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Human parsing is a fine-grained semantic segmentation task, which needs to understand human semantic parts. Most existing methods model human parsing as a general semantic segmentation, which ignores the inherent relationship among hierarchical human parts. In this work, we propose a pose-guided hierarchical semantic decomposition and composition framework for human parsing. Specifically, our method includes a semantic maintained decomposition and composition (SMDC) module and a pose distillation (PC) module. SMDC progressively disassembles the human body to focus on the more concise regions of interest in the decomposition stage and then gradually assembles human parts under the guidance of pose information in the composition stage. Notably, SMDC maintains the atomic semantic labels during both stages to avoid the error propagation issue of the hierarchical structure. To further take advantage of the relationship of human parts, we introduce pose information as explicit guidance for the composition. However, the discrete structure prediction in pose estimation is against the requirement of the continuous region in human parsing. To this end, we design a PC module to broadcast the maximum responses of pose estimation to form the continuous structure in the way of knowledge distillation. The experimental results on the look-into-person (LIP) and PASCAL-Person-Part datasets demonstrate the superiority of our method compared with the state-of-the-art methods, that is, 55.21% mean Intersection of Union (mIoU) on LIP and 69.88% mIoU on PASCAL-Person-Part.

In this paper, we propose a simple yet effective self-supervised method called spatio-temporal contrastive learning (ST-CL for 3D skeleton-based action recognition. ST-CL acquires action-specific features by regarding the spatio-temporal continuity of motion tendency as the supervisory signal. To yield effective representations, ST-CL first designs a novel contrastive proxy task by providing different spatio-temporal observation scenes for the same 3D action and pulling them together in the embedding space. Second, three key components are devised in the action encoding to efficiently extract representations in contrastive tasks: (1 Information Representation introduces the awareness of joint type when analyzing the motion dynamics. (2 Non-local GCN learns a data-driven graph topology structure and promotes a spatial message passing among long-range joints in each frame. (3 Multi-Scale TCN makes larger receptive fields for capturing richer longe-range temporal dynamics amomg adjacent frames. In ST-CL, the effective proxy tasks yield useful representations and efficient action encoding further enhances representation capacity. \revise{As validated on the four large-scale datasets, ST-CL is a strong baseline with high performance and efficiency for the contrastive learning study of the skeleton data. Compared to previous self-supervised methods, the proposed ST-CL achieves significant improvement consistently with a smaller model size and better training efficiency.

Objective To analyze the clinical value of high b-value 3.0 T biparametric magnetic resonance with the Simplified Prostate Image Reporting and Data System (S-PI-RADS) in biopsy-naive men. Methods A retrospective analysis of the data of 224 patients who underwent prostate biopsy (cognitive fusion targeted biopsy combined with systematic biopsy) after a high b-value 3.0 T magnetic resonance examination at Haikou Hospital from July 2018 to July 2020 was performed. Two radiologists performed multi-parameter magnetic resonance imaging (mp-MRI) with the prostate imaging report and data system version 2 (PI-RADS v2) and biparametric magnetic resonance imaging (bp-MRI) with the simplified prostate image reporting and data system (S-PI-RADS). The detection efficacy of the two regimens was evaluated by classifying prostate cancer (PCa) and clinically significant prostate cancer (csPCa) according to pathology, and the statistical significance of the differences between the two regimens was determined by Z-test. Results The area under the receiver operating curve (AUC) values of mp-MRI based on PI-RADS v2 and bp-MRI based on S-PI-RADS to detect PCa were 0.905 and 0.892, respectively, while the AUC values for the detection of csPCa were 0.919 and 0.906, respectively. There was no statistically significant difference between the two tests (Z values were 0.909 and 1.145, p > 0.05). Conclusion There was no significant difference in the detection efficacy of high b-value bp-MRI based on the S-PI-RADS score for prostate cancer and clinically significant prostate cancer compared with the standard PI-RADS v2 score with mp-MRI protocols, which can be applied clinically.

Dialysate potassium concentration directly affects the serum potassium level and safety of hemodialysis patients. In most dialysis centers in China, a single dialysate potassium concentration is used for dialysis, but there is no data on whether this is reasonable or not.Serum potassium values before and after dialysis in maintenance hemodialysis (MHD) patients between 2019 and 2020 were collected from 5 hemodialysis centers in Shanghai, which uniformly use dialysate with a potassium concentration (KD) of 2.0 mmol/L, and data were collected 3 times per patient for analysis. Serum potassium fluctuation was analyzed after administration of individualized KD dialysate.In all, 1,296 MHD patients were included in the study. Predialysis serum potassium was lower than 4.5 mmol/L in 38.0% and higher than 5.5 mmol/L in 14.6% of patients. Postdialysis serum potassium was lower than 3 mmol/L in 11.3% and higher than 4 mmol/L in 10.4% of patients. Pre-dialysis serum potassium was below 4.5 mmol/L and post- dialysis serum potassium was below 3 mmol/L in 9.54% of patients. Compared with patients younger than 40 years, patients80 years more often exhibited predialysis serum potassium below 4.5 mmol/L and Postdialysis serum potassium below 3 mmol/L. A total of 668 patients underwent a trial of hemodialysis with individualized KD dialysate. When receiving individualized KD, compared with uniform KD 2.0 mmol/L, the number of patients with postdialysis serum potassium less than 3 mmol/L significantly decreased, the following predialysis serum potassium level was not significantly different from baseline, and the proportion of patients with predialysis serum potassium less than 4.5 mmol/L and postdialysis serum potassium less than 3 mmol/L significantly decreased.Hypokalemia and fluctuations of serum potassium are common in MHD patients. KD 2.0 mmol/L dialysate should not be used for all patients, and individualized KD dialysate for patients with low serum potassium reduces the incidence of hypokalemia.

Perovskite/silicon tandem solar cell (TSC) is a promising strategy to receive high power conversion efficiency (PCE), exceeding the Shockley-Queisser (S-Q) limit of single junction SC. However, the reflected light still dominates the loss of photocurrent, happened at the surface and interface of two sub cells. Here, a suitable spacer layer is accepted to manage the light harvesting in the four-terminal (4T) perovskite/silicon TSC. The influence of microstructure, refractive index and thickness of spacer layer on the photocurrent has been systematically studied by the photoelectric simulation. And then the designed spacer layer is a double-side textured structure with a refractive index (RI) of 1.4 in 4 μm thickness, receiving the best light-harvesting to being the largest photocurrent. Furthermore, the relationship of light-absorption between perovskite and silicon SCs is investigated as a function of bandgap and thickness of perovskite, yielding the optimal photocurrent of 21.65 mA/cm2 and 19.71 mA/cm2 for top and bottom cells, respectively. Finally, four types of industrialized silicon SCs are integrated into the TSCs to study the photoelectric performance in detail, predicting the theoretical limitation PCE of 33.52%. Therefore, this simulated study provides a theoretical guide for the optical design of high-efficiency 4T TSCs.

BACKGROUND: Over the past decade, there has been a significant increase in research on the use of mobile health (mHealth) apps as disease management tools. However, very few apps are currently available for prostate cancer (PCa) patient management, and the available apps do not combine the needs of physicians with the requirements of patients. This study aimed to describe the development of a mHealth application for PCa survivors called RyPros, which includes dynamic visualization, intelligent reminders, and instant messaging to support decision-making regarding treatment and follow-up and test the initial accessibility and acceptability application. METHODS: The application was developed through a three-step procedure: logical structure design, application programming, and testing. Dynamic visualization, intelligent reminders, and instant messaging were the core functions of RyPros. Twenty-eight participants who had PCa were enrolled in four weeks of follow-up using the RyPros App. We initially evaluated participants’ acceptance of RyPros based on their use of the app (login data, questionnaire completion) and a satisfaction survey. RESULTS: We successfully designed and tested the application. A total of 32 participants were enrolled, of whom 28 completed the 4-week follow-up, yielding a participation rate of 87.5%. Each participant logged on an average of 2.82 times and achieved an average of 0.89 questionnaires per week over the four weeks. Most participants (64%) liked the app, and most participants (71%) were satisfied, giving the RyPros app a rating of 4 or 5. More than half of the participants (61%) intended to use the RyPros app regularly, and the majority of participants agreed that the three core functionalities of RyPros were helpful (20/28, 71% for instant messaging; 16/28, 57% for visualization; and 18/28, 64% for reminders and assessments). CONCLUSIONS: The mHealth application we developed for PCa survivor management provided dynamic visualization, reminders, assessments, and instant messaging to support decision-making based on multidisciplinary collaboration. PCa survivors showed high acceptance of the RyPros app.

The findings regarding the associations between red meat, fish and poultry consumption, and the metabolic syndrome (Mets) have been inconclusive, and evidence from Chinese populations is scarce. A cross-sectional study was performed to investigate the associations between red meat, fish and poultry consumption, and the prevalence of the Mets and its components among the residents of Suzhou Industrial Park, Suzhou, China. A total of 4424 participants were eligible for the analysis. A logistic regression model was used to estimate the OR and 95 % CI for the prevalence of the Mets and its components according to red meat, fish and poultry consumption. In addition, the data of our cross-sectional study were meta-analysed under a random effects model along with those of published observational studies to generate the summary relative risks (RR) of the associations between the highest v. lowest categories of red meat, fish and poultry consumption and the Mets and its components. In the cross-sectional study, the multivariable-adjusted OR for the highest v. lowest quartiles of consumption was 1·23 (95 % CI 1·02, 1·48) for red meat, 0·83 (95 % CI 0·72, 0·97) for fish and 0·93 (95 % CI 0·74, 1·18) for poultry. In the meta-analysis, the pooled RR for the highest v. lowest categories of consumption was 1·20 (95 % CI 1·06, 1·35) for red meat, 0·88 (95 % CI 0·81, 0·96) for fish and 0·97 (95 % CI 0·85, 1·10) for poultry. The findings of both cross-sectional studies and meta-analyses indicated that the association between fish consumption and the Mets may be partly driven by the inverse association of fish consumption with elevated TAG and reduced HDL-cholesterol and, to a lesser extent, fasting plasma glucose. No clear pattern of associations was observed between red meat or poultry consumption and the components of the Mets. The current findings add weight to the evidence that the Mets may be positively associated with red meat consumption, inversely associated with fish consumption and neutrally associated with poultry consumption.

Background Since the national big data strategy was unveiled at the fifth plenary session of the 18th CPC (Communist Party of China) Central Committee, the big data industry has been flourishing in China. Various successful industrial data governance systems have emerged with the rapid development of big data technologies and data management theories. City Brain and Enterprise Data Middle Platform are considered the best data governance systems in urban and corporate governance, respectively. However, in the health and medical sectors, issues of data operation occur frequently due to a lack of systematic data governance. These problems need to be urgently addressed, as health and medical data have been defined as national fundamental strategic resources. Clinical researchers have an increasing demand for data analysis. Methods Therefore, the Medical Data Governance System (MDGS) has been designed to improve data quality and provide simple and convenient data analysis tools for the National Clinical Research Center for Child Health. The MDGS consists of the Medical Data Platform (MDP) and Operation Management System (OMS). The MDP comprises acquisition layer, middle platform, and application layer that persistently elevates data quality and significantly shortens data analysis duration. Organization construction, management regulations, and technical standards are included in the OMS, which guarantees the sustainable operation of the MDGS. The MDGS was established to advance state-of-the-art and state-of-practice data governance for the health and medical sectors in China. Results With the first phase of the MDGS, the quantity and quality of research projects increase, research transformation speeds up, and the researchers' job satisfaction increased. Conclusions Based on our preliminary achievements, it was necessary and feasible to establish the MDGS. It is important to have comprehensive requirement study, top-level design, refined planning, phase-by-phase implementation, and continual optimization.

This letter investigates the resource allocation problem for multiple Unmanned Aerial Vehicles (UAVs)-served Machine-to-Machine (M2M) communications. Our goal is to maximize the sum-rate of UAVs-served M2M communications by jointly considering the transmission power, transmission mode, frequency spectrum, relay selection and the trajectory of UAVs. In order to model the uncertainty of stochastic environments, we formulate the resource allocation problem to be a Markov game, which is the generalization of Markov Decision Process (MDP) for the case of multiple agents. However, owning to the UAVs mobility poses the difficulty of perceiving the environment, we propose a Long Short-Term Memory (LSTM) with Generative Adversarial Networks (GANs) framework to better track and forecast the UAVs mobility and improving the network reward. Numerical results demonstrate that the proposed framework outperforms the conventional LSTM and Deep Q-Network (DQN) algorithms.

Urban infrastructure, a crucial part of the city, is being developed on a large scale under the rapid development of smart cities. The operation and maintenance (O&M) phase is increasingly complex, and the information to be processed is cumulatively massive. So, the significance of urban infrastructure O&M is gradually being realized by the public. Recently, research in Building Lifecycle Management (BLM) and Building Information Modeling (BIM) has partly improved technological innovation and management level of urban infrastructures O&M. However, there are still deficiencies in the research of BIM, VR/AR, internet of things, pervasive computing, big data, and other emerging technologies applied in urban infrastructure O&M, as well as the realization of intelligent service functions. Therefore, based on existing research and oriented to the development need of smart city, this chapter takes “intelligent service for urban infrastructure under the concept of lifecycle” as core to conduct a discussion on how to solve practical problems in the urban infrastructure O&M.

BACKGROUND The most common causes of outlet obstructive constipation (OOC) are rectocele and internal rectal prolapse. The surgical methods for OOC are diverse and difficult, and the postoperative complications and recurrence rate are high, which results in both physical and mental pain in patients. With the continuous deepening of the surgeon’s concept of minimally invasive surgery and continuous in-depth research on the mechanism of OOC, the treatment concepts and surgical methods are continuously improved. AIM To determine the efficacy of the TST36 stapler in the treatment of rectocele combined with internal rectal prolapse. METHODS From January 2017 to July 2019, 49 female patients with rectocele and internal rectal prolapse who met the inclusion criteria were selected for treatment using the TST36 stapler. RESULTS Forty-five patients were cured, 4 patients improved, and the cure rate was 92%. The postoperative obstructed defecation syndrome score, the defecation frequency score, time/straining intensity, and sensation of incomplete evacuation were significantly decreased compared with these parameters before treatment, and the differences were statistically significant (P < 0.05). The postoperative anal canal resting pressure and maximum squeeze pressure in patients decreased compared with before treatment, and the differences were statistically significant (P < 0.05). The initial and maximum defecation thresholds after surgery were significantly lower than those before treatment, and the differences were statistically significant (P < 0.05). The postoperative ratings of rectocele, resting phase, and defecation phase in these patients were significantly decreased compared with those before treatment, and the differences were statistically significant (P < 0.05). CONCLUSION The TST36 stapler is safe and effective in treating rectocele combined with internal rectal prolapse and is worth promoting in clinical work.

Objective:Chest tube drainage placement, a standard procedure in video-assisted thoracoscopic surgery, was reported to cause perioperative complications like pain and increased risk of infection. The present study was designed to evaluate the necessity of chest tube drainage inpaediatric thoracoscopic surgery.Methods:Thirty children admitted to our hospital from April 2018 to April 2020 were included in the current study and were grouped as the tube group (children receiving video-assisted thoracoscopic surgery with chest tube drainage) and the non-tube group (children receiving video-assisted thoracoscopic surgery without chest tube drainage). Laboratory hemogram index, length of hospitalisation, post-operative performance of involved children, and psychological acceptance of indicated therapy by guardians of the involved children were investigated.Results:Laboratory examination revealed that the mean corpuscular haemoglobin concentration in the non-tube group was significantly higher than that in the tube group on post-operative day 1 (p < 0.05). Children in the non-tube group had a shorter length of hospitalisation (7–9 days) than that of patients from the tube group. Additionally, the frequency of crying of children was decreased and psychological acceptance by patients’ guardians was improved in the non-tube group when compared with the tube group.Conclusion:This study showed that chest tube drainage placement may not be necessary in several cases of paediatric video-assisted thoracoscopic surgery. Rapid recovery with decreased perioperative complications in children operated by video-assisted thoracoscopic surgery without tube placement could also reduce the burden of the family and society both economically and psychologically.

BACKGROUND: Congenital hip dysplasia is a common limb deformity in infants and young children. This study aimed to clarify the feasibility of ultrasound Graf method in screening congenital hip dysplasia of infants and young children, and its application value in follow-up treatment. METHODS: A total of 1,313 infants and young children with clinically suspected congenital hip dysplasia in our hospital from December 2016 to January 2018 were selected as the participants and were examined by ultrasound Graf method. The acetabulum shape and the measured values of α and β angles of the participants were observed. The development of the hip joint and distribution of congenital hip dysplasia were analyzed, and the treatment effect was followed up. RESULTS: Among 1,313 infants and young children with suspected congenital hip dysplasia, the positive rate of congenital hip dysplasia was 6.02% (79/1,313). The lesions were located on both sides in 14 cases, on the left side in 67 cases, and on the right side in 26 cases. The α angle of cases with congenital hip dysplasia was significantly lower than that of normal cases, and the β angle was significantly higher than that of normal cases (P

The light spectrometer is one of the most widely used optical instruments, allowing users to measure and analyze spectral components. However, to reach a broad spectral response range, most spectrometers have to combine a silicon photodiode with an additional photodiode to account for the limited operating wavelength range of each in isolation. Here, we developed organic photodiodes (OPDs) by combining a novel narrow-bandgap non-fullerene acceptor (COTIC-4Cl) with a polymer donor (PCE10) in the presence of PC71BM as the third component. The resulting device based on the ternary blended material showed a wide spectral response from 300 to 1200 nm, beyond the response range of the traditional silicon-based photodiode. Moreover, at the wavelength of 1100 nm, the resulting OPD exhibited a specific detectivity of 5 × 1012 Jones and a responsivity of 0.3 A W−1, with a cut-off frequency of >1 MHz and a linear dynamic range of >120 dB, among the best performances of OPDs. Of particular importance is that, as a proof-of-concept, the resulting ternary OPD was successfully utilized as the key component of a spectrometer to measure the absorption across 300–1200 nm. These results indicate the potential applications of the broadband response OPDs for next-generation spectrometers.

Pseudomembranous laryngotracheobronchitis is rarely reported yet potentially life-threatening infectious cause of airway obstruction in children. The causative organisms of this condition are often considered to promote bacterial superinfection following viral infection. We report a case of pseudomembranous laryngotracheobronchitis in a patient caused by human bocavirus 1 and Mycoplasma pneumoniae (M. pneumoniae). A 2-year-old child was admitted to our hospital presenting with cough, hoarseness, and labored breathing. Computed tomography of the chest revealed atelectasis of the right middle lobe of the lung with bronchostenosis and occlusion. Laryngeal edema, pseudomembrane formation and ulceration of the trachea were found during bronchoscopy. Chronic inflammation of the mucosa and local cellulose exudation with acute and chronic inflammatory cell infiltration were confirmed by hematoxylin-eosin staining. Human bocavirus 1 and M. pneumoniae were detected in the bronchoalveolar lavage fluid by next-generation sequencing. The patient tested positive for IgM antibodies against M. pneumoniae. Bronchoscopy was performed three times to clear the secretions in the airway, and azithromycin, ceftriaxone, methylprednisolone, budesonide inhalation, and ambroxol were administered as treatment. The patient’s condition improved and she was discharged 21 days after admission. Clinicians should be aware of the potential involvement of human bocavirus 1 and M. pneumoniae in pseudomembranous laryngotracheobronchitis for accurate diagnosis and timely antibiotic administration, and to lower mortality and morbidity rates.

With the construction of smart cities entering a new phase, it is necessary to broaden the requirements of traditional roads to provide efficient operation and maintenance (OM (2) new Road Operation and Maintenance Functional Requirements (ROMFR) from the perspective of smart cities, which provide a complete definition of road intelligent OM and (3) based on ROMFR and a new generation of information technologies, the design and implementation of a system named RIOMS (Road intelligent operation and maintenance system) that supports the intelligent functional requirements. The proposed solution has been applied to Yanggao Road (Pudong New Area, Shanghai) as a case study to demonstrate its feasibility and validity. Specifically, the proposed ICT artifact has been utilized in handling typical scenarios of road O&M and its effectiveness has been assessed through survey questionnaire and smart city assessment system.

A controllable viewing angle optical film (CVOF) using a microprism array filled with liquid crystal is proposed, the display performance of small and large viewing angles can be tunable for liquid...

OBJECTIVE To assess the efficacy of intensive acupuncture (3 times weekly for 8 weeks) versus sham acupuncture for knee osteoarthritis (OA). METHODS In this multicenter, randomized, sham-controlled trial, patients with knee OA were randomly assigned to receive electroacupuncture (EA), manual acupuncture (MA), or sham acupuncture (SA) 3 times weekly for 8 weeks. Participants, outcome assessors, and statisticians were blinded with regard to treatment group assignment. The primary outcome measure was response rate, which is the proportion of participants who simultaneously achieved minimal clinically important improvement in pain and function by week 8. The primary analysis was conducted using a Z test for proportions in the modified intent-to-treat population, which included all randomized participants who had ≥1 post-baseline measurement. RESULTS Of the 480 participants recruited in the trial, 442 were evaluated for efficacy. The response rates at week 8 were 60.3% (91 of 151), 58.6% (85 of 145), and 47.3% (69 of 146) in the EA, MA, and SA groups, respectively. The between-group differences were 13.0% (97.5% confidence interval [97.5% CI] 0.2%, 25.9%; P = 0.0234) for EA versus SA and 11.3% (97.5% CI -1.6%, 24.4%; P = 0.0507) for MA versus SA. The response rates in the EA and MA groups were both significantly higher than those in the SA group at weeks 16 and 26. CONCLUSION Among patients with knee OA, intensive EA resulted in less pain and better function at week 8, compared with SA, and these effects persisted though week 26. Intensive MA had no benefit for knee OA at week 8, although it showed benefits during follow-up.

Reliability is a critical factor in designing of wireless body area networks. In this letter, we propose a resource scheduling strategy and solving an optimization problem to maximize the reliability of the transmission of emergency-critical sensory data. We jointly consider transmission mode, relay selection, time slot allocation, and transmit power of each body sensor and formulating the scheduling problem to be a Markov decision process. In this strategy, the scheduling decision is made by each body sensor that do not have complete and global network information. Owning to the formulated problem is nonconvex and the high computation complexity, we propose a deep reinforcement learning algorithm to solve the problem. Numerical results reveal that the proposed strategy is capacity of guaranteeing the reliability of transmission with an acceptable convergence speed.

With the increase in the installed capacity of wind power systems, the fault diagnosis and condition monitoring of wind turbines (WT) has attracted increasing attention. In recent years, machine learning (ML) has played a crucial role as an emerging technology for fault diagnosis in wind power systems has played a crucial role. Even though ML methods have shown great potential in dealing with the issues related to the fault diagnosis of WT, there are still some challenges encountered in many aspects. In this paper, typical fault diagnosis methods based on ML methods for wind power systems are thoroughly reviewed in terms of both theoretical fundamentals and industrial applications, including traditional machine learning (TML), artificial neural networks (ANN), deep learning (DL) and transfer learning (TL), in the development line of ML technologies. The advantages and disadvantages of various methods are analyzed and discussed. Meanwhile, a distribution diagram is provided for the discussions of ML methods applied for WT fault diagnosis, and the existing challenges on the applications for fault diagnosis based on ML for wind power generation systems are presented. Moreover, some prospects for future research directions are provided.

A brain-computer interface (BCI) measures and analyzes brain activity and converts this activity into computer commands to control external devices. In contrast to traditional BCIs that require a subject-specific calibration process before being operated, a subject-independent BCI learns a subject-independent model and eliminates subject-specific calibration for new users. However, building subject-independent BCIs remains difficult because electroencephalography (EEG) is highly noisy and varies by subject. In this study, we propose an invariant pattern learning method based on a convolutional neural network (CNN) and big EEG data for subject-independent P300 BCIs. The CNN was trained using EEG data from a large number of subjects, allowing it to extract subject-independent features and make predictions for new users. We collected EEG data from 200 subjects in a P300-based spelling task using two different types of amplifiers. The offline analysis showed that almost all subjects obtained significant cross-subject and cross-amplifier effects, with an average accuracy of more than 80%. Furthermore, more than half of the subjects achieved accuracies above 85%. These results indicated that our method was effective for building a subject-independent P300 BCI, with which more than 50% of users could achieve high accuracies without subject-specific calibration.

Background:. Although breast-conserving surgery is one of the standard treatments for breast cancer, few studies have assessed its recent implementation in China. We aimed to clarify the current real-world status of breast-conserving surgery in China. Methods:. This cross-sectional survey relied on data collected by the Chinese Society of Breast Surgery (CSBrS) to examine patients who underwent this surgery between January 2018 and December 2018. The survey was conducted using a uniform electronic questionnaire to collect information, including clinical and pathological data on these patients. Results:. Overall, 4459 breast-conserving surgeries were performed in 34 member units of CSBrS, accounting for 14.6% of all breast cancer surgeries performed in these units during the study period. In patients who underwent breast-conserving surgery with information on tumor size available, more than half (61.2%) of the tumors were smaller than 2 cm in diameter, and only 87 (3.2%) tumors were larger than 4 cm in diameter. Among patients who underwent breast-conserving surgeries, 457 (10.2%) patients received neoadjuvant therapy before the surgery. Among patients with a reported margin width, 34 (2.0%) patients had a margin of ≤2 mm, and 1530 (88.2%) of them had a margin of >5 mm. Conclusions:. This study demonstrated the rates of breast-conserving surgery in member units of the CSBrS, and introduced the characteristics and surgical margins of patients who underwent this surgery. This information helps describe the real-world status of breast-conserving surgery in China. Trial registration. chictr.org.cn, ChiCTR1900026841; http://www.chictr.org.cn/showproj.aspx?proj=42783

The long non-coding RNA antisense 1 ADAMTS9-AS1 has been reported to predict the survival in several tumors, including bladder cancer and breast cancer. However, the clinical significance and biological behaviors of ADAMTS9-AS1 in colorectal cancer (CRC) have not been reported yet. In this study, the expression of ADAMTS9-AS1 was measured in CRC tissues and cell lines using quantitative real-time PCR analysis. The clinical significance of ADAMTS9-AS1 was evaluated with Chi-squared test, Kaplan-Meier method and Cox regression analysis in CRC patients. CCK8 assay, colony formation assay, flow cytometry and transwell assay were used to explore the biological function of ADAMTS9-AS1 knockdown in CRC cell lines (SW1116 and HT29). We further explore the role of ADAMTS9-AS1 in vivo though xenograft tumor assay. Our data showed that ADAMTS9-AS1 expression level was significantly up-regulated in CRC tissues and cell lines compared with corresponding controls. High ADAMTS9-AS1 level was associated with TNM stage, lymph node invasion and worse survival prognosis. Depletion of ADAMTS9-AS1 significantly suppressed cell proliferation, G1/S transition, migration and invasion, as well as suppressed CDK4/Cyclin D1 and epithelial-mesenchymal transition (EMT). To sum up, these findings illustrated that ADAMTS9-AS1 might be a promising therapeutic target and prognostic factor for CRC.

Perovskite solar cell (PSC) is a promising candidate of tandem solar cells (TSCs), especially as the top cell in perovskite/Si TSCs due to the easily tunable energy bandgap. However, the deposition...

The anode interlayer plays a critical role in the performance of organic photodetectors, which requires sufficient electron-blocking ability to simultaneously attain a high photocurrent and low dark current. Here, we developed two cross-linkable polymers, which can be deposited on the top of the widely used poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) and form a robust layer that can effectively suppress the electron injection from the anode under reverse bias. The optimized device with the resulting cross-linkable XP2 exhibited the lowest dark current density of 5.81 × 10-9 A cm-2 at -0.1 V, which is about 2 orders of magnitude lower than the control devices. A remarkable responsivity of 0.5 A W-1 and a detectivity of >1 × 1013 Jones at a near-infrared wavelength of 800 nm were achieved. Of particular importance is that the resulting device exhibited a linear dynamic range of >135 dB associated with a high working frequency that is shorter than typical commercial digital imagers. The planar heterojunction devices demonstrate that the dark current is closely correlated to the charge generation, which relied on the highest occupied molecular orbital energy levels of the developed cross-linked interlays. The Mott-Schottky analysis revealed that the optimized cross-linked interlayer increased the depletion width of the devices.

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. This work reports a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

Spatiotemporal alignment is a critical problem in video-based person re-identification (re-id) tasks. To address this problem, we propose a pose-guided spatiotemporal alignment (PISA) method to align video sequences for video-based person re-id. First, to perform precise temporal alignment, we align a video sequence to a series of image sets, corresponding to a series of reference pedestrian poses. Each image set is obtained by selecting the images with the same pose and high quality. Furthermore, to perform spatial alignment, we decompose a pedestrian image into human body parts, and accordingly compute the representations over the parts. Finally, we evaluate the similarity between two video sequences by aggregating the distances of the pose-corresponded image sets rather than all pairs. The experimental results on two public datasets show that the proposed method performs favorably against state-of-the-art methods, even deep learning-based approaches.

Background and purpose Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is the most-common form of autoimmune encephalitis, but its early diagnosis is challenging. This study aimed to identify the risk factors for a poor prognosis in anti-NMDAR encephalitis and construct a prognostic composite score for obtaining earlier predictions of a poor prognosis. Methods We retrospectively analyzed the clinical data, laboratory indexes, imaging findings, and electroencephalogram (EEG) data of 60 patients with anti-NMDAR encephalitis. The modified Rankin Scale (mRS) scores of patients were collected when they were discharged from the hospital. The mRS scores were used to divide the patients into two groups, with mRS scores of 3-6 defined as a poor prognosis. Logistic regression analysis was used to analyze independent risk factors related to a poor prognosis. Results This study found that 23 (38.3%) and 37 (61.7%) patients had good and poor prognoses, respectively. Logistic regression analysis showed that age, disturbance of consciousness at admission, and ≥50% slow waves on the EEG were significantly associated with patient outcomes. An age, consciousness, and slow waves (ACS) composite score was constructed to predict the prognosis of patients with anti-NMDAR encephalitis at an early stage based on regression coefficients. Conclusions Age, disturbance of consciousness at admission, and ≥50% slow waves on the EEG were independent risk factors for a poor prognosis. The ACS prognostic composite score could play a role in facilitating early predictions of the prognosis of anti-NMDAR encephalitis.

Liangshan Prefecture, the highest HIV-affected epidemic region in China, has more than 2.5 million Yi people. We firstly investigated the sexual behaviors and the related social determinants of health for HIV infection in Yi women of childbearing age in this area. A total of 800 Yi women of childbearing age were enrolled. Path analysis of the risk factors revealed that casual sex (0.152) and number of sex partners (0.152) were directly associated with HIV infection. Furthermore, education level (0.057), out-migrating for work (0.032), sense of self-worth (0.024) and number of sex partners (0.079) were indirectly related to HIV infection and mediated by casual sex and multiple sexual partners. The epidemic of HIV infection among Yi women of childbearing age in Liangshan Prefecture is serious, future promotion should increase their knowledge about condom and modify their perceptions of sexual behaviors.

A fast handover authentication protocol takes an important role for delay-sensitive applications in wireless networks. Mobile users may be granted different priorities depending on communication fees they paid. In this paper, we present a priority-aware anonymous handover authentication protocol using attribute-based cryptography. The proposed protocol realizes mutual authentication, user anonymity, session key establishment and user revocation etc. Particularly it obtains a charming property, namely, user priority. Compared with some existing schemes, it is more efficient while satisfying security.

Gut microbiota in fish plays an important role in the nutrient digestion, immune responses and disease resistance. To understand the effect of fluoroquinolone antibiotic bath administration on fish gut microbiota, the gut microbiota community in the coral trout Plectropomus leopardus (Lacepède, 1802) was studied after enrofloxacin bathing treatment at two concentrations (5 and 10 mg/L) and 0 mg/L as control. A total of 90 fish were used in this study, and three replicates were used for each treatment. After a 24‐hr bath, the gut bacterial composition was analyzed using high‐throughput Illumina sequencing. The results indicated that the richness, diversity and the dominant bacterial taxa of P. leopardus gut bacteria were not affected by enrofloxacin bathing (p > .05). Proteobacteria and Firmicutes were the dominant phyla, and Exiguobacterium, Citrobacter, Vibrio, Acinetobacter, Pseudomonas were the dominant genus. The findings in the present study provide an understanding on the relationship between fish gut bacteria community and antibiotic bath administration. The findings of this study are instructive on the antibiotic bath administration applied for the management of P. leopardus health in aquaculture., The gut microbiota community in the coral trout Plectropomus leopardus (Lacepède, 1802) was studied after enrofloxacin bathing treatment at two concentrations (5 and 10 mg/L) and 0 mg/L as control. After a 24‐hr bath, the gut bacterial composition was analyzed using high‐throughput Illumina sequencing. The results indicated that the richness, diversity and the dominant bacterial taxa of P. leopardus gut bacteria were not affected by enrofloxacin bathing (p > .05).

Background/Aims: Esophageal squamous cell carcinoma is a common malignant tumor in recent years, and the key for improving the survival rate is early diagnosis and treatment. Computed virtual chromoendoscopy with the Fujinon intelligent color enhancement (FICE) system was reported to improve visualization of neoplastic and nonneoplastic lesions in gastroscopy and colonoscopy. The purpose of this study was to evaluate the value of FICE in the diagnosis of early esophageal squamous cell carcinoma and precancerous lesions. Materials and Methods: Two hundred fifty-seven patients with suspicious lesions of the esophagus were examined successively by FICE, magnifying FICE, Lugol chromoendoscopy, and magnifying Lugol chromoendoscopy in the hospital. The lesions and the intrapapillary capillary loop (IPCL, microvessels at the surface of esophageal carcinoma) were observed and compared with the pathologic diagnosis that was regarded as the golden standard. Results: The positive rates of early esophageal squamous cell carcinoma were 92.6% and 88.9% as examined by FICE and Lugol chromoendoscopy (p>0.05), and 96.3% and 92.6% as examined by magnifying FICE and magnifying Lugol chromoendoscopy (p>0.05), respectively. The magnifying FICE could observe the IPCL of the esophagus clearly. Early esophageal squamous cell carcinoma and high-grade intraepithelial neoplasia were mainly type IV and type V. Low-grade intraepithelial neoplasia and esophagitis were type II and type III, and normal esophagus was type I; however, the observation of the IPCL by magnifying Lugol chromoendoscopy was not clear. Conclusion: Fujinon intelligent color enhancement and magnifying FICE are complements to Lugol chromoendoscopy and magnifying Lugol chromoendoscopy in the diagnosis of early esophageal lesions.

We report a simple means to build a model atomic force microscope (AFM) using 3D printing of thermoplastic materials that are commercially available. The model has many of the key parts of an actual AFM including a z-axis stage, an AFM head with a cantilever assembly, and a laser source that reflects off of the back of the cantilever. Using a magnet attached to the tip of the cantilever and a metal sample, this model AFM enables acquisition of force–distance profiles with characteristic snap-in, pull-off, separate, and contact regions. The model AFM was designed, printed, and used by first- and second-year undergraduate students. Through completion of this project, students learned scientific instrument design and construction via 3D printing and obtained first-hand practice in the measurement of force–distance profiles and the elastic constants of cantilevers. The open design of the model can easily accommodate additional capabilities in which students are interested, e.g., topographical scanning and using cantilevers made from different materials.

Liangshan Yi Autonomous Prefecture in Southwest China has a high human immunodeficiency virus (HIV) prevalence rate. This study examined the changing modes of HIV transmission among women with new HIV infections and explored the spatial heterogeneities in the factors associated with heterosexual transmission in this minority region. The data consisting of women with new HIV infections from 2011 to 2014 were collected from multiple sources. New infections were identified by BED capture enzyme immunoassay. The Bayesian hierarchical model was used to estimate the proportion of women with new HIV infections via heterosexual transmission across all townships in the Prefecture. A geographically weighted regression (GWR) model was utilized to investigate spatial variations in the sociodemographic characteristics associated with the changing modes of HIV transmission. An analytical sample of 927 women with new HIV infections was constructed and utilized to investigate the changing mode of HIV transmission. The rate of heterosexual transmission among women with new HIV infections in 2011 was below 20%. However, by 2014 this rate dramatically increased to nearly 80%. Among sociodemographic characteristics, GWR results revealed significant ethnic differences in heterosexual HIV transmission between Yi women and women in other ethnic groups, with Yi women demonstrating a lower risk of infection through heterosexual transmission. However, such ethnic differences were observed only in 30% of the townships in the Prefecture. Moreover, having a primary education decreased the odds of heterosexual transmission, which was observed in about 56% of the townships. Also, being involved in occupations other than agriculture or animal husbandry and being single or married decreased the odds of HIV infection through heterosexual contact among women, which did not significantly vary across the Prefecture. Heterosexual transmission was the predominant mode of HIV transmission among women in the Prefecture, and this transformation was clearly marked by a fast-growing trend and a spatial diffusion pattern. Spatial variations also existed in sociodemographic factors that were associated with the changing modes of HIV transmission.

At present, natural orifice specimen extraction surgery (NOSES) has attracted more and more attention worldwide, because of its great advantages including minimal cutaneous trauma and post-operative pain, fast post-operative recovery, short hospital stay, and positive psychological impact. However, NOSES for the treatment of gastric cancer (GC) is still in its infancy, and there is great potential to improve its theoretical system and clinical practice. Especially, several key points including oncological outcomes, bacteriological concerns, indication selection, and standardized surgical procedures are raised with this innovative technique. Therefore, it is necessary to achieve an international consensus to regulate the implementation of GC-NOSES, which is of great significance for healthy and orderly development of NOSES worldwide.

The association between milk consumption and the metabolic syndrome remains inconclusive, and data from Chinese populations are scarce. We conducted a cross-sectional study to investigate the association between milk consumption and the metabolic syndrome and its components among the residents of Suzhou Industrial Park, Suzhou, China. A total of 5149 participants were included in the final analysis. A logistic regression model was applied to estimate the OR and 95 % CI for the prevalence of the metabolic syndrome and its components according to milk consumption. In addition, the results of our study were further meta-analysed with other published observational studies to quantify the association between the highest v. lowest categories of milk consumption and the metabolic syndrome and its components. There was no significant difference in the odds of having the metabolic syndrome between milk consumers and non-milk consumers (OR 0·86, 95 % CI 0·73, 1·01). However, milk consumers had lower odds of having elevated waist circumference (OR 0·78, 95 % CI 0·67, 0·92), elevated TAG (OR 0·83, 95 % CI 0·70, 0·99) and elevated blood pressure (OR 0·85, 95 % CI 0·73, 0·99). When the results were pooled together with other published studies, higher milk consumption was inversely associated with the risk of the metabolic syndrome (relative risk 0·80, 95 % CI 0·72, 0·88) and its components (except elevated fasting blood glucose); however, these results should be treated with caution as high heterogeneity was observed. In summary, the currently available evidence from observational studies suggests that higher milk consumption may be inversely associated with the metabolic syndrome.

Several difficult-to-measure production qualities or environment pollution indices of industrial process must be measured using offline laboratory instruments. Soft measurement method is often used to perform online prediction of such parameters. Only small-sample modeling data with high-dimensional input features can be obtained due to the limitations and complex characteristics of the measurement device and process, respectively. Therefore, a new multisource latent feature selective ensemble (SEN) modeling approach is proposed in this study. First, input features are divided into different subgroups according to the characteristics of the modeling data. Second, the extracted multisource latent features evolve from the multi-layered selection algorithms, which are specified by feature reduction ratio, feature contribution ratio and mutual information value orderly for each subgroup. Finally, in order to construct candidate sub-models, an adaptive hyper-parameter selection algorithm based on the multi-step grid search is employed in terms of the reduced features. Sequentially, the optimized ensemble submodels with their weighting strategies are adaptively determined to build the final SEN model. The proposed method is verified by using benchmark near-infrared data, high dimensional mechanical frequency spectrum data and industrial dioxin emission concentration data.

The difference of the aerodynamic influence of two engine models – the Flow Through Nacelle (FTN) and With Powered Nacelle (WPN) – on BWB300 airframe is analyzed by using the 3-D unsteady compressible Reynolds-Averaged Navier-Stokes (RANS) computation. The results indicate that at cruise condition, the engine shape is a primary factor affecting the BWB airframe upper fuselage surface flow, the two engine models exhibit a similar aerodynamic influence on the BWB airframe. However, at takeoff condition, the two engine models’ aerodynamic influence on the airframe is different, because of the air suction caused by the WPN engine model affecting the airframe upper fuselage surface flow obviously. Moreover, at both cruise and takeoff conditions, the tube formed by the engine and airframe shape changes the surface flow under the engine and the air suction caused by the engine power accelerates the surface flow near the engine.

Instance segmentation is a challenging computer vision problem which lies at the intersection of object detection and semantic segmentation. Motivated by plant image analysis in the context of plant phenotyping, a recently emerging application field of computer vision, this paper presents the Exemplar-Based Recursive Instance Segmentation (ERIS) framework. A three-layer probabilistic model is firstly introduced to jointly represent hypotheses, voting elements, instance labels and their connections. Afterwards, a recursive optimization algorithm is developed to infer the maximum a posteriori (MAP) solution, which handles one instance at a time by alternating among the three steps of detection, segmentation and update. The proposed ERIS framework departs from previous works mainly in two respects. First, it is exemplar-based and model-free, which can achieve instance-level segmentation of a specific object class given only a handful of (typically less than 10) annotated exemplars. Such a merit enables its use in case that no massive manually-labeled data is available for training strong classification models, as required by most existing methods. Second, instead of attempting to infer the solution in a single shot, which suffers from extremely high computational complexity, our recursive optimization strategy allows for reasonably efficient MAP-inference in full hypothesis space. The ERIS framework is substantialized for the specific application of plant leaf segmentation in this work. Experiments are conducted on public benchmarks to demonstrate the superiority of our method in both effectiveness and efficiency in comparison with the state-of-the-art.

Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma, and immune-related genes (IRGs) are key contributors to its development. In this study, the gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database and the cBioPortal database, respectively. IRGs were obtained from the ImmPort database. We analyzed the expression of IRGs in ccRCC, and discovered 681 that were differentially expressed between ccRCC and normal kidney tissues. Univariate Cox regression analysis was used to identify prognostic differentially expressed IRGs (PDEIRGs). Using Lasso regression and multivariate Cox regression analyses, we detected seven optimal PDEIRGs (PLAU, ISG15, IRF9, ARG2, RNASE2, SEMA3G and UCN) and used them to construct a risk model to predict the prognosis of ccRCC patients. This model accurately stratified patients with different survival outcomes and precisely identified patients with different mutation burdens. Our findings suggest the seven PDEIRGs identified in this study are valuable prognostic predictors in ccRCC patients. These genes could be used to investigate the developmental mechanisms of ccRCC and to design individualized treatments for ccRCC patients.

The aim of this study was to introduce a method to evaluate the risk of inferior alveolar nerve (IAN) injury following the extraction of impacted lower third molars. Two hundred impacted lower third molars adjacent to the IAN were evaluated. These were divided into four classification groups according to preoperative cone beam computed tomography (CBCT) findings: AR, apical region; LT, lateral region of the tapered root; LE, lateral region of the enlarged root; AE, adjacent to the enlarged root. All teeth were dislocated along the long axis or arc of the root by tooth sectioning technique and extracted by a single surgeon. The primary outcome variable was postoperative neurosensory impairment of the IAN. The χ2 test was used to evaluate differences in postoperative IAN injury between the classifications. Logistic regression analysis was used to evaluate the risk factors for postoperative IAN injury. The overall incidence of postoperative IAN injury was 7%. Specifically, most injuries involved classification AE (AE 36%, LE 8.6%, LT 3.6%, AR 0%), and the difference was statistically significant (P< 0.05). Logistic regression showed that classification AE was the only risk factor for postoperative IAN injury (P< 0.001). According to preoperative CBCT, the risk of postoperative IAN injury is higher when the IAN is adjacent to the enlarged part of the root.

Background Although the anatomic difficulties of laparoscopic surgery for rectal cancer have been resolved by hybrid transanal total mesorectal excision (h-taTME), a completely incisionless surgical procedure has not yet been developed. This study was performed to explore the efficacy of pure taTME (p-taTME) without laparoscopic assistance as a completely non-invasive surgical procedure for rectal cancer. Methods We retrospectively evaluated all patients with rectal cancer who underwent p-taTME between December 2015 and April 2018. Relevant patient characteristics and clinical information including the surgical procedure, specimens, pathological characteristics, and patients’ post-operative state were analysed and the feasibility of p-taTME in patients with rectal cancer was assessed. Results Fifty-five patients who had undergone p-taTME were included in this study. They comprised 32 (58.2%) men and 23 (41.8%) women with a mean age of 65.6 ± 10.6 years and mean body mass index of 23.4 ± 3.3 kg/m2. The median surgical time was 180.0 (range, 130–360) min and estimated blood loss was 25.0 (range, 15–80) mL. The commonest post-operative complication was varying degrees of faecal incontinence (56.4%). However, such incontinence greatly improved after pelvic-floor-function-rehabilitation exercises and did not seriously affect the patients’ quality of life. Conclusions p-taTME is a relatively safe and incisionless procedure for patients with middle and low rectal cancer, especially in those with obesity or a narrow pelvis. However, further studies of the indications and long-term efficacy are needed to verify the suitability of this procedure.

Two-dimensional (2D) van der Waals materials and related heterostructures have shown a wide variety of novel electronic and optoelectronic properties. However, a key challenge in fully realizing th...

This paper focuses on a new method for brain tumor segmentation in Magnetic Resonance Imaging (MRI), using a modified residual block and CBAM for the U-Net network. To deepen the network, we replace the convolutional layer with a residual block with a CBAM module. We also insert the CBAM dual-attention module after skip connection and upsampling at each layer. It solves the problem that the low-level features contain a lot of redundant information because the skip connection connects the feature maps extracted by the encoder directly to the corresponding layer of the decoder. The performance is evaluated on the MRI dataset of Medical Image Computing and Computer Aided Intervention Society (MICCAI) 2018 Brain Tumor Segmentation Challenge. Numerical results are presented in the form of Specifity, Sensitivity, HD_95 and Dice coefficient (DICE) for GD-enhancing tumor (ET), tumor core (TC) and whole tumor (WT), respectively. We compare the proposed method with expert manual method and other state-of- art methods. Experiments show that RDAU-Net achieves state-of-the-art performance.

Objectives: To develop and validate the model for distinguishing brain abscess from cystic glioma by combining deep transfer learning (DTL) features and hand-crafted radiomics (HCR) features in conventional T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI).Methods: This single-center retrospective analysis involved 188 patients with pathologically proven brain abscess (102) or cystic glioma (86). One thousand DTL and 105 HCR features were extracted from the T1WI and T2WI of the patients. Three feature selection methods and four classifiers, such as k-nearest neighbors (KNN), random forest classifier (RFC), logistic regression (LR), and support vector machine (SVM), for distinguishing brain abscess from cystic glioma were compared. The best feature combination and classifier were chosen according to the quantitative metrics including area under the curve (AUC), Youden Index, and accuracy.Results: In most cases, deep learning-based radiomics (DLR) features, i.e., DTL features combined with HCR features, contributed to a higher accuracy than HCR and DTL features alone for distinguishing brain abscesses from cystic gliomas. The AUC values of the model established, based on the DLR features in T2WI, were 0.86 (95% CI: 0.81, 0.91) in the training cohort and 0.85 (95% CI: 0.75, 0.95) in the test cohort, respectively.Conclusions: The model established with the DLR features can distinguish brain abscess from cystic glioma efficiently, providing a useful, inexpensive, convenient, and non-invasive method for differential diagnosis. This is the first time that conventional MRI radiomics is applied to identify these diseases. Also, the combination of HCR and DTL features can lead to get impressive performance.