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Radiation enteritis is one of the most common side effects of ionizing radiation in patients with pelvic cancers. Increasing amounts of evidence indicate that pro-inflammatory responses significantly contribute to the development of radiation enteritis. In this study, we investigated the association between T regulatory (Treg) cells and the risk of developing radiation enteritis in cervical cancer patients. The following observations were made. First, the frequencies of CD25hiFoxp3+ Treg cells were significantly lower in patients with radiation enteritis than in both healthy subjects and cervical cancer patients without radiation enteritis. Also, patients with the more severe grade 3 enteritis presented significantly lower Treg levels than patients with the more common grade 1 enteritis. Second, the expression of several molecules associated with Treg function, including CTLA-4, IL-10, TGF-β, and perforin, was significantly lower in patients with radiation enteritis than in healthy subjects. In patients without radiation enteritis, however, only CTLA-4, but not other Treg-associated suppressive molecules, was reduced in Treg cells. Third, Treg cells can markedly suppress CD8 T cell proliferation, but in patients with radiation enteritis, this function of Treg cells was significantly impaired, in a manner that was associated with lower CTLA-4 expression. Overall, these data suggest that the frequency and function of Treg cells is negatively associated with the risk of developing enteritis following radiation. In clinical practice, the characteristics of Treg cells may be considered to evaluate the risk of developing enteritis if the cancer patient is receiving ionizing radiation.

HBV DNA can be reduced using antiviral drugs in patients with chronic hepatitis B (CHB); however, the rate of HBeAg seroconversion remains low. A clinical trial was conducted to assess the efficacy and safety of a de novo designed liposome-based nanoparticle lipopeptide vaccine, εPA-44, for CHB.A two-stage phase 2 trial, which included a 76-week, randomized, double-blind, placebo-controlled trial (stage 1) and a 68-week open-label extension (stage 2), was conducted in 15 centers across China (Clinicaltrials.gov No. NCT00869778). In stage 1, 360 human leukocyte antigen A2 (HLA-A2)-positive and HBeAg-positive patients were randomly and equally distributed to receive six subcutaneous injections of 600 µg or 900 µg εPA-44 or placebo at week 0, 4, 8, 12, 20, and 28. In stage 2, 183 patients received extended 900 µg εPA-44, and 26 patients were observed for relapse without further treatment. The primary endpoint was the percentage of patients with HBeAg seroconversion at week 76. At week 76, patients receiving 900 µg εPA-44 achieved significantly higher HBeAg seroconversion rate (38.8%) versus placebo (20.2%) (95% CI, 6.9-29.6%; p = 0.002). With a combined endpoint of HBeAg seroconversion, alanine aminotransferase normalization and HBV DNA2,000 IU/mL, both 900 µg (18.1%) and 600 µg (14.3%), resulted in significantly higher rate versus placebo (5.0%) (p = 0.002 and p = 0.02, respectively) at week 76. In stage 2, none (0 of 20) of 900 µg εPA-44-treated patients experienced serologic relapse. The safety profile of εPA-44 was comparable to that of placebo.Among HLA-A2-positive patients with progressive CHB, a finite duration of 900 µg εPA-44 monotherapy resulted in significantly higher HBeAg seroconversion rate than placebo and sustained off-treatment effect. A phase 3 trial is ongoing (ChiCTR2100043708).

BackgroundLung adenocarcinoma, the main subtype of non-small cell lung cancer, leading one of the most aggressive and fatal causes of malignant deaths around the world. Scavenger receptor class A member 5 (SCARA5), a newly discovered tumor suppressor gene, belonged to the SR family. The present study’s object was to explore the clinical impacts of SCARA5 in lung adenocarcinoma treatment. MethodsSCARA5 expressions in 120 paired lung adenocarcinoma patients’ tissues and cell lines were detected by real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). CCK-8, EdU, flow cytometry, and western blot assays further demonstrated the significance of SCARA5 on A549 cell growth. Then, the relationships between the expression level of SCARA5 and pathological factors were analyzed. Finally, the receiver operating characteristic (ROC) curve and overall survival analysis was carried out to verify the diagnostic and prognostic significance of SCARA5 in lung adenocarcinoma. ResultsSCARA5 was prominently decreased in lung adenocarcinoma cells and tissues compared with human bronchial epithelial cells and para-carcinoma non-tumor tissues. Meanwhile, SCARA5 expression was strongly correlated with smoking (P = 0.0011), TNM stage (P < 0.0001) and lymph node metastasis (P = 0.0005). Furthermore, SCARA5 may be a crucial biomarker for lung adenocarcinoma diagnosis with an area under the curve (AUC) of 0.9102 while SCARA5 could significantly reduce overall survival (OS; P = 0.0006). In vitro experiments, we found that SCARA5 overexpressing could significantly hinder A549 cell proliferation but facilitate apoptosis through the AKT signaling pathway. Conclusions SCARA5 might be an important diagnostic and prognostic biomarker for patients with lung adenocarcinoma.

In recent years, with the vigorous development of artificial intelligence and autonomous driving technology, the importance of scene perception technology is increasing. Unsupervised deep learning based methods have demonstrated a certain level of robustness and accuracy in some challenging scenes. By inferring depth from a single input image without any ground truth label, a lot of time and resources can be saved. However, unsupervised depth estimation has defects in robustness and accuracy under complex environment which could be improved by modifying network structure and incorporating other modal information. In this paper, we propose an unsupervised, monocular depth estimation network achieving high speed and accuracy, and a learning framework with our depth estimation network to improve depth performance by incorporating transformed images across different modalities. The depth estimator is an encoder-decoder network to generate the multi-scale dense depth map. The sub-pixel convolutional layer is adopted to obtain depth super-resolution by replacing the up-sample branches. The cross-modal depth estimation using near-infrared image and RGB image enhances the performance of depth estimation than pure RGB image. The training mode is to transfer both images to the same modality and then carry out super-resolved depth estimation for each stereo camera pair. Compared with the initial results of depth estimation using only RGB images, the experiment verifies that our depth estimation network with the cross-modal fusion system designed in this paper achieves better performance on public datasets and a multi-modal dataset collected by our stereo vision sensor.

Right heart catheterization is commonly used to measure right ventricle hemodynamic parameters and is the gold standard for pulmonary arterial hypertension diagnosis; however, it is not suitable for patients’ long-term follow-up. Non-invasive echocardiography and nuclear medicine have been applied to measure right ventricle anatomy and function, but the guidelines for the usefulness of clinical parameters remain to be established. The goal of this study is to identify reliable clinical parameters of right ventricle function in pulmonary arterial hypertension patients and analyze the relationship of these clinical parameters with the disease severity of pulmonary arterial hypertension. In this study, 23 normal subjects and 23 pulmonary arterial hypertension patients were recruited from January 2015 to March 2016. Pulmonary arterial hypertension patients were classified into moderate and severe pulmonary arterial hypertension groups according to their mean pulmonary arterial pressure levels. All the subjects were subjected to physical examination, chest X-ray, 12-lead electrocardiogram, right heart catheterization, two-dimensional echocardiography, and technetium 99m (99mTc) myocardial perfusion imaging. Compared to normal subjects, the right heart catheterization indexes including right ventricle systolic pressure, right ventricle end diastolic pressure, pulmonary artery systolic pressure, pulmonary artery diastolic pressure, pulmonary vascular resistance, and right ventricle end systolic pressure increased in pulmonary arterial hypertension patients and were correlated with mean pulmonary arterial pressure levels. Echocardiography parameters, including tricuspid regurgitation peak velocity, tricuspid regurgitation pressure gradient, tricuspid annular plane systolic excursion and fractional area, right ventricle-myocardial performance index, were significantly associated with the mean pulmonary arterial pressure levels in pulmonary arterial hypertension patients. Furthermore, myocardial perfusion imaging was not observed in the normal subjects but in pulmonary arterial hypertension patients, especially severe pulmonary arterial hypertension subgroup, and showed potential diagnostic properties for pulmonary arterial hypertension. In conclusion, mean pulmonary arterial pressure levels are correlated with several right heart catheterization and echocardiography markers in pulmonary arterial hypertension patients; echocardiography and 99mTc myocardial perfusion can be used to evaluate right ventricle performance in pulmonary arterial hypertension patients. Impact statement In this study, we analyzed the clinical parameters for evaluating RV function, including right ventricle catheterization (RHC), echocardiography, and technetium 99m (99mTc) myocardial perfusion imaging (MPI) in normal Asian subjects and PAH patients ( n = 23 for each group). Our results demonstrated that six RHC indexes, four echocardiography indexes and MPI index were significantly altered in PAH patients and correlated with the levels of mean pulmonary arterial pressure. Importantly, we evaluated the diagnostic performance of MPI and found that MPI has a strong diagnostic accuracy in PAH patients. The findings from this study will be of interest to clinical investigators who make diagnosis and therapeutic strategies for PAH patients.

Stereo cameras are widely used in wearable visually impaired assistance devices (VIADs). However, the inevitable vibration, shock, and mechanical stress may make the camera pair become misaligned and cause a sharp decline in the quality of the acquired depth map, which significantly influences the performance of VIADs. In this paper, we propose an epipolar-constraint-based unconstrained self-calibration method that requires neither user involvement nor specific environment, while achieving a rotation accuracy of 0.83 mrad and a translation accuracy of 0.42 mm. Several approaches are proposed to address the image matching issues, including blurred images removal, mismatched key points removal, etc. Based on correctly matched key point pairs, a planar quadric-distribution approach is proposed to ensure the quality and consistency of the final key point group. These collection approaches ensure the reliability of key point pairs, which is the most important factor to realize high accuracy with minimum constraint. A comprehensive set of experiments demonstrates the high robustness of the proposed methods, which are suitable for VIADs. We also present a field test with blindfolded users to validate the flexibility and applicability of the approach.

Compared to RGB semantic segmentation, RGBD semantic segmentation can achieve better performance by taking depth information into consideration. However, it is still problematic for contemporary segmenters to effectively exploit RGBD information since the feature distributions of RGB and depth (D) images vary significantly in different scenes. In this paper, we propose an Attention Complementary Network (ACNet) that selectively gathers features from RGB and depth branches. The main contributions lie in the Attention Complementary Module (ACM) and the architecture with three parallel branches. More precisely, ACM is a channel attention-based module that extracts weighted features from RGB and depth branches. The architecture preserves the inference of the original RGB and depth branches, and enables the fusion branch at the same time. Based on the above structures, ACNet is capable of exploiting more high-quality features from different channels. We evaluate our model on SUN-RGBD and NYUDv2 datasets, and prove that our model outperforms state-of-the-art methods. In particular, a mIoU score of 48.3\% on NYUDv2 test set is achieved with ResNet50. We will release our source code based on PyTorch and the trained segmentation model at https://github.com/anheidelonghu/ACNet., Accepted to be published in 2019 IEEE International Conference on Image Processing (ICIP 2019), Sep 22-25, 2019, Taipei. IEEE Copyright notice added, 5 pages, 5 figures

Visually Impaired (VI) people around the world have difficulties in socializing and traveling due to the limitation of traditional assistive tools. In recent years, practical assistance systems for scene text detection and recognition allow VI people to obtain text information from surrounding scenes. However, real-world scene text features complex background, low resolution, variable fonts as well as irregular arrangement which make it difficult to achieve robust scene text detection and recognition. In this paper, a scene text recognition system to help VI people is proposed. Firstly, we propose a high-performance neural network to detect and track objects, which is applied to specific scenes to obtain Regions of Interest (ROI). In order to achieve real-time detection, a light-weight deep neural network has been built using depth-wise separable convolutions that enables the system to be integrated into mobile devices with limited computational resources. Secondly, we train the neural network using the textural features to improve the precision of text detection. Our algorithm suppresses the effects of spatial transformation (including translation, scaling, rotation as well as other geometric transformations) based on the spatial transformer networks. Open-source optical character recognition (OCR) is used to train scene texts individually to improve the accuracy of text recognition. The interactive system eventually transfers the number and distance information of inbound buses to visually impaired people. Finally, a comprehensive set of experiments on several benchmark datasets demonstrates that our algorithm has achieved an extraordinary trade-off between precision and resource usage.

Feature matching is at the base of many computer vision algorithms such as SLAM, which is a technology widely used in the area from intelligent vehicles (IV) to assistance for the visually impaired (VI). This article presents an improved detector and a novel semantic-visual descriptor, coined SORB (Semantic ORB), combining binary semantic labels and traditional ORB descriptor. Compared to the original ORB feature, the new SORB performs better in uniformity of distribution and accuracy of matching. We demonstrate it through experiments on some open source datasets and several real-world images obtained by RealSense.

Objective To observe the effect of moxibustion on learning and memory abilities, corticosterone and glucocorticoid receptor (GR) in subacute aging rats.

This paper presents an improved back propagation neural network (BPNN), which highlights a novel feature selection metrics and the combination of Genetic Algorithm (GA) and BPNN. On one hand, feature selection metrics combined deflection speed and square error (DSSE) is designed to reduce dimensionality and optimize the weights of BPNN, which is capable of decreasing the training time. On the other hand, GA is introduced to optimize the hidden layer of BPNN. Experiment results demonstrate that our proposed algorithm reduces training time of 8% and improves the accuracy of prediction of 2.5%.

This paper studies the applicability of vibro-replacement stone pile in combination of a port project in Dalian as well as heavy dynamic sounding and standard penetration test, studies the reinforcement effect of pile distance and feeding type on vibro-replacement stone and analyzes reinforcement effects of the side pile and the earth among piles. The results show: smaller pile distance will bring better pile compactness; for the vibro-replacement stone pile constructed in soft earth with undrained strength less than 20kPa with the conventional method, it is not easy to form compact pile; the reinforcement effect works only within 0.6m on the top; vibro-replacement stone pile with bottom feeding mode can form compact piles, but the pile has the interlayer which is not compact enough partially; the strength of the earth among piles fails to improve obviously before and after the stone pile is formed.

Increased lymphocyte apoptosis has been suggested to contribute to the development of systemic lupus erythematosus (SLE), but the critical factors involved in the apoptotic pathways are still unknown. By long serial analysis of gene expression (LongSAGE) profiles and microarray analyses, a novel apoptosis-related gene BclGL expression was found significantly increased in peripheral blood CD4+ T cells of SLE patients, which was correlated with the enhanced CD4+ T cells apoptosis, anti-nuclear antibody (ANA) titer and proteinuria. In vitro, BclGL expression could be specially upregulated by SLE serum stimulation and positively correlated with induced CD4+ T cell apoptosis. Enforcing BclGL overexpression by lentivirus could directly enhance CD4+ T cell apoptosis, but these apoptosis-inducing effects could be partially inhibited by knockdown of BclGL expression. Collectively, these results indicate that increased BclGL expression may contribute to the aberrant CD4+ T cell apoptosis which causes an inappropriate immune response and impaired homeostasis in SLE.

The aim of this study was to investigate the effect of a topical FK506 nanospheric suspension in a rat model of penetrating keratoplasty.FK506 nanospheres were prepared by using a biodegradable poly (lactic-co-glycolic acid) copolymer (PLGA). Its distribution in the eye and blood after a single instillation was examined in rabbits. Sprague-Dawley (SD) rats received corneal heterografts and were topically treated with phosphate-buffered saline (PBS), PLGA, FK-506 0.01% (nanospheres), or dexamethasone 0.05% solutions twice a day for 28 days. Rejection index and graft-survival time were recorded and compared between the four groups. Three grafts were collected at different time points for immunohistochemical studies.In the cornea, the FK-506 concentration reached its peak within 1 h of a single eye-drop instillation and then decreased by half (1667.85 +/- 611.87 ng/g) at 8 h. FK-506 cannot be detected in rabbit blood. There were significant differences in the graft-survival time between the FK-506 nanosphere group (15.09 +/- 4.81 days) and the other three groups [PBS (7.90 +/- 1.20, t = -4.594, P0.001), PLGA (8.44 +/- 0.88, t = - 4.074, P = 0.001) and dexamethasone (10.44 +/- 1.42, t = -2.790, P = 0.012)]. The rejected corneas in the FK506 nanosphere group showed significantly fewer CD4, CD8, CD68, CD79, vascular endothelial growth factor, ICAM, and tumor growth factor-beta(1)-positive cells than those in the other groups.FK506 0.01% nanospheric-suspension eye drops delayed the occurrence of corneal allograft rejection and prolonged allograft survival time. The FK506 nanospheres may be valuable in suppressing corneal graft rejection.

Firewall, as a mechanism of compulsory access control between the network or system, is an important means to ensure the network security. Firewall can be a very simple filter, but also it can be a carefully targeted gateway. But the principle is the same, which is monitoring and filtering all the information exchanged in internal and external networks. Linux as an open source operating system, is famous for it's stability and security.netfilter/iptables is a firewall system based on Linux which has a great function. This thesis first analysed the working principle of pintables, then introduced pintables rule set, and last proposed an effective algorithm to optimize the rules set which is implemented based on Linux system. In the part of implementation, some key code of the algorithm are given.

Signcryption has been a rapidly emerging efficient approach to achieve authenticity and confidentiality within a logic single step. However, it is still a difficult problem to realize public verifiability of signcryption in an efficient and secure way. Here, we present a generic solution to realize public verifiability based on quadratic residue.

This paper presents a lighter protocol, and it removes the multicast burdens from RSVP to adapt to unicast applications. At the same time, when RSVP is used in wireless networks, some issues about mobility raise popular concerns. The proposed protocol a lightweight mobile RSVP protocol, solves the problems by the following mechanisms: changeless flow identifier, a new state management and “refresh” mechanism.

Underwater video intelligent monitoring system extracts moving objects in a complex and dynamic scene with the impact of wave, illumination changes and reflection, while needs real-time character. To solve these situations, underwater moving object detection algorithm based on codebook model was presented. The algorithm creates a background codebook for each pixel according to color distortion and brightness distortion, and then extracts the moving objects using the current pixel to match with code words in the codebook. To adapt the complex changes of scene, the algorithm updates adaptively the background codebook model using the sample value of pixel of current image. The experiments show that the algorithm can extract the complete moving objects by overcoming the impact of underwater environment and inhibiting noise. And the algorithm has perfect real-time character.

Swimming pool is a dynamic scene with great changes. It is affected by bubbles, light intensity, wave and other factors. In this paper, a new algorithm of underwater moving target tracking is proposed. At first, building the moving target model in underwater video based on RGB histogram. Then particle filter algorithm is adopted to track moving target in view of the complex features of the swimming pool environment. Besides, updating the template adaptively in tracking in order to adapt to target's deformation and external disturbances. Simulation results show that the algorithm proposed in this paper achieves real-time and stable target tracking in the complex surroundings of swimming pool.

The high dimensional data brings dimensionality disaster problem in information fusion and pattern recognition, the similarity frequency band between feature information is clustered by the improved fuzzy clustering algorithm, the feature extraction and data dimension reduction are realized in feature distributed band respectivly. The threshold and clustering parametre are established by compactness degree and separation degree between samples, the cluster validity criterion function is given to determine the optimal clustering for samples, and finally an illustration verifies this method.

the feature extraction is key step to fault diagnosis in nonlinear circuit. An improved particle swarm optimization (PSO)algorithm are presented to competent for the identification and feature extraction problem in nonlinear circuit here. Firstly, the output response from the circuit under diagnosis will be collected and processing, some order frequency-domain kernel function under can be extracted as circuit feature for fault diagnosis. Secondly, the single feature or whole feature group of circuit can be seek by particle swarm optimization solution, the improved article swarm optimization algorithm apply to the searching for optimization solution of system identification based on frequency domain kernel of the nonlinear circuit. At last, the circuit diagnosis result will be give. The results shown: the algorithm is competent for the system identification optimization and pattern classification problem well, the diagnostic efficiency is high.

A new cascade buck-boost topology with passive lossless snubber is proposed in this paper,; it has been successfully used in PFC circuit of high voltage system. Switching losses and EMI noises are reduced by restricting di/dt of the diode reverse recovery current and dv/dt of IGBT collector-emitter voltage. The IGBT in the buck circuit operates at ZVS turn-off and ZCS turn-on. The freewheeling diode is also commutated with ZVS. An APFC prototype has been built in the laboratory to demonstrate the effects of the circuit. Power factor of this 380VAC/600W proof-of-prototype is 0.98 and less than 11% THD can be achieved.

The main research subject in this paper is swimmer detection for visual surveillance of pool. A drowning detection method based on background subtraction is presented in this paper. The consecutive sequence of visual surveillance was obtained by the fixed camera installed in the pool wall. Each pixel is described by Gaussian Mixed Model, set up self-adapted background model and updating timely. When the foreground objects was separated, for getting good results, the shadows and noises must be removed. The experiments results show that this method is effective to detect the drowners and eliminate the shadows.

In the application of ground water source heat pump technology, energy saving considerations play an important role. The main objective of the present study is to investigate the performance characteristics of a groundwater heat pump system (GWHP) on the actual operation, using the energy and exergy analysis method. The system was installed in a apartment buildings of Wuhan, China. In the duration of one year, various operating parameters of the system were monitored and the coefficient of performance (COP) values of system and chiller is determined based on a series of measurements. The exergy transports and destruction between the components of the system are determined for the average measured parameters obtained from the experimental results. Inefficient facts are found out. Lower approach temperature is effective energy saving. In addition to the energy analysis, a full exergy analysis helps to identify the components where inefficiencies occur.