Advanced Electromagnetics

Effects of Nursing Interventions on Quality of Life in Elderly Patients with Cardiovascular Diseases: A Systematic Review

Y. Wang, J. Li, H. X. Zhao, M. Li — Mon, 05 Oct 2026 00:00:00 +0200

Objective To systematically evaluate the effects of different nursing intervention models on the quality of life of elderly patients with cardiovascular diseases, integrate current clinical research evidence, and provide evidence-based references for optimizing standardized nursing protocols and improving long-term prognoses for elderly patients with cardiovascular diseases. Methods Databases including CNKI, Wanfang, VIP, PubMed, Embase and Cochrane Library were electronically searched from database inception to June 2026. Randomized controlled trials and prospective cohort studies involving elderly patients with cardiovascular diseases receiving specialized nursing interventions were included. Basic experiments, reviews, case reports, studies with missing data and non-Chinese-English publications were excluded. Two researchers independently completed literature screening, data extraction and quality assessment. A descriptive systematic review was adopted for qualitative integration and analysis of included studies, so as to summarize the application effects and existing research limitations of different nursing interventions. Results A total of 28 publications were finally enrolled, including 21 Chinese core articles and 7 English articles, with an overall sample size of 4 326 participants. The intervention models of included studies were categorized into five types: transitional care, comprehensive individualized nursing, mindfulness-based psychological nursing, cardiac exercise rehabilitation nursing, and special-topic health education. Multiple studies indicated that multi-mode integrated nursing interventions could significantly improve the multi-dimensional quality of life (physiological, psychological and social functioning) in elderly patients with cardiovascular diseases, enhance medication adherence, and reduce the incidence of adverse cardiovascular events and unplanned readmissions. In contrast, single short-term health education and basic nursing interventions exerted limited effects on improving long-term quality of life. Existing studies had problems such as lack of unified standards for intervention protocols, large variations in follow-up duration, high research heterogeneity, and insufficient evidence for subgroups of frail advanced-age patients. Conclusion Diversified integrated nursing interventions are effective in improving the quality of life of elderly patients with cardiovascular diseases. Among them, transitional comprehensive nursing and exercise rehabilitation combined with psychological nursing yield the most prominent benefits. Standardization of relevant clinical research needs to be further improved. High-quality studies with large-sample, multi-center design and long-term follow-up should be carried out in the future to construct standardized and individualized nursing systems suitable for elderly Chinese patients with cardiovascular diseases.

Association Between Thoracic Radiotherapy and Severity of Coronary Artery Calcification in Lung Cancer: A Retrospective Cohort Study

X. Zhang, Q. Liu — Mon, 05 Oct 2026 00:00:00 +0200

Objective To investigate the association between thoracic irradiation (TIR) and the severity of coronary artery calcification (CAC) in patients with lung cancer, and to provide evidence-based basis for cardiovascular risk stratification and early intervention in lung cancer patients undergoing radiotherapy. Methods A retrospective cohort study design was adopted. A total of 126 patients with primary lung cancer who received thoracic radiotherapy in the oncology department of a tertiary hospital from January 2018 to December 2023 were consecutively enrolled as the radiotherapy group, and 126 lung cancer patients diagnosed during the same period but without radiotherapy were matched at a 1:1 ratio as the non-radiotherapy group. Propensity score matching was performed for baseline characteristics including age, sex, smoking history, hypertension, diabetes, dyslipidemia and tumor stage. The CAC score was semiquantitatively calculated by the Agatston method based on follow-up chest CT images obtained at least 12 months after radiotherapy, and the severity was classified into three grades according to the number of involved vessels: no calcification, single-vessel calcification and multi-vessel calcification. Dosimetric parameters of the radiotherapy group were collected, including mean heart dose (MHD), heart V30 and left anterior descending artery (LAD) dose. Inter-group differences were compared using t-test, χ2 test and rank-sum test. Multivariate ordinal Logistic regression was used to analyze the independent influencing factors of CAC severity. Results The median CAC score in the radiotherapy group was significantly higher than that in the non-radiotherapy group [426.3 (IQR: 118.5–982.7) AU vs. 187.6 (IQR: 42.3–563.2) AU, Z=-4.215, P<0.001]. The proportion of multi-vessel calcification in the radiotherapy group was significantly higher than that in the non-radiotherapy group (46.0% vs. 27.0%, χ2=10.286, P=0.006). Multivariate ordinal Logistic regression analysis showed that after adjusting for age, hypertension, diabetes, dyslipidemia and smoking history, thoracic radiotherapy was an independent risk factor for increased CAC severity (OR=2.87, 95%CI: 1.64–5.02, P<0.001). In the subgroup analysis of the radiotherapy group, MHD≥10 Gy (OR=2.31, 95%CI: 1.12–4.76, P=0.023) and LAD maximum dose≥35 Gy (OR=2.05, 95%CI: 1.03–4.08, P=0.041) were independently associated with more severe CAC. Conclusion Thoracic radiotherapy in lung cancer patients is independently associated with increased severity of coronary artery calcification, and patients with higher cardiac radiation dose tend to have greater CAC severity. Routine baseline CAC assessment before radiotherapy, optimization of cardiac dose constraints during treatment, and strengthened cardiovascular event monitoring and early intervention during follow-up are recommended.

Influence of Grid-Forming Converter Control Parameters on System Stability Boundaries Under Different Grid Strengths

J. T. Guo — Mon, 05 Oct 2026 00:00:00 +0200

The voltage and frequency support capability of grid-forming converters under weak-grid conditions makes them key equipment for power systems with a high share of renewable energy, yet the coupling between their control parameters and grid strength still lacks a boundary-oriented description suitable for parameter tuning. This paper establishes a reduced-order model of a grid-forming converter that includes the active-power synchronization loop, the reactive-power/voltage loop, power-measurement filtering and an equivalent inner-loop lag. Grid strength is characterized by the short-circuit ratio, and the minimum damping ratio and the critical clearing time are adopted as the small-signal and large-signal stability indices, respectively. Through parameter sweeps, the stability boundaries of the virtual inertia, damping coefficient, power-filter time constant, reactive-power droop coefficient and virtual reactance are obtained for short-circuit ratios from 1.2 to 10. The results show that the damping ratio of the dominant electromechanical mode decreases monotonically as grid strength increases: when the short-circuit ratio rises from 1.5 to 10, the minimum damping ratio under the base parameters falls from 0.285 to 0.090, and the damping coefficient required to keep the damping ratio above 0.1 increases from about 11 p.u. to about 31 p.u.; conversely, the transient stability margin shrinks as the grid becomes weaker, with the critical clearing time falling from about 516 ms to about 230 ms as the short-circuit ratio decreases from 10 to 1.2. When the power-filter time constant exceeds about 50 ms, the strong-grid case loses stability first, and the damping improvement provided by the virtual reactance is more pronounced in the strong-grid case. On this basis, a parameter tuning region that accommodates both strong- and weak-grid conditions is given. The conclusions are subject to the assumptions of the reduced-order model; electromagnetic-transient and hardware-in-the-loop validation shows that the damping ratio of the dominant small-signal mode deviates from the reduced-order model by about 6%–16% with a consistent trend, and that the critical clearing time with current limiting is about 17%–24% lower than the reduced-order upper-bound estimate, indicating that the reduced-order model is suitable for trend assessment and preliminary tuning, while the transient margin must be corrected for current-limiting conditions.

DESIGN FPGA-BASED MOVING OBJECT RECOGNITION

Qianqian Liu, Han Diao, Tao Liu, Wendong Lv — Mon, 05 Oct 2026 00:00:00 +0200

With the development of intelligent monitoring, robot vision and IoT technologies, the demand for real-time and low-power mobile object recognition is growing. Traditional CPU/GPU schemes suffer from high latency and energy consumption on edge devices, while FPGA, with high-speed parallel computing and reconfigurable features, becomes ideal for efficient real-time visual process. The paper presents an FPGA-based mobile object recognition system, realizing recognition and tracking. It optimizes traditional algorithms via hardware acceleration to achieve low-latency, cost-effective real-time detection. The frame difference method extracts foreground targets, combined with morphological filtering for denoising. DDR3 stores images, and HDMI outputs videos. Leveraging FPGA’s parallelism, hardware pipeline designs for preprocessing, motion and target detection modules are implemented with Verilog. Modules like ov5640 acquisition, DDR3 control, image processing and HDMI display are developed, finally achieving real-time recognition and frame tracking of moving objects. It provides an efficient hardware solution for low-cost, low-power applications, verifying FPGA’s engineering value in visual processing.

Multi-Source Uncertainty Perception and Spatiotemporal Graph Fusion for Defect-Elimination Robots in Strong Electromagnetic Environments

P. Lei, J. B. Liang, T. L. Zhang, S. Wang, J. L. Wu, S. Wang — Mon, 05 Oct 2026 00:00:00 +0200

To address perception distortion, difficulties in heterogeneous data fusion, and missed detection of small faults in defect-elimination robots for ultra-high-voltage transmission lines under strong electromagnetic interference, a physics-aware spatiotemporal graph fusion network PA-STGFN is proposed. The Middleton Class-A model is employed to estimate the parameters of non-Gaussian impulsive noise, combined with robust statistics for adaptive suppression. EfficientNet enhanced with coordinate attention and MS-TCN are used to extract visual and vibration–acoustic features, respectively. Modality uncertainty is quantified based on Dirichlet evidence, enabling dynamic reconstruction of graph connections and multi-source confidence-weighted fusion. The model is jointly trained using focal loss, reconstruction loss, and uncertainty regularization. Validation on transmission-line data shows that the feature-matching accuracy and anomaly-detection rate reach 95.8% and 96.5%, respectively, with a performance degradation of less than 3% at 10 dB and a single-frame inference latency of 78 ms. The proposed method can improve the perception reliability of defect-elimination robots in strong electromagnetic environments.

Business-Semantic-Aware Joint Orchestration of Data, Computing Services, and Resources for Smart Grid Data Fabrics

Y. C. Gu, S. J. Wei, L. Wei, F. Xia, M. Z. Liu — Mon, 05 Oct 2026 00:00:00 +0200

Smart-grid operational analytics rely on heterogeneous data, analytical services, and distributed computing resources, but existing discovery and unified-access mechanisms do not ensure executable orchestration under operational constraints. This paper proposes BS-DCSO, a business-semantic-aware method for jointly selecting data services, computing services, and resource nodes in a smart-grid data-fabric environment. BS-DCSO integrates type- and permission-aware filtering, QoS-based top-k pruning, business-context scoring, complete-plan evaluation, feasibility-first lexicographic selection, and failure-triggered re-orchestration. Experiments on a synthetic benchmark covering five representative smart-grid scenarios and ten random seeds show a provisioning success rate of 0.4897 ± 0.1139, a feasible-instance success rate of 0.8320 ± 0.0562, and a constraint violation rate of 0.0809 ± 0.0213. Compared with ResourceFirstScheduling, BS-DCSO improves paired provisioning success by 0.1423 ± 0.0552, while outperforming five controlled baselines across the three main metrics. Re-orchestration recovers feasible replacements in 0.8282 ± 0.0398 of eligible single-service failures. Under the sequential fixed-catalogue timing protocol, the method requires 151.39–175.58 ms per request for 100–1000 requests, indicating a practical feasibility–computation trade-off under the tested synthetic setting rather than high-concurrency scalability.

Robust Stability of Linear Time-Delay Systems with Unknown Parameters and Delays

Z. Wang — Mon, 05 Oct 2026 00:00:00 +0200

This paper investigates the robust stability of a class of linear time-delay systems subject to unknown parameters and delays. Since the exact values of these quantities are often unavailable in practice, an analytical framework based on the distribution of characteristic roots is developed. Through theoretical derivation of the characteristic equation for the perturbed system, an upper bound on its unstable eigenvalues is established. Subsequently, by employing the argument principle, sufficient conditions for robust stability are derived for both first-order and high-order time-delay systems. These conditions are easy to verify with low computational cost and are convenient for direct engineering application.

From industrial equipment to communication interface: a study on the visual communicability and urban cultural IP generation mechanism of the No.1 blast furnace in Hanggang Park, Grand Canal

H. Xue, J. H. Chen — Tue, 08 Sep 2026 00:00:00 +0200

In the context of postindustrial cities, large-scale heavy industrial structures are gradually undergoing a fundamental transformation in their functional paradigm. This article takes Hanggang No.1 blast furnace as a typical research case, constructs a three-dimensional quantitative evaluation system for the visual communicability of large-scale industrial equipment, and extracts a fourth-order iterative generation coupling model for urban cultural IP under the guidance of industrial heritage. Firstly, clarify the core connotation, dimensional composition, and quantitative measurement indicators of visual communicability of industrial equipment, and deconstruct the three-dimensional visual symbol system of No.1 blast furnace; Secondly, a vertical review of the evolution of the entire lifecycle of blast furnaces is conducted, elucidating visual communicability as the core driving factor. Empirical analysis shows that: (1) the inherent visual communicability of industrial equipment is a prerequisite core constraint for the cultivation and formation of urban cultural IP; (2) The super tall vertical scale, corroded metal native texture, and complete continuous production flow line of the No.1 blast furnace have built an irreplaceable differentiated visual competitive barrier; (3) A multi-level composite communication interface built on physical space, short video social media, cultural and creative derivative products, and fashion and art exhibitions can promote the sustained diffusion and dissemination of industrial cultural symbols across scenes and age groups. This study expands the research and analysis dimensions of postindustrial heritage semiotics, providing a quantifiable indicator framework for evaluating the visual communication effectiveness of giant industrial structures.

Construction of a Standardized Pain Management Program for Traumatic Orthopedic Patients and Its Impact on Postoperative Rehabilitation Quality

J. Y. Yao, L. J. Zhang, X. L. Yue, M. X. Guan, L. Y. Li — Tue, 08 Sep 2026 00:00:00 +0200

Objective: To construct a standardized pain management program for traumatic orthopedic patients and explore its impact on postoperative rehabilitation quality. Methods: The current status of pain management was reviewed through literature analysis. Based on evidence-based medicine and personalized patient needs, a program was constructed encompassing standardized pain assessment, treatment strategies, and a multidisciplinary collaboration model. A randomized controlled trial was conducted with 200 traumatic orthopedic patients, divided into an experimental group (standardized program) and a control group (routine management). Indicators including pain level, limb function recovery, psychological state, and quality of life were compared between the two groups. Results: The experimental group showed significantly greater improvement in all indicators compared to the control group (P < 0.05). Conclusion: The standardized pain management program can effectively improve the postoperative rehabilitation quality of traumatic orthopedic patients and holds important clinical application and promotion value.

DynChain-Vul: Adaptive Blockchain Sharding and Secure Cross-Shard Vulnerability Data Sharing for Cloud-Based Vulnerability Lifecycle Governance

Z. C. Sun, J. Li, B. Wu — Tue, 08 Sep 2026 00:00:00 +0200

Cloud-based vulnerability lifecycle governance requires continuous sharing of vulnerability intelligence, security evidence, remediation records, exploit verification results, and risk assessment information among cloud service providers, security operation centers, software vendors, and regulatory agencies. These security data are highly distributed, dynamically generated, and privacy-sensitive, demanding scalable, trustworthy, and auditable cross-domain data sharing. Although blockchain provides decentralized trust, tamper resistance, and traceability, conventional blockchain architectures suffer from limited throughput, excessive storage redundancy, and inefficient cross-shard data exchange, making them difficult to support large-scale cloud vulnerability governance involving heterogeneous computing resources. This paper proposes DynChain-Vul, an adaptive blockchain sharding architecture for secure vulnerability data sharing in cloud-based vulnerability lifecycle governance. DynChain-Vul first profiles node computing capability, network bandwidth, communication latency, and storage resources, and then employs Gaussian mixture modeling together with dynamic weighted consistent hashing to allocate virtual nodes according to heterogeneous resource characteristics, thereby improving shard balance and overall system scalability. To accommodate continuously changing workloads, a dynamic shard mapping index supports adaptive shard splitting and merging while minimizing data migration overhead. For secure cross-shard vulnerability information exchange, DynChain-Vul integrates multi-path redundant indexing based on Kademlia routing with a threshold-signature verification mechanism, enabling reliable vulnerability data retrieval without relying on a centralized trusted coordinator. Experimental results on a blockchain emulation platform demonstrate that DynChain-Vul increases system throughput from 725.98 TPS to 1493.17 TPS as the number of shards increases from 2 to 8, reduces transaction confirmation latency from 39.23 ms to 5.92 ms, maintains shard-load covariance within 0.12– 0.15, and keeps aggregated cross-shard signature storage nearly constant. These results indicate that adaptive blockchain sharding combined with verifiable cross-shard vulnerability data sharing provides an efficient and trustworthy foundation for cloud-based vulnerability lifecycle governance, supporting scalable collaborative vulnerability intelligence sharing and secure security operations.