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18 pages, 1266 KB

Open AccessArticle

A Compact Closed-Form Dynamic Hysteresis Model for Energy-Loss Prediction in Power Magnetic Components

by Yingjie Tang, Chayma Guemri and Matthew Franchek

Energies 2026, 19(9), 2078; https://doi.org/10.3390/en19092078 (registering DOI) - 24 Apr 2026

Magnetic hysteresis strongly influences energy dissipation and efficiency in power magnetic components under time-varying excitation. This work proposes a compact dynamic hysteresis model using a Hammerstein structure, consisting of a closed-form arctangent static operator followed by a first-order relaxation dynamic stage. The formulation [...] Read more.

Magnetic hysteresis strongly influences energy dissipation and efficiency in power magnetic components under time-varying excitation. This work proposes a compact dynamic hysteresis model using a Hammerstein structure, consisting of a closed-form arctangent static operator followed by a first-order relaxation dynamic stage. The formulation enables direct datasheet-based parameterization and avoids iterative differential solvers or distributed hysteron representations, resulting in low calibration effort and computational cost. The static hysteresis behavior is characterized using four static parameters directly identified from manufacturer B-H datasheets, while dynamic effects are captured using two global calibration parameters derived from datasheet loss curves. This formulation enables accurate reconstruction of major and minor hysteresis loops, while introducing frequency-dependent phase lag and dynamic loop opening. Model performance is evaluated under diverse excitations, including sinusoidal, amplitude-modulated, FORC and chirp signals, showing waveform deviations below 7.2% peak-to-peak NRMSE relative to classical hysteresis models. Energy-loss predictions are validated against manufacturer datasheet curves for ferrite material 3C90 across multiple frequencies, yielding a root-mean-square relative error of 8.3% with 89% of operating points within ±20% deviation. The proposed model provides a datasheet-driven framework for hysteresis and energy-loss prediction in power magnetic components. Full article

19 pages, 460 KB

Open AccessArticle

Teachers’ and Deputy Head Teachers’ Perceptions of Head Teachers’ Leadership Practices in Zambian Secondary Schools

by Thumah Mapulanga, Victoria Meya Daka, Loyiso Currell Jita, Lineo Mphatsoane-Sesoane and Nonjabulo Madonda

Soc. Sci. 2026, 15(5), 279; https://doi.org/10.3390/socsci15050279 (registering DOI) - 24 Apr 2026

Abstract

School leadership practices may influence teachers’ motivation and professional engagement, which, in turn, may affect overall school performance. This study explores how secondary school teachers and deputy head teachers perceive head teachers’ leadership practices and how these practices are understood to influence teacher [...] Read more.

School leadership practices may influence teachers’ motivation and professional engagement, which, in turn, may affect overall school performance. This study explores how secondary school teachers and deputy head teachers perceive head teachers’ leadership practices and how these practices are understood to influence teacher motivation and professional engagement. Drawing on a qualitative design, data were collected through semi-structured interviews with 12 teachers and six deputy head teachers from six government secondary schools in Kabwe District, Zambia. A qualitative approach enabled an in-depth exploration of leadership perceptions across participants from multiple school contexts. Data were analysed using thematic analysis to identify patterns in leadership practices described by participants. The findings indicate that participants frequently described leadership practices aligned with delegation, mentorship, and open communication, shaped by contextual and organisational factors. However, these practices were not consistently experienced across all school contexts. Participants also described the presence of democratic and autocratic leadership practices. Participants perceived participatory and supportive leadership practices as contributing to their motivation and professional engagement. However, participants from several schools reported that autocratic leadership practices continued to shape decision-making, largely due to contextual, institutional, and workload-related constraints. The study highlights the importance of understanding leadership as contextually negotiated and relationally enacted. It contributes to African educational leadership research by demonstrating how leadership practices are experienced and interpreted within specific school contexts and emphasising the value of examining leadership beyond a single theoretical model. The implications of these findings for school leadership practice, policy development, and international educational leadership research are discussed. Full article

19 pages, 1618 KB

Open AccessArticle

Simulation and Correction Study of Solar Irradiance in Guangdong Based on WRF-Solar and Random Forest

by Yuanhong He, Zheng Li, Fang Zhou and Zhiqiu Gao

Energies 2026, 19(9), 2077; https://doi.org/10.3390/en19092077 (registering DOI) - 24 Apr 2026

Abstract

To improve solar irradiance simulation accuracy for precise photovoltaic power forecasting, we developed a hybrid framework combining WRF-Solar numerical simulation and random forest (RF) machine learning for a PV plant in Guangdong, China. Weather conditions were objectively classified into clear, intermittent cloudy, and [...] Read more.

To improve solar irradiance simulation accuracy for precise photovoltaic power forecasting, we developed a hybrid framework combining WRF-Solar numerical simulation and random forest (RF) machine learning for a PV plant in Guangdong, China. Weather conditions were objectively classified into clear, intermittent cloudy, and overcast using the Daily Variability Index (DVI) and Daily Clear-sky Index (DCI). We calibrated the WRF-Solar model’s microphysics and radiative transfer schemes via sensitivity tests to optimize overcast-sky performance, then applied RF correction to the simulated irradiance. Results show that RF correction significantly reduces simulation errors for intermittent and overcast conditions, while the original WRF-Solar outperforms the corrected results under clear skies due to RF overfitting. Full article

(This article belongs to the Special Issue Advanced Artificial Intelligence for Photovoltaic Energy Systems)

19 pages, 4213 KB

Open AccessArticle

Enhanced Battery Pack Consistency: A Hierarchical Active Balancing System Combining Bidirectional Buck–Boost and Flyback Converters

by Xiangya Qin, Zefu Tan, Qingshan Xu, Li Cai, Xiaojiang Zou and Nina Dai

World Electr. Veh. J. 2026, 17(5), 231; https://doi.org/10.3390/wevj17050231 (registering DOI) - 24 Apr 2026

Abstract

Series-connected lithium-ion battery packs are widely used in electric vehicles (EVs). However, inevitable inconsistency among cells can cause charge imbalance, accelerated aging, and reduced system safety. To improve the consistency of series-connected battery packs under complex EV operating conditions, this study proposes a [...] Read more.

Series-connected lithium-ion battery packs are widely used in electric vehicles (EVs). However, inevitable inconsistency among cells can cause charge imbalance, accelerated aging, and reduced system safety. To improve the consistency of series-connected battery packs under complex EV operating conditions, this study proposes a hierarchical active balancing system. Bidirectional Buck–Boost converters are employed for intra-group balancing, and distributed flyback converters are used for inter-group balancing. A multi-stage coordinated balancing control strategy is further developed to reduce control complexity and improve balancing efficiency. A 16-cell series-connected battery pack model is established in MATLAB R2024a /Simulink and evaluated under resting, charging, and discharging conditions. The results show that, compared with the conventional single-layer Buck–Boost balancing topology, the proposed method reduces the balancing time by 58.09%, 57.97%, and 58.06%, respectively. These results indicate that the proposed system can effectively improve the consistency and balancing performance of series-connected battery packs, providing a scalable solution for EV battery management systems. Full article

(This article belongs to the Section Power Electronics Components)

17 pages, 1226 KB

Open AccessArticle

5-ALA/SFC Mitigates Tau Toxicity via Lowering Oxidative Stress in a Drosophila Model of Tau Toxicity

by Arisa Tamura, Marie Noguchi, Naoko Nozawa, Emiko Suzuki and Kanae Ando

Life 2026, 16(5), 725; https://doi.org/10.3390/life16050725 (registering DOI) - 24 Apr 2026

Abstract

Mitochondrial dysfunctions contribute to the pathogenesis of tauopathies, a group of neurodegenerative diseases with abnormal accumulation of microtubule-associated protein tau. The combination of 5-aminolevulinic acid (5-ALA) and sodium ferrous citrate (SFC) is known to improve mitochondrial functions. Here, we report that 5-ALA combined [...] Read more.

Mitochondrial dysfunctions contribute to the pathogenesis of tauopathies, a group of neurodegenerative diseases with abnormal accumulation of microtubule-associated protein tau. The combination of 5-aminolevulinic acid (5-ALA) and sodium ferrous citrate (SFC) is known to improve mitochondrial functions. Here, we report that 5-ALA combined with SFC (5-ALA/SFC) improves mitochondrial functions and mitigates neurodegeneration in transgenic Drosophila expressing human tau. We found that tau reduces ATP levels, decreases mitochondrial distribution to neurites, and increases mitochondrial reactive oxygen species (ROS). Expression of oxidative phosphorylation (OXPHOS) genes was upregulated, and activities of complexes I and IV were elevated. Feeding 5-ALA/SFC to tau flies lowers oxidative damage without correcting OXPHOS activities or mitochondrial distribution. 5-ALA/SFC treatment suppressed pathological tau phosphorylation and mitigated tau-induced neurodegeneration. These results suggest that 5-ALA/SFC attenuates a neurodegenerative pathway involving tau, mitochondria, and ROS. Full article

(This article belongs to the Special Issue Advances in 5-Aminolevulinic Acid Applications in Medical and Healthcare)

24 pages, 2663 KB

Open AccessArticle

A Fully Integrated Gate-Pole-Dominant Low-Dropout Regulator with Loop-Gain Booster for Maintaining High Power-Supply Rejection over a Wide Load Current Range

by Deok Won Koh, Changin Yoon, Jeong Hoan Park, Seung Hwan Lee and Younghyun Lim

Electronics 2026, 15(9), 1825; https://doi.org/10.3390/electronics15091825 (registering DOI) - 24 Apr 2026

Abstract

This paper introduces a fully integrated gate-pole-dominant low-dropout regulator (LDO) that eliminates the need for external capacitors while sustaining high power-supply rejection (PSR) over a broad load current range. A loop-gain booster (LGB) is proposed to maintain the DC operating point of the [...] Read more.

This paper introduces a fully integrated gate-pole-dominant low-dropout regulator (LDO) that eliminates the need for external capacitors while sustaining high power-supply rejection (PSR) over a broad load current range. A loop-gain booster (LGB) is proposed to maintain the DC operating point of the error amplifier output at its optimal value, thereby preserving a high unity-gain frequency (UGF) even as the load current varies from zero to 200 mA. The parallel signal paths within the LGB inherently produce a left-half-plane (LHP) zero, which cancels one of the poles within the UGF of the feedback loop and guarantees robust stability under diverse operating conditions. Fabricated in a 40 nm CMOS technology, the prototype occupies only 0.008 mm² with a 4 pF on-chip compensation capacitor. The proposed LDO achieves a PSR of −72 dB at 1 MHz and −40 dB at 10 MHz when I_L = 200 mA and V_DO = 0.1 V, and maintains a PSR better than −78 dB at 1 MHz and −42 dB at 10 MHz when I_L = 1 mA and V_DO = 0.1 V. The LGB-enhanced regulator achieves excellent load and line regulation figures of 29 μV/mA and 0.75 mV/V, while the LGB itself consumes merely 7 μA out of a total quiescent current of 108 μA. Full article

(This article belongs to the Special Issue Integrated Circuit-to-System Design for Advanced Sensing and Communication)

15 pages, 2787 KB

Open AccessArticle

Impact of Community-Based Health Education and Sanitation Interventions on Opisthorchis viverrini Infection in an Endemic Area of Northeastern Thailand

by Parichart Boueroy, Nattamol Phetburom, Birabongse Hardthakwong, Ratanee Kammoolkon, Panchamapohn Rattanahon, Peechanika Chopjitt, Narita Fakkaew, Pathanan Suwannaboon, Chavanakorn Krueakaew, Patiwat Yasaka, Janjira Hantakhu and Kulthida Y. Kopolrat

Int. J. Environ. Res. Public Health 2026, 23(5), 553; https://doi.org/10.3390/ijerph23050553 (registering DOI) - 24 Apr 2026

Abstract

Opisthorchis viverrini infection remains a significant public health concern in Southeast Asia, particularly in rural communities of Northeast Thailand, where persistent environmental and behavioral factors sustain transmission. A quasi-experimental study aimed to identify environmental and behavioral risk factors for infection and to evaluate [...] Read more.

Opisthorchis viverrini infection remains a significant public health concern in Southeast Asia, particularly in rural communities of Northeast Thailand, where persistent environmental and behavioral factors sustain transmission. A quasi-experimental study aimed to identify environmental and behavioral risk factors for infection and to evaluate the effectiveness of a community-based intervention program. The intervention program study was conducted over 10 months and comprised three phases: baseline survey‚ health education intervention program implementation‚ and follow-up evaluation. The results were analyzed for the prevalence of parasitic infections, and multivariable logistic regression was performed to identify associated factors. The majority of study participants were female (67.94%)‚ aged 55 to 64 years (48.09%)‚ and farmers (89.31%). Parasitic infections‚ especially O. viverrini‚ substantially decreased during the follow-up period‚ and independent risk factors predicting infection included lower education‚ previous infection‚ raw fish consumption‚ and pesticide use‚ according to multivariable logistic regression analysis. This intervention considerably improved knowledge; mean knowledge score increased by 6.29 points (p < 0.001). Analysis of fecal sludge after treatment with the sand-drying system identified S. stercoralis larvae (20 eggs/L) and Taenia spp. eggs (12.4 eggs/g). These findings indicated that, despite treatment, integrated behavioral and environmental interventions can be effective in interrupting parasite transmission in rural endemic settings. Full article

(This article belongs to the Section Infectious Diseases, Chronic Diseases, and Disease Prevention)

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18 pages, 1734 KB

Open AccessArticle

Blended Learning to Enhance Competencies Among Practicing Pharmacists: A Pre–Post Evaluation of the European Health Professionals’ and the DigitAl Team SkillS Advancement Project in Romania

by Tünde Jurca, Andrei-Flavius Radu, Gabriela S. Bungau, Annamária Pallag, Anett Jolán Karetka, Octavia Gligor, Laura Graţiela Vicaş, Florin Bănică, Diana Teaha, Claudia Costea, Nóra Fazekas, Zoltán Cserháti, Ilie Cirstea and Tiberiu Sebastian Nemeth

Pharmacy 2026, 14(3), 64; https://doi.org/10.3390/pharmacy14030064 - 24 Apr 2026

Abstract

The digital transformation of healthcare requires stronger digital competencies among pharmacists, yet evidence on the effectiveness of structured training remains scarce. This study examines the impact of a blended digital health training programme delivered to practicing pharmacists in Bihor County, Romania, as part [...] Read more.

The digital transformation of healthcare requires stronger digital competencies among pharmacists, yet evidence on the effectiveness of structured training remains scarce. This study examines the impact of a blended digital health training programme delivered to practicing pharmacists in Bihor County, Romania, as part of the Romanian pilot of the EU-funded European Health Professionals’ and the DigitAl team SkillS (H-PASS) project. A single-group pre–post educational design was applied to pharmacists from Bihor County, Romania, participating in a modular digital health training programme delivered between May and July 2025. A total of 84 pharmacists completed both pre-training and post-training self-reported competency assessments comprising 18 items across three modules: digital innovation and change management, communication and collaboration, and data management and digital literacy. Paired samples t-tests, Cohen’s d effect sizes, Cronbach’s alpha, moderator analyses, and ceiling effect analyses were conducted using Python-based statistical workflows. Statistically significant improvements were observed across all three modules (all p < 0.0001), with large effect sizes (d = 1.04–1.30). Post-training internal consistency increased substantially, with overall Cronbach’s alpha reaching 0.74. The greatest item-level gains were recorded in adaptive communication, cultural adaptation of care, and data protection ethics. No significant moderation effects were found for age, gender, or years of experience. Course satisfaction showed a moderate positive correlation with competency gains (r = 0.528), while perceived improvement was not significantly associated with observed score change. A ceiling effect indicated greater gains among participants with lower baseline competencies. The Romanian implementation of the H-PASS training programme was associated with improved self-reported digital health competencies among practicing pharmacists, high-lighting its potential as a scalable model for digital upskilling in healthcare. Full article

(This article belongs to the Section Pharmacy Education and Student/Practitioner Training)

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23 pages, 6671 KB

Open AccessArticle

High-Purity, Uniform, and Spherical Hafnium Carbide Nanoparticles Derived from a Novel Amorphous Hafnium-Based Metal–Organic Framework Precursor for the Preparation of High-Performance Ceramics

by Hongzhi Cheng, Jian Gu, Siyuan Kan, Ran Xie, Quan Li, Sinuo Zhang, Junyang Jin, Yang Wang, Jian Yang and Chang-An Wang

Materials 2026, 19(9), 1754; https://doi.org/10.3390/ma19091754 - 24 Apr 2026

Abstract

A novel amorphous Hf-MOFs precursor was successfully synthesized and converted into HfC nanoparticles via one-step pyrolysis. The effects of metal/ligand molar ratios, solvent types, and pyrolysis temperature were systematically studied. High-purity spherical HfC nanoparticles (44.30 ± 9.63 nm) were obtained at 1500 °C [...] Read more.

A novel amorphous Hf-MOFs precursor was successfully synthesized and converted into HfC nanoparticles via one-step pyrolysis. The effects of metal/ligand molar ratios, solvent types, and pyrolysis temperature were systematically studied. High-purity spherical HfC nanoparticles (44.30 ± 9.63 nm) were obtained at 1500 °C using a 1.5:1 metal/ligand molar ratio with mixed anhydrous ethanol/deionized water solvents. At a pyrolysis temperature of 1700 °C, the as-synthesized HfC nanoparticles possessed an exceptionally low oxygen content of 0.76%, alongside a carbon content of 6.42% that almost perfectly matches the theoretical value of stoichiometric HfC. The formation mechanism involving Hf-O-C coordination and carbothermal reduction was clarified. Additive-free HfC ceramics were fabricated using the as-synthesized HfC nanoparticles via spark plasma sintering (1950 °C, 30 MPa, 20 min). The resulting ceramics exhibited a relative density of 96.7% and a Vickers hardness of 20.2 GPa, both of which are significantly superior to those of ceramics sintered from commercial HfC powders under identical conditions (95.8% and 17.8 GPa, respectively). This work provides a promising and feasible pathway for the preparation of other high-quality ultra-high temperature hafnium-based carbide powders and ceramics. Full article

(This article belongs to the Section Advanced and Functional Ceramics and Glasses)

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18 pages, 60393 KB

Open AccessArticle

Mineralogical Characteristics of White Nephrite from Dikou, Fujian Province, Southeastern China

by Shuo Ran and Yingxin Liu

Crystals 2026, 16(5), 284; https://doi.org/10.3390/cryst16050284 - 24 Apr 2026

Abstract

Nephrite is a significant jade resource, and systematic investigation of its deposits contributes to regional metallogenic synthesis and exploration targeting. The recently discovered white nephrite deposit in the Dikou area, Fujian Province, remains inadequately characterized. This study presents a comprehensive mineralogical investigation employing [...] Read more.

Nephrite is a significant jade resource, and systematic investigation of its deposits contributes to regional metallogenic synthesis and exploration targeting. The recently discovered white nephrite deposit in the Dikou area, Fujian Province, remains inadequately characterized. This study presents a comprehensive mineralogical investigation employing polarizing microscopy, scanning electron microscopy, electron probe microanalysis, X-ray powder diffraction and laser Raman spectroscopy to elucidate the mineralogical and petrochemical characteristics of Dikou nephrite and constrain its genesis. The results demonstrate that tremolite constitutes the predominant mineral phase, accompanied by abundant diopside and quartz, with minor dolomite, prehnite, and apatite. Based on subtle compositional variations, tremolite can be categorized into two generations: early metasomatic Tr-I and late-stage Tr-II. All tremolite samples exhibit Fe-depleted, Mg-enriched composition with Mg# > 0.99. The mineral assemblage and textural relationships record multiple episodes of hydrothermal metasomatism. Integrated with the regional geological constraints, the deposit formation is genetically linked to the Neoproterozoic–Early Paleozoic ocean–continent transition of the South China Plate and is classified as D-type nephrite. The Dikou nephrite exhibits the mineral assemblage typical of dolomite-related deposits, displaying a distinctive felt-like fibrous texture that yields a homogeneous structure and superior aesthetic quality. Its Fe-depleted composition imparts a notably lighter coloration relative to D-type nephrite from other deposits. This study advances understanding of Dikou nephrite genesis, highlights the diversity of metallogenic environments in Fujian Province, and provides a theoretical framework for exploration of analogous deposits. Full article

(This article belongs to the Special Issue Modern Gem Crystals: Synthesis, Characterization, Genesis and Intelligent Analysis)

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25 pages, 28621 KB

Open AccessArticle

Empagliflozin Ameliorates Diabetic Cardiomyopathy by Inhibiting Ferroptosis via SIRT3: Mechanisms and Therapeutic Implications

by Taoshan Feng, Meilian Liu, Dan Zhong, Xusan Xu, Zhengqiang Luo, Wensen Zhang, Yajun Wang, Riling Chen, Xiaoming Chen and Guoda Ma

Antioxidants 2026, 15(5), 543; https://doi.org/10.3390/antiox15050543 (registering DOI) - 24 Apr 2026

Abstract

Empagliflozin (EMPA), a sodium-glucose cotransporter 2 inhibitor, has garnered attention for its cardiovascular benefits beyond glycemic control. Ferroptosis, a novel form of regulated cell death, contributes to the pathogenesis of diabetic cardiomyopathy (DCM). However, whether EMPA mitigates DCM by suppressing ferroptosis remains unclear. [...] Read more.

Empagliflozin (EMPA), a sodium-glucose cotransporter 2 inhibitor, has garnered attention for its cardiovascular benefits beyond glycemic control. Ferroptosis, a novel form of regulated cell death, contributes to the pathogenesis of diabetic cardiomyopathy (DCM). However, whether EMPA mitigates DCM by suppressing ferroptosis remains unclear. Here, Type 2 diabetic db/db mice were used to establish a DCM model and treated with EMPA (10 mg/kg/day) for 12 weeks. EMPA significantly improved cardiac function, reduced myocardial fibrosis, and attenuated ferroptosis, concomitant with upregulated silent information regulator 3 (SIRT3) expression. In the rat cardiomyocytes (H9c2 cells) exposed to high glucose and palmitic acid, EMPA treatment or SIRT3 overexpression alleviated oxidative stress, mitochondrial dysfunction, and ferroptosis. Mechanistically, molecular docking, molecular dynamics simulation, cellular thermal shift assay and drug affinity responsive target stability assay confirmed that SIRT3 is the drug target of EMPA, stabilizing its protein levels and reducing acetylated p53 expression. Notably, SIRT3 silencing abolished EMPA’s beneficial effects on oxidative stress and ferroptosis. Our findings demonstrate that EMPA exerts cardioprotective effects by inhibiting oxidative stress and ferroptosis in cardiomyocytes, which is mediated by SIRT3. This study provides novel insights into the mechanisms underlying EMPA’s therapeutic effects in DCM. Full article

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25 pages, 2895 KB

Open AccessArticle

Evaluation of a Hybrid Physical–LSTM Model for Air-to-Air Heat Pump Control: Insights from Multi-Day Closed-Loop Simulations in Mediterranean Climate

by Ivica Glavan, Ivan Gospić and Igor Poljak

Modelling 2026, 7(3), 81; https://doi.org/10.3390/modelling7030081 - 24 Apr 2026

Abstract

Air-to-air heat pumps are a key technology for improving energy efficiency and reducing carbon emissions in residential buildings, yet their optimal control remains challenging under real-world conditions. This study evaluates the performance of a hybrid physical–LSTM model for controlling an air-to-air heat pump [...] Read more.

Air-to-air heat pumps are a key technology for improving energy efficiency and reducing carbon emissions in residential buildings, yet their optimal control remains challenging under real-world conditions. This study evaluates the performance of a hybrid physical–LSTM model for controlling an air-to-air heat pump in a residential building in Zadar, Croatia. The hybrid framework integrates a first-order energy balance model of the building envelope with LSTM-based temperature correction using adaptive weighting. The physical model was calibrated and validated against 52,128 real IoT measurements collected during the 2024/2025 heating season, achieving high accuracy (RMSE ≈ 0.076 °C). Rolling one-day and continuous multi-day closed-loop simulations (up to 15 days) show that the hybrid model yields slightly lower RMSE in long-term runs compared to the pure physical model. However, this apparent statistical improvement is accompanied by systematic underestimation of indoor temperature and significantly higher simulated energy consumption. The results indicate that the observed effect originates from an implicit virtual heat flux introduced by the LSTM correction, which affects thermodynamic consistency in closed-loop operation. The findings highlight that short-term error metrics such as RMSE alone are insufficient for evaluating hybrid models intended for model predictive control (MPC). The main contribution of this study is the explicit demonstration and quantification of an implicit virtual heat flux generated by the LSTM correction in closed-loop multi-day operation, which leads to misleading statistical improvements while causing significant thermodynamic inconsistency and energy overconsumption. In 15-day continuous simulations the hybrid model (ω = 0.05–0.10) caused an indoor temperature underestimation of 1.25–1.31 °C and increased simulated electricity consumption by more than 300% (316 kWh vs. 72 kWh) compared to the physical model. These results have direct implications for the development of reliable digital twins and model predictive control strategies in residential HVAC systems. Full article

21 pages, 1509 KB

Open AccessArticle

Effect of Submarine Speed on Its Motion in Internal Solitary Waves

by Maolin Wang, Hui Du, Shaodong Wang, Tianyu Zhang, Pu Xuan, Pai Peng, Ruipeng Li and Zhan Wang

J. Mar. Sci. Eng. 2026, 14(9), 786; https://doi.org/10.3390/jmse14090786 - 24 Apr 2026

Abstract

Although extensive research has been carried out on the load characteristics of fixed submarines in internal solitary waves, there is still insufficient understanding of the effect of submarine speed on its motion in internal solitary waves. A rapid calculation method for the motion [...] Read more.

Although extensive research has been carried out on the load characteristics of fixed submarines in internal solitary waves, there is still insufficient understanding of the effect of submarine speed on its motion in internal solitary waves. A rapid calculation method for the motion response of a submarine (SUBOFF standard model) in internal solitary waves between two layers of fluid is established in this study, where the internal wave flow field is constructed based on the extended Korteweg-de Vries theory, and the load on the submarine is calculated using the Morison equation. The accuracy of the proposed method is verified by comparison with numerical results and experimental data. The results of the motion response of the submarine when encountering internal solitary waves at different speeds show that there is a significant nonlinear relationship between speed and vertical motion amplitude and maximum pitch angle. A critical speed is further found, beyond which the submarine experiences a secondary falling deep after the initial vertical falling deep. Full article

(This article belongs to the Section Ocean Engineering)

17 pages, 1538 KB

Open AccessArticle

Predictors of First Anti-TNF Treatment Failure in Patients with Inflammatory Bowel Disease: A Single-Center Cohort Study

by Konstantinos C. Mpakogiannis, Paraskevi Chasani, Ioanna Nefeli Mastorogianni, Konstantinos H. Katsanos and Fotios S. Fousekis

Biomedicines 2026, 14(5), 984; https://doi.org/10.3390/biomedicines14050984 - 24 Apr 2026

Abstract

Introduction: Despite proven efficacy of anti-TNF agents in inflammatory bowel disease, primary non-response affects up to one-third of patients, while secondary loss of response occurs at 13–21% per patient-year, often requiring dose optimization or switching to alternative advanced therapies. Methods: The [...] Read more.

Introduction: Despite proven efficacy of anti-TNF agents in inflammatory bowel disease, primary non-response affects up to one-third of patients, while secondary loss of response occurs at 13–21% per patient-year, often requiring dose optimization or switching to alternative advanced therapies. Methods: The present single-center cohort study at the University Hospital of Ioannina included biologic-naïve patients receiving anti-TNF therapy as their first biologic treatment. First anti-TNF treatment failure was defined as discontinuation due to persistent IBD activity despite maximal dose optimization (infliximab 10 mg/kg every 4 weeks, adalimumab 40 mg weekly). Patients with measurable anti-drug antibodies prior to anti-TNF dose intensification or discontinuation were excluded. Of 528 anti-TNF-treated patients, 286 (173 with CD, 113 with UC) met the inclusion criteria and were included in the final statistical analysis. Results: Anti-TNF failure occurred in 32.7% of Crohn’s (CD) and 32.9% of ulcerative colitis (UC) patients. Multivariable Cox regression identified complicated phenotype (stricturing or/and penetrating CD; HR = 1.9, p = 0.032) and concomitant corticosteroid use at anti-TNF initiation (HR = 2.03, p = 0.012) as independent predictors of anti-TNF failure in CD. Age at CD diagnosis showed a trend for statistical significance (HR = 1.02, p = 0.061), and after stratification, age at diagnosis ≥ 40 years conferred higher risk (HR = 1.93, p = 0.016), alongside persistent effects of complicated phenotype (HR = 1.83, p = 0.027) and corticosteroid use (HR = 2.01, p = 0.013). In UC patients, female sex predicted anti-TNF failure (HR = 2.13, p = 0.025). IBD-related bowel resection occurred in 26.6% of patients with CD and in 5.3% of patients with UC. Conclusions: Anti-TNF failure remains common despite optimization. Identifying immunogenicity-independent predictors may enable personalized treatment strategies and improve outcomes. Full article

(This article belongs to the Special Issue Translational Immunology in Inflammatory Bowel Diseases: From Mechanisms to Precision Medicine)

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14 pages, 5873 KB

Open AccessArticle

Synergistic Regulation of Nitrogen-Doped Carbon Coating and Pseudocapacitive Kinetics in TiO₂ Nanofibers for Enhanced Sodium-Ion Storage

by Fei Guo, Liang Xie, Liangquan Wei, Jinmei Du, Shaohui Zhang, Yuanmiao Xie and Baosheng Liu

Molecules 2026, 31(9), 1418; https://doi.org/10.3390/molecules31091418 (registering DOI) - 24 Apr 2026

Abstract

Sodium-ion batteries (SIBs) represent a compelling alternative to lithium-ion batteries for grid-scale energy storage, owing to the high natural abundance and low cost of sodium resources, as well as their strategic alignment with national energy security priorities. Nevertheless, the sluggish Na⁺ diffusion [...] Read more.

Sodium-ion batteries (SIBs) represent a compelling alternative to lithium-ion batteries for grid-scale energy storage, owing to the high natural abundance and low cost of sodium resources, as well as their strategic alignment with national energy security priorities. Nevertheless, the sluggish Na⁺ diffusion kinetics and limited specific capacity of anode materials continue to impede practical deployment. Herein, nitrogen-doped carbon-coated TiO₂ nanofibers (TiO₂/C-N) were rationally engineered through a facile electrospinning route integrated with synergistic defect and coating engineering. The in situ-formed N-doped carbon shell establishes a continuous, high-conductivity electron-transport network while simultaneously buffering volumetric strain during repeated (de)sodiation, thereby preserving long-term structural integrity. Electrochemical assessments demonstrate that the TiO₂/C-N electrode delivers a reversible specific capacity of 233.64 mAh g⁻¹ at 0.1 A g⁻¹ (initial Coulombic efficiency 54.13%). Quantitative kinetic analysis reveals a pronounced pseudocapacitive contribution of 41.4% at 1.2 mV s⁻¹, confirming a surface-controlled Na⁺ storage pathway that markedly enhances rate capability. Moreover, the electrode retains 245.5 mAh g⁻¹ after 150 cycles at 1 A g⁻¹, underscoring exceptional cycling stability. This work elucidates the synergistic regulation of N-doped carbon coating and pseudocapacitive kinetics in TiO₂-based anodes, offering a robust design strategy for high-rate, long-cycle-life SIB anodes. Full article

(This article belongs to the Special Issue Advanced Materials and Surface Engineering for Sustainable Functional Coatings)

30 pages, 1007 KB

Open AccessArticle

Field-Theoretic Derivation of the Constructal Law from Non-Equilibrium Thermodynamics

by Antonio F. Miguel

Symmetry 2026, 18(5), 732; https://doi.org/10.3390/sym18050732 - 24 Apr 2026

Abstract

Traditional analyses of transport phenomena rely on prescribed geometric boundaries, yet natural flow systems dynamically evolve their architecture to maximize access to currents. To address this disparity, we propose a field-theoretic framework for the constructal law that treats physical geometry as a dynamic [...] Read more.

Traditional analyses of transport phenomena rely on prescribed geometric boundaries, yet natural flow systems dynamically evolve their architecture to maximize access to currents. To address this disparity, we propose a field-theoretic framework for the constructal law that treats physical geometry as a dynamic state variable, represented by a time-dependent conductivity tensor. Using a variational approach grounded in non-equilibrium thermodynamics, we derive a general tensor evolution equation. Within this framework, macroscopic flow architecture emerges deterministically from the continuous competition between non-linear flux-induced accretion, linear entropic relaxation, and spatial smoothing. Scaling analysis reduces this dynamic to a tri-parameter dimensionless phase space: a morphogenic number driving structural growth, a structural diffusion number governing spatial coherence, and a stochastic intensity number providing the microscopic seeds for symmetry breaking. Our principal result is the analytical prediction of a critical bifurcation. When the local morphogenic number strictly exceeds unity, the system escapes its stable, isotropic configuration and branches into highly conductive, anisotropic architectures. We demonstrate the predictive validity and trans-scalar applicability of this continuum theory by mapping it to highly diverse phase transitions, successfully capturing phenomena ranging from microscopic aerosol agglomeration and microbial resistance, to macroscopic coral plasticity and crystal growth instabilities, and finally to the astrophysical launching of relativistic jets from black holes. Full article

(This article belongs to the Special Issue Mathematics: Feature Papers 2026)

21 pages, 8003 KB

Open AccessArticle

Design and Validation of Segmented CFRP Lamella-Based Composite End Shield for Bearing Current Mitigation

by Jiří Sika, Michal Křížek, Tomáš Kavalír and Bohumil Skala

Machines 2026, 14(5), 483; https://doi.org/10.3390/machines14050483 (registering DOI) - 24 Apr 2026

Abstract

This study addresses the premature failure of electric motor bearings caused by inverter-induced parasitic currents. We propose a novel segmented end shield design utilizing 24 carbon fiber-reinforced polymer (CFRP) lamellae to provide both structural support and galvanic isolation. The “main working” of the [...] Read more.

This study addresses the premature failure of electric motor bearings caused by inverter-induced parasitic currents. We propose a novel segmented end shield design utilizing 24 carbon fiber-reinforced polymer (CFRP) lamellae to provide both structural support and galvanic isolation. The “main working” of the design relies on a segmented architecture where the lamellae are adhesively bonded between a central bearing housing and an outer mounting flange, creating a high-impedance path that interrupts circulating currents. Experimental validation focused on both mechanical stability and dielectric performance. Results indicate that the assembly maintains rotor positional integrity under nominal loads while providing an insulation resistance > 1 GΩ at 1 kV and a structural capacitance of 2.47 nF. These parameters effectively mitigate low-frequency circulating currents. Data analysis, derived from the mean values of repeated test cycles, confirms that the composite architecture serves as a viable, mechanically robust alternative to conventional metallic end shields. Full article

(This article belongs to the Section Machine Design and Theory)

26 pages, 1346 KB

Open AccessArticle

Associations Between Problematic TikTok Use, Anxiety, Depression and Sleep Quality: Sex and Generation Differences

by Aglaia Katsiroumpa, Zoe Katsiroumpa, Evmorfia Koukia, Polyxeni Mangoulia, Ioannis Moisoglou and Petros Galanis

Psychiatry Int. 2026, 7(3), 88; https://doi.org/10.3390/psychiatryint7030088 - 24 Apr 2026

Abstract

Our objective was to investigate the relationship between problematic TikTok use and levels of anxiety, depression, and sleep quality. We also explored differences across sex and generational groups. A cross-sectional study was conducted in Greece using a convenience sample. Participants were classified into [...] Read more.

Our objective was to investigate the relationship between problematic TikTok use and levels of anxiety, depression, and sleep quality. We also explored differences across sex and generational groups. A cross-sectional study was conducted in Greece using a convenience sample. Participants were classified into three generational groups: Generation Z (1997–2012), Millennials (1981–1996), and Generation X (1965–1980). Problematic TikTok use was assessed with the TikTok Addiction Scale, while anxiety and depression were measured using the Patient Health Questionnaire-4. Sleep quality was evaluated with the Sleep Quality Scale. To account for potential confounding factors, we performed multivariable linear regression analyses. Our results showed a positive association between problematic TikTok use and both anxiety and depression. Multivariable analysis revealed a negative association between problematic TikTok use and sleep quality. In summary, our findings indicate that problematic TikTok use is linked to higher levels of anxiety and depression, as well as poorer sleep quality. These results highlight the need for policymakers, stakeholders, and healthcare professionals to develop and implement targeted interventions aimed at mitigating the negative effects associated with problematic TikTok use. Full article

(This article belongs to the Special Issue The Impact of Social Media on Mental Health)

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20 pages, 3384 KB

Open AccessArticle

Improved Terminal Integral Sliding Mode Control Based on PMSM for New Energy Vehicle Applications

by Wenqiang He, Jing Bai, Yu Xu, Lei Zhang and Xingyi Ma

Processes 2026, 14(9), 1377; https://doi.org/10.3390/pr14091377 (registering DOI) - 24 Apr 2026

Abstract

To address the deteriorated control performance of permanent magnet synchronous motor (PMSM) drive systems for new energy vehicles (NEVs) under complex conditions caused by multi-source disturbances (internal parameter perturbations and external load mutations), this paper proposes an improved terminal integral sliding mode control [...] Read more.

To address the deteriorated control performance of permanent magnet synchronous motor (PMSM) drive systems for new energy vehicles (NEVs) under complex conditions caused by multi-source disturbances (internal parameter perturbations and external load mutations), this paper proposes an improved terminal integral sliding mode control (ITISMC-ADERL) strategy integrating a piecewise adaptive terminal integral sliding mode surface and an ADERL. The proposed sliding mode surface adopts interval-adaptive switching between high- and low-order power terms, completely eliminating singularity and integral saturation defects of traditional terminal sliding mode control while ensuring fast convergence, and achieving an optimal structural balance between convergence speed and chattering suppression. The state-dependent ADERL leverages the synergy of error-sliding variable coupled dynamic gain adjustment and variable exponential power compensation, realizing dual-mode adaptive switching of “strong driving for fast approaching far from the sliding surface, weak gain for smooth regulation near the sliding surface”, which significantly improves control accuracy and anti-disturbance robustness. The finite-time convergence of the closed-loop system is rigorously proved via Lyapunov stability theory. Full-operating-condition comparative tests on a TMS320F28379D DSP platform show that the proposed strategy outperforms SMC-ERL, ISMC-ERL and ITISMC-ERL in all test scenarios (no-load startup, acceleration/deceleration, sudden load changes, flux linkage perturbation), meeting the requirements of high-performance NEV drive systems and possessing important engineering application potential. Full article

(This article belongs to the Section Automation Control Systems)

17 pages, 3977 KB

Open AccessArticle

An Experimental–Numerical Study on Oxidation Inhibition of SiO₂ Nanoparticles in Biolubricants for Internal Combustion Engines

by Homeyra Piri, Salar Moradi, Massimiliano Renzi and Marco Bietresato

Appl. Sci. 2026, 16(9), 4208; https://doi.org/10.3390/app16094208 (registering DOI) - 24 Apr 2026

Abstract

Modern agriculture depends heavily on machinery to maximize operational efficiency and, consequently, profitability, but the wear-and-tear on the mechanical components of machinery due to ageing can lead to reduced efficiency, more downtime, and higher maintenance expenses, thus raising the operative costs. These problems [...] Read more.

Modern agriculture depends heavily on machinery to maximize operational efficiency and, consequently, profitability, but the wear-and-tear on the mechanical components of machinery due to ageing can lead to reduced efficiency, more downtime, and higher maintenance expenses, thus raising the operative costs. These problems have been addressed by the use of specific lubricant additives for machinery; however, additives have known disadvantages, such as compatibility restrictions and environmental concerns, which represent critical issues especially in case of possible dispersion in the environment. Modern industry is always looking for techniques and solutions to increase efficiency and productivity, and this study investigates the possible advantages of employing nanotechnology in lubricant formulations. Amongst all possible substances, SiO₂ nanoparticles are increasingly promising as lubricant additives due to their unique properties, which include heat resistance, high levels of stability, and good biocompatibility. Moreover, biolubricants, derived from renewable sources, offer an environmentally friendly alternative to conventional lubricants. This article contributes to the field of agricultural technology by demonstrating the potential of SiO₂ nanoparticles in formulations of biolubricants thought to be used in agricultural machines. Key degradation parameters, including density, viscosity, total acid number (TAN), total base number (TBN), oxidation, and elemental composition, were systematically analysed. The results showed that SiO₂ nanoparticles mitigate viscosity loss and density increase, optimize TAN and TBN, reduce oxidation of the biolubricants by up to 17.7% at 1.00 wt% SiO₂, and stabilize elemental composition during ageing. Nanoparticles remained uniformly dispersed without sedimentation for over 30 days. This provides insights that can prevent machinery performance degradation over time, reduce lubricant changes, and suggest a more sustainable and environmentally friendly lubrication solution, thus promoting more sustainable industry. Full article

(This article belongs to the Section Mechanical Engineering)

25 pages, 4382 KB

Open AccessArticle

Spatio-Temporal Joint Network for Coupler Anomaly Detection Under Complex Working Conditions Utilizing Multi-Source Sensors

by Zhirong Zhao, Zhentian Jiang, Qian Xiao, Long Zhang and Jinbo Wang

Sensors 2026, 26(9), 2661; https://doi.org/10.3390/s26092661 (registering DOI) - 24 Apr 2026

Abstract

Owing to the intricate mechanical coupling characteristics and the considerable difficulty in extracting synergistic spatio-temporal features from high-dimensional sensor data under fluctuating alternating loads, this study proposes a robust anomaly detection framework that combines Normalized Mutual Information (NMI) and Spatio-Temporal Graph Neural Networks [...] Read more.

Owing to the intricate mechanical coupling characteristics and the considerable difficulty in extracting synergistic spatio-temporal features from high-dimensional sensor data under fluctuating alternating loads, this study proposes a robust anomaly detection framework that combines Normalized Mutual Information (NMI) and Spatio-Temporal Graph Neural Networks (STGNN). First, NMI is utilized to quantify the nonlinear physical coupling intensity among multi-source sensors, thereby filtering out weakly correlated noise and reconstructing the spatial topological structure of the coupler system. Subsequently, a deep learning architecture incorporating Graph Convolutional Networks (GCN), Gated Recurrent Units (GRU), and one-dimensional convolutional residual connections is developed to capture the dynamic evolutionary characteristics of equipment states across both spatial interactions and temporal sequences. Finally, based on the model’s health-state predictions, a moving average algorithm is introduced to smooth the residual sequences, and an anomaly early-warning baseline is established in conjunction with the 3σ criterion. Experimental validation conducted using field service data from heavy-haul trains demonstrates that, compared to conventional serial CNN and Long Short-Term Memory (LSTM) models, the proposed method exhibits superior fitting performance and robustness against noise, effectively reducing the false alarm rate within normal working intervals. In a real-world case study, the method successfully identified variations in spatial linkage features induced by local damage and triggered timely alerts. Notably, the spatial alarm nodes were highly consistent with the fatigue crack initiation sites identified through on-site magnetic particle inspection. This study provides a viable data-driven analytical framework for the condition monitoring and anomaly identification of critical load-bearing components in heavy-haul trains. Full article

(This article belongs to the Special Issue Deep Learning Based Intelligent Fault Diagnosis)

22 pages, 11126 KB

Open AccessArticle

Cell Type-Specific Downregulation of Dnmt3a in Nucleus Accumbens Oligodendrocytes Prevents Myelin Damage and Reduces Susceptibility to Social Stress in Male Mice

by Yifan Niu, Kaiwei Li, Kaiyuan Zhan, Mingshan Pi, Qi Xiong, Ji Wang, Xiaochuan Wang, Xiji Shu, Yiyuan Xia and Mengbing Huang

Biomolecules 2026, 16(5), 639; https://doi.org/10.3390/biom16050639 - 24 Apr 2026

Abstract

Background: Chronic stress is a major contributing factor to mood disorders, including depression and anxiety; however, the molecular mechanisms underlying individual differences in susceptibility to such disorders remain poorly understood. DNA methyltransferase 3a (Dnmt3a), a key epigenetic regulator, has been increasingly implicated in [...] Read more.

Background: Chronic stress is a major contributing factor to mood disorders, including depression and anxiety; however, the molecular mechanisms underlying individual differences in susceptibility to such disorders remain poorly understood. DNA methyltransferase 3a (Dnmt3a), a key epigenetic regulator, has been increasingly implicated in stress-related neurobiological adaptations. In this study, we employed a well-established mouse model of chronic social defeat stress (CSDS) to investigate the functional role of Dnmt3a in modulating individual susceptibility to social stress. Methods: Male C57BL/6J mice were exposed to chronic/submaximal social defeat stress (CSDS/SSDS). AAV vectors were used to achieve Dnmt3a overexpression or global and oligodendrocyte-specific knockdown in the nucleus accumbens (NAc). Behavioral tests, including social interaction, open field, and elevated zero maze, were conducted alongside Western blotting and immunofluorescence assays. Results: CSDS selectively increased Dnmt3a expression in NAc oligodendrocytes of stress-susceptible mice. Overexpression of Dnmt3a in the NAc enhanced susceptibility to stress, whereas its knockdown conferred resilience, without affecting baseline behaviors. Dnmt3a negatively regulated myelin basic protein (MBP) and dopamine D1 receptor expression. Stress-susceptible mice exhibited shortened myelinated segments and reduced D1 receptor levels, while D2 receptor expression remained unchanged. Conclusions: Dnmt3a in NAc oligodendrocytes modulates susceptibility to social stress through a Dnmt3a-MBP/D1 receptor-NAc pathway, highlighting a critical glia-neuron interaction. This mechanism extends our understanding of the neurobiological basis of stress-related disorders and positions Dnmt3a as a promising therapeutic target for developing precision interventions or biomarkers. Full article

(This article belongs to the Section Molecular Medicine)

29 pages, 2724 KB

Open AccessArticle

Volumetric Control vs. Pneumatic Pressure: A Comparative Analysis of Extrusion in 3D Bioprinting

by Doru-Daniel Cristea, Eduard Liciu, Andreea Trifan and Corneliu Bălan

Micromachines 2026, 17(5), 521; https://doi.org/10.3390/mi17050521 (registering DOI) - 24 Apr 2026

Abstract

Extrusion-based bioprinting faces significant challenges in achieving the shape fidelity and internal porosity necessary for cell viability, often hindered by subjective assessment methods. This study investigated the relationship between rheological properties and print quality using a natural polymer biomaterial ink composed of 12% [...] Read more.

Extrusion-based bioprinting faces significant challenges in achieving the shape fidelity and internal porosity necessary for cell viability, often hindered by subjective assessment methods. This study investigated the relationship between rheological properties and print quality using a natural polymer biomaterial ink composed of 12% gelatin, 5% alginate, and 1% carboxymethylcellulose. We conducted a comparative analysis between traditional pneumatic systems and screw-driven volumetric extrusion, utilizing a suite of quantitative metrics: Spreading Ratio (SR), Printability Index (P_r), Uniformity Ratio (UF), Collapse Angle (θ), and evaluated porosity. Our results demonstrate that the screw-driven system’s positive displacement mechanism provides superior control over filament morphology by enabling precise volumetric modulation. While the pneumatic system exhibited a high SR of 1.82 and the lowest porosity at 59.92%, the screw-driven system allowed for “under-extrusion” to compensate for viscoelastic die swell. Reducing the flow rate to 50% in the screw system lowered the SR to 1.09, nearly matching the nozzle diameter, and increased porosity to 76.46%. Furthermore, the screw-driven system achieved an ideal P_r of 1.0, whereas the pneumatic system produced distorted, rounded pores with a P_r of 1.57. The findings indicate that screw-driven extruders can decouple line complex rheology from the printing process, allowing for finer spatial resolution and better pore interconnectivity. Full article

(This article belongs to the Special Issue Advanced Micro-Manufacturing and BioMEMS: Bridging the Gap from Laboratory Innovation to Industrial Production)

31 pages, 2303 KB

Open AccessArticle

MDCAD-Net: A Multi-Dilated Convolution Attention Denoising Network for Bearing Fault Diagnosis

by Ran Duan, Ruopeng Yan and Guangyin Jin

Vibration 2026, 9(2), 30; https://doi.org/10.3390/vibration9020030 (registering DOI) - 24 Apr 2026

Abstract

Bearing fault diagnosis is an important task for condition monitoring and predictive maintenance of rotating machinery. Nevertheless, many existing deep learning-based methods have difficulty in jointly modeling multi-scale fault characteristics, adaptively highlighting informative features, and maintaining robustness under noisy measurement conditions. To address [...] Read more.

Bearing fault diagnosis is an important task for condition monitoring and predictive maintenance of rotating machinery. Nevertheless, many existing deep learning-based methods have difficulty in jointly modeling multi-scale fault characteristics, adaptively highlighting informative features, and maintaining robustness under noisy measurement conditions. To address these issues, this study presents MDCAD-Net, a multi-dilated convolution attention denoising network that integrates multi-scale temporal feature extraction, attention-based feature refinement, and explicit noise suppression within an end-to-end learning framework. Parallel dilated convolutions with different dilation rates are employed to capture short-duration transient impulses as well as long-range periodic patterns in vibration signals. Channel-wise feature recalibration using squeeze-and-excitation networks and spatial-temporal attention via a convolutional block attention module are combined to enhance informative representations. In addition, a denoising block with gated attention and residual connections is introduced to reduce noise interference while retaining fault-related signal components. Experiments conducted on the Case Western Reserve University bearing dataset show that the proposed method achieves a classification accuracy of 98.93% and yields competitive performance compared with several commonly used deep learning models. Ablation studies and feature visualization results further illustrate the contributions of the individual components and the separability of the learned feature representations under noisy conditions. The results indicate the potential of the proposed framework for practical bearing fault diagnosis under noisy operating conditions. Full article

30 pages, 7225 KB

Open AccessArticle

Causal Learning for Continuous Variables with an Improved Bayesian Network Constructed by Symmetric Kernel Function Acceleration

by Chenghao Wei, Pukai Wang, Chen Li and Zhiwei Ye

Symmetry 2026, 18(5), 731; https://doi.org/10.3390/sym18050731 - 24 Apr 2026

Abstract

Bayesian network-based causal structure learning provides an effective framework for uncovering causal relationships among continuous variables. However, many existing methods for continuous data still rely on strong parametric distribution assumptions, which may introduce information loss and reduce Bayesian network modeling accuracy. Kernel density [...] Read more.

Bayesian network-based causal structure learning provides an effective framework for uncovering causal relationships among continuous variables. However, many existing methods for continuous data still rely on strong parametric distribution assumptions, which may introduce information loss and reduce Bayesian network modeling accuracy. Kernel density estimation (KDE), a non-parametric statistical method that is more flexible in density estimation form, offers a versatile framework for conducting conditional independence (CI) tests. This approach enables the estimation of mutual information and conditional mutual information, thereby facilitating the identification of underlying structural relationships. Nevertheless, the high computational cost of KDE-based CI testing restricts its practical application in continuous-variable causal learning. To address this issue, this study introduces a radial symmetric kernel-based acceleration scheme within a Fast Fourier Transform (FFT) framework to improve the efficiency of density estimation. On this basis, an enhanced Bayesian network structure learning method is developed for continuous variables, enabling more efficient estimation of mutual information and conditional mutual information while improving the computational efficiency and empirical stability of variable dependency discovery. With proper bandwidth and grid resolution, the proposed MMHC-FFTKDE framework achieves a reduction in computational runtime and improves efficiency compared to MMHC-KDE in the ablation setting, while maintaining competitive F1-scores and SHD for causal structure discovery. Full article

(This article belongs to the Special Issue Application of Symmetry/Asymmetry and Machine Learning)

23 pages, 7805 KB

Open AccessArticle

Mie-Scattering-Based Simulation of Underwater Multispectral LiDAR Propagation and Optimal Wavelength Selection

by Zhichao Chen, Zhaoyan Liu, Shi Qiu, Huijing Zhang, Yuwei Chen, Weiyuan Yao, Tong Zhang, Yu Zhang, Hongjia Cheng, Feihong Wang and Zhan Shu

Photonics 2026, 13(5), 423; https://doi.org/10.3390/photonics13050423 (registering DOI) - 24 Apr 2026

Abstract

Multispectral LiDAR can simultaneously obtain distance and spectral information and shows great potential for underwater detection. However, absorption and scattering caused by suspended particles in water lead to energy attenuation and multiple scattering, which affect echo intensity and ranging accuracy, while the propagation [...] Read more.

Multispectral LiDAR can simultaneously obtain distance and spectral information and shows great potential for underwater detection. However, absorption and scattering caused by suspended particles in water lead to energy attenuation and multiple scattering, which affect echo intensity and ranging accuracy, while the propagation characteristics under multi-wavelength conditions remain insufficiently studied. In this study, a simplified underwater propagation simulation model for multispectral LiDAR is established based on the equivalent spherical-particle assumption, combining Mie scattering theory with a semi-analytical Monte Carlo method. The effects of particle size on echo intensity and ranging error are analyzed under fixed concentration conditions. Based on this model, a detection-threshold-constrained optimal wavelength selection criterion is formulated. Multi-distance analysis (3, 5, 8, and 15 m) confirms that the preferred wavelength is primarily governed by particle size and remains stable across depths. The results show that the optimal detection wavelength shifts with particle size, being about 560 nm for fine particles and gradually moving toward the 400–480 nm blue–green band for larger particles. Experimental validation shows that the simulation-based ranging correction reduces RMSE by 9.4–25.9% (average 18.1%) and MAE by 11.8–29.7% (average 22.0%) across five experimental distances. The results provide a preliminary reference for wavelength selection in multispectral LiDAR systems under simplified conditions. Full article

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