities for the MS1 murine endothelial and LL/2 Lewis lung cancer cell lines. Apoptosis and cell cycle arrest induced by liposomal curcumin were analysed by flow cytometry. Anti-angiogenic agents and the resulting anti-tumor effects were investigated in a murine lung cancer model. Zebrafish were used to investigate the anti-angiogenic effect of liposomal curcumin in the development of embryos. In vitro, liposomal curcumin inhibited the proliferation of MS1 cells and induced cell cycle arrest and apoptosis. Notably, LL/2 cells showed less sensitivity to the liposomal curcumin in vitro. In vivo, the systemic administration of liposomal curcumin resulted in significant inhibition of tumor growth. CD31 immunohistochemical analysis and alginate encapsulation assay revealed that angiogenesis was decreased by liposomal curcumin treatment. Angiogenesis was also suppressed in the development of zebrafish. Liposomal curcumin showed potent inhibitory activity against murine endothelial cells but not lung cancer cells. Liposomal curcumin treatment is capable of significantly inhibiting tumor growth in vivo, a process that may depend primarily on its anti-angiogenic effects. Our study also indicates that liposomal curcumin may be developed not only for cancer therapy, but also for the treatment of other angiogenesis-related diseases.

The photovoltaic (PV) panel produces the maximum power as the incident angle of sunlight is 90°. In this paper, two-axis sun-tracking system keeps PV panel perpendicular to sun light by absolute and relative position sensors signal analysis. It is composed of micro-controller, solar illumination sensor, solar position sensors, stepper motors and drivers, two-axis motion mechanism, zero position switches, limit switches and solar system.

The comprehensive analysis of urban public transport has an important role in promoting the development of urban public transport. Based on the characteristics of urban public transport, following the principles of scientific, integrity, independence and operational, this paper built a comprehensive analysis index system for urban public transport, then the comprehensive evaluation method based on the support vector machine (SVM) is brought out trying to analyze the urban public transport of comprehensive after the index system is established. And then, a case study is executed by taking 20 cities in Hebei province in China as an example. The research results reveal that the method can efficiently evaluate comprehensively to the urban public transport of comprehensive. Thus it could be useful for the government to make relevant policies to improve the operational performance for public transport. In the end, some policy advices are given.

The purpose of this study was to test the associations about Helicobacter pylori infection and polymorphisms of IL-1B -31/-511 and IL-1RN VNTR polymorphism with gastric cancer in cases’ and controls’ family members from the areas of high cancer prevalence in China. IL-1B -511T and IL-1RN ∗2 were associated with risks of gastric cancer. The association strength reduced with the relative degree decreasing. Such association was not found in the polymorphisms of IL-1B -31. But the haplotype analysis of IL-1B -511 and IL-1B -31 genotype could enhance the risks of gastric cancer. The positive H. pylori status could increase the risks of IL-1B to gastric cancer.

Publisher Summary This chapter analyzes a tall-pier aqueduct that is simplified as a coupled system of tall pier and rectangular tank. The basic motion equations of structure and fluid are used to analyze the transverse dynamic characteristics and seismic responses of the coupled system. The aqueduct body is assumed as a rectangular cross-section with two rigid walls, where the stationary liquid depth is H, width is 2a, and length is b. The tall pier is assumed to be fixed on the rigid ground. The computational model is finally simplified as a coupled system of tall pier and rectangular tank. The fluid is assumed to be inviscid, incompressible, and irrotational. The governing equations of fluid motion under small translational excitation of the aqueduct body can be expressed in terms of the relative Cartesian coordinates (x, z). This chapter concludes with the discussion of seismic responses and dynamic characteristics of the system.

Background In the island of Hainan, the great majority of malaria cases occur in mountain worker populations. Using the behavioral change communication (BCC) strategy, an interventional study was conducted to promote mountain worker malaria prevention at a test site. This study found the methods and measures that are suitable for malaria prevention among mountain worker populations. Methods During the Plasmodium falciparum elimination stage in Hainan, a representative sampling method was used to establish testing and control sites in areas of Hainan that were both affected by malaria and had a relatively high density of mountain workers. Two different methods were used: a BCC strategy and a conventional strategy as a control. Before and after the intervention, house visits, core group discussions, and structural surveys were utilized to collect qualitative and quantitative data regarding mountain worker populations (including knowledge, attitudes, and practices [KAPs]; infection status; and serological data), and these data from the testing and control areas were compared to evaluate the effectiveness of BCC strategies in the prevention of malaria. Results In the BCC malaria prevention strategy testing areas, the accuracy rates of malaria-related KAP were significantly improved among mountain worker populations. The accuracy rates in the 3 aspects of malaria-related KAP increased from 37.73%, 37.00%, and 43.04% to 89.01%, 91.53%, and 92.25%, respectively. The changes in all 3 aspects of KAP were statistically significant (p 0.05). Furthermore, in the testing areas, both the percentage testing positive in the serum malaria indirect fluorescent antibody test (IFAT) and the number of people inflicted decreased more significantly than in the control sites (p