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Mg alloys are considered the most promising engineering materials because of their unique properties. However, the uncontrolled corrosion rate of these alloys limits their applications. Therefore, in this study, a micro-arc oxidation layer was used as a transition layer to “directly” grow a zinc-based metal-organic framework (MOF) composite coating on the surface of a Mg alloy (AZ91D). Herein, the two zeolitic imidazolate framework (ZIF-8) coatings with different morphologies were separately prepared by homologous metal oxide induction and a one-step in-situ growth method. The superhydrophobic composite coating showed strong hydrophobicity and self-cleaning properties, which could prevent the penetration of water and corrosive ions (Cl−) into the surface of AZ91D. Electrochemical tests demonstrated that the super-hydrophobic composite coatings greatly enhanced the corrosion resistance of AZ91D, and the corrosion current density decreased from 10−5 to 10−9 A/cm2. These results indicate that the ZIF-8 coatings are beneficial for improving the hydrophobicity and enhancing the corrosion resistance of Mg alloys. Therefore, MOF composite coatings provide a new strategy that can be used to prepare multifunctional anticorrosion coatings on metal substrates.

Objective. To investigate patients’ preference and the attitude towards physician attire in an internal medicine clinic in China. Methods. This study was conducted from 1 January 2021 to 30 June 2021 in a tertiary care hospital in China. We surveyed 126 patients in the hospital with 6 sets of pictures of commonly worn physician attires in the hospital setting with a two-part questionnaire. The first part listed respondent demographics to collect basic information. The second part of the questionnaire was administered to adult patients who received care in the internal medicine clinics (outpatients). Survey forms collected demographic data (age, gender, patient age, education, marital status, and employment status), asked questions regarding 6 specific attires (scrubs, scrubs and white coat, casual, casual and white coat, business suit, and formal and white coat), and behavioral items (professional, responsible, reliable, knowledgeable, succession rate, and medical safety), finally, to assess the preference of attire on overall perception. Results. Scrubs and white coat scored the highest through 6 domains about physicians’ attire (professional, reliable, responsible, knowledgeable, medical safety, and succession rate, p < 0.05 for all comparisons). A casual suit without a white coat was the least preferred across the surveyed attributes. There was a significant preference gap between wearing a white coat and not wearing a white coat ( p < 0.001 ). Physician attire to white coat was considered as more professional, reliable, responsible, knowledgeable, having greater medical safety, and a higher success rate than attires without white coat. Conclusion. Patients felt that the physician wearing a white coat was better than other attires. Scrubs and white coat was the most popular attire. Hospital or related authorities may promote the standardized wearing of white coats, leading in a greater patient-physician relationship.

A surface engineering strategy to form a highly active Fe–Ni structure on the surfaces of Ni-based catalysts. The surface Fe is readily oxidized under OER conditions, compensating for the charges of Ni and increasing the activity of Ni active sites.

Inspired by siderophores, a new two-dimensional MOF with homoleptic Fe-tri(hydroxamate) nodes is reported, featuring chemical stability and electrochemical H2O2-sensing potentials.

Discrimination of semantic textual similarity refers to comparing the similarity between two or more entities (including words, short texts and documents) through certain strategies to obtain a specific quantitative similarity value. Traditional research put more experience into the similarity calculation of the original text content, using the matching degree or distance of characters or words as the yardstick to judge whether the text pairs are similar. However, there are still some problems to be solved in the following aspects: the key points of sentence meaning and word semantics, which play important role in the semantic expression of natural language, are not well integrated into the similarity discrimination, and the interactive features between texts are not fully utilized. To solve the above problems, this paper proposes a novel discrimination structure based on the Siamese Network model and the idea of text matching. In this structure, we introduce sentence meaning key information and word semantic information to realize the extraction of word interaction feature information, and then we realize the text vector representation by using Siamese BiLSTM. The experimental results showed that the accuracy of the proposed model is higher than that of the basic models. &nbsp

Existing learning-based point feature descriptors are usually task-agnostic, which pursue describing the individual 3D point clouds as accurate as possible. However, the matching task aims at describing the corresponding points consistently across different 3D point clouds. Therefore these too accurate features may play a counterproductive role due to the inconsistent point feature representations of correspondences caused by the unpredictable noise, partiality, deformation, \etc, in the local geometry. In this paper, we propose to learn a robust task-specific feature descriptor to consistently describe the correct point correspondence under interference. Born with an Encoder and a Dynamic Fusion module, our method EDFNet develops from two aspects. First, we augment the matchability of correspondences by utilizing their repetitive local structure. To this end, a special encoder is designed to exploit two input point clouds jointly for each point descriptor. It not only captures the local geometry of each point in the current point cloud by convolution, but also exploits the repetitive structure from paired point cloud by Transformer. Second, we propose a dynamical fusion module to jointly use different scale features. There is an inevitable struggle between robustness and discriminativeness of the single scale feature. Specifically, the small scale feature is robust since little interference exists in this small receptive field. But it is not sufficiently discriminative as there are many repetitive local structures within a point cloud. Thus the resultant descriptors will lead to many incorrect matches. In contrast, the large scale feature is more discriminative by integrating more neighborhood information. ..., Comment: Accepted to IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) 2022

The Richards’ equation describes the flow phenomenon in unsaturated porous media and is essential to hydrology and environmental science. This study evaluated the numerical stability of two different forms of the Richards’ equation. Sensitivity analyses were performed to investigate the control parameters of the equation. The results show that the h-form Richards’ equation has better applicability for calculating variable saturation flows than the θ-form Richards’ equation. For the h-form Richards’ equation, the hydraulic conductivity of the soil in the low-suction range and the specific moisture capacity in the high-suction range primarily influenced the solution. In addition, sensitivity analyses indicated that the saturated hydraulic conductivity, initial condition, and air-entry pressure have a higher sensitivity to the simulation results than the saturated water content, rainfall intensity, and decline rate of hydraulic conductivity. Moreover, their correctness needs to be guaranteed first in numerical simulations. The research findings can provide a helpful reference for improving the reliability of numerical simulations of unsaturated flows.

Tilmicosin, as an effective broad-spectrum antibacterial drug, has incomplete absorption and low bioavailability due to its low water solubility, which limits its veterinary clinical applications. As a non-polymeric drug carrier, γ-cyclodextrin was complexed with tilmicosin through supercritical carbon dioxide assistance for the first time, and confirmed by FTIR, X-ray diffraction, proton NMR and scanning electron microscopy. The water solubility of tilmicosin was increased 57-fold through complexation with γ-cyclodextrin, and the release and bioavailability of tilmicosin in the complex were significantly improved. The tilmicosin in complex showed better anti-Streptococcus agalactiae activity than that of tilmicosin alone in MIC, MBC and drug susceptibility studies.

Background Currently, the rate of recurrence or metastasis (ROM) remains high in rectal cancer (RC) patients treated with the standard regimen. The potential of diffusion-weighted imaging (DWI) in predicting ROM risk has been reported, but the efficacy is insufficient. Aims This study investigated the potential of a new sequence called readout-segmented echo-planar imaging (RS-EPI) DWI in predicting the ROM risk of patients with RC using machine learning methods to achieve the principle of predictive, preventive, and personalized medicine (PPPM) application in RC treatment. Methods A total of 195 RC patients from two centres who directly received total mesorectal excision were retrospectively enrolled in our study. Machine learning methods, including recursive feature elimination (RFE), the synthetic minority oversampling technique (SMOTE), and the support vector machine (SVM) classifier, were used to construct models based on clinical-pathological factors (clinical model), radiomic features from RS-EPI DWI (radiomics model), and their combination (merged model). The Harrell concordance index (C-index) and the area under the time-dependent receiver operating characteristic curve (AUC) were calculated to evaluate the predictive performance at 1 year, 3 years, and 5 years. Kaplan‒Meier analysis was performed to evaluate the ability to stratify patients according to the risk of ROM. Findings The merged model performed well in predicting tumour ROM in patients with RC at 1 year, 3 years, and 5 years in both cohorts (AUC = 0.887/0.813/0.794; 0.819/0.795/0.783) and was significantly superior to the clinical model (AUC = 0.87 [95% CI: 0.80–0.93] vs. 0.71 [95% CI: 0.59–0.81], p = 0.009; C-index = 0.83 [95% CI: 0.76–0.90] vs. 0.68 [95% CI: 0.56–0.79], p = 0.002). It also had a significant ability to differentiate patients with a high and low risk of ROM (HR = 12.189 [95% CI: 4.976–29.853], p p = 0.002). Conclusion Our developed merged model based on RS-EPI DWI accurately predicted and effectively stratified patients with RC according to the ROM risk at an early stage with an individualized profile, which may be able to assist physicians in individualizing the treatment protocols and promote a meaningful paradigm shift in RC treatment from traditional reactive medicine to PPPM.

Anoikis resistance is a prerequisite for circulating tumor cells to survive. However, the mechanism underlying anoikis resistance is poorly understood. In the current study, the effect of TNF receptor–associated factor 6 (TRAF6)-induced NF-kB activation on anoikis susceptibility in tumor cells was evaluated. Differential TRAF6-binding proteins in anoikis-sensitive versus anoikis-resistant tumor cells were screened by LC/MS-MS analysis. The effects of TRAF6-binding proteins on the stability of TRAF6, the activation of NF-kB signaling and anoikis susceptibility in tumor cells were detected. We found that the loss of TRAF6 expression is an important molecular event linked to anoikis. X-linked inhibitor of apoptosis protein (XIAP), an E3 ligase, can bind, ubiquitinate, and degrade TRAF6 and may lead to inactivation of NF-κB signaling and anoikis sensitivity. High expression of prohibitin 1 (PHB1) competes with XIAP for binding to TRAF6 and confers anoikis resistance to tumor cells. PHB1 and TRAF6 knockdown eliminated tumor cells from the circulation in vivo. Significant correlations between elevated PHB1 and TRAF6 expression and distant metastasis were observed in patients with oral cancer. Collectively, we elucidated a novel mechanism governing anoikis. Our data also indicated that TRAF6 and PHB1 are potential therapeutic targets for tumor cells disseminating in the circulation. Implications: Our data implicate that PHB1 competes with XIAP for binding to TRAF6 and confers anoikis resistance to tumor cells.

In recent years, gas-insulated switchgear (GIS) substations have become widely used in power systems. Due to their compact structure, extremely high oscillation frequencies are prone to extremely high oscillation transient overvoltages or very fast transient overvoltages (VFTOs) when the isolating switch or circuit breaker is operated. The characteristics of these special fast transient processes in GIS and the effect of hybrid reactive power compensation (HRPC) on these fast transient processes were studied. A simulation of the GIS model was established, and based on the transient model of HRPC and the theory of the transmission line, the effects of VFTO produced by HRPC switching operation and the parameters of HRPC on VFTO were studied and the differences in the characteristics of VFTOs in substations with or without HRPC. Based on the conclusions of our study on the influence of HRPC on VFTO, the inhibitory effects of a ferrite magnet ring and an inhibitor busbar on VFTO were verified.

A simple non-isocyanate route is established to synthesize biobased aliphatic thermoplastic polyurethane elastomers (TPEUs) with excellent mechanical properties. Melt transurethane co-polycondensation of bis(hydroxyethyl) butanediurethane (BHBDU) with different polycaprolactone-diols (PCDLs) was conducted at 170°C under a reduced pressure of 3 mmHg, and a series of TPEUs were prepared. The TPEUs were characterized by gel permeation chromatography, FT-IR, 1H-NMR, wide angle X-ray scattering, DSC, TGA, dynamic mechanical analysis, atomic force microscopy, and tensile test. TPUEs exhibited Mn above 25,000 g/mol, Tg of −36 to 1°C, Tm up to 105°C, maximal tensile strength of 38 MPa with a strain at break of 926%, and resilience of 80%–90%. BHBDU and PCDLs may be synthesized from bioresources. Biobased aliphatic TPU elastomers with excellent tensile strength and resilience were prepared successfully through a non-isocyanate route.

Robotic surgery for rectal cancer is gaining popularity, but persuasive evidence on reducing surgical trauma is still lacking. This study compared robotic and laparoscopic abdominoperineal resections (APRs) for the risk of postoperative complications in low rectal cancer.Between December 2013 and 2016, patients with rectal cancer ≤5 cm from anal verge, cT1-T3 N0-1, or ycT1-T3 Nx stage, and no distant metastases were enrolled in a single-center, randomized, controlled trial. Eligible patients were randomly allocated to robotic or laparoscopic APRs at 1:1 ratio. The primary outcome was 30-day postoperative complication rate (Clavien-Dindo grade II or higher) of the intent-to-treat population. The trial registration number is NCT01985698 (http://www.gov).Totally 347 eligible patients were enrolled: 174 in robotic and 173 in laparoscopic group. Robotic APRs significantly reduced postoperative complication rate (13.2% vs. 23.7%, p = 0.013), also reduced open conversion rate (0% vs. 2.9%, p = 0.030), intraoperative hemorrhage (median, 100 vs. 130 ml; p 0.001), 30-day readmission rate (2.3% vs. 6.9%; p = 0.044), postoperative hospital stay (median, 5.0 vs. 7.0 days; p 0.001), and improved urinary and sexual function. No significant difference was observed in long-term oncological outcomes.Compared with laparoscopic APRs, robotic APRs significantly reduced surgical trauma and promoted postoperative recovery.

We establish a feasible central limit theorem with convergence rate n 1 ∕ 8 for the estimation of the integrated volatility of volatility (VoV) based on noisy high-frequency data with jumps. This is the first inference theory ever built for VoV estimation under such a general setup. The central limit theorem is applied to provide interval estimates of the VoV and conduct hypothesis tests. Furthermore, when one is interested in the null hypothesis that the VoV is zero, we show that a more powerful test can be established based on a VoV estimator with a convergence rate n 1 ∕ 5 under the null. Empirical results on the S&P 500 and individual stocks show strong evidence of non-zero VoV.

3D point cloud registration is fragile to outliers, which are labeled as the points without corresponding points. To handle this problem, a widely adopted strategy is to estimate the relative pose based only on some accurate correspondences, which is achieved by building correspondences on the identified inliers or by selecting reliable ones. However, these approaches are usually complicated and time-consuming. By contrast, the virtual point-based methods learn the virtual corresponding points (VCPs) for all source points uniformly without distinguishing the outliers and the inliers. Although this strategy is time-efficient, the learned VCPs usually exhibit serious collapse degeneration due to insufficient supervision and the inherent distribution limitation. In this paper, we propose to exploit the best of both worlds and present a novel robust 3D point cloud registration framework. We follow the idea of the virtual point-based methods but learn a new type of virtual points called rectified virtual corresponding points (RCPs), which are defined as the point set with the same shape as the source and with the same pose as the target. Hence, a pair of consistent point clouds, i.e. source and RCPs, is formed by rectifying VCPs to RCPs (VRNet), through which reliable correspondences between source and RCPs can be accurately obtained. Since the relative pose between source and RCPs is the same as the relative pose between source and target, the input point clouds can be registered naturally. Specifically, we first construct the initial VCPs by using an estimated soft matching matrix to perform a weighted average on the target points. Then, we design a correction-walk module to learn an offset to rectify VCPs to RCPs, which effectively breaks the distribution limitation of VCPs. Finally, we develop a hybrid loss function to enforce the shape and geometry structure consistency ..., Accepted by IEEE Transactions on Circuits and Systems for Video Technology

The development of temporomandibular joint (TMJ) osteoarthritis is highly associated with mechanical overloading, which can result in accelerated cartilage degradation and damage due to increased interfacial friction and the release of inflammatory factors and catabolic enzymes. In the present study, we for the first time developed self-assembled drug-free nanospheres with pharmaceutical-active functions, which could be used as an intra-articularly injected biolubricant for the treatment of TMJ osteoarthritis based on a synergistic therapy of enhanced lubrication, anti-inflammation, and antisenescence. The nanospheres possessed the hydrophobic core of dopamine methacrylamide and the hydrophilic shell of sulfobetaine methacrylate, which formed into spherical aggregates in aqueous solution by specific interactions following reversible addition-fragmentation chain transfer polymerization. The biodegradation test, tribological test, and free radical scavenging test showed that the nanospheres were endowed with physiological stability, lubrication enhancement, and free radical scavenging capability. In addition, the in vitro cell test revealed that the nanospheres alleviated inflammatory and senescent phenotype for inflammation and oxidative stress stimulated chondrocytes. Furthermore, the in vivo animal test indicated that the nanospheres, after intra-articular injection into TMJ with an osteoarthritis environment, effectively protected condylar cartilage and subchondral bone from structural damage and attenuated cartilage matrix degradation and aging. In summary, the self-assembled nanospheres might be used as a promising biolubricant for achieving anti-inflammatory and antisenescent treatment of TMJ osteoarthritis.

Separation of Cs/Sr is one of many coordination-chemistry-centered processes in the grand scheme of spent nuclear fuel reprocessing, a critical link for a sustainable nuclear energy industry. To deploy a crystallizing Cs/Sr separation technology, we planned to systematically screen and identify candidate ligands that can efficiently and selectively bind to Sr

Background Atherosclerosis is the main pathological change in atherosclerotic cardiovascular disease, and its underlying mechanisms are not well understood. The aim of this study was to explore the hub genes involved in atherosclerosis and their potential mechanisms through bioinformatics analysis. Methods Three microarray datasets from Gene Expression Omnibus (GEO) identified robust differentially expressed genes (DEGs) by robust rank aggregation (RRA). We performed connectivity map (CMap) analysis and functional enrichment analysis on robust DEGs and constructed a protein‒protein interaction (PPI) network using the STRING database to identify the hub gene using 12 algorithms of cytoHubba in Cytoscape. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic potency of the hub genes.The CIBERSORT algorithm was used to perform immunocyte infiltration analysis and explore the association between the identified biomarkers and infiltrating immunocytes using Spearman’s rank correlation analysis in R software. Finally, we evaluated the expression of the hub gene in foam cells. Results A total of 155 robust DEGs were screened by RRA and were revealed to be mainly associated with cytokines and chemokines by functional enrichment analysis. CD52 and IL1RN were identified as hub genes and were validated in the GSE40231 dataset. Immunocyte infiltration analysis showed that CD52 was positively correlated with gamma delta T cells, M1 macrophages and CD4 memory resting T cells, while IL1RN was positively correlated with monocytes and activated mast cells. RT-qPCR results indicate that CD52 and IL1RN were highly expressed in foam cells, in agreement with bioinformatics analysis. Conclusions ​This study has established that CD52 and IL1RN may play a key role in the occurrence and development of atherosclerosis, which opens new lines of thought for further research on the pathogenesis of atherosclerosis.

Introduction and objectives: The study examines the factors influencing the major choice of medical students in China, including individual preferences, social needs, role models, personal characteristics, and the impact of COVID-19. The aim is to provide insights for medical educators to help students make informed career decisions.Methods The study collected data from 11 universities with the largest medical student enrollment in China. A total of 14,016 valid questionnaires were analyzed using statistical methods.Results The study found that social needs and personal interests were the most significant factors influencing the choice of major for medical students in China. The majors with the largest number of enrollments are Obstetrics and Gynecology &Reproductive medicine, Oncology and Ophthalmology. However, there was a shortage of medical professionals in certain fields, such as emergency medicine and anesthesiology, due to medical students' preference for specialties that do not require emergency room visits or night shifts. COVID-19 also had a significant impact on the major choice of medical students in China, with students showing a greater inclination to pursue clinical medicine.Conclusions The study concludes that addressing the shortage of medical professionals in certain fields requires concerted efforts from the government, society, and educational institutions. Providing incentives and subsidies to doctors who face high work intensity and low pay, as well as offering relevant courses to stimulate students' interest in particular specialties, are some possible solutions. Furthermore, medical schools should ensure that students have sufficient personal time and space outside of their studies and provide adequate psychological support to help students manage the pressures of their demanding profession.

Background High blood pressure, anxiety, depression and sleep disorder is very common in patients with hypertension. We aimed to perform a meta-analysis to evaluate the effects of adjuvant music therapy for patients with hypertension, to provide insights to the clinical management of hypertension. Methods Two authors searched PubMed, Embase, Web of Science, the Cochrane Library, Chinese National Knowledge Infrastructure, China Biomedical Literature Database, Wanfang Databases for randomized controlled trials (RCTs) on the role of music therapy in hypertension up to Oct 15, 2022. RevMan 5.3 software was used for meta-analysis. Results A total of 20 RCTs including 2306 patients were finally included. 1154 patients received music therapy. Meta-analysis showed that music therapy can effectively reduce the systolic blood pressure(MD = − 9.00, 95%CI: − 11.99~- 6.00), diastolic blood pressure(MD = -6.53, 95%CI: -9.12~- 3.93), heart rate (MD = -3.76, 95%CI: -7.32~- 0.20), self-rating anxiety scale (SAS) score(MD =-8.55, 95%CI: -12.04~-4.12), self-rating depression scale (SDS) score(MD = -9.17, 95%CI: -13.85~-5.18), Hamilton anxiety scale (HAMA), score(MD = -3.37, 95%CI: − 5.38~- 1.36), PSQI score(MD =-1.61, 95%CI:-2.30~- 0.93) compared with routine therapy in patients with hypertension(all P 0.05). Conclusion Music therapy can effectively control blood pressure and heart rate, reduce anxiety and depression levels, and improve sleep quality in hypertensive patients. Limited by the quantity and quality of included studies, the above conclusions need to be verified by more high-quality studies.