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After the “6 • 1” Lushan earthquake, unstable rock mass was discovered in Zhangjiagou, posing a severe threat to the safety of the residents and their property below. The dangerous rock mass was evaluated using stability calculation and the discrete element numerical analysis method, and the seismic condition with the highest threat level was selected for kinematic analysis. Based on this research, a combination of analytical solution and numerical solution was used to design corresponding protective measures. The main conclusions are as follows : (1) The structure of the unstable rock mass in Zhangjiagou is broken, and a controlling structural plane is developed along the slope. (2) The stability calculations and numerical simulations show that the Zhangjiagou unstable rock mass will become unstable under natural, rainstorm and seismic conditions, with the longest movement distance occurring during an earthquake. (3) The failure mode of the dangerous rock mass under seismic conditions is a shatter-slip type, where the rock mainly slips during movement, and the jump height is small. Additionally, the slope shape significantly affects the characteristics of rockfall movement. (4) The collision and extrusion between rockfalls can change their motion characteristics and impact kinetic energy, potentially increasing the scope of the disaster. The research results can provide a reference for similar disaster prevention and control efforts.

Wire arc additive manufacturing (WAAM) excels in producing medium to large components with a high deposition rate. Process optimization is crucial for uniform, defect-free components. This research employs orthogonal experimental design and response surface methodology (RSM) to control TIG WAAM-ed 308L stainless steel components. Varied parameters, including tungsten electrode angle, welding current, and speed, target weld bead attributes. Analysis of variance (ANOVA) evaluates multi-processing parameter influence on weld bead formation. Comparison with experimental results confirms accurate modeling of the relationship between parameters and bead attributes. The study optimizes process parameters and swing to enhance dimensional accuracy in single-layer and multi-layer components, improving precision, quality, and accuracy in thin-walled structures.

Objective The effect of fetal oval foramen restriction and premature contraction of the arterial catheter for the right heart function of fetuses and infants was studied by evaluating the right and left ventricular (RV/LV) ratios, the tricuspid annular plane systolic excursion (TAPSE) value, and the Tei index of right heart function parameters. Methods This study was approved by the Ethics Committee of First Affiliated Hospital of Hebei North University (K20190116). We collected 257 fetuses between March 2020 and December 2021. Among these, 98 fetuses that did not have any heart abnormalities were assigned to group A, 91 fetuses with restriction of the left and right atrial channels were assigned to group B, and 68 fetuses with premature contraction of the arterial catheter were assigned to group C. The ventricular transverse diameter, the right heart TAPSE value and the Tei index of fetuses in late pregnancy and 90 days after birth were measured in the three groups, and the diagnostic value of each index for the right heart function injury was evaluated. P 0.05, which was not significant; however, P

Although prior studies have extensively investigated the effect of working conditions upon professional satisfaction, the cross-national variance in the effect remains largely understudied due to technical or financial restrictions. The Teaching and Learning International Survey (TALIS) provides an opportunity to investigate the cross-country differences in the impact of working conditions upon principals’ professional satisfaction. The current study attempts to investigate the overall and specific effects of principals’ workplace environment satisfaction, rewards satisfaction, and workload stress on their professional satisfaction in 47 countries included in the TALIS 2018. The results indicate that workplace environment, rather than the typically regarded effort-reward issues, is the most powerful contributor to individual principals’ professional satisfaction across 47 countries, while, in countries with low overall professional satisfaction, rewards satisfaction and workload stress are more powerful predictors for principals’ professional satisfaction on the country level. This study may inform policymakers in school principal stimulation and retention that effective practice to stimulate and/or retain school principals may vary across countries and research findings derived from data on the individual level may not be applicable to practice on the country level.

Floor water inrush has always been an important problem affecting coal mine safety. The water inrush from the deep coal seam floor is the final manifestation of the water inrush channel formed by the expansion and penetration of rock mass cracks under the combined action of a high ground temperature, high ground stress, high karst water pressure and strong mining disturbance. The fault is a structurally weak plane developed in the complete rock layer, which can be regarded as a permeable channel with good permeability. In order to explore the location of confined water from the fault to rock stratum caused by the tensile fracture of a fault during floor water inrush, floor water inrush is regarded as the result of the joint action of water pressure and mining stress. The COMSOL Multiphysics numerical simulation software was used to simulate the advancing process of the working face of the coal seam with a fault structure. Different fault dip models were established for comparative analysis. The objective weight CRITIC based on data volatility was used to analyze the water pressure and principal stress near the fault. The results show that the uplift strength of highly confined water increases with the increase in the fault dip angle, and the weight of water pressure near the fault has a certain relationship with the location of the water body entering the rock stratum from the fault.

Objective: The objective of the study is to construct a regional ST-segment elevation myocardial infarction (STEMI) treatment network system using the WeChat platform as a carrier and to explore the effect of this system on the time to reperfusion treatment and efficacy of treatment for patients with acute STEMI. Materials and Methods: The Department of Cardiology at our hospital constructed a STEMI rescue WeChat group including 120 emergency departments and acute care hospitals in the district. For all suspected STEMIs, relevant medical history data were uploaded to the WeChat group, a physician from the Department of Cardiology was consulted electronically, and this cardiologist was able to inform the local physician of a reperfusion treatment plan. One hundred and seventy-seven STEMI patients were transferred to our hospital within 12 h of presentation, of which 81 cases were transferred before the establishment of the WeChat group (the control group), and 96 cases were transferred using the WeChat system (WeChat group). The time to reperfusion, O-to-FMC time, FMC-to-B time, D-to-B time, average hospitalization stay, and mortality during hospitalization were observed and compared between the two groups. Results: The WeChat group had a lower O-to-FMC time compared with the control group, but this difference was not statistically significant. The FMC-to-B time, the time of D-to-B, and the average days of hospitalization in the WeChat group were all lower compared with those in the control group. The incidence of cardiovascular events and the heart function ratio of the patients after 6 months were compared, and the WeChat group was statistically superior to the control group in relation to these outcomes. Conclusion: The establishment of a STEMI regional treatment network based on the WeChat platform can shorten the time to reperfusion treatment, reduce postreperfusion cardiovascular events, shorten the days of hospitalization, and improve the heart function of patients.

Understanding the space-time dynamics of human activities is essential in studying human security issues such as climate change impacts, pandemic spreading, or urban sustainability. Geotagged social media posts provide an open and space-time continuous data source with user locations which is convenient for studying human movement. However, the reliability of Chinese geotagged social media data for representing human mobility remains unclear. This study compares human movement data derived from the posts of Sina Weibo, one of the largest social media software in China, and that of Baidu Qianxi, a high-resolution human movement dataset from ‘Baidu Map’, a popular location-based service in China with 1.3 billion users. Correlation analysis was conducted from multiple dimensions of time periods (weekly and monthly), geographic scales (cities and provinces), and flow directions (inflow and outflow), and a case study on COVID-19 transmission was further explored with such data. The result shows that Sina Weibo data can reveal similar patterns as that of Baidu Qianxi, and that the correlation is higher at the provincial level than at the city level and higher at the monthly scale than at the weekly scale. The study also revealed spatial variations in the degree of similarity between the two sources. Findings from this study reveal the values and properties and spatiotemporal heterogeneity of human mobility data extracted from Weibo tweets, providing a reference for the proper use of social media posts as the data sources for human mobility studies.

In addition to eliminating voids in a billet, the reduction pretreatment (RP) process can refine the austenite structure after reheating and can deform the residual voids, which affect the void healing behavior during insulation before rolling, and then can affect the final quality of the steel plate. In this study, the effect of the RP process on the evolution of voids in billets and steel plates was investigated by experimental and numerical simulation. RP and non-RP billets were reheated and rolled into 60 mm-thick steel plates, respectively, and the evolutionary behavior of voids within the plates was analyzed using ultrasonic flaw detection methods. Finite element method (FEM) and phase-field method (PFM) were used to investigate the mechanism behind improving the quality of steel plates under the RP process. The simulation results show that, in addition to directly closing the voids through plastic deformation, the RP process can promote the diffusive healing behavior during insulation before rolling by refining the reheated austenite organization and by increasing the curvature of the void surface. Due to the reduction in voids inside the steel plate, the impact energy of the RP steel plate is higher.

High-temperature reduction pretreatment (HTRP) is a process that can significantly improve the core quality of a billet. The existing flow stress data cannot meet the needs of simulation due to lack of high temperature data. To obtain the hot forming process parameters for the high-temperature reduction pretreatment process of 42CrMo steel, a hot compression experiment of 42CrMo steel was conducted on Gleeble-3500 thermal-mechanical at 1200–1350 °C with the rates of deformation 0.001–10 s−1 and the deformation of 60%, and its deformation behavior at elevated temperature was studied. In this study, the effects of flow stress temperature and strain rate on austenite grain were investigated. Moreover, two typical constitutive models were employed to describe the flow stress, namely the Arrhenius constitutive model of strain compensation and back propagation artificial neural network (BP ANN) model. The performance evaluation shows that BP ANN model has high accuracy and stability to predict the curve. The thermal processing maps under strains of 0.1, 0.2, 0.3, and 0.4 were established. Based on the analysis of the thermal processing map, the optimal high reduction process parameter range of 42CrMo is obtained: the temperature range is 1250–1350 °C, and the strain rate range is 0.01–1 s−1.

A Gauss process state-space model trained in a laboratory cannot accurately simulate a nonlinear system in a non-laboratory environment. To solve this problem, a novel Gauss process state-space model optimization algorithm is proposed by combining the expectation–maximization algorithm with the Gauss process Rauch–Tung–Striebel smoother algorithm, that is, the EM-GP-RTSS algorithm. First, a theoretical formulation of the Gauss process state-space model is proposed, which is not found in previous references. Second, a Gauss process state-space model optimization framework with the expectation–maximization algorithm is proposed. In the expectation–maximization algorithm, the unknown system state is considered as the lost data, and the maximization of measurement likelihood function is transformed into that of a conditional expectation function. Then, the Gauss process–assumed density filter algorithm and the Gauss process Rauch–Tung–Striebel smoother algorithm are proposed with the Gauss process state-space model defined in this article, in order to calculate the smoothed distribution in the conditional expectation function. Finally, the Monte Carlo numerical integral method is used to obtain the approximate expression of the conditional expectation function. The simulation results demonstrate that the Gauss process state-space model optimized by the EM-GP-RTSS can simulate the system in the non-laboratory environment better than the Gauss process state-space model trained in the laboratory, and can reach or exceed the estimation accuracy of the traditional state-space model.

Controlling the segregation of alloying elements in steel can improve the uniformity of the structure and properties of the material. High Temperature Reduction Pretreatment (HTRP) is an effective technique to improve the internal quality of steel by generating plastic deformation in the core and providing the recrystallization energy. Comparative analysis was conducted to illustrate the effect of the HTRP on the internal quality of 42CrMo cast billets. To quantitatively analyze the recrystallization and diffusion mechanisms, the tested samples were measured using Scanning Electron Microscopy (SEM), Original Position Statistic Distribution Analysis (OPA) and Electron Probe Microanalysis (EPMA). The results show that the plastic deformation prompts the austenite to recrystallize. As the deformation of the HTRP sample increases, the recrystallized austenite grain size decreases significantly. It is also found that the statistical macro-segregation and micro-segregation ratios of substitutional elements Si, Mn, Cr and Mo decrease. The increase in austenite grain boundaries enables the increase in diffusion coefficient of the solid solution elements, which is the main reason for improving the segregation of the cast billet.

The reduction pretreatment (RP) process is an effective method to improve billet quality, and the deformation recrystallization plays an important role in the process. Exploring the RP process parameters, a dynamic recrystallization model of GCr15 steel was established by the phase-field method and physical simulation. The recrystallization kinetics and flow stress curves during hot compression were simulated by using this mode. The effects of deformation parameters and initial grain size on the dynamic recrystallization were investigated. Moreover, by using the results obtained by Finite element method (FEM), dynamic recrystallization during the RP process was investigated though this model. It was found that increasing the deformation temperature, deformation rate and decreasing the initial grain size can promote the dynamic recrystallization kinetics. Large Zener-Hollomon parameters can enhance recrystallized grain refinement, while the recrystallized grain size was not affected by the initial grain size. During the RP process, when the reduction is insufficient (10%), partial recrystallization occurs in the billet. With the increase of reduction from 10% to 16%, the area of complete recrystallization increases gradually. When the reduction is the same, the recrystallization in the billet center increases with the decrease of casting speed. When the reduction is 10%, partial recrystallization occurs in the billet center at a casting speed of 0.7 m min ^−1 , and fully recrystallization occurs in the billet center with a casting speed of 0.5 m min ^−1 . Thus, when the reduction is difficult to increase further, the recrystallization in the billet center can be improved by decreasing the casting speed.

It is difficult to answer the problem whether the range rate measurement should be adopted to track a target in a tracking scenario. A practical adaptive nonlinear tracking algorithm with the range rate measurement is proposed, which avoids this problem and achieves good accuracy of target state estimation. First, three popular nonlinear filtering algorithms only with the position measurement are surveyed. Second, three popular nonlinear filtering algorithms with the position and range rate measurements are surveyed. Then, a novel tracking algorithm with range rate measurement is proposed based on the cumulative sum detector and the above two kinds of nonlinear algorithms. The results of simulation experiment demonstrate that the range rate measurement could reduce accuracy of the target state estimation in mismatch tracking scenarios. The results of simulation experiment also verify that the performance of proposed algorithm is better than the current state and the art interacting multiple-model algorithm and can well follow the state estimation output of the measurement equation matching the tracking scenario.

The problem of maneuvering target tracking is a hot issue in the field of target tracking. Due to the range rate measurement containing the maneuvering information of target, it has the important practical significance to study how to use the range rate measurement to improve the effect of maneuvering target tracking. In the framework of interacting multiple model algorithm, the range rate measurement is used to update target state estimate and the probability of motion model to improve the tracking performance. As the measurement equation including the range rate measurement is strongly nonlinear, square root cubature Kalman filter algorithm is selected as the filter in interacting multiple model algorithm. The normal acceleration is deduced from the range rate with the reality constraint. And through Monte Carlo simulation, the empirical distribution functions of the normal acceleration statistics corresponding to different motion models are obtained. Their approximate distribution functions are obtained by the use of the expectation maximization algorithm with Gaussian mixture model. Then the probability distribution and probability distribution of measurement prediction residual are combined into a new likelihood function to improve the efficiency of updating the model probability. The experimental results show that the interacting multiple model algorithm proposed in this article has the smaller root mean square error of position and velocity and has the smaller average Kullback-Leibler divergence of model probability during the motion model stable phase.

Articular chondrocytes are the main cell population in cartilage, and damage to them is a key step in osteoarthritis. There are chondrocyte-based strategies to treat osteoarthritis, among which includes nonviral gene therapy. However, so far there is no ideal way to achieve this because chondrocyte cells are very difficult to transfect. Also, an effective tracking system to evaluate exogenous DNA delivery in chondrocytes is a necessary part of this strategy. Here, we show our development of a novel tracking system by labelling cell membranes, nuclei, and plasmids, without disturbing their expression, to view the intracellular behaviour of plasmids before, after, and during the entire transfection process. We applied this system to compare the intracellular behaviour of exogenous DNA in chondrocytes and cancer cells. We also used this system to compare the intracellular behaviour of exogenous DNA which is transfected by liposomes or polymers. Finally, we discovered that when transfected by liposomes, exogenous DNA has a quicker cell entry and nucleus entry in cancer cells than in chondrocytes, and the transfection efficiency is higher in cancer cells than in chondrocytes. When the cells are transfected by polymers, exogenous DNA has the same quick cell entry and nucleus entry in both types of cells. However, the transfection efficiency was higher in cancer cells than in chondrocytes. Applying this system has proved to be simple, easy to operate, repeatable, and stable and it enables tracking of the behaviour of plasmid DNA before and after expression. Meanwhile, the rate-limiting zones of exogenous plasmid DNA in living cells and a comprehensive overview of the expression and transfection efficiency of DNA can also be obtained through this system, making it ideal for the research and development of nonviral DNA delivery systems.

A contextual effects model, built based on Bayesian spatial modeling strategy, was used to investigate contextual effects on neighborhood burglary risks in Wuhan, China. The contextual effects denote the impact of the upper-level area on the lower-level units of analysis. These effects are often neglected in Bayesian spatial crime analysis. The contextual effects model accounts for the effects of independent variables, overdispersion, spatial autocorrelation, and contextual effects. Both the contextual effects model and the conventional Bayesian spatial model were fitted to our data. Results showed the two models had almost the same deviance information criterion (DIC). Furthermore, they identified the same set of significant independent variables and gave very similar estimates for burglary risks. Nonetheless, the contextual effects model was preferred in the sense that it provides insights into contextual effects on crime risks. Based on the contextual effects model and the map decomposition technique, we identified, worked out, and mapped the relative contribution of the neighborhood characteristics and contextual effects on the overall burglary risks. The research contributes to the increasing literature on modeling crime data by Bayesian spatial approaches.

A multivariate Bayesian spatial modeling approach was used to jointly model the counts of two types of crime, i.e., burglary and non-motor vehicle theft, and explore the geographic pattern of crime risks and relevant risk factors. In contrast to the univariate model, which assumes independence across outcomes, the multivariate approach takes into account potential correlations between crimes. Six independent variables are included in the model as potential risk factors. In order to fully present this method, both the multivariate model and its univariate counterpart are examined. We fitted the two models to the data and assessed them using the deviance information criterion. A comparison of the results from the two models indicates that the multivariate model was superior to the univariate model. Our results show that population density and bar density are clearly associated with both burglary and non-motor vehicle theft risks and indicate a close relationship between these two types of crime. The posterior means and 2.5% percentile of type-specific crime risks estimated by the multivariate model were mapped to uncover the geographic patterns. The implications, limitations and future work of the study are discussed in the concluding section.

A Bayesian random effects modeling approach was used to examine the influence of neighborhood characteristics on burglary risks in Jianghan District, Wuhan, China. This random effects model is essentially spatial; a spatially structured random effects term and an unstructured random effects term are added to the traditional non-spatial Poisson regression model. Based on social disorganization and routine activity theories, five covariates extracted from the available data at the neighborhood level were used in the modeling. Three regression models were fitted and compared by the deviance information criterion to identify which model best fit our data. A comparison of the results from the three models indicates that the Bayesian random effects model is superior to the non-spatial models in fitting the data and estimating regression coefficients. Our results also show that neighborhoods with above average bar density and department store density have higher burglary risks. Neighborhood-specific burglary risks and posterior probabilities of neighborhoods having a burglary risk greater than 1.0 were mapped, indicating the neighborhoods that should warrant more attention and be prioritized for crime intervention and reduction. Implications and limitations of the study are discussed in our concluding section.