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Abstract As one of the major geological disasters in southeastern China, typhoon-induced vegetation slope instability causes significant loss of life and property each year. Despite the criticality of this issue, the response mechanism of vegetated slopes to wind loading in terms of soil deformation and stability still remains unclear. This research conducted field investigations on 330 historical landslides in Yongjia County, Zhejiang Province, analyzing their spatiotemporal distribution and developmental characteristics to establish a conceptual model. The influence of wind and vegetation conditions on slope dynamic parameters and soil strength parameters were subsequently determined through numerical simulations using FLAC3D software, model tests, and direct shear tests. The results show that: (1) The influence of wind on the dynamic response of vegetated slopes is significantly affected by wind speed. At wind forces ≤ 12 (hurricane: 32.7–36.9 m/s), vegetation plays a positive role in enhancing slope stability. At wind forces ≥ 13 (typhoon: 37.0–41.4 m/s), vegetation exerts a negative influence under the combined action of strong wind loads. (2) Based on the experimentally determined evolution of soil strength parameters, a formula c (v, w) was fitted to express the variation of cohesion with wind speed (v) and moisture content (w). (3) The optimized evaluation model demonstrates increased sensitivity compared to the traditional model, resulting in a 17.88% increase in sliding force and a 10.62–11.64% increase in anti-sliding force. This research accounts for both the direct and indirect effects of wind loading on vegetated slopes. The findings are expected to enhance the stability assessment of vegetated slopes under strong winds and facilitate the development of more accurate machine learning and statistical models in the future.

Abstract Conventional methods for identifying voltage sag sources are difficult to categorize accurately due to the complexity of transmission lines and the influence of noise. In order to solve the problem of difficulty in recognizing voltage sag sources of transmission lines under different locations, this paper proposes a new method for transmission line fault diagnosis based on modified wavelet denoising and multi‐location information convolution transformer. The improved wavelet denoising method proposed in this paper solves the problems of discontinuity and bias of the traditional wavelet denoising method, and is able to better reconstruct the original voltage signal in a strong noise environment. In addition, multi‐location information convolution transformer adopts a new model combining multi‐location information convolution and multi‐scale convolution transformer, which realizes the combination of global information and local context information capturing ability under multi‐location faults. This paper validates the method through simulation experiments and practical situations, and the results show that the method can well classify and identify the type and location of voltage sag sources in transmission lines.

Objective: This study aims to systematically assess physical exercise-related symptoms of post-acute sequelae of SARS-CoV-2 infection (PASC or long COVID) in coronavirus disease 2019 (COVID-19) survivors. Methods: Eight databases were systematically searched on March 03, 2024. Original studies that compared physical exercise-related parameters measured by exercise testing between COVID-19 survivors who recovered from SARS-CoV-2 infection over 3 months and non-COVID-19 controls were included. A random-effects model was utilized to determine the mean differences (MDs) or standardized MDs in the meta-analysis. Results: A total of 40 studies with 6241 COVID-19 survivors were included. The 6-min walk test, maximal oxygen consumption (VO2max), and anaerobic threshold were impaired in COVID-19 survivors 3 months post-infection compared with non-COVID-19 controls in exercise testing, while VO2 were comparable between the two groups at rest. In contrast, no differences were observed in SpO2, heart rate, blood pressure, fatigue, and dyspnea between COVID-19 survivors and non-COVID-19 controls in exercise testing. Conclusion: The findings suggest an underestimation of the manifestations of PASC. COVID-19 survivors also harbor physical exercise-related symptoms of PASC that can be determined by the exercise testing and are distinct from those observed at rest. Exercise testing should be included while evaluating the symptoms of PASC in COVID-19 survivors.

Improving the lubrication condition of oil-starved rolling bearings is a proven method to improve their reliability and service life. In this study, a composite surface texture was designed inspired by the microscopic structure of cactus spine, pitcher plant and blood clam. Superhydrophobic surface coating technology was also employed. An oil self-transportation biomimetic composite surface was developed on the guiding surface of a thrust ball bearing. Experimental results show that the biomimetic composite surface effectively drives oil for high-speed directional transport. The biomimetic composite guiding surface bearing demonstrated excellent best vibration and friction torque performance. Compared to conventional bearing, it has an overall vibration performance improvement of 37.4 %, as well as a significant reduction in friction torque of 43.3 % and wear of 72.2 %. We conclude that oil self-transportation biomimetic composite surfaces on rolling bearings can significantly improve the lubrication condition.

Abstract Background Physical resilience is known to minimize the adverse outcomes of health stressors for older people. However, validated instruments that assess physical resilience in older adults are rare. Therefore, the purpose of this study was to translate the Physical Resilience Scale (PRS) into Chinese and to validate its psychometric properties in a population of community-dwelling older adults following SARS-CoV-2 infection. Methods This study used a cross-sectional design and translated the Physical Resilience Scale into Chinese. A total of 426 older adults who had recovered from SARS-CoV-2 infection were chosen for assessment through convenience sampling. The measurement data were analyzed using the Rasch analysis. Results Rasch analysis indicates that the Physical Resilience Scale demonstrates excellent reliability, validity, and unidimensionality. The Infit MNSQ and Outfit MNSQ of each entry were 0.77 ~ 1.19, and the degree of fit of each entry to the scale was good. Person and item separation reliability support the internal consistency of the studied samples and PRS items. Conclusions The Physical Resilience Scale has good reliability and is suitable for the assessment of physical resilience tests in older people. However, the overall difficulty of the scale is not suitable for older adults of all ability ranges, and it is possible to add higher and lower difficulty items and adjust the difficulty spacing between items in a later study.

To reveal the effects of milling methods on the physicochemical properties of rice flour and the qualities of fresh rice noodles, the rice was treated by dry, semi-dry, and wet milling methods and the resultant products were utilized to produce fresh rice noodles. The basic chemical components, the damaged starch rate, the size distribution, the morphology, the solubility and swelling power, and the pasting properties of the rice flour, as well as the texture, cooking, and sensory qualities of fresh rice noodles, were investigated. The obtained results suggested that the rice flour produced by drying methods with a 300 mesh had the highest damaged starch rate (17.55%) and solubility, smallest particle size, peak viscosity, final viscosity, and setback viscosity. By contrast, the rice flour produced from wet milling methods showed the lowest damaged starch rate (2.87%) and solubility, and the highest peak viscosity, final viscosity, and setback viscosity. Increasing the moisture content during the semi-dry milling treatment, the damaged starch rate of the rice flour decreased from 4.49% to 3.55%, and similar trend was observed for particle size distribution and solubility. Scanning electron microscopy suggested that the lower damaged starch rate, the more intact structure of the rice flour. The fresh rice noodles made from wet milling flour showed the best cooking qualities, and the cooking qualities of semi-dry milled flour-made and semi-soaking milled flour-made fresh noodles were close to those of wet milled flour-made fresh rice noodles while the rice flour produced from dry milled method was not suitable for making fresh rice noodles. The semi-dry and semi-soaking milled rice flour can replace the wet milled rice flour for the preparation of rice noodles during the practical production process. The findings in this study may assist the revolution for the traditional production of rice noodles.

ObjectiveTo analyze the disease group structure and its trends in key departments of large public hospitals using diagnosis related group (DRG) data, explore the key points of intervention and optimization of disease groups in departments, and further promote the rational allocation of department resources.MethodsWe retrospectively collected DRG data from two surgical departments in a large public hospital in Beijing from 2017 to 2023. When the case mix index (CMI) of the two surgical departments declined, interventions such as performance appraisal, department education, and hospital publicity were promptly adopted. The changesin CMI values were observed and the trends in disease group weights, time consumption index, cost consumption index, and mortality rate in low-risk groups were analyzed.ResultsAfter the interventions, in surgical department Ⅰ, the proportion of patients with lower-weight diseases, such as major thyroid surgery (KD1), significantly decreased, while that of patients with higher-weight diseases, such as colorectal malignancy surgery (GB2) and pancreatic malignancy surgery (HB1), significantly increased. In surgical department Ⅱ, the proportion of patients with lower-weight diseases, such as chemotherapy (RE1), decreased markedly, while that of patients with higher-weight diseases, including major surgery for malignancy of kidney, ureter, and bladder (LA1), adrenal gland surgery (KC1), surgery for kidney/ureter/bladder except for major malignancy surgery (LB1), and male genital organ malignancy surgery (MA1), increased significantly. Both surgical departments achieved the goal of increasing their CMI values. In terms of efficiency, cost, and quality indicators, the time consumption index and cost consumption index of the two surgical departments were significantly lower than 1, and the mortality rate in low-risk groups was 0.ConclusionBased on actual conditions and development goals, large public hospitals can achieve improvements in CMI values and optimization of disease group structures through reasonable interventions, thereby enhancing medical efficiency and rational utilization of resources.

ObjectiveTo identify the key issues in emergency response to public health emergencies in the Yangtze River Delta region, and to provide a basis for the formulation of relevant policies.MethodLiterature on emergency response to public health emergencies in the Yangtze River Delta region was systematically reviewed and collected, and 18 main problems were identified after collecting and organizing the problems. A questionnaire survey and cluster analysis were used to identify the key issues.ResultsThe study of 18 major problems revealed that "insufficient reserve of emergency medical supplies", "insufficient financial investment to meet the needs of emergency response", "lack of a sound mechanism for the deployment of supplies, resulting in the untimely deployment of materials", were the key issues of emergency response to public health emergencies in the Yangtze River Delta region.ConclusionFuture development of the emergency response system in the Yangtze River Delta region should focus on accelerating the integration process of the Yangtze River Delta, establishing and improving information systems, optimizing the material storage and deployment network, prioritizing the fund investment and utilization mechanism, and improving the effectiveness of public health emergency response.

ObjectiveTo identify and clarify the key issues faced by tertiary hospitals in responding to public health emergencies.MethodsA literature review index system was constructed, and key issues were identified using hierarchical analysis.ResultsAfter a systematic literature review, 20 types of problems faced by tertiary hospitals in responding to public health emergencies were identified. Three key issues were ultimately identified by prioritizing the issues that needed to be addressed.ConclusionThe key issues of tertiary hospitals in responding to public health emergencies are concentrated in the areas of emergency response capabilities and competencies of medical staff, the number of emergency response personnel, and the standardization and specificity of training and drills. Tertiary hospitals should focus on these issues in developing public health emergency response systems to improve the effectiveness of their emergency response.

To better realize direction control of the single-pump double-motor hydraulic system and simplify the system, structure and principle of a six-position six-way direction control valve was proposed, which the valve spool has two motion modes: sliding and rotating. Using this valve, the inner and outer motors can work independently and simultaneously. The pressure loss of the valve was tested by building a transmission system, and the experiment results were compared with theoretical analysis. The results show that the performance of the valve working in left and right positions is better than that in meso-position, and the maximum pressure loss occurred in meso-position. Under the rated flow, the maximum pressure loss is 0.331 MPa. Then the characteristic curve of flow-pressure loss and the relationship of pressure loss among oil ports are obtained. In the same conditions, except that the oil inlet pressure loss in the meso-position is greater than the oil outlet pressure loss, the oil inlet pressure loss in the left and right positions are less than the oil outlet pressure loss, the pressure loss in the forward position is less than the pressure loss in the reverse position. The experiment verifies the correctness and feasibility of the structure and principle.

Abstract Background Mucoepidermoid Carcinoma of the Esophagus (MECE) is a relatively rare tumor type, with most of the current data derived from case reports or small sample studies. This retrospective study reports on the 10-year survival data and detailed clinicopathological characteristics of 48 patients with esophageal MEC. Methods Data were collected from 48 patients who underwent curative surgery for esophageal MEC at the Fourth Hospital of Hebei Medical University between January 1, 2004, and December 31, 2020. These were compared with contemporaneous cases of Esophageal Squamous Cell Carcinoma (ESCC) and Esophageal Adenocarcinoma (EAC). Using the Kaplan-Meier method and multivariate Cox regression analysis, we investigated the clinicopathological factors affecting the survival of patients with MEC. Results The incidence of MECE was predominantly higher in males, with a male-to-female ratio of approximately 7:1. The mid-thoracic segment emerged as the most common site of occurrence. A mere 6.3% of cases were correctly diagnosed preoperatively. The lymph node metastasis rate stood at 35.4%. The overall 1-year, 3-year, 5-year, and 10-year survival rates for all patients were 85.4%, 52.1%, 37.0%, and 31.0%, respectively. Post 1:1 propensity score matching, no significant statistical difference was observed in the Overall Survival (OS) between MEC patients and those with Esophageal Squamous Cell Carcinoma (ESCC) and Esophageal Adenocarcinoma (EAC) (P = 0.119, P = 0.669). Univariate analysis indicated that T staging and N staging were the primary factors influencing the prognosis of esophageal MEC. Conclusions MECE occurs more frequently in males than females, with the mid-thoracic segment being the most common site of occurrence. The rate of accurate preoperative endoscopic diagnosis is low. The characteristic of having a short lesion length yet exhibiting significant extramural invasion may be a crucial clinicopathological feature of MECE. The OS of patients with MEC does not appear to significantly differ from those with esophageal squamous carcinoma and adenocarcinoma.

ObjectiveTo analyze the satisfaction of service recipients with the preliminary assessment service of the unified elderly care needs evaluation in Shanghai， so as to provide reference for further optimization of the service system.MethodsA multi-stage random sampling method was employed to recruit participants. A total of 110 individuals who had received unified elderly care needs evaluation service in six districts of Shanghai were investigated using a structured questionnaire. SPSS 25.0 was used to analyze the data. Univariate analyses were conducted using the Chi-square test and Fisher’s precision probability test， while multivariate analysis was performed using ordinal regression.ResultsThere were differences in satisfaction with various aspects of the preliminary assessment process among participants from different areas， with those from outer suburbs generally exhibiting lower satisfaction （P

ObjectiveTo clarify the perception of the work and satisfaction levels among personnel conducting unified elderly care needs assessment in Shanghai， to analyze the factors influencing their job satisfaction， and to provide references for optimizing the job satisfaction of unified elderly care needs assessment personnel in Shanghai.MethodsA survey was conducted among 93 assessment personnel randomly selected from 29 elderly care needs assessment agencies in Shanghai. The personnel’s perception of their work and their levels of job satisfaction were examined. Chi-square test and Fisher’s precision probability test were used to compare regional differences， while the two-factor theory was employed to analyze the factors influencing job satisfaction.ResultsRegarding perception of the work， 92.5% of the surveyed personnel believed their work was important. Moreover， 87.1% were interested in their assessment tasks， and 84.9% believed they made a positive contribution to the assessment work and the assessment position was in line with their personal preferences. Regarding job satisfaction， 83.9% of the participants were satisfied with their assessment work， 78.5% considered the workload appropriate， and 74.2% found the working hours suitable. Additionally， 65.6% expressed satisfaction with the level of cooperation from the assessment subjects， while 94.6% and 91.4% of the personnel were satisfied with the support provided by the assessment agencies and had a sense of belonging， respectively. Furthermore， 65.6% of the personnel expressed satisfaction with their job compensation and benefits. Hygiene factors affecting job satisfaction included salary and compensation， workload， time spent on the job and institutional support related to external assistance， job suitability， teamwork， and client cooperation （P

ObjectiveTo conduct a comparative analysis of the efficacy, safety, and impact on quality of life outcomes between thermal ablation and surgical interventions in patients diagnosed with papillary thyroid carcinoma (PTC).MethodsA prospective study was undertaken, enrolling patients with PTC ≤5mm who underwent radiofrequency ablation (RFA), laser ablation (LA), or surgery, for analysis of efficacy and safety outcomes. The Thyroid Cancer-Specific Quality of Life questionnaire was administered to all patients before treatment and at 3, 6, and 12 months post-treatment.ResultsA total of 162 eligible patients were included in the study. Major complications were not observed in the RFA and LA groups, while five cases were reported in the surgery group, although no statistically significant differences were observed. Minor complications were documented in two, three, and 14 patients in the RFA, LA, and surgery groups, respectively, with no significant variances noted. Surgical duration and hospitalization time were notably shorter in the thermal ablation groups. At the final follow-up, complete disappearance of nodules was seen in 71.4% of cases treated with RFA and 71.0% of cases managed with LA, with no significant disparities between the groups. Both RFA and LA exhibited similar effects on quality of life, with thermal ablation techniques showing better functional outcomes in comparison to surgery. Across all groups, adverse effects were most pronounced at the 3-month post-treatment mark but gradually reverted to baseline levels in the thermal ablation group, contrasting with the surgery group.ConclusionsFor PTC ≤5mm, both RFA and LA exhibited similar cancer control outcomes and superior quality of life on par with surgery, while minimizing complications. These findings underscore the promise of RFA and LA as potential standard treatments for small PTCs, subject to further confirmation in future studies.

Background Insomnia is a common health problem among cancer patients, which is not only a physical problem but also a psychological problem. Sleep plays an important role in the mental and somatic rehabilitation of cancer patients, and the sleep beliefs and attitudes of cancer patients are key factors in improving their sleep situation and quality of life. The aim of this study was to translate the Cancer-Related Dysfunctional Beliefs and Attitudes about Sleep (C-DBAS-14) scale into Chinese and to validate its reliability and validity in cancer patients. Method The C-DBAS-14 scale was translated into Chinese using the backward and forward translation procedure. The reliability of the scale was measured by internal consistency, split-half reliability and retest reliability. The validity of the scale was assessed through the content validity indicators, exploratory factor analysis and validation factor analysis. Result The Cronbach's ɑ coefficient of the Chinese version of the C-DBAS-14 was 0.932 while the McDonald’s omega coefficient (ω t) was 0.934. The split-half reliability coefficient was 0.908, and the test-retest reliability was 0.857. The four-factor model was obtained using exploratory factor analysis, explaining 72.7% of the variance, with each item loading greater than 0.4 on the common factor. The results of the confirmatory factor analysis revealed that all indicators of model fit were within an acceptable range, indicating a well-fitting model. Conclusion The Chinese version of the C-DBAS-14 has good reliability and validity among cancer patients. It can be used to measure the sleep beliefs and attitudes of Chinese cancer patients.

The gradual acceleration of the aging population in China has led to an increased demand for mobility aids, and the reliability of domestic wheeled walking-aid is one of their important attributes, but there is little research on the reliability of mobility aids. This paper conducts the failure mode, effects and criticality analysis on domestic wheeled walking-aid. By collecting, collating and analyzing the 26 failure modes, the key modules are the chassis and the lifting system. The key modules are obtained, and the failure data is analyzed to find out that the lifetime distribution model is log-normal and the 0.95 lower confidence limit for reliability life of product t0.9 is 2489.4 hours. The study aims to provide ideas for the reliability analysis of other active medical devices and calls for the formation of a reliability study review point for the industry that meets the requirements of Chinese medical device regulations.

Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted rehabilitation training due to its noninvasive, less physical restriction, and no electromagnetic disturbance. Previous research has proved the cross-session reliability of fNIRS responses to non-motor tasks (e.g., visual stimuli) and fine-motor tasks (e.g., finger tapping). However, it is still unknown whether fNIRS responses remain reliable 1) in gross-motor tasks, 2) within a training session, and 3) for different training parameters. Hence, this study aimed to investigate the within-session reliability of fNIRS responses to gross-motor tasks for different training parameters. Ten healthy participants were recruited to conduct right elbow extension-flexion in three robot-assisted modes. The Passive mode was fully motor-actuated, while Active1 and Active2 modes involved active engagement with different resistance levels. FNIRS data of three identical runs were used to assess the within-session reliability in terms of the map- ( ${R}^{{2}}$ ) and cluster-wise ( ${R}_{\textit {over}\textit {lap}}$ ) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability ( ${R}^{{2}}$ up to 0.69, ${R}_{\textit {over}\textit {lap}}$ up to 0.68) at the subject level. Besides, the within-session temporal reliabilities of Slope, Max/Min, and Mean were between good and excellent ( $0.60< $ ICC < 0.86). We also found that the within-session reliability was positively correlated with the intensity of the training mode, except for the temporal reliability of HbO in Active2 mode. Overall, our results demonstrated good within-session reliability of fNIRS responses, suggesting fNIRS as reliable neurofeedback for constructing closed-loop robot-assisted rehabilitation systems.

Abstract Background High technical thresholds, long operative times, and the need for expensive and specialized equipment impede the widespread adoption of endodontic microsurgery in many developing countries. This study aimed to compare the effects of a simplified, cost-effective, and time-efficient surgical approach involving orthograde obturation using biological ceramic material greater than 6 mm combined with apicoectomy for single-rooted teeth with short lengths with those of the conventional and current standard methods. Materials and methods Forty-five premolars equally categorized into three groups: conventional surgery group, standard surgery group, and modified surgery group. A µCT scan was used to calculate the volume of voids. A micro-leakage test and scanning electron microscope (SEM) were performed to assess the sealing effect. Additionally, four cases of chronic periapical periodontitis in the anterior region were selected, and the patients received either the modified approach or the standard surgery for endodontic microsurgery. Results The volumes of voids in the apical 0–3 mm of the modified group and the standard group were comparable. The micro-leakage test and SEM examination demonstrated closely bonded fillings in the dentinal walls in both the modified surgery group and standard surgery group. The outcomes of the preliminary application of this modified procedure on patients were successful at the time of the follow-up cutoff. Conclusions The modified surgery group exhibited similar root canal filling and apical sealing abilities with the standard procedure for single-rooted teeth with short lengths (

Due to the weak structural features of pipelines and underwater light attenuation, the complex and harsh environment of the seabed greatly increases the possibility of an underwater autonomous remotely operated vehicle losing a detected seabed-contacting segment during pipe-laying operations. To address this problem, we propose a cascade attention module and a prefusion module with a convolutional neural network. The cascade attention module samples the feature maps in a non-convolutional form to realize the interaction between structure and channels, and the attention map is generated by cascading attention. The prefusion module pre-fuses the three layers of feature maps from different stages in the backbone, and the delicate features of the shallow feature maps are fused with the deeper feature maps to generate richer feature maps with space location and semantic classification information. We conduct experiments to verify our modules, both on the underwater pipeline dataset and in a tank test. The results show that our modules can improve the performance of different neural network models for seabed-contacting segment detection. The target detection and instance segmentation performance of the best model is improved through a 6.3% increase in AP and a 3.8% increase in mean intersection over union compared with the baseline model.

Abstract Patients with methicillin‐resistant Staphylococcus aureus (MRSA) infections may have higher death rates than those with non‐drug‐resistant infections. Nanozymes offer a promising approach to eliminating bacteria by producing reactive oxygen species. However, most of the conventional nanozyme technologies encounter significant challenges with respect to size, composition, and a naturally low number of active sites. The present study synthesizes a iron‐single‐atom structure (Fe‐SAC) via nitrogen doped‐carbon, a Fe‐N5 catalyst (Fe‐SAC) with a high metal loading (4.3 wt.%). This catalyst permits the development of nanozymes consisting of single‐atom structures with active sites resembling enzymes, embedded within nanomaterials. Fe‐SAC displays peroxidase‐like activities upon exposure to H2O2. This structure facilitates the production of hydroxyl radicals, well‐known for their strong bactericidal effects. Furthermore, the photothermal properties augment the bactericidal efficacy of Fe‐SAC. The findings reveal that Fe‐SAC disrupts the bacterial cell membranes and the biofilms, contributing to their antibacterial effects. The bactericidal properties of Fe‐SAC are harnessed, which eradicates the MRSA infections in wounds and improves wound healing. Taken together, these findings suggest that single Fe atom nanozymes offer a novel perspective on the catalytic mechanism and design, holding immense potential as next‐generation nanozymes.

Pulse tube refrigerators with active displacers have become increasingly popular due to superior phase shift capability and avoidance of dissipation losses. However, mechanisms of thermodynamic processes within refrigerators due to variations in parameters related to critical structures and operations are not yet clear, making it difficult to optimize the comprehensive performance. In this paper, multi-dimensional flow simulation method instead of one-dimensional simulation method with poor computational accuracy is used to analyze the influence of five key parameters on performance of pulse tube refrigerators with active displacers. An intelligent optimization algorithm combined with efficient Kriging surrogate models is developed for single-objective and multi-objective optimization. Results demonstrate that the mean errors of the Kriging models for cooling capacity, total input power and performance coefficient are 1.81%, 3.94% and 3.37%. The single-objective optimization produces a maximum cooling capacity of 7.29 W and performance coefficient of 7.38%. The combined optimal solution delivers 6.65W in cooling capacity and 7.02% in performance coefficient, obtaining improvements of 150.94% and 75.94%. This study reveals the influence mechanism of key parameters on cooling performance of pulse tube refrigerators with displacers and establishes an efficient global optimization method, which is of great significance for the development of advanced refrigeration technology.

Abstract Background The clinical relevance of circulating tumor cell-white blood cell (CTC-WBC) clusters in cancer prognosis is a subject of ongoing debate. This study aims to unravel their contentious predictive value for patient outcomes. Methods We conducted a comprehensive literature search of PubMed, Embase, and Cochrane Library up to December 2022. Eligible studies that reported survival outcomes and examined the presence of CTC-WBC clusters in solid tumor patients were included. Hazard ratios (HR) were pooled to assess the association between CTC-WBC clusters and overall survival (OS), as well as progression-free survival (PFS)/disease-free survival (DFS)/metastasis-free survival (MFS)/recurrence-free survival (RFS). Subgroup analyses were performed based on sampling time, treatment method, detection method, detection system, and cancer type. Results A total of 1471 patients from 10 studies were included in this meta-analysis. The presence of CTC-WBCs was assessed as a prognostic factor for overall survival and PFS/DFS/MFS/RFS. The pooled analysis demonstrated that the presence of CTC-WBC clusters was significantly associated with worse OS (HR = 2.44, 95% CI: 1.74–3.40, P

Background: Overweight and obese older adults have a high risk for developing cardiovascular disease. Aerobic exercise is a valuable strategy to improve vascular health, but the effects of aerobic exercise on vascular endothelial function in obese and overweight older adults remain controversial. The purpose of this meta-analysis was to investigate the effects of aerobic exercise on vascular function in obese and overweight older adults with or without comorbidity. Methods: A systematic literature search for related studies published in English was conducted between January 1989 and October 30, 2022, in the PubMed, Embase, and Cochrane Library databases. A random effects model was chosen for meta-analysis, which calculated the effect sizes of control and intervention groups after exercise intervention using standardized mean differences (SMDs) corrected for Hedges' g bias and 95% confidence intervals (95% CIs). Results: Twenty-six studies containing 1418 participants were included in the study. After excluding three studies contributing to higher heterogeneity by sensitivity analysis, there are small effects of regular aerobic exercise on vascular function of obese and overweight older adults, including flow-mediated dilation (FMD) [SMD = 0.21, 95% CI (0.02, 0.41), z = 2.16, df = 19, I2 = 52.2%, P = 0.031] and pulse wave velocity (PWV) [SMD = −0.24, 95% CI (−0.46, −0.02), z = 2.17, df = 10, I2 = 8.6%, P = 0.030], and no significant effect was observed on augmentation index (Aix). Subgroup analysis showed small effects of regular aerobic exercise on FMD [SMD = 0.37, 95% CI (0.13, 0.61), z = 3.05, df = 9, I2 = 52.6%, P = 0.002] in the overweight not obese subgroup (25 = BMI

Power quality is an important metric for the normal operation of a power system, and the accurate identification of transient signals is of great significance for the improvement of power quality. The diverse types of power system transient signals and strong characteristic coupling brings new challenges to the analysis and identification of power system transient signals. In order to enhance the identification accuracy of transient signals, one method of power system transient signal identification is proposed based on a dynamic large convolution kernel and multilevel feature fusion network. First, the more fine-grained and more informative features of the transient signals are extracted by the dynamic large convolution kernel feature extraction module. Then, the multi-scale local features are adaptively fused by the multilevel feature fusion module. Finally, the fused features are reduced in dimension by the fully connected layer in the classification module and fed into the SoftMax layer for transient signal type detection. The proposed method can effectively improve the small receptive field problem of convolutional neural networks and the lack of ability of Transformer network in extracting local context information. Compared with five other power quality transient disturbance identification models, the experimental results show that the proposed method has better diagnostic accuracy and anti-noise capability.

Voltage sag source location provides a solution to improve the operation and maintenance efficiency and resolve disputes between power supply and consumption. The existing sag source locating methods are based on the fault recording system’s sampling value waveform data, which requires more storage space and transmission channels. Based on sag event list with easy access and high real-time performance and takes the line as the location result, this paper proposes a voltage sag source locating method based on sag event amplitude information. Firstly, Based on the voltage amplitude of the monitoring nodes recorded in the sag event list, a matrix of voltage amplitude of disturbed monitoring nodes is formed. Secondly, the voltage amplitude and fault type of the disturbed nodes are used as inputs, and the line number is used as a classification number. The multi-classifier model based on multi-layer perceptron is trained to locate the voltage sag source. Finally, the method in this paper is verified by IEEE39 node simulation model and the actual monitoring data of sag events in an area in East China. The results show that the method is effective and feasible. Compared with the existing commonly used multi classification algorithms, it is found that the accuracy of sag source location in this method is 10% ∼ 20% higher than other multi classification algorithms.

Abstract Background Occupational health is essential for nurses in clinical nursing practice. However, there is no specific tool for measuring the health behaviour of clinical nurses in China. This study aimed to translate the Positive Health Behaviours Scale into Chinese and validate its psychometric properties among clinical nurses. Design A cross-sectional design with repeated measures. Methods A total of 633 clinical nurses were recruited by convenience sampling from hospitals in Liaoning Province, China. After obtaining the authorization of the original author, the PHBS was translated into Chinese by the Brislin back-translation method. Item analysis was completed to evaluate item discrimination, and the Delphi method was adopted to analyse content validity. Exploratory factor analysis and confirmatory factor analysis were conducted to explore and validate the underlying factor structure. Internal consistency and test-retest reliability were calculated to evaluate reliability. Results A total of 29 items were retained in the item analysis, and the content validity index of the translated scale was 0.956. In the EFA, four common factors were extracted (nutrition, physical activity, relaxation and behaviours related to mental health and preventive behaviours), explaining 60.81% of the total variance. The results of the CFA were as follows: χ2/df = 1.363, GFI = 0.902, NFI = 0.909, IFI = 0.974, TLI = 0.971, CFI = 0.974, RMSEA = 0.034, and RMR = 0.023. The results of the EFA and CFA showed that the translated scale had good structural validity. Cronbach’s α coefficient, the split-half reliability and the test-retest reliability of the Chinese version of the PHBS were 0.928, 0.953 and 0.891, respectively. At the same time, the translated scale had good reliability. Conclusions The Chinese version of the PHBS for clinical nurses had good psychometric properties. The results of the questionnaire survey effectively and comprehensively reflect the level of health behaviours in clinical nurses, which provides a scientific reference for determining the intervention target.

Abstract IscU2 is a scaffold protein that is critical for the assembly of iron–sulfur (Fe–S) clusters and the functions of Fe–S-containing mitochondrial proteins. However, the role of IscU2 in tumor development remains unclear. Here, we demonstrated that IscU2 expression is much higher in human pancreatic ductal adenocarcinoma (PDAC) tissues than in adjacent normal pancreatic tissues. In PDAC cells, activated KRAS enhances the c-Myc-mediated IscU2 transcription. The upregulated IscU2 stabilizes Fe–S cluster and regulates the activity of tricarboxylic acid (TCA) cycle enzymes α-ketoglutarate (α-KG) dehydrogenase and aconitase 2, which promote α-KG catabolism through oxidative and reductive TCA cycling, respectively. In addition to promoting mitochondrial functions, activated KRAS-induced and IscU2-dependent acceleration of α-KG catabolism results in reduced α-KG levels in the cytosol and nucleus, leading to an increase in DNA 5mC due to Tet methylcytosine dioxygenase 3 (TET3) inhibition and subsequent expression of genes including DNA polymerase alpha 1 catalytic subunit for PDAC cell proliferation and tumor growth in mice. These findings underscore a critical role of IscU2 in KRAS-promoted α-KG catabolism, 5mC-dependent gene expression, and PDAC growth and highlight the instrumental and integrated regulation of mitochondrial functions and gene expression by IscU2 in PDAC cells.

Abstract Drug development based on target proteins has been a successful approach in recent decades. However, the conventional structure-based drug design (SBDD) pipeline is a complex, human-engineered process with multiple independently optimized steps. Here, we propose a sequence-to-drug concept for computational drug design based on protein sequence information by end-to-end differentiable learning. We validate this concept in three stages. First, we design TransformerCPI2.0 as a core tool for the concept, which demonstrates generalization ability across proteins and compounds. Second, we interpret the binding knowledge that TransformerCPI2.0 learned. Finally, we use TransformerCPI2.0 to discover new hits for challenging drug targets, and identify new target for an existing drug based on an inverse application of the concept. Overall, this proof-of-concept study shows that the sequence-to-drug concept adds a perspective on drug design. It can serve as an alternative method to SBDD, particularly for proteins that do not yet have high-quality 3D structures available.

Abstract Objective The objective of this study was to translate the Elderly-Constipation Impact Scale into Chinese and to examine its reliability and validity in a population of older people suffering from chronic constipation. Methods In this study, the scale was paraphrased, back-translated, cross-culturally adapted and pre-experimented using the Brislin double translation-back-translation method to create the initial Chinese version of the Elderly-Constipation Impact Scale. A convenience sampling method was used to select 564 study participants who met the inclusion and exclusion criteria in Liaoning and Shanxi, China, to evaluate the reliability and validity of the scale. General information about the study population was using descriptive statistics; item analysis was used to screen the items of the scale. Content validity, exploratory factor analysis, and validation factor analysis were chosen to validate the scales; internal consistency, spilt-half reliability and retest reliability were used determine the reliability of the measurement scales. Results The Chinese version of the Elderly-Constipation Impact Scale contains 7 dimensions and 21 items. The Cronbach's alpha coefficient for the total scale was 0.901 and the range of Cronbach's alpha values for each dimension was 0.707 to 0.918. The split-half reliability of the scale was 0.736 and the retest reliability was 0.763. The exploratory factor analysis showed a KMO value of 0.873 and a Bartlett's spherical test X 2 value of 3499.978 (p 0.4 on its common factor. In the validation factor analysis, the model fit results were X 2 / df = 1.886, GFI = 0.910, AGFI = 0.874, PGFI = 0.654, IFI = 0.955, TLI = 0.942, CFI = 0.954, RMSEA = 0.056 and PNFI = 0.718. The model fit indicators were all within acceptable limits. Conclusion The Chinese version of the E-CIS has good reliability and validity in the chronic constipation population of elderly individuals. The results of the questionnaire can effectively and comprehensively reflect the impact of chronic constipation on the quality of life of elderly individuals. It provides a meaningful reference for identifying targets for intervention.

Abstract Bacterial infection can impede the healing of chronic wounds, particularly diabetic wounds. The high‐sugar environment of diabetic wounds creates a favorable condition for bacterial growth, posing a challenge to wound healing. In clinical treatment, the irregular shape of the wound and the poor mechanical properties of traditional gel adjuvants make them susceptible to mechanical shear and compression, leading to morphological changes and fractures, and difficult to adapt to irregular wounds. Traditional gel adjuvants are prepared in advance, while in situ gel is formed at the site of administration after drug delivery in a liquid state, which can better fit the shape of the wound. Therefore, this study developed an in situ HA/GCA/Fe2+‐GOx gel using a photothermal‐enhanced Fenton reaction to promote the generation of hydroxyl radicals (·OH). The generation of ·OH has an antibacterial effect while promoting the formation of the gel, achieving a dual effect. The addition of double‐bonded adamantane (Ada) interacts with the host‐guest effect of graphene oxide and the double‐bond polymerization of HAMA gel, making the entire gel system more complete. At the same time, the storage modulus (G′) of the gel increased from 130 to 330 Pa, enhancing the mechanical properties of the gel. This enables the gel to have better injectability and self‐healing effects. The addition of GOx can consume glucose at the wound site, providing a good microenvironment for the repair of diabetic wounds. The gel has good biocompatibility and in a diabetic rat wound model infected with S. aureus, it can effectively kill bacteria at the wound site and promote wound repair. Meanwhile, the inflammation of wounds treated with HA/GCA/Fe2+‐GOx + NIR was lighter compared to untreated wounds. Therefore, this study provides a promising strategy for treating bacterial‐infected diabetic wounds.

Introduction With an increasing number of older adults in China, the number of people with cognitive impairment is also increasing. To decrease the risk of dementia, it is necessary to timely detect mild cognitive impairment (MCI), which is the preliminary stage of dementia. The prevalence of MCI is relatively high among older adults with diabetes mellitus (DM); however, no effective screening strategy has been designed for this population. This study will construct a nurse-led screening system to detect MCI in community-dwelling older adults with DM in a timely manner.Methods and analysis A total of 642 participants with DM will be recruited (n=449 for development, n=193 for validation). The participants will be divided into MCI and none-MCI groups. The candidate predictors will include demographic variables, lifestyle factors, history of diseases, physical examinations, laboratory tests and neuropsychological tests. Univariate analysis, least absolute shrinkage and selection operator regression screening, and multivariate logistic regression analysis will be conducted to identify the outcome indicators. Based on the multivariate logistic regression equation, we will develop a traditional model as a comparison criterion for the machine learning models. The Hosmer-Lemeshow goodness-of-fit test and calibration curve will be used to evaluate the calibration. Sensitivity, specificity, area under the curves and clinical decision curve analysis will be performed for all models. We will report the sensitivity, specificity, area under the curve and decision curve analysis of the validation dataset. A prediction model with better performance will be adopted to form the nurse-led screening system.Ethics and dissemination This prospective study has received institutional approval of the Medical Ethics Committee of Qidong Hospital of TCM (QDSZYY-LL-20220621). Study results will be disseminated through conference presentations, Chinese Clinical Trial Registry and publication.Trial registration number ChiCTR2200062855.

With the increasing utilization of urban underground space in densely populated cities, it is crucial to understand the interactive impact of the excavation sequence on the excavation group of foundation pits. The foundation pit of Tianta Station of Tianjin Metro Line 7 was adjacent to a deep foundation pit of an apartment, which provided a good case for the study of simultaneous excavation of foundation pits. In this paper, based on two deep foundation pit excavation projects, a finite element model was established to better understand the mutual influence of simultaneous foundation pit excavation. The responses of the two deep foundation pits under five different excavation sequences were investigated, including the horizontal displacement of the ground-connected wall and the displacement of the top of the wall, the settlement of the ground surface, and the supporting axial force of the basement floor slab. The position of the maximum horizontal displacement in different modes is the same, and the shape of the deformation curve was fish-bellied. When both pits B and C were excavated simultaneously, the surface settlement between adjacent pits was smaller than in other working conditions. Mode 5 is optimal among these five modes, in which not only the construction progress is the fastest but also the underground wall deformation and the ground settlement are relatively small. The findings and lessons learned from these two adjacent pits, both of which were constructed using the cap-and-reverse method, can help professionals optimize excavation design and construction, as well as performance prediction and control.

Renewable energy generation (REG) has continued to grow strongly and resulted in the lower profitability of conventional generation. Meanwhile, the indeterminacy of REG will also lead to electricity balancing challenges and more volatile and less-predictable physical flows in the power grid. In this case, a capacity market is essential to motivate new investments and, therefore, ensure supply adequacy. Considering the low-carbon transition goal and the requirements of the reliability of the power system, this paper develops a reliability-constrained capacity market framework in which the reliability criterion rather than the capacity supply–demand equilibrium is taken into account. The ramping constraints, devices’ random failures, and REG uncertainties are comprehensively considered in the capacity requirement determination and allocation. First, a comprehensive capacity market mechanism coordinated with multi-objective regulations is proposed to compensate the capacity providers and encourage the renewable energy transition. Then, a novel capacity market model is proposed to clear the market with reliability constraints. Moreover, to reduce the computational burden caused by the explicit consideration of reliability constraints, several techniques are applied including the root-event-based state screening technique and the adaptive Kriging metamodel. A modified IEEE-RTS-79 case is studied to illustrate the benefits of the proposed reliability-constrained capacity market model.

ObjectiveThis study’s objectives were to translate the Health Behavior Motivation Scale (HBMS) into Chinese and verify the scale’s validity and reliability among Chinese healthy adults.MethodThe HBMS scales were translated into Chinese based on Brislin’s principles. The Chinese version of HBMS is created through translation, back translation, and cross-cultural adaptation. This investigation implemented the convenience sampling method to conduct a survey on 781 healthy respondents, utilizing the Chinese version of the HBMS and a general demographic questionnaire. We used AMOS (v28.0) and SPSS (v26.0) for statistical analysis. We employed test–retest reliability, split-half reliability, and internal consistency to assess the reliability of the translation questionnaire. Structure validity and content validity were used to assess validity.ResultsThe Chinese version of the Health Behavior Motivation Scale (HBMS) had a Cronbach’s alpha coefficient of 0.885, and the range of Cronbach’s alpha values for each dimension was 0.820–0.885. The scale’s test–retest reliability was 0.824, and its split-half reliability was 0.906. Five public factors with a cumulative variance contribution of 56.527% were retrieved from the exploratory factor analysis. Moreover, the factor loading value for each item exceeded 0.4.In confirmatory factor analysis, the indicators were reported as follows: χ2/df = 1.567, GFI = 0.900, CFI = 0.952, IFI = 0.952, TLI = 0.946, AGFI = 0.881, PGFI = 0.757, PNFI = 0.789, RMSEA = 0.039, and the results of the model fit metrics were within the reference range.ConclusionThe Chinese version of the HBMS exhibits strong discrimination, validity, and reliability. The tool effectively identifies the motivation of healthy people to engage in healthy behaviors. It can be used by healthcare practitioners to assist in the development of follow-up interventions to reduce the prevalence of chronic disease in older people and the incidence of chronic disease in populations of young and middle-aged people.

Electric power is vital for the national security, economy, and people’s livelihood of a country. Ensuring the stable and secure supply of electric power is crucial for achieving carbon peaking and carbon neutrality. Therefore, it is imperative to analyze the weaknesses and challenges of power supply security in China and construct a power supply guarantee system that adapts to the new era and facilitate high-quality economic development. Herein, the research progress of power security supply is reviewed, the current status of power supply in China is summarized, and the trend in power security supply in China during the 14th Five-Year period and for the medium and long terms is analyzed. Moreover, considering the recent power rationing incidents, the problems and challenges for power supply in China are summarized and analyzed. On this basis, the basic principles of adhering to security first, a low-carbon path, market-oriented reforms, and technological innovations are proposed, and a three-step roadmap for constructing a new power supply guarantee system is investigated. Furthermore, we propose the following suggestions: (1) enhancing China’s power supply guarantee capabilities to solidify its foundation for power supply security; (2) improving the intrinsic security of power supply by focusing on the demand side; (3) establishing a new-generation technical system for guaranteeing power supply security; and (4) optimizing the market system to construct a power security ecology participated by all.

Due to the complexity of the structure of doubly-fed induction generator (DFIG), it is difficult to conduct real-time simulation. For this reason, this paper designs an embeddable parallel digital image IP of DFIG based on field programmable logic array (FPGA) to realize efficient electromagnetic simulation of DFIG. First, this paper proposes a virtual capacitor equivalent method for induction machine equivalent “T” circuit decoupling; Secondly, based on the principle of data independence and parallelism within the time step, a parallel algorithm for the internal components of DFIG is proposed; Finally, the FPGA-DFIG digital image constructed in this paper is connected to the RT-LAB/power grid, and hardware experiments are carried out under three working conditions: steady state, voltage sag and DC side fault. The experimental results are compared with the simulation results of DFIG grid connected system built in MATLAB/Simulink environment to verify the effectiveness and rapidity of the methods and models proposed in this paper.

Deep learning has achieved remarkable performance in semantically segmenting remotely sensed images. However, the high-frequency detail loss caused by continuous convolution and pooling operations and the uncertainty introduced when annotating low-contrast objects with weak boundaries induce blurred object boundaries. Therefore, a dual-stream network MAE-BG, consisting of an edge detection (ED) branch and a smooth branch with boundary guidance (BG), is proposed. The ED branch is designed to enhance the weak edges that need to be preserved, simultaneously suppressing false responses caused by local texture. This mechanism is achieved by introducing improved multiple-attention edge detection blocks (MAE). Furthermore, two specific ED branches with MAE are designed to combine with typical deep convolutional (DC) and Codec infrastructures and result in two configurations of MAE-A and MAE-B. Meanwhile, multiscale edge information extracted by MAE networks is fed into the backbone networks to complement the detail loss caused by convolution and pooling operations. This results in smooth networks with BG. After that, the segmentation results with improved boundaries are obtained by stacking the output of the ED and smooth branches. The proposed algorithms were evaluated on the ISPRS Potsdam and Inria Aerial Image Labelling datasets. Comprehensive experiments show that the proposed method can precisely locate object boundaries and improve segmentation performance. The MAE-A branch leads to an overall accuracy (OA) of 89.16%, a mean intersection over union (MIOU) of 80.25% for Potsdam, and an OA of 96.61% and MIOU of 86.63% for Inria. Compared with the results without the proposed edge optimization blocks, the OAs from the Potsdam and Inria datasets increase by 5.49% and 7.64%, respectively.

Background Macroautophagy/autophagy is an essential recycling process that is involved in a wide range of biological functions as well as in diseases. The regulation of autophagy by exercise and the associated health benefits have been revealed by rodent studies over the past decade, but the evidence from human studies remains inconclusive. Methods The MEDLINE, Embase, Cochrane, Scopus, and Web of Science databases were systematically searched from inception until September 2022. Human studies that explored potential effects of physical exercise on autophagy at the protein level were selected according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A random-effects model was used for the meta-analysis. Results Twenty-six studies were included in the meta-analysis. Subgroup analyses revealed that an acute bout of resistance exercise attenuated autophagy, as characterized by lower levels of microtubule-associated proteins 1A/1B light chain 3B (LC3-II) and higher levels of sequestosome 1 (SQSTM1). In contrast, the long-term resistance exercise elevated autophagy, as shown by higher levels of LC3-II and lower levels of SQSTM1. No significant changes in LC3-II levels were observed with moderate- or vigorous-intensity endurance exercise either as an acute bout or long-term. In terms of tissue types, exercise exerted opposite effects between skeletal muscles and peripheral blood mononuclear cells (PBMCs), whereby autophagy was suppressed in skeletal muscles when activated in the PBMCs. Other meta-analyses have also shown significant alterations in the level of many canonical autophagic and mitophagic proteins, including unc-51 like autophagy activating kinase (ULK1)S317, ULK1S757, Beclin-1, ATG12, BCL2/adenovirus E1B 19 kDa protein-interacting protein 3, and PARKIN following exercise, suggesting the activation of canonical autophagy and mitophagy, although the scope of those analyses was more limited. Conclusion Our findings demonstrate that physical exercise probably regulates autophagy in an exercise modality- and tissue-dependent manner in humans, although further investigation is needed. Customized exercise prescriptions should be aimed for when implementing exercise to regulate autophagy in humans. Abbreviations: ATG: autophagy-related gene; BCL2L13: BCL2-like 13; BECN1: beclin1; BNIP3: BCL2/adenovirus E1B 19 kDa protein-interacting protein 3; GABARAP: gamma-aminobutyric acid receptor-associated protein; GAPDH: glyceraldehyde 3-phosphate dehydrogenase; LAMP2: lysosome-associated membrane protein 2; LC3B: microtubule-associated proteins 1A/1B light chain 3B; MD: mean difference; mTOR: mammalian target of rapamycin; PBMC: peripheral blood mononuclear cells; PINK1: PTEN-induced kinase 1; PRISMA: preferred reporting items for systematic review and meta-analysis; SD: standard deviation; SQSTM1: sequestosome 1; ULK1: unc-51 like autophagy activating kinase 1; VDAC1: voltage-dependent anion-selective channel 1.

The new generation of pavement technology with the goal of longevity is an important supporting technology that can promote the achievement of sustainable development of high-speed roadways. To further investigate the evolution trend of long-life pavement performance, this paper paved experimental sections to explore the correlations between pavement structure combinations and pavement performances. This paper presented four experimental sections with different pavement structures, asphalt concrete layer thicknesses, and pavement materials. Then, this paper analyzed the effects of the seasonal factors, pavement structure, and lanes on the deflection value and rut depth from three dimensions by the Pearson correlation coefficient (PCC). Finally, this paper used the analysis of variance (ANOVA) to analyze the relationships between the layer thickness of various materials in the pavement structure and the pavement performances, including the deflection value, international roughness index (IRI), texture depth (TD), British Pendulum Number (BPN), sideway force coefficient (SFC), rut depth, and disease area. The results showed that the seasonal factors significantly affected the deflection values of pavement structures with PCCs of 0.61, 0.72, 0.53, and 0.78. The high temperatures increased the average deflection values by 22.85%, 72.88%, 77.61%, and 88.13%, respectively. Under the influence of high temperature in summer and traffic loads, the increased ranges of average rut depth were −0.2%, 4.89%, 9.56%, and 7.31%, respectively. The results of ANOVA showed that the pavement structure type and thickness of each structural layer significantly affected the deflection value, and there also was a strong correlation between the pavement structure type, thickness, BPN, and SFC with p-values less than 0.05. Increasing the thickness of the asphalt surface was beneficial for reducing the area of defects, while laying the semi-rigid base layer was beneficial for maintaining the deflection value and rut depth at a lower level.

ObjectiveThe purpose of this study was to translate the Geriatric Anxiety Scale-Long-Term Care into Chinese and to assess its reliability and validity in a long-term care population, as well as to explore factors contributing to anxiety in older adults requiring long-term care.MethodsThe study recruited 399 older adults residents requiring long-term care and used the Brislin double translation-back-translation method to create the initial Chinese version of the Geriatric Anxiety Scale-Long-Term Care. The study used internal consistency and split-half reliability to assess the reliability of the scale, as well as exploratory factor analysis, validation factor analysis, and content validity to assess the validity of the scale. Linear regression was used to analyze the relationship between the independent variables and anxiety levels in the long-term care population.ResultsThe Cronbach’s coefficient value of the Chinese version of the Geriatric Anxiety Scale-Long-Term Care was 0.81, and the split-half reliability was 0.80. The results of exploratory factor analysis showed support for a one-dimensional factor structure. The results of the validation factor analysis indicated a good fit for the one-factor model. Gender (β = 0.190, 95% CI:0.540 ~ 1.546, p

IntroductionInflammation is closely associated with tumor development and patient prognosis. The objective of this study is to assess the prognostic value of the preoperative inflammatory indexes in pediatric hepatoblastoma patients who receive neoadjuvant chemotherapy.Methods:A retrospective analysis was performed on clinical and pathological data of 199 hepatoblastoma patients who underwent hepatectomy with preoperative neoadjuvant chemotherapy from January 2015 to June 2020. The receiver operating characteristic curve was used to evaluate the prognostic value of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) in predicting OS and EFS. Patients were grouped based on optimal cutoff values of preoperative inflammatory indexes. Survival rates were calculated using the Kaplan-Meier method, and survival outcomes were compared between groups using the log-rank test. Univariate and multivariate Cox proportional hazards regression models were used to identify independent prognostic factors, and a nomogram was constructed using R software to predict the probability of OS.ResultsThe receiver operating characteristic curve showed prognostic value for OS, not EFS, in preoperative inflammatory indexes. Patients were categorized into low/high groups: SII ≤ 266.70/higher, NLR ≤ 1.24/higher, PLR ≤ 85.25/higher, and SIRI ≤ 0.72/higher. High NLR, PLR, SII, and SIRI groups had significantly lower 5-year OS than their low counterparts (all p-value < 0.05). The Cox analysis identified four independent prognostic factors: SIRI (HR=2.997, 95% CI: 1.119-8.031), microvascular invasion (HR=2.556, 95% CI: 1.14-5.73), the post-treatment extent of disease (POSTTEXT) staging (IV vs. I: HR=244.204, 95% CI:11.306-5274.556), and alpha-fetoprotein (>100 ng/ml: HR=0.11, 95% CI: 0.032-0.381) for hepatoblastoma patients with neoadjuvant chemotherapy. High SIRI group had more patients with adverse NLR, SII, and POSTTEXT III (all p-value < 0.05). Independent prognostic factors led to an OS nomogram with a concordance index of 0.85 (95% CI: 0.78-0.91, p-value = 1.43e-27) and the calibration curve showed a good fit between the prediction curve and the true curve.ConclusionsSIRI is an independent prognostic factor of hepatoblastoma patients receiving neoadjuvant chemotherapy. The OS nomogram based on SIRI, POSTTEXT staging, MiVI, and AFP can be used to assess the prognosis of those patients.

This paper examines whether and to what extent student engagement with the learning management system (LMS) Blackboard affects students’ academic performance during the COVID-19 pandemic. We find strong evidence that higher student engagement with Blackboard is associated with better academic performance. We also find that the association between student engagement and student academic performance varies with different blended learning formats. Specifically, the positive effects are more pronounced when synchronous online lectures and face-to-face tutorials are implemented. Given that COVID-19 is a constantly moving situation, this study highlights that a blended learning approach needs to engage students actively to facilitate social interaction with teachers and peers during periods of social restrictions.

A double potential well flat ion trap was designed as an ion accumulating and focusing device for multi-reflection time-of-flight mass analyzer. Two potential wells of the trap were severally used for accumulation of injected ions, controlled cooling and ejection of trapped ions, which had features to accumulate ions continuously and cool ion for almost one period. While a flat ion trap with only one potential well is a traditional and excellent ion accumulating and focusing device, which has an intermittent ion accumulation and an ion cooling around half period. Compared with the single potential well flat ion trap, the double potential well flat ion trap had better performance on ion accumulation and focusing in principle. Four steps to run the trap were simulated and researched by an ion optics simulator of SIMION 8.1. The first step was ion accumulation, ions were successively injected into the trap, and then stored and accumulated in the first potential well. The second step was ion transfer, the trapped ions were transferred from the first potential well to the second potential well. The third step was ion cooling, the trapped ions were confined in the second potential well, and were simultaneously cooled by collisions with 0.5 Pa He. The fourth step was ion ejection, the trapped ions were ejected from the trap and focused into the next device. Ion optics simulations indicated that the trap had a period from 1 ms to above 10 ms, a total ion transmission efficiency of 83%, and an ion flux of at most 1.6×106 ions. In addition, ion packets ejected from the trap had thermalized with radial diameters of 1.0 and 1.0 mm, angular standard deviations of 24 mrad and 16 mrad, and an energy standard deviation of 15 eV. This trap can be coupled with and provide high-flux and full-focusing ion packets for multi-reflection time-of-flight mass analyzers, due to an excellent suitability between the operation of the analyzer and the period, the ion transmission efficiency, the ion flux, and ejected ion packets of the trap.

Abstract Background Pulpitis is a common disease mainly caused by bacteria. Conventional approaches of diagnosing the state of dental pulp are mainly based on clinical symptoms, thereby harbor deficiencies. The accurate and rapid diagnosis of pulpitis is important for choosing the suitable therapy. The study aimed to identify pulpits related key genes by integrating micro-array data analysis and systems biology network-based methods such as weighted gene co-expression network analysis (WGCNA). Methods The micro-array data of 13 inflamed pulp and 11 normal pulp were acquired from Gene Expression Omnibus (GEO). WGCNA was utilized to establish a genetic network and categorize genes into diverse modules. Hub genes in the most associated module to pulpitis were screened out using high module group members (MM) methods. Pulpitis model in rat was constructed and iRoot BP plus was applied to cap pulp. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used for validation of hub genes. Results WGCNA was established and genes were categorized into 22 modules. The darkgrey module had the highest correlation with pulpitis among them. A total of 5 hub genes (HMOX1, LOX, ACTG1, STAT3, GNB5) were identified. RT-qPCR proved the differences in expression levels of HMOX1, LOX, ACTG1, STAT3, GNB5 in inflamed dental pulp. Pulp capping reversed the expression level of HMOX1, LOX, ACTG1. Conclusion The study was the first to produce a holistic view of pulpitis, screen out and validate hub genes involved in pulpitis using WGCNA method. Pulp capping using iRoot BP plus could reverse partial hub genes.

This work presents the design and application of a low-cycle reciprocating loading test on 23 recycled aggregate concrete-filled steel tube columns and 3 ordinary concrete-filled steel tube columns. Additionally, a systematic study on the influence of various parameters (e.g., slenderness ratio, axial compression ratio, etc.) was conducted on the seismic performance of the specimens. The results show that all the specimens have good hysteresis performance and a similar development trend of skeleton curve. The influence of slenderness ratio on the seismic index of the specimens is more significant than that of the axial compression ratio and the steel pipe wall thickness. Furthermore, artificial intelligence was applied to estimate the influence of parameter variation on the seismic performance of concrete columns. Specifically, Random Forest with hyperparameters tuned by Firefly Algorithm was chosen. The high correlation coefficients (R) and low root mean square error values from the prediction results showed acceptable accuracy. In addition, sensitivity analysis was applied to rank the influence of the aforementioned input variables on the seismic performance of the specimens. The research results can provide experimental reference for the application of steel tube recycled concrete in earthquake areas.

Abstract Background The purpose of this paper is to study how the Delta variant spread in a China city, and to what extent the non-pharmaceutical prevention measures of local government be effective by reviewing the contact network of COVID-19 cases in Xi’an, China. Methods We organize the case reports of the Shaanxi Health Commission into a database by text coding and convert them into a network matrix. Then we construct a dynamic contact network for the corresponding analysis and calculate network indicators. we analyze the cases’ dynamic contact network structure and intervals between diagnosis time and isolation time by using data visualization, network analysis method, and Ordinary Least Square (OLS) regression. Results The contact network for this outbreak in Xi’an is very sparse, with a density of less than 0.0001. The contact network is a scale-free network. The average degree centrality is 0.741 and the average PageRank score is 0.0005. The network generated from a single source of infection contains 1371 components. We construct three variables of intervals and analyze the trend of intervals during the outbreak. The mean interval (interval 1) between case diagnosis time and isolation time is − 3.9 days. The mean of the interval (interval 2) between the infector’s diagnosis time and the infectee’s diagnosis time is 4.2 days. The mean of the interval (interval 3) between infector isolation time and infectee isolation time is 2.9 days. Among the three intervals, only interval 1 has a significant positive correlation with degree centrality. Conclusions By integrating COVID-19 case reports of a Chinese city, we construct a contact network to analyze the dispersion of the outbreak. The network is a scale-free network with multiple hidden pathways that are not detected. The intervals of patients in this outbreak decreased compared to the beginning of the outbreak in 2020. City lockdown has a significant effect on the intervals that can affect patients’ network centrality. Our study highlights the value of case report text. By linking different reports, we can quickly analyze the spread of the epidemic in an urban area.

Abstract Background The aim of this cross-sectional survey was to apply the Objective Structured Clinical Examination (OSCE) to evaluate the cardiopulmonary resuscitation (CPR) and endotracheal intubation skills of resident dentists for stage assessment in standardized training. Methods A total of 146 third-year resident dentists were recruited and randomly assigned to perform either CPR or endotracheal intubation. Their performance was scored by experienced anesthesiologists with standardized scoring criteria. Participants were also asked to rated their self-assessed competence, willingness, and perceptions on training status using Likert-type scales in a questionnaire. Student’s ttest was applied to compare scores for CPR and endotracheal intubation performed by resident dentists with different characteristics. The results of the questionnaires were analyzed and visualized by the R package ‘Likert’. Significance was set at the P

Visible-infrared person re-identification (VI-ReID) aims at matching pedestrian images with the same identity between different modalities. Existing methods ignore the problems of detailed information loss and the difficulty in capturing global features during the feature extraction process. To solve these issues, we propose a Transformer-based Feature Compensation Network (TFCNet). Firstly, we design a Hierarchical Feature Aggregation (HFA) module, which recursively aggregates the hierarchical features to help the model preserve detailed information. Secondly, we design the Global Feature Compensation (GFC) module, which exploits Transformer’s ability to capture long-range dependencies in sequences to extract global features. Extensive results show that the rank-1/mAP of our method on the SYSU-MM01 and RegDB datasets reaches 60.87%/58.87% and 91.02%/75.06%, respectively, which is better than most existing excellent methods. Meanwhile, to demonstrate our method‘s transferability, we also conduct related experiments on two aerial photography datasets.