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This research presents an intelligent beam-hopping-based grant-free random access (GFRA) architecture designed for secure Internet of Things (IoT) communications in Low Earth Orbit (LEO) satellite networks. In light of the difficulties associated with facilitating extensive device connectivity while ensuring low latency and high reliability, we present a beam-hopping GFRA (BH-GFRA) scheme that enhances access efficiency and reduces resource collisions. Three distinct resource-hopping schemes, random hopping, group hopping, and orthogonal group hopping, are examined and utilized within the framework. This technique utilizes orthogonal resource allocation algorithms to facilitate efficient resource sharing, effectively tackling the irregular and dynamic traffic. Also, a kind of activity mechanism is proposed based on the constraints of the spatio-temporal distribution of devices. We assess the system’s performance through a thorough mathematical analysis. Furthermore, we ascertain the access delay and success rate to evaluate its capability to serve a substantial number of IoT devices under satellite–terrestrial delay and interference of massive connections. The suggested method demonstrably improves connection, stability, and access efficiency in 6G IoT satellite networks, meeting the rigorous demands of next-generation IoT applications.

Satellite IoT networks (S-IoT-N), which have been a hot issue regarding the next generation of communication, are quite important for the coming era of digital twins and the metaverse because of their performance in sensing and monitoring anywhere, anytime, and anyway, in more dimensions. However, this will cause communication links to face greater traffic loads. Satellite internet networks (SIN) are considered the most possible evolution road, possessing characteristics of many satellites, such as low earth orbit (LEO), the Ku/Ka frequency, and a high data rate. Existing research on load balancing schemes for satellite networks cannot solve the problems of low efficiency under conditions of extremely non-uniform distribution of users (DoU) and dynamic density variances. Therefore, this paper proposes a novel load balancing scheme of adjacent beams for S-IoT-N based on the modeling of spatial–temporal DoU and advanced GA. In our scheme, the PDF of the DoU in the direction of movement of the SSP’s trajectory was modeled first, which provided a multi-directional constraint for the non-uniform distribution of users in S-IoT-N. Fully considering the prior periodicity of satellite movement and the similarity of DoU in different areas, we proposed an adaptive inheritance iteration to optimize the crossover factor and mutation factor for GA for the first time. Based on the proposed improved GA, we obtained the optimal scheme of load balancing under the conditions of the adaptation from the local balancing scheme to global balancing, and a selection of Ser-Beams to access. Finally, the simulations show that the proposed method can improve the average throughput by 3% under specific conditions and improve processing efficiency by 30% on average.

Background This study aimed to investigate the potential relationship between the newly defined adiposity metric, the Body Roundness Index (BRI), which assesses central obesity, and the development of new-onset hyperuricemia. Methods In the Kailuan cohort study from 2006 to 2019, 91,804 eligible participants were included. A multivariate Cox regression model was used to test the correlation between BRI and hyperuricemia. At the same time, the restricted cubic spline was applied to solve the dose-response relationship between BRI and the risk of hyperuricemia.Then, stratified analysis was carried out using multivariate Cox regression according to age, sex, hs-CRP level, TG level, education level, smoking status and hypertension status. Results The results showed that the risk of new-onset hyperuricemia was significantly increased in the highest quartile compared with the lowest quartile. After adjusting for confounders, compared with Q1, the HR (95% CI) for new-onset hyperuricemia was 1.24 (1.18–1.30), 1.32 (1.25–1.40), and 1.40 (1.29–1.52) for Q2, Q3, and Q4, respectively. Restricted cubic spline analysis showed a J-curve relationship between baseline BRI levels and new-onset hyperuricaemia. Age, sex, hs-CRP level, TG level, income level, education level, smoking, and hypertension each had a multiplicative interaction with BRI at baseline. Conclusion We found that elevated BRI increased the risk of developing new-onset hyperuricaemia. In addition, the association between elevated BRI and the risk of new-onset hyperuricemia showed dependency on age, sex, hs-CRP level, TG level, education level, smoking status and hypertension status.

The low Earth orbit (LEO) satellite internet network (LEO-SIN) has become a heated issue for the next generation of mobile communications, serving as a crucial means to achieve global wide-area broadband coverage and, especially, mobile phone directly to satellite cell (MPDTSC) communication. The ultra-high-speed movement of LEO satellites relative to the Earth results in serious Doppler effects, leading to signal de-synchronization at the user end (UE), and relative high-speed motion leading to frequent satellite handovers. Satellite ephemeris, which indicates the satellite’s position, has the potential to determine the position of the transmit (Tx) within the LEO-SIN, thereby enhancing the reliability and efficiency of satellite communication. The adoption of ephemeris in the LEO-SIN has met some new challenges: (1) how UEs can acquire ephemerides before signal synchronization is complete, (2) how to minimize the frequency of ephemeris broadcasting, and (3) how to decrease the overhead of ephemeris broadcasting. To address the above challenges, this paper proposes a method for extrapolating the LEO-SIN orbit based on multi-satellite ephemeris coordination (MSEC) and the multi-stream fractional autoregressive integrated moving average (MS-FARIMA). First, a multi-factor global error analysis model for ephemeris-extrapolation error is established, which decomposes it into three types; namely, random error (RE), trending error (TE), and periodic error (PE), with a focus on increasing the extrapolation accuracy by improving RE and TE. Second, RE is eliminated by utilizing the ephemerides from multiple satellites received at the same UE at the same time, as well as multiple ephemerides from the same satellite at different times. Subsequently, we propose a new FARIMA algorithm with the innovation of a multi-stream data time-series forecast (TSF), which effectively improves ephemeris extrapolation errors. Finally, the simulation results show that the proposed method reduces ephemeris extrapolation errors by 33.5% compared to existing methods, which also contributes to a performance enhancement in the Doppler frequency offset (DFO) estimation of MPDTSC.

Chronic low-grade inflammation is increasingly recognized as a contributing factor in the development of cardiovascular events. This study aimed to evaluate the association between time-weighted cumulative exposure to high-sensitivity C-reactive protein (cumhsCRP) and the risk of new-onset cardiac conduction block (CCB). A total of 48,703 participants from a prospective community-based cohort were included. The average exposure time for cumhsCRP was 6.36 years. Participants were stratified into two groups: cumhsCRP < 2 mg/L and cumhsCRP ≥ 2 mg/L. The incidence of new-onset cardiac conduction block and its subtypes was identified through standard 12-lead electrocardiograms. Cox proportional hazards models were used to assess the relationship between cumhsCRP levels and incident CCB risk, adjusting for potential confounders. A restricted cubic spline curve further explored the dose-response pattern. During a mean follow-up period of 9.24 years, 803 cases of new-onset CCB were documented (incidence rate: 1.65%). After full multivariable adjustment, individuals in the cumhsCRP ≥ 2 mg/L group exhibited a significantly higher risk of CCB compared to those with cumhsCRP < 2 mg/L (HR: 1.24, 95% CI: 1.07-1.44). The RCS analysis suggested a linear association between log-transformed cumhsCRP and CCB risk ( for non-linearity = 0.294). Elevated cumulative exposure to high-sensitivity C-reactive protein is independently associated with an increased risk of developing CCB, especially left bundle branch block and left anterior fascicular block. This study will provide new insights into the prevention of CCB.

Small-signal instability issues of interconnected converter systems can be addressed by the impedance-based stability analysis method, where the impedance ratio at the point of common connection of different subsystems can be regarded as the open-loop gain, and thus the stability of the system can be predicted by the Nyquist stability criterion. However, the right-half plan (RHP) poles may be present in the impedance ratio, which then prevents the direct use of Nyquist curves for defining stability margins or forbidden regions. To tackle this challenge, this paper proposes a general rule of impedance-based stability analysis with the aid of Bode plots. The method serves as a sufficient and necessary stability condition, and it can be readily used to formulate the impedance specifications graphically for various interconnected converter systems. Experimental case studies validate the correctness of the proposed method.

This paper is for the filter users. It introduces a simple method to design Butterworth active low pass filter. By means of calculating, simulating, making a material object and debugging, it verifies the feasibility of the method. Combining design with practice, it shows the merit and demerit, which is of great significance for the design and manufacture of filters.

Energy efficiency is one of the key considerations in WSNs (Wireless Sensor Networks). Cross-layer design is a commonly-used technique for improving network performance, such as energy conservation. Based on LEACH (the Low Energy Adaptive Clustering Hierarchy algorithm) clustering routing protocol, this paper puts forward a cross-layer protocol called CL-LEACH for energy efficiency of clustered WSNs. By introducing FSK (Frequency Shift Keying) and taking its constellation size as the global cross-layer variance, CL-LEACH jointly considers physics layer, link layer, MAC layer and routing layer, accordingly, integrating a battery non-linearity discharge model, FSK orthogonal modulation scheme, TDMA and CSMA MAC protocols, and cluster routing algorithm. Simulation results reveal that CL-LEACH decreases, to a great extent, the energy consumption and prolong the lifetime of clustered WSNs by comparison with the LEACH protocol.

The stability of multi-vendor, multi-terminal HVDC systems can be analyzed in frequency domain by black-box impedance models using the generalized Nyquist stability criterion. Based on the impedance stability analysis, a multi-level sensitivity analysis approach using frequency-domain sensitivity functions is proposed to identify the root cause of potential instability. Case studies on a four-terminal HVDC system are carried out for stability and sensitivity analysis based on the impedance measurement in PSCAD. The analysis results are finally validated by electromagnetic transient simulations.

Background Although radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. Emerging radiomics can reveal subtle structural changes in tumors by analyzing preoperative contrast-enhanced computer tomography (CECT) imaging data and may provide new ways to predict early recurrence (recurrence within 2 years) in AFP-negative HCC. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC. Patients and methods Patients with AFP-negative HCC who underwent radical resection were included in this study. A computerized tool was used to extract radiomic features from the tumor region of interest (ROI), select the best radiographic features associated with patient’s postoperative recurrence, and use them to construct the radiomics score (RadScore), which was then combined with clinical and follow-up information to comprehensively evaluate the reliability of the model. Results A total of 148 patients with AFP-negative HCC were enrolled in this study, and 1,977 radiographic features were extracted from CECT, 2 of which were the features most associated with recurrence in AFP-negative HCC. They had good predictive ability in both the training and validation cohorts, with an area under the ROC curve (AUC) of 0.709 and 0.764, respectively. Tumor number, microvascular invasion (MVI), AGPR and radiomic features were independent risk factors for early postoperative recurrence in patients with AFP-negative HCC. The AUCs of the integrated model in the training and validation cohorts were 0.793 and 0.791, respectively. The integrated model possessed the clinical value of predicting early postoperative recurrence in patients with AFP-negative HCC according to decision curve analysis, which allowed the classification of patients into subgroups of high-risk and low-risk for early recurrence. Conclusion The nomogram constructed by combining clinical and imaging features has favorable performance in predicting the probability of early postoperative recurrence in AFP-negative HCC patients, which can help optimize the therapeutic decision-making and prognostic assessment of AFP-negative HCC patients.