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Introduction and hypothesis This study was aimed at exploring the mediating role of the prolonged second stage of labor (PSSL) in the association between delivery mode and urinary incontinence (UI) among postpartum women in Shandong, China. Methods A cross-sectional study involving postnatal women from the Women's Pelvic Floor Functional Health Center in Shandong, China, was conducted. An electronic questionnaire was used to collect the data between June 2020 and February 2021. UI was assessed using the International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form (ICIQ-UI SF). Logistic regression and multiple linear regression were employed to explore the association among delivery mode, PSSL, and UI, and the mediating role of PSSL. Results Among the total of 5,586 postpartum women included in this study, the prevalence of UI was 13.3%. Among the 742 patients with UI, the prevalence of stress urinary incontinence (78.3%) was greater than urge urinary incontinence (8.6%), mixed urinary incontinence (9.3%), and others (3.8%). After adjusting for controlling variables, delivery mode was found to be significantly associated with PSSL, whereby women with vaginal delivery were more likely to be in PSSL, and women with PSSL had a higher probability of suffering from UI. PSSL played a partial mediating effect in delivery mode and UI. Conclusions This study provided evidence that the effect of delivery mode on UI was partially mediated by PSSL among postpartum women in Shandong, China. Strategies to prevent PSSL should be actively adopted to reduce the risk of UI in women.

Emerging machine learning (ML) methodologies are widely applied in chemistry and materials science studies and are constructing a data-driven research paradigm. This review summarizes the applications of ML in rechargeable batteries from microscale to macroscale. Specifically, ML affords an emerging strategy to explore new functional for density functional theory calculations and new potentials for molecular dynamics simulations, which are expected to significantly enhance the challenging description concerning with interfaces or amorphous structures. Besides, ML possesses great potential to mine and unveil valuable information from both experimental and theoretical datasets. A quantitative "structure-function" correlation can thusly be established, the application of which includes predicting ionic conductivity of solids as well as forecasting battery lifespan. ML also exhibits great advantages in strategy optimization, such as fast-charge protocols. Lastly, an outlook on the future combination of multi-scale simulations, experiments, and ML is provided and the role of human in the data-driven research paradigm is highlighted.

Due to the lack of an efficient cold chain logistics process, China's agricultural postpartum loss has been serious for a long time, and frequent food safety accidents occur. It is of necessity to establish a quality safety management system for the agricultural product cold chain in China. From the five dimensions of man, machine, material, method, and environment (4M1E), we identify the quality risk structure of the agri-food cold chain. An evaluation system is established with the combination of the analytic hierarchy process and entropy value method. A case study demonstrates the effectiveness of the risk assessment system to help enterprises for decision-making on cold chain operations.

Flurbiprofen axetil has been proved as an alternative analgesia for postoperative pain. The aim of this study was to investigate the effects of different strategies of flurbiprofen axetil administration on postoperative pain. A total of 160 patients undergoing abdominal surgery were randomly assigned to four groups (n = 40 each): (A) 30 min before the start of surgery, the group was given 1 mg/kg flurbiprofen, then the intravenous patient-controlled analgesia (PCIA) pump contained 0.7μg/kg sufentanil, 1 mg/kg flurbiprofen axetil, 10 mg tropisetron, and 0.4 mg/kg dezocine. (B) The group received 1 mg/kg flurbiprofen axetil before surgical suture, and the PCIA pump was same as group A. (C) The group received no flurbiprofen axetil during operation, but the PCIA pump contained 1 μg/kg sufentanil, 2 mg/kg flurbiprofen axetil, 10 mg tropisetron, and 0.4 mg/kg dezocine. (D) The group was given 1 mg/kg flurbiprofen axetil at 30 min prior to the beginning of surgery and before surgical suture simultaneously, and PCIA pump was the same as group C, but flurbiprofen axetil was not used. Visual Analog Scale at rest/movement (VAS-R/M), sedation score, comfort score, and side effects were observed 48 h postoperatively. Preoperative or intraoperative intravenous flurbiprofen axetil injection decreased the VAS at 8 h, 12 h, and 24 h after surgery compared with postoperative PCIA contained flurbiprofen axetil. VAS scores at rest with intravenous flurbiprofen axetil at 30 min prior to the start of surgery were significantly decreased compared to that before surgical suture at 2 h, 8 h, and 48 h postoperatively. Flurbiprofen axetil ameliorates postoperative pain of patients with abdominal surgery, enhances analgesic effects of sufentanil, and decreases the consumption of sufentanil.

As the multi-daily electricity consumption behaviors have the strong characteristics of dynamicity, nonlinearity and locality caused by temporal manifold structure, the existing methods are difficult to fine-grained and accurately classify it. To solve this problem, this paper proposes a hierarchical classification method based on the temporal extension of the neighborhood preserving embedding algorithm (TNPE) and Bayes. The input data are multi daily-load curves of a single consumer, including power-hour-day three dimensions, which contains the full information of the user’s consumption behaviors not only in hours, but also in days. Firstly, electricity consumption behaviors are divided into routine and non-routine types by k-means clustering algorithm. Secondly, the load feature mapping matrix of different industries is extracted through the TNPE, and each TNPE model can regard as one binary classifier, so the multi-classifier is constructed through multiple TNPE models. Finally, by converting the feature similarity between samples into probabilities, a Bayesian model is established to realize which the power consumption type belongs to. The case results show that this method can effectively recognize the local dynamic features in the temporal load data, and obtain a higher classification accuracy through a smaller number of training samples.

Unlike fixed-base offshore wind turbine, the soft floating platform introduces 6 more degrees of freedom of motions to the floating offshore wind turbine. This may cause much more complex inflow environment to the wind turbine rotors compared with fixed-base wind turbine. The wind seen locally on the blade changes due to the motions of the floating wind turbine platform which has a direct impact on the aerodynamic condition on the blade such as the angle of attack and the inflow velocity. Such unsteady aerodynamic effects may lead to high fluctuation of the loads and power output. The present work aims to study the high unsteady aerodynamic performance of the floating wind turbine under platform surge motion. The unsteady aerodynamic loads are predicted with a lifting surface method with a free wake model. A preview predict control algorithm is used as the pitch control strategy. A full scale U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) 5 MW floating wind turbine is chosen as the subject of the present study. The unsteady aerodynamic performance and instabilities have been discussed in detail under prescribed platform surge motions with different control targets. Both minimizing the power output and rotor thrust fluctuation are set as the control objectives respectively. The theory analysis and the simulation results indicate that the blade pitch control can effectively alleviate the variation of the rotor thrust under platform surge motions. Larger amplitude of the variation of blade pitch is needed to alleviate the variation of the wind turbine power and this leads to high rotor thrust fluctuation. It is also shown that negative damping can be achieved during the blade pitch control process and may lead the floating platform wind turbine system into unstable condition.

Aims Noninvasive music adjuvant therapy shows great potential in improving seizure control when combined with routine antiepileptic drugs. However, the diversity of previous music protocols has resulted in disparate outcomes. The optimized protocol and features for music adjuvant therapy are still not fully understood which limits its feasibility. Methods By applying different regimens of music therapy in various temporal lobe epilepsy models, we evaluated the effect of music in combination with sub‐dose drugs on epileptic seizures to determine the optimized protocol. Results A subgroup of kindled mice that were responsive to music adjuvant therapy was screened. In those mice, sub‐dose drugs which were noneffective on kindled seizures, alleviated seizure severity after 12 h/day Mozart K.448 for 14 days. Shorter durations of music therapy (2 and 6 h/day) were ineffective. Furthermore, only full‐length Mozart K.448, not its episodes or other music varieties, was capable of enhancing the efficacy of sub‐dose drugs. This music therapeutic effect was not due to increasing cerebral drug concentration, but instead was related with the modulation of seizure electroencephalogram (EEG) spectral powers in the hippocampus. Conclusion These results indicate that long‐term full‐length Mozart K.448 could enhance the anti‐seizure efficacy of sub‐dose drugs and may be a promising noninvasive adjuvant therapy for temporal lobe epilepsy., Music adjuvant therapy promotes the efficacy of sub‐dose antiepileptic drugs in both hippocampal and amygdaloid kindled temporal lobe epileptic mice. Listening to full‐length Mozart K.448 for 12 h/day is the optimal protocol for music adjuvant therapy.

Accurately estimating and mapping forest structural parameters are essential for monitoring forest resources and understanding ecological processes. The novel deep learning algorithm has the potential to be a promising approach to improve the estimation accuracy while combining with advanced remote sensing technology. Airborne light detection and ranging (LiDAR) has the preferable capability to characterize 3-D canopy structure and estimate forest structural parameters. In this study, we developed a deep learning-based algorithm (Deep-RBN) that combined the fully connected network (FCN) deep learning algorithm with the optimized radial basis neural network (RBN) algorithm for forest structural parameter estimation using airborne LiDAR data. The multiple iterations were used to constantly update the internal weights to achieve the optimized accuracy of model fitting, and the optimized RBN algorithm was developed for the limited training sets. We assessed the efficiency and capability of the Deep-RBN in the estimation of forest structural parameters in a subtropical planted forest of southern China, by comparing the traditional FCN algorithm and multiple linear regression. We found that Deep-RBN had the strongest capability in estimates of forest structural parameters (R2 = 0.67-0.86, rRMSE = 6.95%-20.34%). The sensitivity analysis of the key hyperparameters of Deep-RBN algorithm showed that the learning rate is one of the most important parameters that influence the performance of predictive models, and while its value equal is to 0.001, the predictive models had the highest accuracy (mean DBH: RMSE = 1.01, mean height: RMSE = 1.45, volume: RMSE = 26.49, stem density: RMSE = 121.06). With the increase of training samples added in Deep-RBN model, the predictive models performed better; however, no significant improvements of accuracy were observed while the number of training set is larger than 80. This study demonstrates the benefits of jointly using the Deep-RBN algorithm and airborne LiDAR data to improve the accuracy of forest structural parameter estimation and mapping, which provides a promising methodology for sustainable forest resources monitoring.

Background: Cancer is a leading cause of death worldwide. Extensive research over decades has led to the development of therapies that inhibit oncogenic signaling pathways. The mammalian target of rapamycin (mTOR) signaling pathway plays an important role in the development of many cancers. Several mTOR inhibitors are approved for the treatment of cancers. However, the anticancer efficacies of mTOR inhibitor monotherapy are still limited. Methods: Western blot was used to detect the expression of indicated molecules. Thioredoxin reductase (TrxR) activity in cells was determined by the endpoint insulin reduction assay. Immunofluorescence staining was used to analyze precise location and expression of target proteins. Nude mice were used for xenograft tumor models. Results: We identified a synergistic lethal interaction of mTOR and TrxR inhibitors and elucidated the underlying molecular mechanisms of this synergism. We demonstrated that mTOR and TrxR inhibitors cooperated to induce cell death by triggering oxidative stress, which led to activation of autophagy, endoplasmic reticulum (ER) stress and c-Jun N-terminal Kinase (JNK) signaling pathway in cancer cells. Remarkably, we found that auranofin (AF) combined with everolimus significantly suppressed tumor growth in HCT116 and SGC-7901 xenograft models with no significant signs of toxicity. Conclusion: Our findings identify a promising therapeutic combination for cancer and has important implications for developing mTOR inhibitor-based combination treatments.

Most cluster identification studies regarding consumer electricity load is faced with problems of erroneous clustering method similarity, low clustering quality and poor identification accuracy. To solve these problems, this paper utilizes the elbow method, k- Means ++, entropy weight method and a graph convolutional neural network to provide a means for cluster identification based on electrical appliance power data collected via smart sockets. In this article, elbow and entropy weight methods were used to achieve the adaptive clustering algorithm. To obtain the electrical appliance load curves, Euclidean and dynamic time warping (DTW) distances were integrated and the similarity measurement method was used to improve the k-means ++ algorithm, which was then applied to data collected via smart socket clustering. Next, clustering results were input into the graph convolutional neural network (GCN) for identification purposes and appliance type information was obtained. Finally, experiments were conducted using electrical load data from 20 commercial users. The method used was a combination of the k-means algorithm and long short-term memory network (LSTM). The results show that under optimal K value conditions (as determined by the elbow score), the methods used in this paper have improved clustering quality and recognition accuracy, when compared to LSTM.

To investigate the attack rate of active tuberculosis (TB) cases and detection rate of latent tuberculosis infection (LTBI) cases, and to identify possible factors contributed to the outbreak in a high school. We analyzed the investigation data of 35 teachers and 108 students, including active TB cases and their close contacts. The symptoms inquiry, tuberculin skin test (TST), and chest X-ray/CT scan were conducted in the close contact screening. We did variable-number-of-tandem-repeat genotyping and whole-genome sequencing of isolates. The time interval between the onset of symptoms and diagnosis was 36 days. The total attack rate of active TB was 7.69% (11/143), with a class attack rate of 27.78% (10/36) among students. The genetic differences between any two available isolates were less than 5 SNPs. Approximately 15.38% (22/143) of persons were LTBI cases, and the total detection rates of LTBI for students and teachers were 7.40% (8/108) and 40% (14/35), respectively. Being in the same class as the index case resulted in a significantly higher risk of being diagnosed with active TB (P = 0.0001, RR = 18.51, 95%CI (2.44,140.42)) and either LTBI and MTB infection (RR = 14.40, RR = 16.46, respectively) compared with that of students in a non-index class. The case-finding delay should be reduced to prevent the spread in classes and schools. Effective surveillance and regulated screening for student contacts should be strengthened in schools to detect infections early.

BACKGROUND: Ultrasonography patterns and molecular testing may assist in stratifying the malignancy risk of indeterminate cytology diagnosis. The purpose of this study was to assess the value of fine needle aspiration (FNA) cytology in combination with American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) and BRAF(V600E) mutation in differentiating high-risk thyroid nodules. METHODS: From February 2010 to February 2014, 2,643 consecutive thyroid nodules from 2,399 patients (688 men and 1,711 women; mean age, 44.3±12.5 years) who underwent preoperative FNA biopsies were enrolled. The Jiangsu Institute of Nuclear Medicine has adopted TI-RADS stratification and BRAF(V600E) mutation analysis as a routine procedure to assist in evaluating FNA cytopathology since January 2016. From February 2017 to July 2018, 1,905 thyroid nodules of 1,837 patients (501 men and 1,336 women, 49.5±12.8 years) who underwent preoperative ultrasound-guided FNA biopsies with BRAF(V600E) mutation analysis and ACR TI-RADS grading data available were enrolled for comparison in this study. RESULTS: The cancer risk in nodules with BRAF(V600E) mutation was 99.7% (905/908) according to the histological findings. The risk of malignancy (ROM) was found to increase with advancing ACR TI-RADS category. High-risk ultrasound features (TI-RADS 5) did show a good performance in predicting malignancy (98.1%). The combination of TI-RADS 5 and BRAF(V600E) mutation reached the best diagnostic efficiency [sensitivity 97.7%, specificity 94.8%, positive predictive value (PPV) 99.6%]. It is apparent that after the implementation of ACR TI-RADS and the BRAF(V600E) mutation analysis, the resection rates (RRs) of The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) I and III categories showed significant decreases (39.1% vs. 21.6% and 36.1% vs. 16.7%, respectively). In contrast, the risks of malignancy of TBSRTC I and III categories indicated substantial increases (41.5% vs. 80.0% and 34.6% vs. 50.0%, respectively). The ROM of thyroid nodules with nondiagnostic (ND, I) category showed the most significant increase of 41.5% to 80.0%. CONCLUSIONS: ACR TI-RADS, together with BRAF(V600E) mutation and cytological diagnoses, can assist in improving the prediction of malignancy of thyroid nodules, especially in the TBSRTC I and III categories.

Texture segmentation is a frequently occurring and challenging problem in many computer vision and pattern recognition applications. The importance of phase information for texture analysis has been earlier established for many image processing. Undecimated dual tree complex wavelet transform (UDTCWT) is a new image decomposition. It not only provides exact translational invariance and rich directional selectivity, but also offers perfect consistent relative phase relationships across scales. In this paper, we propose a novel texture image segmentation framework using Vonn mixtures-based hidden Markov trees (HMT) and UDTCWT domain relative phase. Firstly, we analyze the robustness and marginal distribution of UDTCWT relative phases, and various strong dependencies between UDTCWT relative phases. Then, we propose a new HMT statistical model in UDTCWT domain, namely Vonn mixtures-based HMT, by describing the UDTCWT relative phases statistical distribution with Vonn mixtures (VM), which can capture both the subband marginal distributions and the strong dependencies across scales of the UDTCWT relative phases. Finally, we develop a texture image segmentation framework using the Vonn mixtures-based HMT model of UDTCWT domain relative phases, in which expectation–maximization (EM) parameter estimation, Bayesian multiscale raw segmentation, and context based multiscale fusion are used. Comparing to the state-of-the-art techniques, the proposed method can not only produce high-quality segmentation results in a more efficient way, but also keep a lot of boundary details in the segmentation results.

Objective To evaluate the performance of whole-genome sequencing (WGS) for predicting Mycobacterium tuberculosis (MTB) drug resistance. Methods 276 rifampin-resistance tuberculosis (RR-TB) and 30 rifampicin-sensitive clinical isolates were randomly selected from patients with tuberculosis in Shanghai Pulmonary Hospital (SPH). Phenotypic drug susceptibility testing (DST) against six anti-TB drugs was performed, and WGS was used to predict the drug resistance using an online ‘TB-Profiler’ tool. Results Using phenotypic susceptibility as the gold standard, the overall sensitivities and specificities for WGS were 94.53% and 92.00% for isoniazid, 97.10% and 100.00% for rifampicin, 97.46% and 64.36% for ethambutol, 97.14% and 95.83% or streptomycin, 93.02% and 98.87% for ofloxacin, and 75.00% and 100.00% for amikacin, respectively. The concordances of WGS-based DST and phenotypic DST were: isoniazid (94.12%), rifampicin (97.39%), ethambutol (77.12%), streptomycin (96.73%), ofloxacin (96.41%) and amikacin (97.06%). Conclusions WGS could be a promising approach to predict resistance to isoniazid, rifampicin, ethambutol, streptomycin, ofloxacin, and amikacin.

A TiO2 coating was grown on a CdTe absorber by atomic layer deposition for stabilization against its photocorrosion during photoelectrochemical water splitting. Under simulated sunlight (AM 1.5G, 1...

LIVIN, a member of the inhibitor of apoptosis proteins (IAPs), is reported playing important roles in the development and progression of multiple human cancers. However, its underlined mechanisms in human renal cell carcinoma (RCC) are still needed to be clarified. In the present study, we reported that inhibition of miR‐214 promoted the expression of LIVIN, then facilitated RCC cells growth and reduced the sensitivity of RCC cells to chemotherapeutic drugs. In constant, overexpression of miR‐214 had contradictory effects. Further investigation showed that miR‐214 was down‐regulated in RCC because of abnormal methylation. In addition, DNA methyltransferase DNMT1, miR‐214 and LIVIN are directly correlated in RCC patients. In conclusion, these results suggest that abnormal miR‐214 methylation negatively regulates LIVIN, which may promote RCC cells growth and reduced the sensitivity of RCC cells to chemotherapeutic drugs.

Diabetic nephropathy (DN) is one of the serious complications in diabetes. Cyanidin-3-glucoside (C3G) from black rice was reported to have hypoglycemic effects and an anti-osteoporosis effect in diabetic rats. Whether it has preventive effects on DN has not been reported. In this study, we established a rat model of DN, and C3G at two doses (10 and 20 mg kg-1 day-1) were administered to see its anti-DN effect. A total of 8 weeks of C3G supplementation decreased blood glucose and serum insulin, improved the renal function, and relieved renal glomerular sclerosis and interstitial fibrosis of DN rats. Also, the kidneys of DN rats had improved the oxidative defense system. Pro-inflammatory mediators were markedly reduced in serum and kidneys of the C3G-treated groups. Transforming growth factor β1 (TGF-β1), phosphor-Smad2, and phosphor-Smad3 protein expression levels were significantly decreased in the kidney of the C3G-treated group, whereas the Smad7 expression level was upregulated by C3G. Our results indicate that C3G can ameliorate DN via antioxidative stress and anti-inflammation and regulate the TGF-β1/Smad2/3 pathway. Our results suggest that C3G from black rice might be used as a renal-protective nutrient in DN.

Feature-based image watermarking is a well-developed area of digital image watermarking. The key advantage of such an approach is the ability to guard against the local desynchronization attacks. However, research in this area usually suffers from the following limitations: (1) The feature points focus too much on the high contrast region and are distributed unevenly. (2) The feature point detector is sensitive to the texture region, and some noise feature points are always detected in the texture region. Based on superpixel image segmentation and quaternion wavelet transform, we propose a digital image watermarking approach which is highly robust against common image processing operations and local geometric transformations. First, the entropy rate superpixel segmentation is used to segment the host image into several homogeneous regions. Then, for each segment region, image feature points are extracted using the SIFER detector, and the affine invariant local regions are constructed adaptively. Finally, the digital watermark is embedded into the local regions by modulating the invariant modulus coefficients. Experimental results are provided to illustrate the efficiency of the proposed image watermarking, especially for noise attacks and local desynchronization attacks.

OBJECTIVE Excessive iron intake has been linked to diabetes risk. However, the evidence is inconsistent. This study examined the association between dietary heme and nonheme iron intake and diabetes risk in the Chinese population. RESEARCH DESIGN AND METHODS We included 17,026 adults (8,346 men and 8,680 women) who were part of the China Health and Nutrition Survey (1991–2015) prospective cohort. Dietary intake was measured by three consecutive 24-h dietary recalls combined with a household food inventory. Diabetes cases were identified through a questionnaire. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs. RESULTS A total of 547 men and 577 women developed diabetes during 202,138 person-years of follow-up. For men, the adjusted HRs (95% CIs) for quintiles of nonheme iron intake were 1.00, 0.77 (0.58–1.02), 0.72 (0.54–0.97), 0.63 (0.46–0.85), and 0.87 (0.64–1.19) (P-nonlinearity = 0.0015). The corresponding HRs (95% CIs) for women were 1.00, 0.63 (0.48–0.84), 0.57 (0.43–0.76), 0.58 (0.43–0.77), and 0.67 (0.49–0.91) (P-nonlinearity < 0.0001). The dose-response curves for the association between nonheme iron and total iron intake and diabetes followed a reverse J shape in men and an L shape in women. No significant associations were observed between heme iron intake and diabetes risk. CONCLUSIONS Total iron and nonheme iron intake was associated with diabetes risk, following a reverse J-shaped curve in men and an L-shaped curve in women. Sufficient intake of nonheme or total iron might be protective against diabetes, while excessive iron intake might increase the risk of diabetes among men.

Age-related jawbone loss directly impact the function of oral cavity resulted from tooth loss, implant failure, and jaw fracture. Numerous evidences show that age-related senescence of bone marrow stromal cells (BMSCs) play a critical role in bone loss, but little attention has been paid to jawbone. Here, we delineated the critical role of sirtuin family protein 6 (SIRT6) in senescence, autophagy, and osteogenesis of BMSCs from jawbones. Radiography analysis showed less jawbone quality in elderly than young people. We also showed that SIRT6 expression decreased in bone tissue and BMSCs from the elderly by immunochemical staining. BMSCs from the elderly exhibited decreased osteogenic differentiation and inclined senescence which these phenotypes could be simulated by SIRT6 knockdown. Furthermore, accompanied with the inhibition of SIRT6, the autophagy level and ostogenesis of BMSCs was also decreased. However, using rapamycin, an autophagy activator, could rescue these adverse effects of BMSCs caused by SIRT6 inhibition. Mechanistically, SIRT6 regulated the autophagy and osteogenesis of BMSCs by activating AKT-mTOR pathway, at least in part. Finally, a decreased jawbone quality was shown in SIRT6 haploinsufficiency mice by Wnt1 specific tissue knockdown (Wnt1-Cre;SIRT6fl/+) model. Taken together, our data revealed that SIRT6 adjusted senescence and osteogenesis of BMSCs via altering autophagy level, and associated with age-related bone loss. SIRT6 could be as a promising therapeutic target for age-related osteoporosis of jawbone.

BackgroundMany patients with pancreatic cancer (PC) suffer from abdominal pain and back pain. However, the cause of pain associated with PC is largely unclear. In this study, we tested the potential influence of the sonic hedgehog (sHH) signaling pathway on PC pain.MethodsSubstance P (SP) and calcitonin gene-related peptide (CGRP) expression was measured in cultured PC cells and dorsal root ganglions (DRG) by real-time PCR, western blotting analysis and ELISA. Small interfering RNA transfection and plasmid constructs were used to regulate the expression of sHH in the AsPc-1 and Panc-1 cell lines. Pain-related behavior was observed in an orthotopic tumor model in nude mice.ResultsIn this study, the results show that sHH increased the expression of SP and CGRP in DRGs in a concentration and time-dependent manner. Additionally, sHH secretion from PC cells could activate the sHH signaling pathway and, in turn, increase the expression of nerve growth factor (NGF), P75, and TrkA in DRGs. Furthermore, the sHH signaling pathway and NGF/NGF receptor contributed to pain sensitivity in a nude mouse model.ConclusionOur results demonstrate that PC pain originates from the sHH signaling pathway, and NGF mediates the pain mechanism via regulating SP and CGRP.

OBJECTIVE The purpose of this study was to assess the fibrinolytic status after cardiopulmonary bypass in rheumatic valvular heart disease patients, and detect the associated factors of post-cardiopulmonary bypass hyperfibrinolysis. METHODS According to the fibrinolytic status after cardiopulmonary bypass, 203 rheumatic valvular heart disease patients were divided into two groups: hyperfibrinolysis group (H group, n = 78) and non-hyperfibrinolysis group (NH group, n = 125). The demographic characteristics, operative variables, and postoperative follow-ups were compared between these two groups. RESULTS The incidence of hyperfibrinolysis was 38.4% after cardiopulmonary bypass. Patients in the H group had a significant higher incidence of preoperative atrial fibrillation than patients in the NH group (92.3% vs. 55.2%, P

Background: Burnout is considered a global problem, particularly in the emergency health sector; however, no large-sample cross-sectional study has assessed the prevalence of burnout among emergency physicians and its associated factors. Methods: A nationally representative cross-sectional survey of 15,243 emergency physicians was conducted in 31 provinces across China between July and September 2019. Multiple linear regression analysis was performed to identify predictors of burnout. Results: The participants’ mean scores were 25.78 (SD = 15.94) on the emotional exhaustion (EE) subscale, 8.13 (SD = 7.85) on the depersonalization (DP) subscale, and 26.80 (SD = 12.53) on the personal accomplishment (PA) subscale, indicating a pattern of moderate EE, moderate DP, and high PA. Having poor self-perceived health status and sleep quality, working in developed regions and governmental hospitals, having an intermediate professional title, experiencing depression, performing shift work and experiencing workplace violence made emergency physicians more likely to experience occupational burnout. Conclusion: The results of the large-sample survey found that 14.96% of emergency physicians had a high level of burnout in China, with 46.78% scoring high for EE, 24.09% scoring high for DP, and 60.51% having a high risk of low PA. Positive measures should be taken to reduce the burnout of emergency physicians and improve their work enthusiasm to maintain the quality of emergency medical services. Funding Information: No funding was received for this study. Declaration of Interests: We declare that we have no conflict of interests. Ethics Approval Statement: The study protocol was approved by the Institutional Ethics Board of the Second Affiliated Hospital of Hainan Medical University, Haikou, China. All individuals provided written informed consent.

Background: As more and more countries enter the low-transmission phase, maintaining prevention awareness among the population is critical to prevent a secondary outbreak. With large-scale interpersonal communication, whether Chinese residents can maintain a high awareness of prevention and control and adhere to the use of masks during the Chinese New Year of 2021 is worth studying.Methods: A cross-sectional survey was conducted in China from February 4 to 26, 2021. A convenient sampling strategy was adopted to recruit participators. Participants were asked to fill out the questions that assessed the questionnaire on face mask use. Descriptive statistics were used to assess the mask-wearing behaviors of the public. A binary logistic regression analysis was performed to identify the risk factors affecting mask-wearing behaviors.Results: A total of 2,361 residents filled out the questionnaire. In the mixed-effect logistic regression analysis, Chinese residents who were older (OR = 7.899, 95%CI = 4.183–14.916), employed (OR = 1.887, 95%CI = 1.373–2.594), had a chronic disease (OR = 1.777, 95%CI = 1.307–2.418), reused face masks (OR = 22.155, 95%CI = 15.331–32.016) and have read the face mask instructions (OR = 3.552, 95%CI = 1.989–6.341) were more likely to use face masks in interpersonal communication during the Spring Festival; while people who have breathing discomfort caused by face masks (OR = 0.556, 95%CI = 0.312–0.991) and considered that using masks repeatedly is wasteful (OR = 0.657, 95%CI = 0.482–0.895) were more unlikely to use face masks.Conclusions: Our results revealed that 83.86% of people wore face masks during the Chinese New Year; however, some aspects require further promotion. By investigating the use of masks by Chinese residents during the Spring Festival and its influencing factors, we can reflect the prevention awareness of the residents during the low transmission period of COVID-19, which can provide a reference for Chinese and global public health policymakers.

Background: By investigating the incidence of post-traumatic stress disorder (PTSD) among residents during a period of low transmission, this study reflects the long-term impact of coronavirus disease 2019 (COVID-19) and identify which categories of residents are more likely to develop PTSD due to an acute infectious disease crisis, facilitating the development of targeted strategies to protect mental health after outbreaks of similar acute infectious diseases in the future.Methods: A cross-sectional survey was conducted in China from 4 to 26 February 2021. A convenience sampling strategy was adopted to recruit participants. Participants were asked to complete the PTSD Checklist for DSM-5 (PCL-5). A multivariable linear stepwise regression analysis model was used to identify which factors were associated with PTSD in residents of China.Results: A total of 2,361 Chinese residents completed the questionnaire. The mean PCL-5 score for the respondents was 13.65 (SD = 8.66), with 219 (9.28%) patients having probable PTSD symptoms. Respondents who were female (β = 0.038), had a relative or friend who had contracted COVID-19 (β = 0.041), and had poor health (β = 0.184) had higher PCL-5 scores, while the population aged over 60 years (β = −0.063), who agreed that COVID-19 information was released in a timely manner (β = −0.347), who had experienced a relatively limited impact of COVID-19 on their life (β = −0.069), and who agreed that the local prevention initiatives were sophisticated (β = −0.165) had lower PTSD scores.Conclusions: Outbreaks of acute infectious diseases can have long-term psychological health effects in the general population. In addition, health policy makers need to be concerned about and implement measures to support the mental health of vulnerable groups.

Background Nowadays, liver transplantation has become a main therapy for end-stage liver disease. However, studies show that there are high mortality and severe complications after liver transplantation. Although gastrointestinal dysfunction is a common and major complication after liver transplantation, there was rarely relative research. This study aims to elucidate the factors about ileus after liver transplantation and patients’ survival. Methods We collected and analyzed the data (n = 318, 2016–2019) from the First Affiliated Hospital of Xi’an Jiaotong University. After excluding cases, a total of 293 patients were included for this study. The subjects were divided into a non-ileus group and an ileus group. We reviewed 38 variables (including preoperative, operative and postoperative relative factors). Additionally, other complications after liver transplantation and survival data were compared between two groups. Results Of the 293 patients, 23.2% (n = 68) experienced postoperative ileus. Ileus patients were not different with non-ileus patients in preoperative, operative and postoperative factors. HBV-positive patients with ileus had a lower MELD score (P = 0.025), and lower postoperative total bilirubin was correlated with ileus (P = 0.049). Besides, Child–Pugh score of HCC patients with ileus was low (P = 0.029). The complications after liver transplantation were not different between two groups. Compared with the patients without ileus, the patients with ileus had a higher mortality rate. Conclusion According to our research, ileus-patients had a lower 1-year survival rates. The preoperative MELD score and postoperative total bilirubin of HBV-positive patients with ileus were lower, and Child–Pugh score of HCC patients with ileus was also lower.

Neuroevolution, a field that draws inspiration from the evolution of brains in nature, harnesses evolutionary algorithms to construct artificial neural networks. It bears a number of intriguing capabilities that are typically inaccessible to gradient-based approaches, including optimizing neural-network architectures, hyperparameters, and even learning the training rules. In this paper, we introduce a quantum neuroevolution algorithm that autonomously finds near-optimal quantum neural networks for different machine-learning tasks. In particular, we establish a one-to-one mapping between quantum circuits and directed graphs, and reduce the problem of finding the appropriate gate sequences to a task of searching suitable paths in the corresponding graph as a Markovian process. We benchmark the effectiveness of the introduced algorithm through concrete examples including classifications of real-life images and symmetry-protected topological states. Our results showcase the vast potential of neuroevolution algorithms in quantum architecture search, which would boost the exploration towards quantum-learning advantage with noisy intermediate-scale quantum devices., 7 pages (main text) + 5.5 pages (supplementary materials), 14 figures

Ao-lin Yuan,1 Xin Shen,2 Bin Chen1 1Minimally Invasive Spine Surgery, Chengde Medical University Affiliated Hospital, Chengde, Hebei Province, People’s Republic of China; 2Breast and Thyroid Surgical Oncology, Hebei Medical University Second Affiliated Hospital, Shijiazhuang, Hebei Province, People’s Republic of ChinaCorrespondence: Bin Chen, Minimally Invasive Spine Surgery, Chengde Medical University Affiliated Hospital, Chengde, Hebei Province, People’s Republic of China, Email drchenbin@vip.sina.comPurpose: This study aimed to investigate the use of the percutaneous intervertebral foramen lens technology for secondary molding of the intervertebral foramen in the treatment of calcified lumbar discs.Methods: The study included 104 patients who were divided into two groups. Group A comprised 50 patients with calcified lumbar disc herniation and group B comprised 54 patients with non-calcified lumbar disc herniation diagnosed by computed tomography and magnetic resonance imaging. Patients underwent a percutaneous endoscopic lumbar discectomy at our hospital from January 1, 2017, to December 31, 2019. Demographic characteristics before the surgery and perioperative outcomes were retrospectively reviewed. The treatment outcome was analyzed using the numerical rating scale (NRS) score, Oswestry Disability Index (ODI) score, and modified Macnab criteria.Results: Patients in groups A and B showed significant improvement in both the NRS and ODI scores after the surgery and maintained relatively low ODI and NRS scores during subsequent follow-ups. According to the evaluation under the modified MacNab standard, the good–excellent rate of clinical efficacy was 94% in group A and 92.6% in group B at the 3 month follow-up. In group A, one patient developed neck pain during the surgery, which was diagnosed as spinal hypertension syndrome, and the surgery was suspended until the patient’s condition improved. No similar complications occurred in group B. In both the groups, no patient reported any dural leak, infection, or other related complications.Conclusion: The use of transforaminal remolding technology can significantly improve the symptoms and dysfunction of patients with calcified and non calcified lumbar disc herniation. There are few intraoperative and postoperative complications and have little impact on vertebral stability. It can provide a reference for the treatment of special types of lumbar disc herniation.Keywords: lumbar disc herniation, calcification, percutaneous transforaminal endoscopic surgery, nerve root compression, visual analog scale, Oswestry, disability index, Macnab criteria

Background Tai Chi has been shown to improve motor symptoms in Parkinson’s disease (PD), but its long-term effects and the related mechanisms remain to be elucidated. In this study, we investigated the effects of long-term Tai Chi training on motor symptoms in PD and the underlying mechanisms. Methods Ninety-five early-stage PD patients were enrolled and randomly divided into Tai Chi (n = 32), brisk walking (n = 31) and no-exercise (n = 32) groups. At baseline, 6 months and 12 months during one-year intervention, all participants underwent motor symptom evaluation by Berg balance scale (BBS), Unified PD rating-scale (UPDRS), Timed Up and Go test (TUG) and 3D gait analysis, functional magnetic resonance imaging (fMRI), plasma cytokine and metabolomics analysis, and blood Huntingtin interaction protein 2 (HIP2) mRNA level analysis. Longitudinal self-changes were calculated using repeated measures ANOVA. GEE (generalized estimating equations) was used to assess factors associated with the longitudinal data of rating scales. Switch rates were used for fMRI analysis. False discovery rate correction was used for multiple correction. Results Participants in the Tai Chi group had better performance in BBS, UPDRS, TUG and step width. Besides, Tai Chi was advantageous over brisk walking in improving BBS and step width. The improved BBS was correlated with enhanced visual network function and downregulation of interleukin-1β. The improvements in UPDRS were associated with enhanced default mode network function, decreased L-malic acid and 3-phosphoglyceric acid, and increased adenosine and HIP2 mRNA levels. In addition, arginine biosynthesis, urea cycle, tricarboxylic acid cycle and beta oxidation of very-long-chain fatty acids were also improved by Tai Chi training. Conclusions Long-term Tai Chi training improves motor function, especially gait and balance, in PD. The underlying mechanisms may include enhanced brain network function, reduced inflammation, improved amino acid metabolism, energy metabolism and neurotransmitter metabolism, and decreased vulnerability to dopaminergic degeneration. Trial registration This study has been registered at Chinese Clinical Trial Registry (Registration number: ChiCTR2000036036; Registration date: August 22, 2020).

Open-domain dialogue generation in natural language processing (NLP) is by default a pure-language task, which aims to satisfy human need for daily communication on open-ended topics by producing related and informative responses. In this paper, we point out that hidden images, named as visual impressions (VIs), can be explored from the text-only data to enhance dialogue understanding and help generate better responses. Besides, the semantic dependency between an dialogue post and its response is complicated, e.g., few word alignments and some topic transitions. Therefore, the visual impressions of them are not shared, and it is more reasonable to integrate the response visual impressions (RVIs) into the decoder, rather than the post visual impressions (PVIs). However, both the response and its RVIs are not given directly in the test process. To handle the above issues, we propose a framework to explicitly construct VIs based on pure-language dialogue datasets and utilize them for better dialogue understanding and generation. Specifically, we obtain a group of images (PVIs) for each post based on a pre-trained word-image mapping model. These PVIs are used in a co-attention encoder to get a post representation with both visual and textual information. Since the RVIs are not provided directly during testing, we design a cascade decoder that consists of two sub-decoders. The first sub-decoder predicts the content words in response, and applies the word-image mapping model to get those RVIs. Then, the second sub-decoder generates the response based on the post and RVIs. Experimental results on two open-domain dialogue datasets show that our proposed approach achieves superior performance over competitive baselines., Accepted by ACM MultiMedia 2021

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease accompanied by an itchy and scaly rash. Compound traditional Chinese medicine dermatitis ointment (CTCMDO) is a traditional classics aimed at AD composed of a mixture of extracts from five plants known to have anti-inflammatory and antiallergic effects. Materials and methods: In this study, we used HPLC and LC/MS to analyze the effective components of CTCMDO in detail and establish its HPLC fingerprint analysis. On this basis, this article studied the anti-inflammatory and antipruritic activities of CTCMDO in the treatment of DNCB-induced AD in mice.Results: Through comparison with literature data, a total of 43 compounds were identified, including phenylpropionic acid compounds; alkaloid compounds; curcumin compounds and lignans. On this basis, a fingerprint with 17 common peaks was established. In AD-like mice, CTCMDO treatment suppressed the scratching behavior induced by DNCB in a dose-dependent manner and inhibited the production of Th1/2 cytokines in serum. CTCMDO treatment reversed the up regulation of P substance levels of itch-related genes in the skin. Furthermore, CTCMDO suppressed the phosphorylation of JNK、ERK and p38 in the skin. Conclusion: In all, our work indicated that CTCMDO can signifificantly attenuate the pathological alterations of Th1/2 cytokines and itch-related mediators, and inhibit the phosphorylation of MAPKs to treat AD.

ObjectivesThis study was aimed to assess the willingness of elderly people to seek medical care for tuberculosis (TB) and the associated influencing factors.DesignA cross-sectional study.SettingA multistage random survey was conducted in Bao’an District of Shenzhen in China.ParticipantsA total of 1200 elderly people aged 65 or above were recruited for the study and completed a structured questionnaire between September and October 2019.Main outcome measuresDescriptive and binary logistic stepwise regression analyses were conducted to analyse the characteristics of elderly individuals, their willingness to seek medical care for TB and associated factors.ResultsAmong the final 1123 respondents, 943 (84.0%) were willing to seek medical care if they discovered suspicious TB symptoms. Binary logistic stepwise regression analysis indicated that respondents whose family annual income per capita was 50 000–100 000¥ (OR=2.56, 95% CI: 1.44 to 4.54, pConclusionsWillingness to seek medical care for TB in the elderly population can be improved according to the determinants.

Background Part of tuberculosis (TB) patients were missed if symptomatic screening was based on the main TB likely symptoms. This study conducted to compare the yield and relative costs of different TB screening algorithms in active case-finding in the whole population in China. Methods The study population was screened based on the TB likely symptoms through a face-to-face interview in selected 27 communities from 10 counties of 10 provinces in China. If the individuals had any of the enhanced TB likely symptoms, both chest X-ray and sputum tests were carried out for them furtherly. We used the McNemar test to analyze the difference in TB detection among four algorithms in active case-finding. Of four algorithms, two were from WHO recommendations including 1a/1c, one from China National Tuberculosis Program, and one from this study with the enhanced TB likely symptoms. Furthermore, a two-way ANOVA analysis was performed to analyze the cost difference in the performance of active case-finding adjusted by different demographic and health characteristics among different algorithms. Results Algorithm with the enhanced TB likely symptoms defined in this study could increase the yield of TB detection in active case-finding, compared with algorithms recommended by WHO (p Conclusions Active case-finding based on the enhanced symptom screening is meaningful for TB case-finding and it could identify more active TB cases in time. The findings indicated that this enhanced screening approach cost more compared to algorithms recommend by WHO and China NTP, but the increased yield resulted in comparative costs per patient. And it cost much more that only smear/bacteriological-positive TB cases are screened in active case-finding.

Background: Policymakers must promote the development of public health education and human resources. As a feature of the political environment, public opinion is essential for policy-making, but virtually the attitudes of Chinese citizens toward human resources development in public health is unknown.Methods: This study conducted a crosssectional survey from February 4, 2021 to February 26, 2021 in China. We adopted a convenient sampling strategy to recruit participators. Participants filled out the questions, which assess the attitudes of the expanding public health professionals. A logistic regression analysis was given to identify the predictors associated with the attitudes of the subjects.Results: There were 2,361 residents who have finished our questionnaire. Chinese residents who lived in urban (OR = 1.293, 95% CI = 1.051–1.591), “themselves or relatives and friends have participated in relevant epidemic prevention work” (OR = 1.553, 95% CI = 1.160–2.079), “themselves or family members engaged in medical-related work” (OR = 1.468, 95% CI = 1.048–2.056), and those who “were aware of public health before the outbreak of COVID-19” (OR = 1.428, 95% CI = 1.125–1.812) were more likely to support the promotion of public health education and training.Conclusions: The present study found that 74.50% of Chinese citizens supported the promotion of public health education and training in China, in which economic status, personal perception, and comprehension are the crucial factors that influence public opinion. COVID-19 has aroused the attention of Chinese residents to public health education, with only 22.11% of residents being aware of public health before the outbreak of COVID-19. The COVID-19 pandemic has profound implications for human society. Literally, this impact will feed back into future public health policies based on public opinion. This innovative perspective will also help us better understand the potential social impact of COVID-19 on human resources and development for health in the modern world.

This paper considers the unsupervised domain adaptation problem, in which we want to find a good prediction function on the unlabeled target domain, by utilizing the information provided in the labeled source domain. A common approach to the domain adaptation problem is to learn a representation space where the distributional discrepancy of the source and target domains is small. Existing methods generally tend to match the marginal distributions of the two domains, while the label information in the source domain is not fully exploited. In this paper, we propose a representation learning approach for domain adaptation, which is addressed as JODAWAT. We aim to adapt the joint distributions of the feature-label pairs in the shared representation space for both domains. In particular, we minimize the Wasserstein distance between the source and target domains, while the prediction performance on the source domain is also guaranteed. The proposed approach results in a minimax adversarial training procedure that incorporates a novel split gradient penalty term. A generalization bound on the target domain is provided to reveal the efficacy of representation learning for joint distribution adaptation. We conduct extensive evaluations on JODAWAT, and test its classification accuracy on multiple synthetic and real datasets. The experimental results justify that our proposed method is able to achieve superior performance compared with various domain adaptation methods.

Objective To evaluate the efficacy and safety of Hua Shi Bai Du Granule (Q-14) plus standard care compared with standard care alone in adults with coronavirus disease (COVID-19). Study Design A single-center, open-label, randomized controlled trial. Setting Wuhan Jinyintan Hospital, Wuhan, China, February 27 to March 27, 2020. Participants A total of 204 patients with laboratory-confirmed COVID-19 were randomized into the treatment group and control group, consisting of 102 patients in each group. Interventions In the treatment group, Q-14 was administered at 10 g (granules) twice daily for 14 days, plus standard care. In the control group, patients were provided standard care alone for 14 days. Main Outcome Measure The primary outcome was the conversion time for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral assay. Adverse events were analyzed in the safety population. Results Among the 204 patients, 195 were analyzed according to the intention-to-treat principle. A total of 149 patients (71 vs. 78 in the treatment and control groups, respectively) tested negative via the SARS-CoV-2 viral assay. There was no statistical significance in the conversion time between the treatment group and control group (Full analysis set: Median [interquartile range]: 10.00 [9.00-11.00] vs. 10.00 [9.00-11.00]; Mean rank: 67.92 vs. 81.44; P = 0.051). The recovery time for fever was shorter in the treatment group than in the control group. The disappearance rate of symptoms like cough, fatigue, and chest discomfort was significantly higher in the treatment group. In chest computed tomography (CT) examinations, the overall evaluation of chest CT examination after treatment compared with baseline showed that more patients improved in the treatment group. There were no significant differences in the other outcomes. Conclusion The combination of Q-14 and standard care for COVID-19 was useful for the improvement of symptoms (such as fever, cough, fatigue, and chest discomfort), but did not result in a significantly higher probability of negative conversion in the SARS-CoV-2 viral assay. No serious adverse events were observed. Trial Registration ChiCTR2000030288

Background The incidence and risk of tuberculosis (TB) among the elderly population have increased with the ageing population in China. This study aimed to assess the current status and associated factors of TB knowledge, attitudes, and practices among elderly people in Shenzhen City, China, which may provide references for the development of TB prevention and treatment policies targeting elderly people. Methods A multistage random sampling method was used to collect data with a self-designed questionnaire from 1078 elderly people (response rate, 90.66%) living in Bao’an District of Shenzhen between September and October 2019. Univariate and multiple linear regression analyses were used to analyse factors associated with TB knowledge, attitudes, and practices among elderly people. Results Among the respondents, 3.13% had previously been treated for TB, and 3.09% of respondents had family members or friends with a previous TB history. The percentages of elderly people who were aware of TB and had positive attitudes and practices regarding TB were 69.23%, 48.87%, and 42.62%, respectively. Multiple linear stepwise regression analysis showed that elderly people with a junior high school education or higher, a family annual income per capita of less than 100,000 RMB, a better self-perceived health status, and family members or friends with a previous TB history had higher TB knowledge scores (P P P Conclusions Elderly people were aware of TB, but their positive attitudes and practices were at a low level. Corresponding prevention and treatment policies should be developed according to these influencing factors to reduce the incidence of TB among elderly people and improve their quality of life.

Increasing evidence has indicated that thyroid hormone receptor interacting protein 13 (TRIP13) exerts a cancer-promoting role in a broad spectrum of cancers. However, the detailed relevance and function of TRIP13 in cervical cancer remain undefined. The goal of this work was to evaluate the functional significance and mechanism of TRIP13 in cervical cancer. Our data demonstrated that TRIP13 expression was markedly increased in cervical cancer tissue, and high expression of TRIP13 predicted a low survival rate in cervical cancer patients. Knockdown of TRIP13 caused a significant reduction in the proliferation and invasion of cervical cancer cells. By contrast, over-expression of TRIP13 accelerated the proliferation and invasion of cervical cancer cells. Further data revealed that TRIP13 enhanced the activation of Wnt/β-catenin signaling associated with modulation of α-Actinin-4 (ACTN4). Knockdown of ACTN4 markedly reversed TRIP13-mediated activation of Wnt/β-catenin signaling. In addition, inhibition of Wnt/β-catenin signaling reversed TRIP13-induced cancer-promoting effects in cervical cancer cells. Knockdown of TRIP13 markedly retarded the tumor formation and growth of cervical cells in vivo in nude mice. Taken together, the data of this work indicate that TRIP13 accelerates the proliferation and invasion of cervical cancer by enhancing Wnt/β-catenin signaling via regulation of ACTN4. These findings underscore a relevance of the TRIP13/ACTN4/Wnt/β-catenin signaling axis in the progression of cervical cancer and suggest TRIP13 as a potential target for treatment of cervical cancer.

In order to solve the environmental pollution problem caused by winter heating of rural residential building in northern of China, in this paper a biomass gasification (BG)-solid oxide fuel cell (SOFC) combined heat and power (CHP) system has been establishedand numerically investigated. Taking a rural village around Xi’an which is an ancient city and located at central of northern China as the study object, according to heat and electricity output of the system and the heating and electrical load characteristics of the residential building of village, the energy saving ratio and economical efficiency of the CHP system under three different operation schemes compared with the traditional energy system have been analyzed. The results show that the operation scheme for heating designated rooms in rural buildings and meeting the average heat demand of users is the most energy-efficient and economical way. The primary energy saving rate and annual cost saving rate can reach 18.0% and 10.3%, respectively. When the user’s heat and power load demand is clear, the closer the system’s output heat and power ratio to the user’s heat and power load ratio, the more significant the system’s energy saving effect.

The wind turbine size is nowadays becoming increasingly larger as an effective approach to reduce cost of energy. Passive load control technique is introduced to alleviate the increasing loads on an upscaling wind turbine blade to improve its fatigue life. In this paper, the composite bend-twist coupled blade is investigated and utilized to mitigate the cyclic fluctuating loads in shear wind. The NREL 5-MW blade is firstly inversely redesigned of its composite layup configuration. The fiber on the spar cap is rotated away from the blade axis to implement the bend-twist coupling (BTC). An advanced aeroelastic model of the wind turbine blade is developed to conduct the study. The geometrically exact beam theory is used to account for the large deformation effects, while the tool VABS is utilized to generate the cross-section stiffness matrices. Meanwhile, the free wake lifting surface model is adopted to calculate the aerodynamic loads, which is physically more realistic than the traditionally used BEM method. Based the established model, the influences of BTC on the rotor aerodynamic performance are investigated. Load mitigation effects of the blades with various spar cap fiber angles are evaluated. The influences of coupling region and different wind speeds are also discussed.

Photocatalytic water splitting using particulate suspensions is a promising approach for achieving large-scale production of renewable hydrogen fuels. Previous studies have hypothesized that band energy levels of such photocatalysts in water are both flat and symmetrical, and charge separation in such photocatalysts is driven by random charge carrier diffusion. However, it is not well understood how the observed asymmetry of carrier diffusion is achieved during photocatalysis. To fully understand this charge separation process, we used double-side polished, intrinsic silicon as a model light absorber and manipulated the direction of charge-carrier diffusion using combinations of carrier-selective contacts. Degenerately p-type doped and n-type doped silicon, along with the as-grown and annealed TiO2 overlayers grown by atomic layer deposition, was used as carrier selective back and front contacts, respectively. The protective TiO2 layers along with nickel oxide co-catalysts enabled bi-functional, stable silicon photoelectrodes for photoelectrochemical hydrogen evolution and water oxidation in alkaline solution. A device simulation was applied to analyse the experimental results and further gain understanding on the charge separation process in photocatalysts involving semiconductor/liquid junctions. Combined experimental and simulation studies indicated that the contacts established asymmetric band bending inside the intrinsic silicon layer and drove directional charge separation, primarily carrier diffusion. By scaling down the thickness of the silicon layer in the simulation, analogies of charge separation in particulate photocatalysts can be drawn. Based on the findings from intrinsic silicon, we further revealed that photocatalysts generally do require asymmetric band bending to drive diffusional charge separation and that a small band edge offset of 0.45 eV between reductive and oxidative catalytic sites can provide a sufficient, steady-state photovoltage of over 1.23 V for overall water splitting by using a model SrTiO3 absorber. This study provides insightful guidance for designing efficient and stable particulate photocatalysts especially those using Si and III–V semiconductors with protective layers such as TiO2.

Background Glioblastoma multiforme (GBM) is a fatal disease without effective therapy. Identification of new biomarkers for prognosis would enable more rational selections of strategies to cure patients with GBM and prevent disease relapse. Methods Seven datasets derived from GBM patients using microarray or next generation sequencing in R2 online database (http://r2.amc.nl) were extracted and then analyzed using JMP software. The survival distribution was calculated according to the Kaplan-Meier method and the significance was determined using log-rank statistics. The sensitivity of a panel of GBM cell lines in response to temozolomide (TMZ), salinomycin, celastrol, and triptolide treatments was evaluated using MTS and tumor-sphere formation assay. Findings We identified that CD44, ATP binding cassette subfamily C member 3 (ABCC3), and tumor necrosis factor receptor subfamily member 1A (TNFRSF1A) as highly expressed genes in GBMs are associated with patients' poor outcomes and therapy resistance. Furthermore, these three markers combined with MGMT, a conventional GBM marker, can classify GBM patients into five new subtypes with different overall survival time in response to treatment. The four-gene signature and the therapy response of GBMs to a panel of therapeutic compounds were confirmed in a panel of GBM cell lines. Interpretation The data indicate that the four-gene panel can be used as a therapy response index for GBM patients and potential therapeutic targets. These results provide important new insights into the early diagnosis and the prognosis for GBM patients and introduce potential targets for GBM therapeutics. Fund Baylor Scott & White Health Startup Fund (E.W.); Collaborative Faculty Research Investment Program (CFRIP) of Baylor University, Baylor Scott & White Health, and Baylor College of Medicine (E.W., T.S., J.H.H.); NIH R01 NS067435 (J.H.H.); Scott & White Plummer Foundation Grant (J.H.H.); National Natural Science Foundation of China 816280007 (J.H.H. and Fu.W.).

In this paper, we study regional discrimination in a peer-to-peer lending scenario and provide novel empirical evidence for theories of soft information collection and information cost. We find that the regional information matters for borrowers’ funding probabilities and that discrimination is profit-oriented or taste-oriented depending on the specific region. Moreover, using borrowers’ birthplace as an instrumental variable, we find no evidence of genuine discrimination based purely on region in the peer-to-peer lending market.

Jia-Xin Shen,1 Ze-Hao Zhuang,1 Qiao-Xian Zhang,2 Jiao-Feng Huang,3 Gong-Ping Chen,4 Ying-Ying Fang,5 Ai-Guo Cheng6 1Endoscopy Center, First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 2Nursing Department, First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 3Department of Liver Research Center, First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 4Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 5Department of Tuberculosis, Third People’s Hospital of Yichang, Yichang, People’s Republic of China; 6Department of Critical Care, Third People’s Hospital of Yichang, Yichang, People’s Republic of ChinaCorrespondence: Ze-Hao ZhuangEndoscopy Center, First Affiliated Hospital of Fujian Medical University, 20, Chazhong Road, Taijiang District, Fuzhou, 350005, Fujian Province, People’s Republic of ChinaTel +86-131-7803-2412Fax +89-59187981370Email zhuang203@yeah.netPurpose: COVID-19 is a new infectious disease with global spread. The aim of the present study was to explore possible risk factors and evaluate prognosis in COVID-19 with liver injury.Methods: A retrospective study was conducted on 356 COVID-19 patients in the Third People’s Hospital of Yichang, Hubei, China. Clinical characteristics and laboratory tests between patients with and without liver injury were compared, while risk factors of COVID-19–related liver injury were analyzed. Univariate and multivariate Cox regression analyses were conducted to identify risk factors of in-hospital death.Results: Of the patients with liver injury, severe and critical types of COVID-19 comprised 12.43% and 14.69%, respectively, higher than in patients without liver injury (both P< 0.05). CRP and male sex were independent risk factors for for patients with liver injury, while decreased lymphocyte count (HR 0.024, 95% CI 0.001– 0.821) and elevated monocytes (HR 1.951, 95% CI 1.040– 3.662) and CRP (HR 1.028, 95% CI 1.010– 1.045) were independent risk factors of prognosis of death in COVID-19 patients with liver injury.Conclusion: Liver injury is a common complication in severe COVID-19 patients. Male sex and elevated CRP were independent risk factors in COVID-19 complicated by liver damage. Liver damage with increased CRP and monocyte count and decreased lymphocyte count may imply a poor prognosis.Keywords: COVID-19, liver injury, risk factors, prognosis

Open-domain multi-turn conversations mainly have three features, which are hierarchical semantic structure, redundant information, and long-term dependency. Grounded on these, selecting relevant context becomes a challenge step for multi-turn dialogue generation. However, existing methods cannot differentiate both useful words and utterances in long distances from a response. Besides, previous work just performs context selection based on a state in the decoder, which lacks a global guidance and could lead some focuses on irrelevant or unnecessary information. In this paper, we propose a novel model with hierarchical self-attention mechanism and distant supervision to not only detect relevant words and utterances in short and long distances, but also discern related information globally when decoding. Experimental results on two public datasets of both automatic and human evaluations show that our model significantly outperforms other baselines in terms of fluency, coherence, and informativeness., Accepted by ICASSP 2021

OBJECTIVETo evaluate the efficacy and safety of Chinese medicine (Q-14) plus standard care compared with standard care alone in adult with coronavirus disease 2019 (COVID-19).Study DESIGNSingle-center, open label, randomised controlled trial.SETTINGWuhan Jinyintan Hospital, Wuhan, China, February 27 to March 27, 2020.PARTICIPANTS204 patients with laboratory confirmed COVID-19 were randomised in to treatment group and control group, which was 102 patients each group.INTERVENTIONSIn treatment group, Q-14 was administrated at 10g (granules), twice daily for 14 days and plus standard care. In control group, patients were given standard care alone for 14 days.MAIN OUTCOME MEASUREThe primary outcome was conversion time of SARS-CoV-2 viral assay. Adverse events were analyzed in the safety population.RESULTSAmong 204 patients, 195 were analyzed according to the intention to treat principle. There were 149 patients (71 vs. 78 in treatment group and control group respectively) turning to negative via SARS-CoV-2 viral assay. No statistically significance showed in conversion time between treatment group and control group (FAS: Median (IQR): 10.00 (9.00-11.00) vs. 10.00 (9.00-11.00); Mean rank: 67.92 vs. 81.44; P=0.051.). Time to recovery of fever was shorter in treatment group as compared in control group. The disappearance rate of symptom in cough, fatigue, chest discomfort was significantly higher in treatment group. In chest computed tomography (Chest CT) examinations, overall evaluation of chest CT examination after treatment compared with baseline showed more patients improved in treatment group .There were no significant differences in the other outcomes.CONCLUSIONAdministration of Q-14 on standard care for COVID-19 was useful for improvement of symptoms (such as fever, cough, fatigue and chest discomfort), while did not result in a significantly higher probability of negative conversion of SARS-CoV-2 viral assay. No serious adverse events were reported.TRIAL REGISTRATIONChiCTR2000030288

Being able to reply with a related, fluent, and informative response is an indispensable requirement for building high-quality conversational agents. In order to generate better responses, some approaches have been proposed, such as feeding extra information by collecting large-scale datasets with human annotations, designing neural conversational models (NCMs) with complex architecture and loss functions, or filtering out untrustworthy samples based on a dialogue attribute, e.g., Relatedness or Genericness. In this paper, we follow the third research branch and present a data filtering method for open-domain dialogues, which identifies untrustworthy samples from training data with a quality measure that linearly combines seven dialogue attributes. The attribute weights are obtained via Bayesian Optimization (BayesOpt) that aims to optimize an objective function for dialogue generation iteratively on the validation set. Then we score training samples with the quality measure, sort them in descending order, and filter out those at the bottom. Furthermore, to accelerate the "filter-train-evaluate" iterations involved in BayesOpt on large-scale datasets, we propose a training framework that integrates maximum likelihood estimation (MLE) and negative training method (NEG). The training method updates parameters of a trained NCMs on two small sets with newly maintained and removed samples, respectively. Specifically, MLE is applied to maximize the log-likelihood of newly maintained samples, while NEG is used to minimize the log-likelihood of newly removed ones. Experimental results on two datasets show that our method can effectively identify untrustworthy samples, and NCMs trained on the filtered datasets achieve better performance., Comment: Accepted by CIKM 2021

Background. The classical Chinese herbal prescription Beimu-Gualou formula (BMGLF) has been diffusely applied to the treatment of respiratory diseases, including bronchiectasis. Although concerning bronchiectasis the effects and mechanisms of action of the BMGLF constituents have been partially elucidated, it remains to be determined how the formula in its entirety exerts therapeutic effects. Methods. In this study, the multitarget mechanisms of BMGLF against bronchiectasis were predicted with network pharmacology analysis. Using prepared data, a drug-target interaction network was established and subsequently the core therapeutic targets of BMGLF were identified. Furthermore, the biological function and pathway enrichment of potential targets were analyzed to evaluate the therapeutic effects and pivotal signaling pathways of BMGLF. Finally, virtual molecular docking was performed to assess the affinities of compounds for the candidate targets. Results. The therapeutic action of BMGLF against bronchiectasis involves 18 core target proteins, including the aforementioned candidates (i.e., ALB, ICAM1, IL10, and MAPK1), which are assumed to be related to biological processes such as drug response, cellular response to lipopolysaccharide, immune response, and positive regulation of NF-κB activity in bronchiectasis. Among the top 20 signaling pathways identified, mechanisms of action appear to be primarily related to Chagas disease, allograft rejection, hepatitis B, and inflammatory bowel disease. Conclusion. In summary, using a network pharmacology approach, we initially predicted the complex regulatory profile of BMGLF against bronchiectasis in which multilink suppression of immune/inflammatory responses plays an essential role. These results may provide a basis for novel pharmacotherapeutic approaches for bronchiectasis.