Correlation between vitamin D levels and blood pressure in elderly hypertensive patients with osteoporosis

ObjectivesThe association between vitamin D and blood pressure in elderly patients with hypertension complicated by osteoporosis remains unclear. The objective of this study is to explore whether vitamin D deficiency contributes to elevated blood pressure in elderly individuals with both hypertension and osteoporosis.MethodsThis study represents a single-center retrospective observational investigation carried out at the Zhongshan Hospital Affiliated to Xiamen University. Ambulatory blood pressure, bone density, vitamin D levels, and additional laboratory parameters were collected upon admission. The association between vitamin D and ambulatory blood pressure outcomes was assessed using Spearman correlation tests and partial correlation analyses. The relationship between vitamin D and changes in blood pressure was analyzed through Generalized Additive Models, and threshold analysis was conducted to explore potential thresholds.Results139 patients with newly diagnosed osteoporosis were consecutively included (mean age 73 years, 84.9% female). There is a negative correlation between 25-(OH) D3 and 24 h mean systolic blood pressure (mSBP), diurnal mSBP, nocturnal mSBP, maximum SBP, respectively. The results of the generalized additive model analysis show that there is a nonlinear relationship between 25-(OH) D3 and 24 h mSBP, diurnal mSBP, nocturnal mSBP, respectively. After determining the critical point of 25-(OH) D3 as 42 nmol/L, a segmented linear regression model was used to calculate the effect size and 95% confidence interval on both sides of the critical point. When 25-(OH) D3 is ≤42 nmol/L, it significantly negatively correlates with 24 h, diurnal, and nocturnal mean SBP. Conversely, when 25-(OH) D3 exceeds 42 nmol/L, there is no statistically significant association with 24 h, diurnal, or nocturnal mSBP.ConclusionThere was a significant negative correlation between vitamin D levels and blood pressure levels in elderly patients with hypertension and osteoporosis

A Bearingless Induction Motor Direct Torque Control and Suspension Force Control Based on Sliding Mode Variable Structure

Aiming at the problems of the large torque ripple and unstable suspension performance in traditional direct torque control (DTC) for a bearingless induction motor (BIM), a new method of DTC is proposed based on sliding mode variable structure (SMVS). The sliding mode switching surface of the torque and flux linkage controller are constructed by torque error and flux error, and the exponential reaching law is used to design the SMVS direct torque controller. On the basis of the radial suspension force mathematical model of the BIM, a radial suspension force closed-loop control method is proposed by utilizing the inverse system theory and SMVS. The simulation models of traditional DTC and the new DTC method based on SMVS of the BIM are set up in the MATLAB/Simulink toolbox. On this basis, the experiments are carried out. Simulation and experiment results showed that the stable suspension operation of the BIM can be achieved with small torque ripple and flux ripple. Besides, the dynamic response and suspension performance of the motor are improved by the proposed method

Sliding Mode Control for Bearingless Induction Motor Based on a Novel Load Torque Observer

For the problem of low control performance of Bearingless Induction Motor (BIM) control system in the presence of large load disturbance, a novel load torque sliding mode observer is proposed on the basis of establishing sliding mode speed control system. The load observer chooses the speed and load torque of the BIM control system as the observed objects, uses the speed error to design the integral sliding mode surface, and adds the low-pass filter to reduce the torque observation error. Meanwhile, the output of the load torque is used as the feedforward compensation for the control system, which can provide the required current for load changes and reduce the adverse influence of disturbance on system performance. Besides, considering that the load changes lead to the varying rotational inertia, the integral identification method is adopted to identify the rotational inertia of BIM, and the rotational inertia can be updated to the load observer in real time. The simulation and experiment results all show that the proposed method can track load torque accurately, improve the ability to resist disturbances, and ameliorate the operation quality of BIM control system. The chattering of sliding mode also is suppressed effectively

GTC Simulation of Ideal Ballooning Mode in Tokamak Plasmas

U.S. Department of Energy (DOE) SciDAC GSEP Center; National Special Research Program of ChinaIn the present paper, we first derive the eigenmode equation of the ideal ballooning mode in tokamak plasmas using a gyrokinetic equation. It is shown that the gyrokinetic eigenmode equation can be reduced to the magnetohydrodynamic (MHD) form in the long wavelength limit when kinetic effects are ignored. Then, the global gyrokinetic toroidal code (GTC) is applied for simulations of the edge-localized ideal ballooning modes. The obtained mode structures are compared with the results of ideal MHD simulations. The observed scaling of the linear growth rate with the toroidal mode number is consistent with the ideal MHD theory. The simulation results verify the GTC capability of simulating MHD processes in toroidal plasmas

Frequency-Self-Adaptive Radio Frequency Power Harvester Enabled by Shape-Reconfigurable Liquid Metal

Radio frequency (RF) energy harvester as an efficient tool for capturing and converting the flourishing ambient RF energy provides a promising solution for long-term powering the wireless sensor networks and the Internet of things (IoTs). However, the actual distribution of the environmental RF signals is dynamically frequency-dependent due to the diverse wireless terminals only interacting with specified frequencies. To take full advantage of the RF energy carrying this characteristic, an intelligent RF energy harvester is in demand to automatically sense the frequency information of an incident signal and conduct the corresponding RF-to-direct current transformation process. Here, to the best of my knowledge, a frequency-self-adaptive RF harvester is first presented with the help of the shape-reconfigurable liquid metal, which can precisely identify and efficiently convert an arbitrary signal from the frequency span of 1.8 to 2.6 GHz. Companied with a microcontroller unit and a tensile system, the dynamic functionality of the entire system is comprehensively demonstrated, showing promising potential to significantly advance various fields, including sustainable IoT applications, green wearable technologies, and self-powered devices

Macrophage-mediated trogocytosis contributes to destroying human schistosomes in a non-susceptible rodent host, Microtus fortis

Schistosoma parasites, causing schistosomiasis, exhibit typical host specificity in host preference. Many mammals, including humans, are susceptible to infection, while the widely distributed rodent, Microtus fortis, exhibits natural anti-schistosome characteristics. The mechanisms of host susceptibility remain poorly understood. Comparison of schistosome infection in M. fortis with the infection in laboratory mice (highly sensitive to infection) offers a good model system to investigate these mechanisms and to gain an insight into host specificity. In this study, we showed that large numbers of leukocytes attach to the surface of human schistosomes in M. fortis but not in mice. Single-cell RNA-sequencing analyses revealed that macrophages might be involved in the cell adhesion, and we further demonstrated that M. fortis macrophages could be mediated to attach and kill schistosomula with dependence on Complement component 3 (C3) and Complement receptor 3 (CR3). Importantly, we provided direct evidence that M. fortis macrophages could destroy schistosomula by trogocytosis, a previously undescribed mode for killing helminths. This process was regulated by Ca2+/NFAT signaling. These findings not only elucidate a novel anti-schistosome mechanism in M. fortis but also provide a better understanding of host parasite interactions, host specificity and the potential generation of novel strategies for schistosomiasis control

Sliding Mode Variable Structure Control of a Bearingless Induction Motor Based on a Novel Reaching Law

In order to improve the performance of the Bearingless Induction Motor (BIM) under large disturbances (such as parameter variations and load disturbances), an adaptive variable-rated sliding mode controller (ASMC) is designed to obtain better performance of the speed regulation system. Firstly, the L 1 norm of state variables is applied to the conventional exponential reaching law and an adaptive variable-rated exponential reaching law is proposed to reduce system chattering and improve bad convergence performance of the sliding mode variable structure. Secondly, an integral sliding-mode hyper plane is produced according to the speed error in speed regulation system of BIM. Current signal is extracted by the combination of the sliding-mode hyper plane, the electromagnetic torque and the equation of motion. Finally, the feedback speed can adjust operating state adaptively according to speed error and make system chattering-free moving. The simulation and experiment results show that the proposed ASMC can not only enhance the robustness of the system’s uncertainties, but also improve the dynamic performance and suppress system chattering

MarineGym:Accelerated Training for Underwater Vehicles with High-Fidelity RL Simulation

Reinforcement Learning (RL) is a promising solution, allowing Unmanned Underwater Vehicles (UUVs) to learn optimal behaviors through trial and error. However, existing simulators lack efficient integration with RL methods, limiting training scalability and performance. This paper introduces MarineGym, a novel simulation framework designed to enhance RL training efficiency for UUVs by utilizing GPU acceleration. MarineGym offers a 10,000-fold performance improvement over real-time simulation on a single GPU, enabling rapid training of RL algorithms across multiple underwater tasks. Key features include realistic dynamic modeling of UUVs, parallel environment execution, and compatibility with popular RL frameworks like PyTorch and TorchRL. The framework is validated through four distinct tasks: station-keeping, circle tracking, helical tracking, and lemniscate tracking. This framework sets the stage for advancing RL in underwater robotics and facilitating efficient training in complex, dynamic environments