Saved Queries

by Viorel Țarcă, Solange Tamara Roșu, Elena Cojocaru, Lăcrămioara Ionela Butnariu, Iulia Cristina Roca, Ancuța Lupu, Dana Elena Mindru, Paula Popovici and Elena Țarcă

Medicina 2026, 62(6), 1020; https://doi.org/10.3390/medicina62061020 (registering DOI) - 25 May 2026

Abstract

Background and Objectives: The COVID-19 pandemic caused unprecedented mortality shocks worldwide, but its differential impact across European regions and the mediating mechanisms remain inadequately quantified. Materials and Methods: We conducted a longitudinal multilevel analysis using data from 29 European countries (2015–2023; N = 261 country-years). Linear mixed models estimated the impact of the pandemic on life expectancy, controlling for regional differences, vaccination rates, healthcare expenditures, gross domestic product, and excess mortality. The primary outcome was national life expectancy at birth. Results: The pandemic period was associated with an average reduction of 1.12 years in life expectancy (95% CI: 0.95 to 1.49, p < 0.001) after adjusting for pre-existing trends. Eastern Europe experienced 56% greater impact than Western Europe (interaction β = −0.623, p = 0.002). Excess mortality emerged as the primary mediator, explaining 79% of the pandemic effect. Each 1% increase in excess mortality reduced life expectancy by 0.091 years (p < 0.001). Healthcare expenditures showed protective effects (β = 0.000327 per purchasing power standards (PPS), p = 0.049), while vaccination rates, as a direct predictor, were not significantly associated with life expectancy in multivariate models. This critical finding on vaccination rates does not imply biological inefficacy but rather suggests a misspecification of its role. Conclusions: Excess mortality, rather than its direct component, COVID-19-specific mortality, appears to mediate most of the pandemic’s impact on life expectancy. Regional disparities reflect structural differences in healthcare systems and socioeconomic conditions more than differential vaccination uptake. The protective effect of vaccination on life expectancy operates entirely through the reduction in excess mortality. Consequently, health policies should prioritize strengthening resilient health systems as well as disease-specific interventions. Full article

(This article belongs to the Special Issue Impact on Human Health, Lifestyle and Quality of Care After COVID-19, 2nd Edition)

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5 pages, 964 KB

Open AccessProceeding Paper

Urban Pluvial Flooding Assessment with a Subgrid Approach for the Secondary Drainage Network: An Application in Padova

by Tommaso Lazzarin, Pierfranco Costabile and Daniele Pietro Viero

Eng. Proc. 2026, 135(1), 29; https://doi.org/10.3390/engproc2026135029 (registering DOI) - 25 May 2026

Abstract

This study presents a practical application of a subgrid approach for urban pluvial flooding that implicitly accounts for the secondary drainage network. Parameters required by the subgrid model (e.g., pipe diameter, spacing) can be easily estimated, reducing the data requirements and modelling efforts compared to classical 1D/2D simulations. Applied to simulate the 2009 flooding of a Padova district, the model improves accuracy in flood extent and water levels compared to models that ignore the secondary network, without the need for surveys of smaller-scale pipes. This data-efficient approach proves to be a practical tool for simulating urban pluvial floods, particularly in data-scarce urban areas. Full article

(This article belongs to the Proceedings of II International Conference on Challenges and Perspectives in Urban Water Management Systems (CSDU-CSSI DAYS 25))

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16 pages, 8085 KB

Open AccessArticle

Multifunctional Polysaccharide Hydrogel Ameliorates Cardiac Function After Myocardial Infarction via Antioxidant, Immunomodulatory, and Pro-Angiogenic Activities

by En-Can Zhu, Xiao-Yun Lan, Zhen Chen, Jin-Yu Yue, Qi-Hang Yang and Chuang-Nian Zhang

J. Compos. Sci. 2026, 10(6), 287; https://doi.org/10.3390/jcs10060287 (registering DOI) - 25 May 2026

Abstract

Myocardial infarction (MI) triggers excessive oxidative stress, a detrimental immune response, and insufficient angiogenesis, which collectively impede effective cardiac repair. This study developed a multifunctional composite polysaccharide hydrogel, termed KgXd^gel, based on konjac glucomannan (KGM) and xanthan gum (XG) functionalized with gallic acid (GA) and dopamine (DA), respectively, to integrate reactive oxygen species (ROS) scavenging, macrophage polarization, and pro-angiogenic activities. In vitro assays demonstrated that the KgXd^gel hydrogel exhibited excellent cytocompatibility, effectively scavenged ROS, promoted the polarization of macrophages towards the reparative M2 phenotype, and enhanced the migration and tube formation of human umbilical vein endothelial cells. In a rat MI model, treatment with KgXd^gel significantly improved cardiac function (e.g., left ventricular ejection fraction, LVEF; left ventricular fractional shortening, LVFS), attenuated left ventricular dilation (LVIDs), and favorably modulated the post-infarction microenvironment. This was evidenced by the upregulation of the M2 marker CD163 and the angiogenic factor VEGF, alongside the downregulation of pro-inflammatory cytokines (e.g., IL-1β, TNF-α) and the M1 marker iNOS. These findings conclusively demonstrate that the KgXd^gel hydrogel synergistically promotes cardiac repair post-MI through its integrated antioxidant, immunomodulatory, and pro-angiogenic functions, presenting a promising multi-targeted therapeutic strategy. Full article

(This article belongs to the Special Issue Functional Composites: Fabrication, Properties and Applications)

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9 pages, 441 KB

Open AccessArticle

MicroRNA-21 Emerges as Key Prognostic Indicator After Breast Cancer Surgery

by Kağan Gökçe, Murat Üner, Nur Adil and Mehrdad Sheikhvatan

J. Clin. Med. 2026, 15(11), 4053; https://doi.org/10.3390/jcm15114053 (registering DOI) - 25 May 2026

Abstract

Background/Objective: MicroRNA-21 (miR-21) is one of the most widely studied oncogenic microRNAs and has been implicated in breast cancer progression, therapy resistance, and metastatic potential. However, its utility as a long-term prognostic biomarker in patients undergoing mastectomy remains insufficiently clarified. This study evaluated the prognostic significance of miR-21 expression in predicting overall and disease-free survival. Methods: A retrospective cohort of 426 breast cancer patients who underwent mastectomy between 2010 and 2017 was analyzed. Tumor miR-21 expression was measured using quantitative real-time PCR and categorized as high or low based on cohort-derived thresholds. Long-term outcomes were assessed over a median follow-up of 112 months. Kaplan–Meier survival curves, log-rank tests, and multivariable Cox proportional hazards models were used to estimate associations between miR-21 levels and survival outcomes. Results: High miR-21 expression was identified in 48.8% of cases. Patients with high miR-21 demonstrated significantly poorer overall survival (10-year OS: 61.4% vs. 82.7%; log-rank p < 0.001) and disease-free survival (10-year DFS: 54.9% vs. 78.3%; log-rank p < 0.001). In multivariable analysis, high miR-21 remained an independent predictor of decreased OS (HR = 2.18; 95% CI: 1.56–3.04) and DFS (HR = 2.44; 95% CI: 1.78–3.33). Conclusions: Elevated miR-21 expression is a significant independent biomarker of adverse long-term prognosis in breast cancer patients undergoing mastectomy. Integrating miR-21 into postoperative risk stratification may improve individualized management strategies. Full article

(This article belongs to the Section Clinical Laboratory Medicine)

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11 pages, 276 KB

Open AccessPerspective

Professors Joe Gani and Chris Heyde and Their Contributions to Finance and Risk Management

by Shuangzhe Liu, Ross Maller and Svetlozar T. Rachev

J. Risk Financial Manag. 2026, 19(6), 378; https://doi.org/10.3390/jrfm19060378 - 25 May 2026

Abstract

This Perspective is dedicated to the memory of Professor Joseph Mark (Joe) Gani (1924–2016) and Professor Christopher Charles (Chris) Heyde (1939–2008), two scholars whose intellectual leadership profoundly shaped applied probability, mathematical statistics, and their interface with finance, insurance, and risk management. Their contributions extend beyond specific technical results to the development of research cultures grounded in probabilistic rigor, empirical relevance, and methodological transparency. We emphasize three enduring themes central to modern quantitative risk analysis. First, the systematic incorporation of heavy-tailed and non-Gaussian features in stochastic modeling, reflecting persistent empirical deviations from classical Gaussian assumptions in financial data. Second, the development of stochastic and time-series methodologies capable of handling dependence structures, including conditional heteroskedasticity and long-range dependence. Third, the principled integration of probabilistic modeling with data-driven and machine learning approaches, ensuring predictive performance is accompanied by interpretability and robustness. We situate these contributions within contemporary challenges in financial risk management, including systemic risk, environmental, social and governance (ESG) considerations, and climate finance. In particular, climate-related financial risks arise from both physical impacts (such as extreme weather events and long-term environmental change) and transition dynamics associated with the shift toward a low-carbon economy (including policy, technological, and market adjustments). These sources of risk introduce additional forms of dependence, nonlinearity, and model uncertainty, particularly in high-dimensional, data-rich settings. This Perspective highlights a forward-looking research agenda that preserves the foundational principles of applied probability while adapting them to modern financial systems characterized by real-time information flows and evolving risk structures. This legacy continues to shape how financial risk is modeled, measured, and understood in increasingly complex and interconnected environments. Full article

(This article belongs to the Section Mathematics and Finance)

1 pages, 126 KB

Open AccessCorrection

Correction: Zhou et al. A Mathematical Model Accounting for Pore Pressure Generation in Sedimentary Basins. Processes 2026, 14, 297

by Lihao Zhou, Liangbin Dou, Chengyun Ma, Shanshan Quan, Fengtao Qu, Wenxuan Kou, Chenbo Gu, Chi Zhao, Baiqi Mao, Kai Zhao and Yanfang Gao

Processes 2026, 14(11), 1704; https://doi.org/10.3390/pr14111704 - 25 May 2026

Abstract

Yanfang Gao was not included as an author in the original publication [...] Full article

32 pages, 4292 KB

Open AccessSystematic Review

Advancing Building Health Assessment: A Systematic Review of Indicators and Methods

by Hasnaa Bourziza, Xinhao Suo, Lingzhi Li and Jiajia Cheng

Buildings 2026, 16(11), 2096; https://doi.org/10.3390/buildings16112096 - 25 May 2026

Abstract

The concept of building health has gained increasing attention due to its strong association with occupant well-being, safety, and the long-term performance of buildings. However, despite the existence of models that assess individual aspects of building conditions, standardized frameworks for comprehensively evaluating overall building health remain limited. A systematic assessment of building health can help identify potential risks and prevent unexpected consequences caused by system failures. This study provides a systematic review of existing approaches to building health assessment by synthesizing relevant indicators and evaluation methods reported in the literature. Key variables are standardized and organized into six major performance dimensions: safety performance, environmental quality, occupant-centred performance, system and infrastructure performance, energy performance, and economic performance. In addition, the review examines the roles of widely used assessment approaches, including Post-Occupancy Evaluation (POE), Internet of Things (IoT)- based monitoring, and machine learning techniques, in supporting building health evaluation. Finally, future directions are proposed to support the development of more comprehensive, data-driven building health assessment frameworks. Full article

(This article belongs to the Special Issue Urban Infrastructure and Resilient, Sustainable Buildings—2nd Edition)

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11 pages, 260 KB

Open AccessArticle

External Load During Official Competition in Under-18 Padel Players

by Rafael Albalad-Aiguabella, Alejandra Gutiérrez-Logroño, Alberto Roso-Moliner, Oscar Villanueva-Guerrero and Elena Mainer-Pardos

Appl. Sci. 2026, 16(11), 5261; https://doi.org/10.3390/app16115261 - 24 May 2026

Abstract

In padel, an emerging racket sport, evidence regarding competition demands in adolescent players remains limited. Therefore, this study aimed to analyze absolute external load during official competition in male and female U18 padel players. A total of 18 official matches from the Spanish Championship of Regional Teams were analyzed. Eighteen U18 players (9 females: age 15.1 ± 1.5 years, height 162.9 ± 8.2 cm, body mass 54.6 ± 9.1 kg; 9 males: age 15.4 ± 1.8 years, height 175.1 ± 9.4 cm, body mass 67.2 ± 11.0 kg), competing at the regional and national levels, were monitored using OLIVER™ inertial devices. External load variables included playing time, total distance, high-intensity accelerations and decelerations, changes of direction, time spent at high metabolic power, session volume, session intensity, and maximum speed. Statistical analysis was performed using linear mixed models to compare differences between sexes. Male players showed significantly higher values than female players in playing time (82.34 ± 23.95 vs. 51.03 ± 12.39 min; p < 0.001) and total distance (3958.50 ± 242.57 vs. 2225.54 ± 257.29 m; p < 0.001). They also presented significantly greater values in high-intensity external load variables, including accelerations, decelerations, changes of direction, time spent at high metabolic power, session volume, and session intensity (all p ≤ 0.009). No significant differences were found for maximum speed (p = 0.074). These findings suggest that official competition demands differ according to sex in U18 padel and may help inform more specific training prescriptions and load-monitoring strategies. Full article

(This article belongs to the Special Issue Innovative Technologies for and Approaches to Sports Performance)

35 pages, 4528 KB

Open AccessArticle

DO-PI-EATCNet: Efficient-Attention- and Dream-Optimization-Based Channel Selection for EEG Motor Imagery Classification

by Xiaoyan Shen, Hongkui Zhong, Yujie Gu and Ruiqing Han

Sensors 2026, 26(11), 3336; https://doi.org/10.3390/s26113336 - 24 May 2026

Abstract

Existing deep-learning-based motor imagery (MI) electroencephalogram (EEG) decoding methods face challenges in generalizing across sessions and providing channel-level physiological interpretability. These limitations hinder the practical application of MI-EEG systems. Accordingly, DO-PI-EATCNet (Dream-Optimization-Enhanced, Physics-Inspired, Efficient-Attention Temporal Channel Network) is proposed to improve generalization and interpretability in MI-EEG classification. Unlike models that simply combine multiple components, DO-PI-EATCNet assigns distinct roles to feature representation, temporal channel modeling, temporal regularization, and channel compactness. Latent-Projected Attention (LPA) enhances spatiotemporal discriminability by aligning attention in a low-dimensional latent space, and Temporal Channel Cascaded Collaborative Attention (TCCA) refines dependencies between time and channels. Fractional-Order Difference Temporal Consistency Loss (FD-TCL) is introduced as a neurodynamics-inspired temporal regularizer to reduce high-frequency fluctuations in prediction sequences and improve within-subject cross-session prediction stability. The Multi-Population Dream Optimization Algorithm (MPDOA) is used for channel selection to obtain a compact EEG channel subset and reduce computational load, although it introduces a slight accuracy decrease compared with the uncompressed full model. Under a within-subject cross-session protocol on the BCI Competition IV-2a four-class MI dataset, the final compact model achieves an average accuracy of 84.4% and Cohen’s κ of 0.790, outperforming the reimplemented baselines. Compared with the uncompressed LPA-TCCA-FD-TCL variant, MPDOA slightly decreases accuracy from 84.9% to 84.4%, but reduces EEG channels from 22 to about 15 and decreases MACs by 27%. Scalp topographies and selected-channel visualizations provide qualitative support for channel-level anatomical plausibility, as the selected electrodes are mainly located over expected sensorimotor-related regions, while t-SNE offers a descriptive visualization of the learned feature distributions. Full article

(This article belongs to the Section Intelligent Sensors)

18 pages, 699 KB

Open AccessArticle

Orange-Peel Waste Enzymatic Saccharification: Scaling-Up Under Diverse pH-Control Strategies

by Ramón J. Ceballos-Zúñiga and Miguel Ladero

Fermentation 2026, 12(6), 254; https://doi.org/10.3390/fermentation12060254 - 24 May 2026

Abstract

Waste from the fruit juice industry presents high sugar and phenolic contents, high humidity and biological activities and cumbersome disposal or low-added valorization. Orange-peel waste (OPW) represents 35–55% w/w of processed fruit, with oranges being the main citric crop. OPW saccharification leads to sugar-rich hydrolysates that can be further processed via fermentative and catalytic routes. In this work, OPW enzymatic hydrolysis was studied via batch and fed-batch processing using either a 50 mM citrate buffer or a 9 g/L NaCl solution with pH control by adding CaCO₃ to ensure high enzyme activity across the enzymatic process. Preliminary runs showed that particle size of 3.4 mm diameter and a 300 r.p.m. stirring speed, a six-blade Rushton turbine and wall baffles were adequate to reach high sugar yields in batch. Further scale-up in batch at medium solid loading (12.5% w/w) and fed-batch operation at high-solid loading (20% w/w) led to high yields and glucose and fermentable sugars (up to 74 and 136 g/L, respectively, when using the saline solution and CaCO₃ as pH-controlling agent, in only 50 h; notably shorter and higher than when using the citrate buffer). Fractal kinetic models have been shown to accurately represent the compositional change across all batch and fed-batch conditions, highlighting NaCl reaction medium and alkali-driven pH control as the most appropriate approach to achieve high yields at low process times, a promising result for further developments at demonstration and industrial scales using automatic pH control. Full article

(This article belongs to the Special Issue 10th Anniversary of Fermentation: Feature Papers in the “Fermentation Process Design” Section)

19 pages, 1021 KB

Open AccessFeature PaperArticle

Kinesiophobia and Work Disability in Fibromyalgia: Cognitive Mediation in a Population-Based Study of Women

by Giordano Mayer De Freitas, Guilherme Teixeira Lopes, Graziele Borges Bueno, Mariana Lentino Coelho, Julia Gomes, Caroline Leffa Venturini, Maria Eduarda Louzada, Sara Machado Peres, Barbara Regina França, Iraci L. S. Torres Pham, Felipe Fregni, Andrea Cristiane Janz Moreira and Wolnei Caumo

Eur. J. Investig. Health Psychol. Educ. 2026, 16(6), 72; https://doi.org/10.3390/ejihpe16060072 - 24 May 2026

Abstract

Background: Work disability in fibromyalgia is only partially explained by symptom severity, suggesting a relevant contribution of cognitive–behavioral mechanisms. Objective: This study aimed to determine whether kinesiophobia is associated with fibromyalgia impact and work-related disability and to assess whether pain catastrophizing mediates these relationships within a hierarchical biopsychosocial framework. Methods: This cross-sectional study included 2096 women with fibromyalgia recruited through a nationwide online survey. Participants completed validated instruments assessing fibromyalgia impact (FIQ), pain catastrophizing (PCS), depressive symptoms (PHQ-9), central sensitization (CSI), and kinesiophobia (Tampa Scale). Pain-related work disability was defined using the Graded Chronic Pain Scale–Revised (GCPS-R). Hierarchical logistic regression models identified factors independently associated with work disability. Mediation was tested using bootstrapped analyses (5000 resamples). Results: Kinesiophobia demonstrated a robust independent association with work disability (OR 1.03; 95% CI 1.02–1.05) after adjustment for sociodemographic factors, clinical pain phenotype, systemic burden, pain severity, psychocognitive load, and medication burden. Other relevant contributors included pain severity (OR 1.96; 95% CI 1.70–2.27), psychocognitive burden (OR 1.35; 95% CI 1.15–1.58), use of benzodiazepines (OR 1.74; 95% CI 1.33–2.28), and opioid use (OR 1.29; 95% CI 1.06–1.56). Mediation analysis indicated a significant indirect effect of kinesiophobia on work disability through pain catastrophizing (β = 0.131; 95% CI 0.078–0.188). Conclusions: Kinesiophobia is a proximal determinant of work disability in fibromyalgia, exerting direct and cognitively mediated effects through pain catastrophizing, reinforcing the fear-avoidance framework and the need for psychologically informed rehabilitation. Full article

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25 pages, 1604 KB

Open AccessArticle

Rural Income Growth Through Digital Infrastructure: Evidence from China’s Yellow River Basin

by Ruomeng Zhou, Yunsheng Zhang and Ruyu Yang

Agriculture 2026, 16(11), 1154; https://doi.org/10.3390/agriculture16111154 - 24 May 2026

Abstract

The digital economy has changed the way agricultural production is organized and how rural households access markets, jobs, and information. Yet it remains unclear whether these changes translate into higher income for rural residents, especially in major agricultural regions. This study examines the income effect of digital infrastructure development by using the rollout of the Broadband China policy as a quasi-natural experiment. The analysis draws on panel data for 77 prefecture-level administrative units in the Yellow River Basin, one of China’s major agricultural regions, from 2009 to 2021. A staggered difference in differences model is used to estimate the policy effect. The results show that digital infrastructure development significantly increases rural residents’ income. Under the log income specification, the baseline coefficient indicates an average income increase of about 8.33%. The mechanism analysis shows that innovation capacity and nonfarm employment both serve as positive partial transmission channels, with innovation capacity explaining a larger share of the total effect. The heterogeneity results suggest that the income effect is stronger in regions with higher GDP and larger population size. These findings indicate that digital infrastructure can support rural income growth when it is linked with local innovation capacity, employment opportunities outside agriculture, and rural development policies suited to local conditions. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

13 pages, 3008 KB

Open AccessCommunication

Charge-Balanced Design for Redox-Responsive Disassembly of Ampholytic β-Sheet Peptide Nanofibers

by Tomonori Waku, Kaede Akita, Takehiro Deromachi, Kazuya Matsuo and Akio Kobori

Polymers 2026, 18(11), 1291; https://doi.org/10.3390/polym18111291 - 24 May 2026

Abstract

Self-assembling β-sheet-forming peptides are attractive building blocks for drug delivery nanomaterials. However, their strong intermolecular interactions often lead to high structural stability, which can hinder intracellular dissociation and limit cargo availability. Here, we propose a charge-compensated ampholytic design strategy for β-sheet peptide nanofibers that undergo destabilization and disassembly under reducing conditions. Six ampholytic peptides comprising an anionic main-chain peptide (β-sheet-forming motif, model antigenic cargo, and oligoglutamic acid segment) and a disulfide-linked cationic segment were designed and synthesized to vary the lengths and charges of the anionic and cationic segments, as well as the cationic insertion position. Four peptides formed nanofibers in 4×phosphate buffered saline (4×PBS) and the resulting nanofibers remained stable after dilution to 1×PBS, retaining β-sheet-rich secondary structures and fibrillar morphologies for at least 24 h. Under reducing conditions, the four preformed nanofibers exhibited distinct behaviors, including reduction-insensitive persistence, disassembly, and transient destabilization followed by re-stabilization, depending on peptide charge design. Redox-triggered disassembly was favored when the main-chain peptide had sufficient anionic character and the cationic segment was of moderate length and charge. This study therefore provides a molecular design strategy for controlling the destabilization of β-sheet peptide nanofibers under reducing conditions through disulfide-cleavage-induced disruption of charge compensation. Full article

(This article belongs to the Special Issue Stimuli-Responsive Functional Polymers for Drug Delivery)

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19 pages, 4213 KB

Open AccessArticle

Dissection of the EIAV Core Packaging Region Identifies SL2 Stem and SL2-SL3 Junction as Gag-Associated Packaging Determinants and Antiviral Targets

by Qiyan Chen, Rui Li, Li Wang, Jinzhong Wang and Ying Wang

Int. J. Mol. Sci. 2026, 27(11), 4728; https://doi.org/10.3390/ijms27114728 - 24 May 2026

Abstract

Equine infectious anemia virus (EIAV), with the simplest lentiviral genome, is a key model for studying fundamental lentiviral biology. Infectious viral particles are produced only when the Gag protein selectively encapsidates full-length genomic RNA via the packaging signal (Psi), yet the structural and functional features of EIAV Psi remain poorly characterized. Using computational prediction and dimethyl sulfate probing, we identified four stem-loops (SLs) within a ~120 nt region in the 5′ leader of the genome, spanning from downstream of the primer binding site through 20 nt into the gag coding sequence. In vitro dimerization assays demonstrated that a palindromic sequence (5′-CUGGCCAG-3′) within SL3 acts as a critical determinant of RNA dimerization. Functional screening using both an EIAV pseudovirus packaging system and the infectious clone EIAVuk revealed that deletion or mutation of the stem-loops significantly impairs viral packaging and replication, with SL2 deletion or its stem disruption causing the most severe defects. RNA-seq analysis of RNAs bound by wild-type Gag versus a zinc-finger mutant (H391K/H410K) identified two candidate Gag-associated sites: the SL2 stem and the SL2-SL3 junction. Targeting these regions with phosphorothioate-modified antisense oligonucleotides potently inhibited pseudovirus production and the replication of infectious EIAVuk. Our findings defined the secondary structure and functional organization of the EIAV core packaging region and established the SL2 stem and SL2-SL3 junction as candidate packaging determinants and promising targets for RNA-based antiviral intervention. Full article

(This article belongs to the Section Molecular Microbiology)

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13 pages, 1280 KB

Open AccessArticle

Neuroadaptive Learning of Output-Constrained Magnetic Drive Transmission Systems with Disturbance Compensation

by Haotian Xu, Guichao Yang, Hua Wang and Fuchang Huang

Mathematics 2026, 14(11), 1823; https://doi.org/10.3390/math14111823 - 24 May 2026

Abstract

This paper focuses on the output-constrained tracking control problem of magnetic drive transmission systems subject to modeling uncertainties. Specifically, a tracking error-based time-varying transformation function is introduced to convert the constrained system into an unconstrained framework. And radial basis function-based neural networks (RBFNN) will be employed to approximate the unknown nonlinear dynamics. Meanwhile, the extended state observer will be incorporated to estimate and compensate for external disturbances. The simulation results demonstrate the effectiveness of the proposed neuroadaptive learning algorithm in the presence of uncertainties. Full article

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