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Slope instability through can cause catastrophic consequences, so slope stability analysis has been a key topic in the field of geotechnical engineering. Traditional analysis methods have shortcomings such as high operational difficulty and time-consuming, for this reason many researchers have carried out slope stability analysis based on AI. However, the current relevant studies only judged the importance of each factor and did not specifically quantify the correlation between factors and slope stability. For this purpose, this paper carried out a sensitivity analysis based on the XGBoost and SHAP. The sensitivity analysis results of SHAP were also validated using GeoStudio software. The selected influence factors included slope height (H), slope angle (β), unit weight (γ), cohesion (c), angle of internal friction (φ) and pore water pressure coefficient (ru). The results showed that c and γ were the most and least important influential parameters, respectively. GeoStudio simulation results showed a negative correlation between γ, β, H, ru and slope stability, while a positive correlation between c, φ and slope stability. However, for real data, SHAP misjudged the correlation between γ and slope stability. Because current AI lacked common sense knowledge and, leading SHAP unable to effectively explain the real mechanism of slope instability. For this reason, this paper overcame this challenge based on the priori data-driven approach. The method provided more reliable and accurate interpretation of the results than a real sample, especially with limited or low-quality data. In addition, the results of this method showed that the critical values of c, φ, β, H, and ru in slope destabilization are 18 Kpa, 28°, 32°, 30 m, and 0.28, respectively. These results were closer to GeoStudio simulations than real samples.

Abstract Accumulation landslides are prone to occur during the continuous infiltration of heavy rainfall, which seriously threatens the lives and property safety of local residents. In this paper, based on the Green-Ampt (GA) infiltration model, a new slope rainfall infiltration function is derived by combining the effect of air resistance and lateral seepage of saturated zone. Considering that when the soil layer continues to infiltrate after the saturation zone is formed, the air involvement cannot be discharged in time, which delays the infiltration process. Therefore, the influence of air resistance factor in soil pores is added. According to the infiltration characteristics of finite long slope, the lateral seepage of saturated zone is introduced, which makes up for the deficiency that GA model is only applicable to infinite long slope. Finally, based on the seepage characteristics of the previous analysis, the overall shear strength criterion is used to evaluate the stability of the slope. The results show that the safety factor decreases slowly with the increase of size and is inversely correlated with the slope angle and initial moisture content. The time of infiltration at the same depth increases with the increase of size and slope angle, and is inversely correlated with the initial moisture content, but is less affected by rainfall intensity. By comparing with the results of experimental data and other methods, the results of the proposed method are more consistent with the experimental results than other methods.

Friction torque disturbance affects the tracking performance of electromechanical actuator servo system, bringing position and speed tracking errors, and even may leading to instability of the servo system. Aiming at the problem of poor tracking performance of electromechanical actuator servo system under friction torque disturbance, a FOANN friction compensation algorithm is proposed to estimate and compensate the friction torque. Firstly, base on LuGre friction model, a electromechanical actuator model is established, and the unmeasured state variable in the LuGre model is estimated by radial basis function neural network. Secondly, a FOANN controller is designed, and the stability of corresponding closed-loop system is proved by Lyapunov stability theory. Finally, through simulation and experimental platform, the dynamic performance of FOANN is compared with those of traditional PD and MRAC. The simulation and experimental results show that, with the proposed FOANN friction torque compensation algorithm, the tracking errors of both position and velocity of electromechanical actuator servo system are greatly reduced. FOANN algorithm can effectively estimate and compensate friction torque, reduce the impact of friction disturbance and enhance the dynamic performance of the servo system.

Septic shock is a life-threatening disease worldwide often associated with thrombocytopenia. Platelets play a crucial role in bridging the gap between immunity, coagulation, and endothelial cell activation, potentially influencing the course of the disease. However, there are few studies specifically evaluating the impact of thrombocytopenia on the prognosis of pediatric patients. Therefore, the study investigates effects of early thrombocytopenia in the prognosis of children with septic shock. Pediatric patients with septic shock from 2015 to 2022 were included monocentrically. Thrombocytopenia was defined as a platelet count of

Concrete is the most popular construction material in infrastructure projects due to its numerous natural advantages. Nevertheless, concrete constructions frequently suffer from low tensile strength and poor durability performance which are always urgent tasks to be solved. The concrete reinforced by various nanomaterials, especially graphene and its associated nanostructures (GANS), shows excellent chemical and physical properties for engineering applications. The influence of GANS on cement composites is a multiscale behavior from the nanoscale to the macroscale, which requires a number of efforts to reveal via numerical and experimental approaches. To meet this need, this study provides a comprehensive overview of the numerical modeling for GANS reinforced concrete in various scales. The background and importance of the topic are addressed in this study, along with the review of its methodologies, findings, and applications. Moreover, the study critically summarizes the performance of GANS reinforced concrete, including its mechanical behavior, transport phenomena, and failure mechanism. Additionally, the primary challenges and future prospects in the research field are also discussed. By presenting an extensive overview, this review offers valuable insights for researchers and practitioners interested in numerical simulation to advance concrete science and engineering.

Primary Sjögren’s Syndrome (pSS) is a complex autoimmune disorder characterized by exocrine gland dysfunction, leading to dry eyes and mouth. Despite growing interest in biologic therapies for pSS, FDA approval has proven challenging due to trial complications. This review addresses the absence of a molecular-target-based approach to biologic therapy development and highlights novel research on drug targets and clinical trials. A literature search identified potential pSS treatment targets and recent advances in molecular understanding. Overlooking extraglandular symptoms like fatigue and depression is a notable gap in trials. Emerging biologic agents targeting cytokines, signal pathways, and immune responses have proven efficacy. These novel therapies could complement existing methods for symptom alleviation. Improved grading systems accounting for extraglandular symptoms are needed. The future of pSS treatment may involve gene, stem-cell, and tissue-engineering therapies. This narrative review offers insights into advancing pSS management through innovative biologic interventions.

Abstract Construction accidents in the construction industry cause a large amount of property damage and human casualties. Therefore, avoiding construction accidents as much as possible is a problem that engineers have been working on for a long time. Currently, few construction managers use artificial intelligence methods for construction safety management. The purpose of this article is to propose a new artificial neural network (ANN) prediction model to provide early warning for future construction and to provide reference for construction organization decision‐makers. In the proposed method, atomic search optimization algorithm is used to optimize the weights and thresholds of back propagation neural network, and the Tent chaotic mapping is used to initialize the population to increase the diversity of the population. The statistical data of production safety accidents of housing and municipal engineering in China from 2015 to 2019 are used as an example, and the prediction results of the proposed model are compared with back‐propagation neural network (BPNN) and wavelet neural network (WNN). The mean absolute error (MAE) of predicting construction accidents is 0.2225, with small fluctuations in the predicted results. The mean absolute percentage error (MAPE) of the predictions is 0.6048%. The research results indicate that IASO‐BPNN has higher prediction accuracy than standard BPNN and WNN, providing judgment methods for ensuring construction progress and decision support for construction organization decision‐makers.

Background: The incidence of Pseudomonas aeruginosa (P. aeruginosa) bacteremia in children ranks third to fourth among gram-negative bacilli bacteremia, which is one of the main conditional pathogens in hospitals. This study aimed to identify the clinical characteristics and risk factors of 60-day in-hospital mortality in children with P. aeruginosa bacteremia. Methods: This retrospective study was conducted in a tertiary pediatric hospital between January 2015 and December 2021 including children with P. aeruginosa bacteremia. Kaplan–Meier survival analysis was used to investigate the time-to-event outcomes. Logistic regression was used to explore the independent risk factors for 60-day mortality. Results: Overall, 75 patients with P. aeruginosa bacteremia episodes were identified. Immunosuppression (52%) was the most common underlying condition, followed by neutropenia (50.7%) and hematological malignancies (48%). Among 75 patients with P. aeruginosa bacteremia, 25 (33.3%) had septic shock, 30 (40%) had respiratory failure, and 20 (26.7%) had liver function impairment. The 60-day in-hospital mortality was 17.3%. In multivariate analysis, independent risk factors for 60-day mortality were respiratory failure [odds ratio (OR) 39.329; 95% CI:3.212–481.48, P = 0.004) and liver function impairment (OR 17.925; 95% CI:2.909–139.178, P = 0.002). Conclusion: Respiratory failure and liver function impairment seem to be related to poor prognosis in children with P. aeruginosa bacteremia.

Abstract Background Preimplantation genetic testing for aneuploidy (PGT-A) was demonstrated to be superior to conventional IVF in reducing the incidence of miscarriage and abnormal offspring after the first embryo transfer (ET). PGT-A requires several embryo trophectoderm cells, but its negative impacts on embryo development and long-term influence on the health conditions of conceived children have always been a concern. As an alternative, noninvasive PGT-A (niPGT-A) approaches using spent blastocyst culture medium (SBCM) achieved comparable accuracy with PGT-A in several pilot studies. The main objective of this study is to determine whether noninvasive embryo viability testing (niEVT) results in better clinical outcomes than conventional IVF after the first embryo transfer. Furthermore, we further investigated whether niEVT results in higher the live birth rate between women with advanced maternal age (AMA, > 35 years old) and young women or among patients for whom different fertilization protocols are adopted. Methods This study will be a double-blind, multicenter, randomized controlled trial (RCT) studying patients of different ages (20–43 years) undergoing different fertilization protocols (in vitro fertilization [IVF] or intracytoplasmic sperm injection [ICSI]). We will enroll 1140 patients at eight reproductive medical centers over 24 months. Eligible patients should have at least two good-quality blastocysts (better than grade 4 CB). The primary outcome will be the live birth rate of the first embryo transfer (ET). Secondary outcomes will include the clinical pregnancy rate, ongoing pregnancy rate, miscarriage rate, cumulative live birth rate, ectopic pregnancy rate, and time to pregnancy. Discussion In this study, patients who undergo noninvasive embryo viability testing (niEVT) will be compared to women treated by conventional IVF. We will determine the effects on the pregnancy rate, miscarriage rate, and live birth rate and adverse events. We will also investigate whether there is any difference in clinical outcomes among patients with different ages and fertilization protocols (IVF/ICSI). This trial will provide clinical evidence of the effect of noninvasive embryo viability testing on the clinical outcomes of the first embryo transfer. Trial registration Chinese Clinical Trial Registry (ChiCTR) Identifier: ChiCTR2100051408. 9 September 2021.