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Tb3Sc1.95Lu0.05Al3O12 (TSLAG) crystals are novel and high-quality magneto-optical materials with the most promising application as the core component of Faraday devices. Cracking is an obstacle to TSLAG crystal growth and is closely influenced by crystal thermal stress distribution. In this work, the evolution of thermal stress during TSLAG crystal growth in the initial Czochralski (Cz) furnace is numerically studied. The reasons for high thermal stress in TSLAG crystal are explained based on the results about the melt flow, the temperature distribution in the furnace, and the crystal/melt interface shape. A large crucible with a shallow melt is proposed to address the problem of significant variations in melt depth during TSLAG crystal growth. Based on the numerical results, the proposed design can stabilize the melt flow structure, suppressing changes in the crystal/melt interface shape and effectively improving thermal stress in the TSLAG crystal growth process, which contributes to precisely regulating the preparation of large-sized high-quality TSLAG crystals.

Background Amyotrophic lateral sclerosis (ALS) lacks sensitive, objective staging tools to guide clinical management and trials. Existing methods have limited granularity and rely on subjective assessment, while biomarker and imaging approaches can be invasive or impractical for serial use. Ultrasound is a safe, portable imaging modality that can detect neuromuscular changes, but it has not yet been applied to ALS staging. We developed and validated an interpretable ultrasound model for clinical staging and risk stratification in ALS. Methods We enrolled 300 ALS patients, classified as early-stage (King’s stages 1–2; n  = 148) or late-stage (3–4; n  = 152). Each patient underwent ultrasound of key muscle groups, including the diaphragm (excursion and thickening), geniohyoid (shear-wave velocity), and peripheral skeletal muscles (thickness and cross-sectional area). Six machine learning models were trained to predict early vs late stage from these ultrasound metrics combined with clinical factors. Performance was evaluated on a test set using area under the curve (AUC), F 1 score and Brier score. Feature importance was analyzed with SHapley Additive exPlanation (SHAP) values. Results In the test set, the random forest achieved an AUC of 0.843, an F 1 score of 0.727, and a Brier score of 0.177, with sensitivity 0.80 and specificity 0.68. SHAP analysis identified diaphragm excursion during deep breathing (DEDB) as the top predictor, followed by masseter muscle thickness (MMT) and geniohyoid shear-wave velocity (GHSWVmean). Higher DEDB, MMT and GHSWVmean values predicted earlier stage, whereas lower peripheral muscle thickness and older age indicated late-stage disease. Conclusions Multiparameter ultrasound combined with machine learning offers a non-invasive, bedside tool for ALS staging. The model’s accuracy and interpretability enable objective tracking of disease progression and may support timely interventions and patient stratification in clinical practice and trials. Leveraging widely accessible ultrasound technology, this approach is feasible for routine ALS care and research.

Background After the coronavirus disease 2019 (COVID-19) pandemic, no studies on bacterial and atypical pathogens were conducted in primary care. We aimed to describe the etiological composition of acute respiratory tract infections (ARTIs) presenting to primary care with limited resources after the pandemic. Methods 1958 adult patients with ARTIs from 17 primary care clinics were recruited prospectively from January 2024 to March 2024. 17 and 62 pathogens in throat swab samples were tested using polymerase chain reaction (PCR) and targeted next-generation sequencing (tNGS), respectively. We analyzed the pathogen spectrum and co-infectious pattern of viral, bacterial or atypical pathogens. Then, the associations between clinical characteristics and pathogens were investigated. Results In PCR test, the positive rate of any pathogens was 80.3%, consisting of 60.2% for viruses, 41.8% for bacteria and 21.7% for viral-bacterial co-infection. In tNGS test, the positive rate was 89.1%, consisting of 64.7% for viruses, 55.2% for bacteria and 30.9% for viral-bacterial co-infection. Influenza virus B (18.2%), influenza virus A (16.8%) and severe acute respiratory syndrome coronavirus 2 (14.1%) were the three leading viral pathogens, and H. influenzae (36.1%), S. anginosus (15.7%) and S. pneumoniae (8.4%) were the three leading bacterial pathogens. Few M. pneumoniae (1.6%) were detected. The mixed bacterial or mixed viral-bacterial co-infections were the most common co-infectious patterns. The mixed bacterial or mixed viral-bacterial co-infections were the most common co-infectious patterns. Overall, patients with viral infection or viral-bacterial co-infection had more clinical symptoms, and patients with bacterial infection had higher inflammatory indicators. Conclusions After the COVID-19 pandemic, the main viral pathogens of ARTIs were unevenly distributed, and less bacterial and atypical pathogens were detected in primary care. The microbiological evidences can optimize the precision diagnosis and treatment of ARTIs in primary care with limited resources.

Under the low speed condition, a method of real-time tracking and estimation of rotor position based on PLL technology is proposed, which is used to solve the control system detection accuracy problem of permanent magnet synchronous motor (PMSM) for electric vehicles. The control principles of high frequency signal fluctuation are analyzed, and the mathematical model of three phases PMSM under rotor estimated synchronous rotating reference frame is established. The basic principles of phase locked loop (PLL) are analyzed. Based on phase locked loop, a rotor position estimation method is designed and analyzed. Finally, simulation model of sensorless control system is set up, and the simulation experiment is carried out. The simulation experiment results show that the sensorless control based on PLL can obtain the accurate rotor positions and the excellent control ability. Therefore, the rotor positions estimation method based on PLL is an ideal method for the sensorless control of electric vehicle drive motor, which can provide theoretical and technical support for improving the control precision of PMSM and quality of electric vehicles.

The phase cycling method is a state-of-the-art method to reconstruct complex-valued MR image. However, when it follows practical two-dimensional (2D) subsampling Cartesian acquisition which is only enforcing random sampling in the phase-encoding direction, a number of artifacts in magnitude appear. A modified approach is proposed to remove these artifacts under practical MRI subsampling, by adding one-dimensional total variation (TV) regularization into the phase cycling method to “pre-process” the magnitude component before its update. Furthermore, an operation used in SFISTA is employed to update the magnitude and phase images for better solutions. The results of the experiments show the ability of the proposed method to eliminate the ring artifacts and improve the magnitude reconstruction.

The traditional electromagnetic–thermal bidirectional coupling model (EMTBCM) of permanent magnet synchronous motors (PMSMs) requires a long time to solve, and the temperature-induced torque change is not accounted for in the finite element (FE) numerical calculation of the EM field. This paper presents a precise and efficient EMTBC reduced-order solution model. The specific methods are as follows: First, a torque control technology based on the current injection method is proposed for determining the effect of temperature on the properties of EM materials and EM torque in an EM field, and the accuracy of the FE numerical calculation model is improved. Second, we use the improved EM field finite element numerical calculation model (FEMNCM) to analyze the correlation between the EM loss, the temperature, and the load, and we replace the FEMNCM with the EM field reduction model using the least-squares method. Then, we analyze the law of the PMSM’s internal temperature distribution. We choose the GA-BP algorithm with as few samples as possible and a high accuracy and stability to build the regression prediction model of the temperature field. We use this regression prediction model to replace the complex temperature field calculation. After analyzing the EMTBCM solution strategy, the original complex EMTBC numerical calculation model is substituted with iterations of the magnetic field reduction model and the temperature field regression prediction model. The FE numerical calculation is then used to validate the reduced-order model. The proposed model is validated through numerical simulations. The numerical results indicate that the proposed reduced-order EMTBC model in this paper is accurate and computationally efficient.

In order to study the linear instability and turbulence of the boundary plasma, this paper uses the BOUT++ numerical simulation tool. Mainly analyze the driving mechanism of the instability of the ideal balloon model, and the instability suppression mechanism of the ion diamagnetic effect, and compare with the analysis results of the dispersion relationship. Subsequently, the integral dispersion relationship is used to analyze the suppression mechanism of the shear flow. In addition, the dispersion relationship is not suitable for analyzing the global effect of the shear flow. Due to the locality of the dispersion relationship, the integral dispersion relationship uses the numerical integration of the mode structure to resolve the dispersion relationship. Used to analyze shear flow. Then, use the numerical integration of kinetic energy in the whole space to study the contribution of these effects to free energy. Finally, using the above linear analysis method, the physical mechanism of these effects under the EAST divertor configuration is studied.

The robust finite-time control for a Francis hydroturbine governing system is investigated in this paper. Firstly, the mathematical model of a Francis hydroturbine governing system is presented and the nonlinear vibration characteristics are analyzed. Then, on the basis of finite-time control theory and terminal sliding mode scheme, a new robust finite-time terminal sliding mode control method is proposed for nonlinear vibration control of the hydroturbine governing system. Furthermore, the designed controller has good robustness which could resist external random disturbances. Numerical simulations are employed to verify the effectiveness and superiority of the designed finite-time sliding mode control scheme. The approach proposed in this paper is simple and also provides a reference for relevant hydropower systems.

First, this paper analyzes the plasma discharge and fluid model, and constructs the plasma discharge model by drift-diffusion approximation control equation, heavy particle component control equation, electric field distribution and volume force calculation, and plasma chemical kinetic model. Next, the coupling mechanism of inductively coupled RF plasma and its discharge characteristics are analyzed. Finally, the magnetized inductively coupled plasma discharge is simulated numerically. The results demonstrate that the current flowing on an inductor coil develops quicker at 0.045T and then calms down with an increase in the supplied constant dynamic magnetic field power, but the coil voltage exhibits the reverse effect.

This paper studies the application of frequency distributed model for finite-time control of a class of fractional-order nonlinear systems. Firstly, a class of fractional-order nonlinear systems with model uncertainties and external disturbances are introduced, and a new frequency distributed model with theoretical inference is presented. Secondly, a novel fast terminal sliding surface is proposed and its stability to origin is proved based on the frequency distributed model and Lyapunov stability theory. Furthermore, based on finite-time stability and sliding mode control theory, a robust control law to ensure the occurrence of the sliding motion in a finite time is designed for stabilization of the fractional-order nonlinear systems. Finally, two typical examples of three-dimensional nonlinear fractional-order Lorenz system and four-dimensional nonlinear fractional-order Chen system are employed to demonstrate the validity of the proposed method.