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25 pages, 2296 KB

Open AccessArticle

A Novel Softsign Fractional-Order Controller Optimized by an Intelligent Nature-Inspired Algorithm for Magnetic Levitation Control

by Davut Izci, Serdar Ekinci, Mohd Zaidi Mohd Tumari and Mohd Ashraf Ahmad

Fractal Fract. 2025, 9(12), 801; https://doi.org/10.3390/fractalfract9120801 (registering DOI) - 7 Dec 2025

Abstract

This study presents a novel softsign-function-based fractional-order proportional–integral–derivative (softsign-FOPID) controller optimized using the fungal growth optimizer (FGO) for the stabilization and precise position control of an unstable magnetic ball suspension system. The proposed controller introduces a smooth nonlinear softsign function into the conventional [...] Read more.

This study presents a novel softsign-function-based fractional-order proportional–integral–derivative (softsign-FOPID) controller optimized using the fungal growth optimizer (FGO) for the stabilization and precise position control of an unstable magnetic ball suspension system. The proposed controller introduces a smooth nonlinear softsign function into the conventional FOPID structure to limit abrupt control actions and improve transient smoothness while preserving the flexibility of fractional dynamics. The FGO, a recently developed bio-inspired metaheuristic, is employed to tune the seven controller parameters by minimizing a composite objective function that simultaneously penalizes overshoot and tracking error. This optimization ensures balanced transient and steady-state performance with enhanced convergence reliability. The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. Statistical analyses, including boxplot comparisons and the nonparametric Wilcoxon rank-sum test, demonstrated that the FGO consistently achieved the lowest objective function value with superior convergence stability and significantly better (p < 0.05) performance across multiple independent runs. In time-domain evaluations, the FGO-tuned softsign-FOPID exhibited the fastest rise time (0.0089 s), shortest settling time (0.0163 s), lowest overshoot (4.13%), and negligible steady-state error (0.0015%), surpassing the best-reported controllers in the literature, including the sine cosine algorithm-tuned PID, logarithmic spiral opposition-based learning augmented hunger games search algorithm-tuned FOPID, and manta ray foraging optimization-tuned real PIDD². Robustness assessments under fluctuating reference trajectories, actuator saturation, sensor noise, external disturbances, and parametric uncertainties (±10% variation in resistance and inductance) further confirmed the controller’s adaptability and stability under practical non-idealities. The smooth nonlinearity of the softsign function effectively prevented control signal saturation, while the fractional-order dynamics enhanced disturbance rejection and memory-based adaptability. Overall, the proposed FGO-optimized softsign-FOPID controller establishes a new benchmark in nonlinear magnetic levitation control by integrating smooth nonlinear mapping, fractional calculus, and adaptive metaheuristic optimization. Full article

(This article belongs to the Section Engineering)

14 pages, 738 KB

Open AccessArticle

Diroximel Fumarate-Loaded Solid Lipid Nanoparticles (DRF-SLNs) as Potential Carriers for the Treatment of Multiple Sclerosis: Preformulation Study

by Debora Santonocito, Giuliana Greco, Maria Grazia Sarpietro, Aurélie Schoubben, Claudia Sciacca, Giuseppe Romeo, Katia Mangano and Carmelo Puglia

Int. J. Mol. Sci. 2025, 26(24), 11827; https://doi.org/10.3390/ijms262411827 (registering DOI) - 7 Dec 2025

Abstract

Diroximel fumarate (DRF) is an orally administered prodrug used in multiple sclerosis (MS) treatment. Although it exhibits better gastrointestinal (GI) tolerability than its analogues, many patients still discontinue therapy due to frequent GI adverse events. To overcome these limitations, alternative drug delivery systems [...] Read more.

Diroximel fumarate (DRF) is an orally administered prodrug used in multiple sclerosis (MS) treatment. Although it exhibits better gastrointestinal (GI) tolerability than its analogues, many patients still discontinue therapy due to frequent GI adverse events. To overcome these limitations, alternative drug delivery systems that bypass the GI tract are needed. Direct nose-to-brain delivery represents a promising approach to circumvent the blood–brain barrier and target the central nervous system; however, limited nasal mucosal absorption and the small volume of the nasal cavity pose significant challenges. Solid lipid nanoparticles (SLNs) can potentially overcome these obstacles by enhancing drug bioavailability and protecting against enzymatic degradation. This research aimed to develop an innovative intranasal nanoformulation of DRF to improve brain targeting and patient compliance. DRF-loaded SLNs were prepared using a solvent-diffusion technique with stearic acid as the lipid phase and Poloxamer 188 as the surfactant. The obtained nanoparticles displayed favorable technological characteristics, with a mean diameter of 210 nm, a polydispersity index of 0.17, and a zeta potential of −36 mV, suggesting good long-term stability. Interactions between SLNs and biomembrane models (MLV) were also studied to elucidate their cellular uptake mechanism. Future work will focus on evaluating the in vivo efficacy of this novel nanoformulation. Full article

(This article belongs to the Special Issue Multiple Sclerosis: From Molecular Pathology to Novel Therapeutic Approaches)

29 pages, 11796 KB

Open AccessArticle

Vitamin B12-Loaded Chitosan Nanoparticles Promote Skeletal Muscle Injury Repair in Aged Rats via Amelioration of Aging-Suppressed Efferocytosis

by Walaa Bayoumie El Gazzar, Amina A. Farag, Heba Bayoumi, Shaimaa E. Radwaan, Lina Abdelhady Mohammed, Hend Elsayed Nasr, Nashwa E. Ahmed, Reham M. Ibrahim, Mahmoud Mostafa, Shimaa K. Mohamed, Dania Abdelhady, Eman E. Elwakeel, Amira M. Badr and Sahar Soliman

Biomolecules 2025, 15(12), 1709; https://doi.org/10.3390/biom15121709 (registering DOI) - 7 Dec 2025

Abstract

Muscle gradually loses its regenerative capacity with aging. Recent evidence highlights age-related immune dysregulation as a key driver of satellite cell dysfunction and reduced muscle regeneration. Timely elimination of apoptotic cells by phagocytes through efferocytosis is essential for tissue repair. Therefore, exploring age-related [...] Read more.

Muscle gradually loses its regenerative capacity with aging. Recent evidence highlights age-related immune dysregulation as a key driver of satellite cell dysfunction and reduced muscle regeneration. Timely elimination of apoptotic cells by phagocytes through efferocytosis is essential for tissue repair. Therefore, exploring age-related alterations in the molecular machinery of efferocytosis and their impact on muscle regeneration is of great relevance. This study examined the efferocytic machinery in the gastrocnemius muscle tissue of young and aged rats after doxorubicin-induced acute myotoxicity and assessed the potential of Vitamin B12-loaded chitosan nanoparticles (B12 CS NPS) to enhance efferocytosis and promote skeletal muscle injury repair in aged rats. Aged rats exhibited impaired efferocytosis with a significant reduction in MerTK, PPARγ, and miR-124 expression, and increased ADAM17 expression. B12 CS NPS administration significantly improved efferocytosis and reduced necrotic tissue areas, accompanied by increased MerTK, PPARγ, and miR-124, and reduced ADAM17 expression. Supplementation with B12 CS NPS significantly enhanced satellite cell proliferation and differentiation, which was indicated by upregulated expression of Pax7, Myog, and MyoD. These findings reveal that age-related alterations in regulatory molecules impair efferocytosis in aged muscle and demonstrate the potential of B12 CS NPs to enhance efferocytosis and improve skeletal muscle repair. Full article

(This article belongs to the Section Molecular Medicine)

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13 pages, 720 KB

Open AccessArticle

An Improved Dengue Virus Serotype-Specific Non-Structural Protein 1 Capture Immunochromatography Method with Reduced Sample Volume

by Warisara Sretapunya, Thitiya Buranachat, Montita Prasomthong, Rittichai Tantikorn, Areerat Sa-ngarsang, Sirirat Naemkhunthot, Laddawan Meephaendee, Pattara Wongjaroen, Chika Tanaka, Yoriko Shimadzu, Katsuya Ogata, Kunihiro Kaihatsu, Ryo Morita, Michinori Shirano, Juthamas Phadungsombat, Tadahiro Sasaki, Ritsuko Kubota-Koketsu, Yoshihiro Samune, Emi E. Nakayama and Tatsuo Shioda

Biosensors 2025, 15(12), 802; https://doi.org/10.3390/bios15120802 (registering DOI) - 7 Dec 2025

Abstract

The four serotypes of dengue virus (DENV), types 1 to 4 (DENV-1 to DENV-4), exhibit approximately 60% identity in the encoded amino acid residues of viral proteins. Reverse transcription of RNA extracted from patient serum specimens followed by PCR amplification with serotype-specific probes [...] Read more.

The four serotypes of dengue virus (DENV), types 1 to 4 (DENV-1 to DENV-4), exhibit approximately 60% identity in the encoded amino acid residues of viral proteins. Reverse transcription of RNA extracted from patient serum specimens followed by PCR amplification with serotype-specific probes is the current standard technique for DENV serotyping. However, this method is time- and cost-consuming, and rapid detection systems with low cost are desirable. Previously, we developed a prototype serotype-specific immunochromatography system. That system was composed of four strips with four corresponding distinct sample buffers, each specifically detecting a single DENV serotype. In the present study, we improved this system by combining pairs of strips into one lateral-flow cassette each, providing DENV-1 and DENV-2 detection in one device and DENV-3 and DENV-4 detection in a second device; this strategy successfully reduced the required sample volume. Furthermore, we were able to adjust the composition of the sample buffers such that a single sample buffer sufficed for all four DENV serotype detection reactions, allowing much easier handling of the devices. Evaluation of this new device against laboratory and clinical DENV isolates and clinical specimens from DENV-infected individuals showed sensitivity that was comparable to that of our previous version, yielding serotype specificity of 100%. These new devices are expected to be of use in the clinical setting, accelerating both prospective and retrospective epidemiological studies. Full article

(This article belongs to the Special Issue Biosensors for Healthcare and Environment: Current and Future Perspectives)

33 pages, 1134 KB

Open AccessReview

Antioxidant, Antimicrobial, and Anticancer Activity of Basil (Ocimum basilicum)

by Efthymios Poulios, Sousana K. Papadopoulou, Evmorfia Psara and Constantinos Giaginis

Antioxidants 2025, 14(12), 1469; https://doi.org/10.3390/antiox14121469 (registering DOI) - 7 Dec 2025

Abstract

Background/Objectives: For many years, herbs and spices have been used, due to their aroma and flavor, in the food industry and cuisine. It is also well known that phytochemicals from these plant parts have many health benefits and are used for the prevention [...] Read more.

Background/Objectives: For many years, herbs and spices have been used, due to their aroma and flavor, in the food industry and cuisine. It is also well known that phytochemicals from these plant parts have many health benefits and are used for the prevention and treatment of many human diseases. Basil (with the most representative species Ocimum basilicum) is a perennial herb with a characteristic aroma, containing many bioactive components such as phenolic acids, flavonoids, tannins, saponins, alkaloids, polysaccharides, vitamins, proteins, amino acids, and essential oils, with beneficial effects on human health. The aim of this study is to review the antioxidant, antimicrobial, and anticancer activity of basil, according to recent literature. Methods: A thorough search in the international databases (Scopus, PubMed, Google Scholar, and Web of Sciences) was conducted from January 2015 to October 2025, using characteristic keywords in combinations. Results: Bioactive components of basil show a significant antioxidant activity, as detected by radical scavenging activity (measured by the 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid (ABTS), ferric reducing antioxidant power (FRAP), oxygen radical absorbance capacity (ORAC) assays), activation of antioxidant enzymes (glutathione peroxidase (GPX), superoxide dismutase (SOD), catalase (CAT)), enhancement of reduced glutathione (GSH) and reduction in malondialdehyde (MDA) and thiobarbituric acid-reactive substance (TBARS) levels, and protection of cells from hydrogen peroxide (H₂O₂)-toxicity. Additionally, inhibition of growth and cell death of many Gram-positive and Gram-negative bacteria strains, maintained by cell membrane damage, inhibition of efflux pumps, as well as inhibition of biofilm formation, anti-protozoan, antifungal, and antiviral activities, have been noticed for basil bioactive components. A synergism with antibiotics has also been reported. Finally, anticancer activity has been reported, according to apoptosis induction, cell cycle arrest, anxiety reduction, and health improvement of cancer patients. Conclusions: Basil bioactive components have been reported for their high antioxidant, antimicrobial, and anticancer properties. However, future studies, especially at the clinical level, are strongly proposed in order to unravel the significant role of basil in human health and the safety of its bioactive components in healthcare usage. Full article

(This article belongs to the Section Natural and Synthetic Antioxidants)

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48 pages, 24714 KB

Open AccessArticle

A Novel Hybrid Model Using Demand Concentration Curves, Chaotic AFDB-SFS Algorithm and Bi-LSTM Networks for Heating Oil Price Prediction

by Seçkin Karasu

Electronics 2025, 14(24), 4814; https://doi.org/10.3390/electronics14244814 (registering DOI) - 7 Dec 2025

Abstract

Nowadays, renewable energy sources are gaining importance, yet global energy demand is primarily met by burning fossil fuels. Fluctuations in fossil fuel availability, driven by geopolitical tensions, supply–demand changes, and natural disasters, can lead to sudden energy price spikes or supply shortages, adversely [...] Read more.

Nowadays, renewable energy sources are gaining importance, yet global energy demand is primarily met by burning fossil fuels. Fluctuations in fossil fuel availability, driven by geopolitical tensions, supply–demand changes, and natural disasters, can lead to sudden energy price spikes or supply shortages, adversely affecting the global economy. Despite its negative impact on carbon emissions and climate change, Heating Oil (HO) offers advantages over other fossil fuels in efficiency, reliability, and availability. Accurate time series prediction models for HO are crucial for stakeholders. This study proposes a novel hybrid model, integrating the Chaotic Adaptive Fitness-Distance Balance-based Stochastic Fractal Search (AFDB-SFS) algorithm with a Bidirectional Long-Short Term Memory (Bi-LSTM) network, for HO close price prediction. The dataset comprises daily observations of five financial time series (close, open, high, low, and volume) over 4260 trading days, yielding a total of 21,300 data points (4260 days × 5 variables). During the feature extraction stage, financial signal processing methods such as Demand Concentration Curve (DCC) and traditional technical indicators are utilized. A total of 189 features are extracted at appropriate intervals for each indicator. Due to the large number of features, the AFDB-SFS algorithm then efficiently identifies the most compatible feature subsets, optimizing the Bi-LSTM model based on three criteria: maximizing R², minimizing RMSE, and minimizing feature count. Experimental results demonstrate the proposed hybrid model’s superior performance, achieving high accuracy (R² of 0.9959 and RMSE of 0.0364), outperforming contemporary models in the literature. Furthermore, the model is successfully implemented on the Jetson Orin Nano Developer Platform, enabling real-time, high-frequency HO price predictions with ultra-low latency (1.01 ms for Bi-LSTM), showcasing its practical utility for edge computing applications in commodity markets. Full article

(This article belongs to the Section Computer Science & Engineering)

20 pages, 620 KB

Open AccessArticle

The Cost of Victory over Cancer: Psychosocial Dysfunction and Depressive Symptoms Among Polish Adolescent Cancer Survivors in the Context of Quality of Life and Psychosocial Health

by Piotr Pawłowski, Karolina Joanna Ziętara, Joanna Milanowska, Anna Aftyka, Mateusz Sobierajski, Zuzanna Kania and Marzena Samardakiewicz

Cancers 2025, 17(24), 3916; https://doi.org/10.3390/cancers17243916 (registering DOI) - 7 Dec 2025

Abstract

Background: Adolescent cancer survivors constitute a clinically vulnerable population whose psychosocial adjustment following oncological treatment remains insufficiently characterized, particularly within Central and Eastern Europe. The present study aimed to evaluate health-related quality of life (HRQoL) and depressive symptomatology among Polish adolescent survivors, identify [...] Read more.

Background: Adolescent cancer survivors constitute a clinically vulnerable population whose psychosocial adjustment following oncological treatment remains insufficiently characterized, particularly within Central and Eastern Europe. The present study aimed to evaluate health-related quality of life (HRQoL) and depressive symptomatology among Polish adolescent survivors, identify their psychological predictors, and determine age-related differences in these associations. Methods: A cross-sectional study was conducted among 165 survivors aged 11–18 years, recruited from four pediatric oncology centers. Participants completed the KIDSCREEN-10 (HRQoL) and the Children’s Depression Inventory-2™ (CDI-2™). Descriptive statistics, Spearman rank-order correlations, and multiple regression analyses were performed separately for younger (primary school) and older (secondary school) cohorts. Results: The findings demonstrated a pronounced polarization of HRQoL, with approximately one-third of participants (32.7%) scoring within the clinically low range. Depressive symptoms were prevalent, particularly in the domains of Negative Mood (M = 19.93) and Ineffectiveness (M = 15.45), while Negative Self-Esteem levels were comparatively low (M = 8.02). HRQoL correlated strongly and inversely with Interpersonal Problems (rs = −0.89, p < 0.001). Regression analyses indicated that Negative Self-Esteem (CDI-2D) was the strongest negative predictor of HRQoL in both age groups, whereas Ineffectiveness (CDI-2C) and Negative Mood (CDI-2A) emerged as significant positive predictors. Interpersonal Problems (CDI-2B) were predictive only in older adolescents, suggesting a developmental shift in determinants of well-being. Conclusions: Adolescent cancer survivors exhibit a distinctive psychological pattern characterized by pronounced emotional distress without pervasive self-devaluation. HRQoL appears highly polarized and primarily determined by self-esteem and interpersonal functioning. These findings underscore the necessity of developmentally tailored psychosocial interventions addressing self-worth, peer reintegration, and socio-economic stressors in survivorship care. Full article

(This article belongs to the Section Cancer Survivorship and Quality of Life)

16 pages, 5118 KB

Open AccessArticle

Deep Learning-Supported Panoramic Infrared Framework for Quantitative Diagnosis of Building Envelope Thermal Anomalies

by Bo-Kyoung Koo, Hye-Sun Jin and Jin-Woo Jeong

Buildings 2025, 15(24), 4423; https://doi.org/10.3390/buildings15244423 (registering DOI) - 7 Dec 2025

Abstract

This study presents a modular diagnostic framework for evaluating thermal degradation in aging building envelopes by integrating infrared thermography, panoramic reconstruction, and deep learning-based semantic segmentation into a unified workflow. The methodology combines image registration, panoramic synthesis, façade component segmentation, and quantitative surface [...] Read more.

This study presents a modular diagnostic framework for evaluating thermal degradation in aging building envelopes by integrating infrared thermography, panoramic reconstruction, and deep learning-based semantic segmentation into a unified workflow. The methodology combines image registration, panoramic synthesis, façade component segmentation, and quantitative surface temperature analysis to provide scalable and reproducible diagnostics. By excluding fenestration zones—where infrared measurements are physically unreliable—the framework focuses on opaque wall regions and window surroundings to ensure physically meaningful evaluation. Field validation was conducted on a multi-story office building constructed in 1996. The diagnostic indicators revealed a mean wall surface temperature of 14.3 °C with a standard deviation of 5.6 °C, and a temperature factor ranging from 0.67 to 0.78 under measured conditions. The vulnerable area ratio reached 9.1% for walls, while window areas showed greater vulnerability at 12.74%, with anomalies concentrated at frame–glass interfaces and perimeter seals. These quantitative results confirmed the framework’s ability to detect thermal irregularities and visualize localized anomalies. More importantly, the contribution of this study lies in establishing a systematic and extensible diagnostic pipeline that advances building envelope analysis, supporting large-scale energy audits, retrofit prioritization, and sustainable building management. Full article

(This article belongs to the Special Issue Research on the Thermal, Environmental, and Economic Performance of Building Envelopes: Advancing Sustainable Solutions)

24 pages, 2738 KB

Open AccessArticle

Frequency-Controlled AC-MAO Coatings with Ca, P, and Se on Magnesium: Toward Tailored Surfaces for Biodegradable Implants

by Balbina Makurat-Kasprolewicz and Endzhe Matykina

Materials 2025, 18(24), 5505; https://doi.org/10.3390/ma18245505 (registering DOI) - 7 Dec 2025

Abstract

The present study investigates the influence of alternating current (AC) frequency on the formation and properties of calcium-, phosphorus-, and selenium-containing micro-arc oxidation (MAO) coatings on high-purity magnesium. Coatings were produced at 50–400 Hz in a phytic-acid-based electrolyte containing Ca, P, and Se [...] Read more.

The present study investigates the influence of alternating current (AC) frequency on the formation and properties of calcium-, phosphorus-, and selenium-containing micro-arc oxidation (MAO) coatings on high-purity magnesium. Coatings were produced at 50–400 Hz in a phytic-acid-based electrolyte containing Ca, P, and Se precursors, and their structure, chemistry, and functional performance were systematically evaluated. Surface morphology, analyzed by SEM and optical profilometry, revealed frequency-dependent features: lower frequencies (50 Hz) promoted thicker, rougher coatings with extensive cracking, whereas intermediate frequencies (100–200 Hz) yielded more uniform, porous surfaces. The CaPSe_100 specimen exhibited the most homogeneous topography (lowest S10z and SD) combined with the highest porosity (28.4%), strong hydrophilicity, and the greatest selenium incorporation (1.30 wt.%). Hydrogen evolution testing in Hanks’ solution demonstrated a drastic improvement in corrosion resistance following MAO treatment: the degradation rate of bare Mg (5.50 mm/year) was reduced to 0.012 mm/year for the CaPSe_100 coating—well below the clinical tolerance threshold for biodegradable implants. This outstanding performance is attributed to the synergistic effect of a uniform oxide barrier, optimized porosity, and homogeneous surface morphology. The results highlight the potential of frequency-controlled AC-MAO processing as a route to tailor magnesium surfaces for multifunctional, corrosion-resistant biomedical applications. Full article

(This article belongs to the Section Biomaterials)

20 pages, 882 KB

Open AccessArticle

Bifurcation Analysis in a Cross-Protection Model

by Yufei Wu, Zikun Han, Weixiang Wang, Yingting Yang and Qiubao Wang

Axioms 2025, 14(12), 903; https://doi.org/10.3390/axioms14120903 (registering DOI) - 7 Dec 2025

Abstract

We analyze the population dynamics of a microbial cross-protection model and derive the exact conditions under which a Fold–Hopf bifurcation emerges. By applying center-manifold reduction and normal-form theory, we reduce the infinite-dimensional delay differential system to a finite-dimensional ordinary differential system, enabling rigorous [...] Read more.

We analyze the population dynamics of a microbial cross-protection model and derive the exact conditions under which a Fold–Hopf bifurcation emerges. By applying center-manifold reduction and normal-form theory, we reduce the infinite-dimensional delay differential system to a finite-dimensional ordinary differential system, enabling rigorous bifurcation analysis. Numerical simulations reveal a rich repertoire of dynamical behaviors, including stable equilibria, sustained oscillations, and noise-induced irregularities. Our findings identify time-delay-induced Fold–Hopf bifurcation as a fundamental mechanism driving oscillatory coexistence in cross-protection mutualisms, for previously reported experimental observations. Full article

12 pages, 559 KB

Open AccessArticle

Sarcomatoid and Aggressive Variants in High R.E.N.A.L. Score T1b RCC: Outcomes After Laparoscopic and Robotic Radical Nephrectomy

by Murad Asali, Galeb Asali, Ron Batash and Moshe Schaffer

Cancers 2025, 17(24), 3918; https://doi.org/10.3390/cancers17243918 (registering DOI) - 7 Dec 2025

Abstract

Objectives: To assess the outcomes of laparoscopic radical nephrectomy (LRN) in patients with moderate-to-high R.E.N.A.L. score T1b renal cell carcinoma (RCC), with particular attention to the incidence and prognostic implications of sarcomatoid and other aggressive pathological variants. The management of T1b RCC with [...] Read more.

Objectives: To assess the outcomes of laparoscopic radical nephrectomy (LRN) in patients with moderate-to-high R.E.N.A.L. score T1b renal cell carcinoma (RCC), with particular attention to the incidence and prognostic implications of sarcomatoid and other aggressive pathological variants. The management of T1b RCC with moderate-to-high R.E.N.A.L. nephrometry scores presents unique challenges in surgical decision-making. Although partial nephrectomy has shown benefits in renal function preservation, the optimal approach for complex tumors remains debatable. Methods: A retrospective analysis was performed on patients who underwent LRN for T1b RCC with moderate-to-high R.E.N.A.L. scores (≥8) between 2008 and 2024. Primary outcomes included perioperative complications, renal function preservation, and pathological findings. All patients return for follow-up one month after surgery with laboratory tests. An upper abdominal and urinary tract ultrasound is performed at three months, and an additional CT or ultrasound examination is recommended during the first postoperative year, then every six months for the first three years, and annually thereafter. Creatinine levels were monitored preoperatively and at multiple time points postoperatively up to 30 months. Results: A total of 118 patients (62 male; 56 female) with a mean age of 66.9 years underwent LRN. The average R.E.N.A.L. score was 10.02, with a mean tumor diameter of 6.0 cm by CT and 4.7 cm by pathology. Mean operative time was 151.6 min, with average blood loss of 75.2 mL. A total of nine complications were reported (7.6%). Pathological analysis revealed aggressive features in 29.7% of cases, including high-grade tumors (G3), multiple tumors, and rare aggressive variants. Conclusions: LRN appears to be a safe and effective treatment option for T1b RCC with moderate-to-high R.E.N.A.L. scores, providing adequate oncological control while maintaining acceptable renal function. The high incidence of aggressive pathological features (29.7%) supports the role of radical nephrectomy in this patient population. Full article

(This article belongs to the Section Tumor Microenvironment)

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29 pages, 1782 KB

Open AccessArticle

Planar Dirac Equation with Radial Contact Potentials

by José Tadeu Lunardi, Sergio Salamanca, Javier Negro and Luis Miguel Nieto

Mathematics 2025, 13(24), 3916; https://doi.org/10.3390/math13243916 (registering DOI) - 7 Dec 2025

Abstract

We investigate the planar Dirac equation with the most general time-independent contact (singular) potential supported on a circumference. Taking advantage of the radial symmetry, the problem is effectively reduced to a one-dimensional one (the radial), and the contact potential is addressed in a [...] Read more.

We investigate the planar Dirac equation with the most general time-independent contact (singular) potential supported on a circumference. Taking advantage of the radial symmetry, the problem is effectively reduced to a one-dimensional one (the radial), and the contact potential is addressed in a mathematically rigorous way using a distributional approach that was originally developed to treat point interactions in one dimension, providing a physical interpretation for the interaction parameters. The most general contact interaction for this system is obtained in terms of four physical parameters: the strengths of a scalar and the three components of a singular Lorentz vector potential supported on the circumference. We then investigate the bound and scattering solutions for several choices of the physical parameters, and analyze the confinement properties of the corresponding potentials. Full article

(This article belongs to the Section E4: Mathematical Physics)

16 pages, 490 KB

Open AccessArticle

Profiles of Classroom Management Across Five Countries: A Person-Centered Analysis of TALIS 2018 Data

by Célia Oliveira and João Lopes

Educ. Sci. 2025, 15(12), 1653; https://doi.org/10.3390/educsci15121653 (registering DOI) - 7 Dec 2025

Abstract

Classroom management is a crucial aspect of effective teaching. However, little is known about how teachers’ approaches vary across countries. This study identified classroom management profiles using data from the OECD’s Teaching and Learning International Survey in five countries: Brazil, Canada (Alberta), Japan, [...] Read more.

Classroom management is a crucial aspect of effective teaching. However, little is known about how teachers’ approaches vary across countries. This study identified classroom management profiles using data from the OECD’s Teaching and Learning International Survey in five countries: Brazil, Canada (Alberta), Japan, Portugal, and South Africa. We applied latent class analysis (LCA) to four behavioral indicators, testing structural invariance and exploring associations with teacher characteristics and cultural dimensions. Three profiles emerged: Rule-Enforcing, Rule-Balanced, and Rule-Avoidant, which were structurally invariant across countries but varied in prevalence. Rule-Enforcing teachers reported the highest classroom management self-efficacy, whereas Rule-Avoidant teachers reported the lowest, with differences also observed in instructional and engagement efficacy. Cross-national variation in profile prevalence aligned descriptively with Hofstede’s cultural values, suggesting that cultural context shapes how universal management dimensions are enacted. These findings support the notion that classroom management is a universal construct shaped by significant national and cultural specificities. Full article

25 pages, 2850 KB

Open AccessArticle

Parameter Uncertainty in Water–Salt Balance Modeling of Arid Irrigation Districts

by Ziyi Zan, Zhiming Ru, Changming Cao, Kun Wang, Guangyu Chen, Hangzheng Zhao, Xinli Hu, Lingming Su and Weifeng Yue

Agronomy 2025, 15(12), 2814; https://doi.org/10.3390/agronomy15122814 (registering DOI) - 7 Dec 2025

Abstract

Soil salinization poses a major threat to agricultural sustainability in arid regions worldwide, where it is intrinsically linked to irrigated agriculture. In these water-scarce environments, the equilibrium of the water and salt balance is easily disrupted, causing salts to accumulate in the root [...] Read more.

Soil salinization poses a major threat to agricultural sustainability in arid regions worldwide, where it is intrinsically linked to irrigated agriculture. In these water-scarce environments, the equilibrium of the water and salt balance is easily disrupted, causing salts to accumulate in the root zone and directly constraining crop growth, thereby creating an urgent need for precise water and salt management strategies. While precise water and salt transport models are essential for prediction and control, their accuracy is often compromised by parameter uncertainty. To address this, we developed a lumped water–salt balance model for the Hetao Irrigation District (HID) in China, integrating farmland and non-farmland areas and vertically structured into root zone, transition layer, and aquifer. A novel calibration approach, combining random sampling with Kernel Density Estimation (KDE), was introduced to identify optimal parameter ranges rather than single values, thereby enhancing model robustness. The model was calibrated and validated using data from the Yichang sub-district. Results showed that the water balance module performed satisfactorily in simulating groundwater depth (R² = 0.79 for calibration, 0.65 for validation). The salt balance module effectively replicated the general trends of soil salinity dynamics, albeit with lower R² values, which reflects the challenges of high spatial variability and data scarcity. This method innovatively addresses the common challenge of parameter uncertainty in the model, narrows the parameter value ranges, enhances model reliability, and incorporates sensitivity analysis (SA) to identify key parameters in the water–salt model. This study not only provides a practical tool for managing water and salt dynamics in HID but also offers a methodological reference for addressing parameter uncertainty in hydrological modeling of other data-scarce regions. Full article

(This article belongs to the Special Issue Water–Salt in Farmland: Dynamics, Regulation and Equilibrium)

22 pages, 1112 KB

Open AccessArticle

Electrolyte-Driven Oxidant Generation on Ti/IrO₂–SnO₂–Sb₂O₅ Electrodes for the Efficient Removal of Alachlor and Isoproturon from Water

by Nelson Bravo-Yumi, Isabel Oller, Ana Ruiz-Delgado, Martin O. A. Pacheco-Álvarez and Juan M. Peralta-Hernández

Water 2025, 17(24), 3472; https://doi.org/10.3390/w17243472 (registering DOI) - 7 Dec 2025

Abstract

In this study, anodic oxidation (AO) was evaluated using Ti/IrO₂–SnO₂–Sb₂O₅ electrodes in chloride, sulfate, and mixed electrolytes, along with electro-Fenton (EF) and photoelectro-Fenton (PEF) at pH 3.0, for the degradation of alachlor and isoproturon, each 50 [...] Read more.

In this study, anodic oxidation (AO) was evaluated using Ti/IrO₂–SnO₂–Sb₂O₅ electrodes in chloride, sulfate, and mixed electrolytes, along with electro-Fenton (EF) and photoelectro-Fenton (PEF) at pH 3.0, for the degradation of alachlor and isoproturon, each 50 mg L⁻¹. Active chlorine species were monitored using UV–Vis, while the removal of both herbicides was quantified using High Performance Liquid Chromatography (HPLC), along with the reduction in Total Organic Carbon (TOC), mineralization current efficiency (MCE), and specific energy per TOC removed (EC_TOC). The results show that electrolyte composition influences AO more than current density. In a chloride medium, isoproturon was eliminated within minutes, whereas alachlor required mixed electrolytes of Cl⁻/SO₄²⁻, allowing simultaneous combination of HClO/ClO⁻, ^●OH, and S₂O₈²⁻/SO₄^●−, or coupling with EF. An optimal current density of ~30 mA cm⁻² limited voltage rise and radical scavenging. EF introduced measurable mineralization (15% TOC), whereas PEF achieved rapid alachlor reduction and TOC reductions of up to 76% at low Fe²⁺. Overall, sequential AO followed by PEF maximized mineralization per unit of energy, and the mixed electrolytes provided a controllable pathway to scale up oxidant speciation generation. Full article

(This article belongs to the Special Issue Applications of Advanced Oxidation Technologies in Water and Wastewater Treatment)

19 pages, 5192 KB

Open AccessArticle

Hurricanes and Human Health in Louisiana: Insights from Hurricanes Laura, Delta, and Ida

by Shobha Kumari Yadav, Robert V. Rohli, M. E. Betsy Garrison, Elisabeth Ponce-Garcia, Nazla Bushra and Charleen McNeill

Sustainability 2025, 17(24), 10944; https://doi.org/10.3390/su172410944 (registering DOI) - 7 Dec 2025

Abstract

Louisiana is one of the most disaster-prone states, with hurricanes ranking among the most destructive hazards. Hurricanes impede sustainability by straining hospital infrastructure, overwhelming emergency departments, and disrupting continuity of care. Louisiana’s healthcare system, characterized by high uninsured rates, limited rural access, and [...] Read more.

Louisiana is one of the most disaster-prone states, with hurricanes ranking among the most destructive hazards. Hurricanes impede sustainability by straining hospital infrastructure, overwhelming emergency departments, and disrupting continuity of care. Louisiana’s healthcare system, characterized by high uninsured rates, limited rural access, and notable racial and socioeconomic disparities, is particularly vulnerable during disasters. This research explores trends of mental and respiratory health in Louisiana surrounding Hurricanes Laura (2020), Delta (2020), and Ida (2021). Analysis reveals a substantial increase in admissions after landfall of all three storms, with mental health conditions showing a larger surge than respiratory ones in already-vulnerable communities. Gender disparities were evident, with female patients accounting for a higher percentage across all three hurricanes and across all age groups. The results suggest the importance of considering social determinants of health during disasters and ensuring adequate resources for older populations with complex medical needs, thereby promoting more sustainable health systems. These results underscore how critical preparedness and recovery planning are for hospitals in hurricane-prone areas. Incorporating resilience measures such as reliable power systems, clearer evacuation pathways, and better coordination of post-disaster care can help protect patients and providers in the future. Full article

(This article belongs to the Special Issue Climate Change, Air Pollution and Sustainable Environmental Protection)

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27 pages, 24407 KB

Open AccessArticle

Enhancing Cement Hydration and Mechanical Strength via Co-Polymerization of Sodium Humate with Superplasticizer Monomers and Sequential Blending with Aluminum Sulfate and Carbon Fibers

by Zhiyuan Song, Sidra Chaudhary, Yan Ding, Yujiao Yan, Qinxiang Jia, Yong Wu, Xiaoyong Li and Yang Sun

Buildings 2025, 15(24), 4422; https://doi.org/10.3390/buildings15244422 (registering DOI) - 7 Dec 2025

Abstract

This study presents a new ternary copolymer synthesized via aqueous free-radical polymerization from sodium humate, sodium 2-methylprop-2-ene-1-sulfonate (SMAS), and 2-acrylamido-2-methylpropane sulfonic acid (AMPS). The resulting highly water-soluble, three-dimensional porous copolymer is complexed with aluminum sulfate to form a composite admixture containing AlO(OH), which [...] Read more.

This study presents a new ternary copolymer synthesized via aqueous free-radical polymerization from sodium humate, sodium 2-methylprop-2-ene-1-sulfonate (SMAS), and 2-acrylamido-2-methylpropane sulfonic acid (AMPS). The resulting highly water-soluble, three-dimensional porous copolymer is complexed with aluminum sulfate to form a composite admixture containing AlO(OH), which acts as a highly effective accelerator for cement hydration. This system significantly shortens the initial and final setting times to averages of 2.62 min and 4.53 min, respectively, and enhances early-age mechanical strength (1.7 MPa compressive, 1.4 MPa flexural at 6 h). These improvements are correlated with the formation of key crystalline phases, including Al₂Si₂O₅(OH)₄ and Ca₃Al₂O₆·xH₂O gel. Incorporation of 50-mesh carbon fibers further reduces setting times (2.21 min initial, 3.93 min final) and increases 24 h strength (5.2 MPa compressive, 2.7 MPa flexural), despite a slight reduction in early strength (at 6 h). In contrast, 200-mesh carbon fibers extend the initial setting time and diminish early strength, associated with the formation of less effective gel phases such as Ca₃Al₂O₆·xH₂O, (CaO)_x(Al₂O₃)₁₁, and Ca₄Al₂O₇·xH₂O. Among these, the Al₂Si₂O₅(OH)₄ phase demonstrates superior performance, while finer carbon fibers show limited effectiveness in bridging hydration products. Conventionally employed as retarders or reinforcing agents, humate-based polymers and carbon fibers are shown here to function as dual-functional admixtures—serving as efficient setting accelerators while enhancing mechanical properties through tailored material design. This strategy offers a promising pathway for developing advanced multifunctional cement admixtures. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

27 pages, 1177 KB

Open AccessReview

Autophagy-Mediated Adaptation: Revealing the Role of Autophagy in Plant Responses to Abiotic Stress

by Zixuan Yu, Abdul Waheed, Daoyuan Zhang, Asigul Ismayil and Yakupjan Haxim

Genes 2025, 16(12), 1461; https://doi.org/10.3390/genes16121461 (registering DOI) - 7 Dec 2025

Abstract

Autophagy, an evolutionarily conserved intracellular recycling pathway, is essential for maintaining cellular homeostasis and enhancing plant resilience to a variety of abiotic stresses, including drought, salinity, extreme temperatures, and heavy metal toxicity. Be-yond its canonical role in nutrient recycling, autophagy is now recognized [...] Read more.

Autophagy, an evolutionarily conserved intracellular recycling pathway, is essential for maintaining cellular homeostasis and enhancing plant resilience to a variety of abiotic stresses, including drought, salinity, extreme temperatures, and heavy metal toxicity. Be-yond its canonical role in nutrient recycling, autophagy is now recognized as a central regulator of stress signaling, hormonal crosstalk, and metabolic reprogramming. Here we synthesize the functions of autophagy under diverse abiotic stresses, highlighting its role in organellar quality control, metabolic adaptation, and stress-specific responses. We further discuss innovative strategies for enhancing crop resilience, including genome editing, integrative multi-omics analyses, and synthetic biology applications. Elucidating the autophagy regulatory network provides the foundation for designing next-generation crops that maintain high yield and resilience under climate-driven stress. Full article

(This article belongs to the Special Issue Physiological and Molecular Mechanisms of Plant Stress Response)

16 pages, 27126 KB

Open AccessArticle

Runtime-Robust Edge Inference System with Masking-Based Partial Update on Dynamic Reconfigurable FPGA

by Myeongjin Kang and Daejin Park

Sensors 2025, 25(24), 7448; https://doi.org/10.3390/s25247448 (registering DOI) - 7 Dec 2025

Abstract

Edge inference systems must sustain real-time performance under dynamic environments such as sensor noise, illumination change, and new object classes. Conventional edge devices deploy static offline-trained models, causing accuracy degradation when the input distribution drifts. This study proposes a runtime-robust edge inference framework [...] Read more.

Edge inference systems must sustain real-time performance under dynamic environments such as sensor noise, illumination change, and new object classes. Conventional edge devices deploy static offline-trained models, causing accuracy degradation when the input distribution drifts. This study proposes a runtime-robust edge inference framework that enables continuous adaptation without interrupting execution. The edge device partitions its memory into active and adaptive regions, applying task-specific masked updates generated by a server-side FPGA. The FPGA performs layer-wise importance analysis, partial retraining, and adaptive mask generation using dynamic partial reconfiguration (DPR) to minimize reconfiguration delay. Experiments on MNIST, CIFAR-10, and Tiny ImageNet show that the proposed method reduces adaptation latency by up to 1.3× compared with GPU full retraining while cutting the communication cost to 28% of full model transmission. These results demonstrate that combining masking-based selective updates with FPGA DPR acceleration achieves real-time adaptability, low latency, and communication-efficient learning in cloud–edge collaborative environments. Full article

(This article belongs to the Special Issue Applications of Sensors Based on Embedded Systems)

27 pages, 1168 KB

Open AccessReview

Emerging Frontiers in Neuro-Oncology: Insights into Extracellular Vesicle-Driven Tumor Mechanisms and Nanotherapeutic Strategies

by Tommaso Colangelo, Anna Alessia Saponaro, Gianluigi Mazzoccoli, Gaetano Serviddio and Rosanna Villani

Int. J. Mol. Sci. 2025, 26(24), 11826; https://doi.org/10.3390/ijms262411826 (registering DOI) - 7 Dec 2025

Abstract

Brain tumors encompass a heterogeneous group of neoplasms, including primary and secondary metastatic lesions, with glioblastoma multiforme (GBM) representing the most aggressive primary malignancy. Despite advancements in surgical resection, radiotherapy, and chemotherapy, the prognosis for GBM remains poor due to its infiltrative nature, [...] Read more.

Brain tumors encompass a heterogeneous group of neoplasms, including primary and secondary metastatic lesions, with glioblastoma multiforme (GBM) representing the most aggressive primary malignancy. Despite advancements in surgical resection, radiotherapy, and chemotherapy, the prognosis for GBM remains poor due to its infiltrative nature, tumor heterogeneity and resistance mechanisms. Emerging diagnostic tools, such as liquid biopsies, and therapeutic strategies leveraging extracellular vesicles (EVs) are reshaping the field of neuro-oncology. EVs, lipid bilayer-enclosed particles secreted by cells, carry oncogenic cargo such as microRNAs and molecular chaperones, influencing tumor progression, immune evasion, and therapy resistance. Recent research highlights their potential as biomarkers for early diagnosis and vehicles for targeted drug delivery across the blood–brain barrier (BBB). EV-based nanotherapeutics show promise in improving treatment precision, reducing systemic toxicity, and advancing precision medicine in brain tumor management. However, challenges related to EV heterogeneity, cargo-loading efficiency, and large-scale production must be addressed to fully realize their therapeutic potential. This review explores the multifaceted roles of EVs in brain tumors, emphasizing their diagnostic, prognostic, and therapeutic applications. Full article

(This article belongs to the Special Issue Novel Extracellular Vesicle-Based Therapy for Central Nervous System Diseases)

22 pages, 3722 KB

Open AccessArticle

Sodium Alginate-Based Antibacterial Coatings Reinforced with Quaternized Lignin–Cinnamaldehyde Composite Particles for Fruit Preservation

by Jianshuo Miao, Yuanrong Lai, Yidan Zhang, Jiapeng Wei, Kehao Fan, Ningjing Sun and Zhiyong Qin

Foods 2025, 14(24), 4203; https://doi.org/10.3390/foods14244203 (registering DOI) - 7 Dec 2025

Abstract

Sodium alginate (SA) is widely used as an edible coating for fruit preservation, but its weak water barrier and antibacterial properties limit broader application. In this study, quaternary ammonium lignin–cinnamaldehyde (QKC) composite particles were incorporated into SA as multifunctional fillers to construct antibacterial [...] Read more.

Sodium alginate (SA) is widely used as an edible coating for fruit preservation, but its weak water barrier and antibacterial properties limit broader application. In this study, quaternary ammonium lignin–cinnamaldehyde (QKC) composite particles were incorporated into SA as multifunctional fillers to construct antibacterial coatings. Electrostatic and hydrogen-bonding interactions between cationic QKC and anionic SA yielded a uniform, stable network with improved hydrophobicity and UV-shielding capacity. At 5 wt% QKC loading (SA5), the tensile strength increased from 11.53 to 24.42 MPa (111.8% higher than SA0), while water vapor permeability decreased by 35.4%. SA coatings also exhibited strong antioxidant activity, and the ABTS radical scavenging rate increased to 70.22% at 7 wt% QKC, with SA5 offering a favorable balance between antioxidant, barrier, and mechanical properties. SA5 showed pronounced antibacterial efficacy, giving inhibition rates of 96% against Staphylococcus aureus and 65% against Escherichia coli. Coating trials on persimmons and tangerines demonstrated that SA5 reduced weight loss, delayed firmness decline, and mitigated decay during storage. In addition, calcium-crosslinked SA/QKC hydrogel beads markedly delayed visible mold growth on blueberries. These results indicate that QKC-reinforced SA coatings provide a promising strategy for enhancing the postharvest quality and shelf life of fresh fruit. Full article

(This article belongs to the Special Issue Postharvest Technologies to Enhance Food Quality and Safety)

23 pages, 8231 KB

Open AccessArticle

Influence of Environmental Factors on the Starch Quality of Sorghum: A Multifaceted Analysis of Structural, Nutritional, and Functional Profiles

by Fulai Ke, Baizhi Chen, Kuangye Zhang, Jiaxu Wang, Linlin Yang, Zeyang Zhao, Fei Zhang, Han Wu, Zhipeng Zhang, Feng Lu, Yanqiu Wang, Youhou Duan, Zhiqiang Liu, Jianqiu Zou and Kai Zhu

Foods 2025, 14(24), 4204; https://doi.org/10.3390/foods14244204 (registering DOI) - 7 Dec 2025

Abstract

Understanding how environmental factors modulate starch structure and functionality in sorghum is critical for optimizing its application in the food processing and fermentation industries. In this study, two sorghum cultivars with distinct starch types—Liaonian 3 (LN3, waxy) and Liaoza 82 (LZ82, non-waxy)—were cultivated [...] Read more.

Understanding how environmental factors modulate starch structure and functionality in sorghum is critical for optimizing its application in the food processing and fermentation industries. In this study, two sorghum cultivars with distinct starch types—Liaonian 3 (LN3, waxy) and Liaoza 82 (LZ82, non-waxy)—were cultivated across four major ecological regions in China to systematically investigate the combined effects of temperature and precipitation on grain composition, starch molecular structure, and processing properties. Comprehensive analyses, including scanning electron microscopy, molecular weight profiling, chain-length distribution, crystallinity, molecular order, and thermal/pasting behaviors, demonstrated that precipitation is the predominant environmental factor driving starch biosynthesis and structural assembly. High precipitation levels promoted amylopectin accumulation, shorter chain formation, increased branching degree, and higher crystallinity and molecular order, ultimately enhancing starch thermal stability and paste consistency. Genotypic differences further modulated starch structural patterns and environmental responsiveness, with LN3 consistently exhibiting higher amylopectin content, crystallinity, double-helix proportion, and gelatinization enthalpy compared to LZ82. Correlation analyses revealed genotype-dependent regulatory relationships linking environmental cues to starch structure and processing functionality. These findings provide a comprehensive framework elucidating the environmental regulation of starch structure–function relationships in sorghum, offering theoretical insights for climate-resilient breeding and functional starch development. Full article

(This article belongs to the Section Grain)

11 pages, 213 KB

Open AccessArticle

RNN-Based F0 Estimation Method with Attention Mechanism

by Ales Jandera, Martin Muzelak and Tomas Skovranek

Information 2025, 16(12), 1089; https://doi.org/10.3390/info16121089 (registering DOI) - 7 Dec 2025

Abstract

Fundamental frequency estimation, also known as F0 estimation, is a crucial task in speech processing and analysis, with significant applications in areas such as speech recognition, speaker identification, and emotion detection. Traditional algorithms, while effective, often encounter challenges in real-time environments due to [...] Read more.

Fundamental frequency estimation, also known as F0 estimation, is a crucial task in speech processing and analysis, with significant applications in areas such as speech recognition, speaker identification, and emotion detection. Traditional algorithms, while effective, often encounter challenges in real-time environments due to computational limitations. Recent advances in deep learning, especially in the use of recurrent neural networks (RNNs), have opened new opportunities for enhancing F0 estimation accuracy and efficiency. This paper introduces a novel RNN-based F0 estimation method with an attention mechanism and evaluates its performance against selected state-of-the-art F0 estimation approaches, including standard baseline methods, as well as neural-network-based regression and classification models. By integrating attention mechanisms, the model eliminates the necessity for post-processing steps and enables a more efficient seq2scal estimation process. While the self-attention mechanism used in Transformers captures all pairwise temporal dependencies at a quadratic computational cost, the proposed method’s implementation of the attention mechanism enables it to selectively focus on the most relevant acoustic cues for F0 prediction, enhancing robustness without increasing the model’s complexity. Experimental results using the LibriSpeech and Common Voice datasets demonstrate superior computational efficiency of the proposed method compared to current state-of-the-art RNN-based seq2seq models, while maintaining comparable estimation accuracy. Furthermore, the proposed “RNN-based F0 estimation method with an attention mechanism” achieves the lowest computational complexity among all compared models, while maintaining high accuracy, making it suitable for low-latency, resource-limited deployments and competitive even with standard baseline methods, such as pYIN or CREPE. Finally, the performance of the developed RNN-based F0 estimation method with attention mechanism in terms of RMSE and FLOPs demonstrates the potential of attention mechanisms and sequence modelling in achieving high accuracy alongside lightweight F0 estimation suitable for modern speech processing applications, which aligns with the growing trend towards deploying intelligent systems on resource-constrained devices. Full article

(This article belongs to the Special Issue Signal Processing and Machine Learning, 2nd Edition)

30 pages, 11979 KB

Open AccessArticle

GIS-Based Analysis of Retail Spatial Distribution and Driving Mechanisms in a Resource-Based Transition City: Evidence from POI Data in Taiyuan, China

by Xinrui Luo, Rosniza Aznie Che Rose and Azahan Awang

ISPRS Int. J. Geo-Inf. 2025, 14(12), 483; https://doi.org/10.3390/ijgi14120483 (registering DOI) - 7 Dec 2025

Abstract

Rapid urbanization in China has reshaped retail spatial structures, creating challenges of accessibility and service equity. This study employs a Geographic Information Systems (GIS)-based analytical framework to examine the spatial distribution and driving mechanisms of retail outlets in Taiyuan, a resource-based transition city [...] Read more.

Rapid urbanization in China has reshaped retail spatial structures, creating challenges of accessibility and service equity. This study employs a Geographic Information Systems (GIS)-based analytical framework to examine the spatial distribution and driving mechanisms of retail outlets in Taiyuan, a resource-based transition city in central China. Using 2023 Point of Interest (POI) data and a 2 km × 2 km grid system, kernel density estimation (KDE), Average Nearest Neighbor (ANN) Analysis, Location Quotient (LQ), and spatial autocorrelation were applied to identify clustering patterns and functional specialization. The GeoDetector (Word version, downloaded 2025) model further quantified the explanatory power of twelve natural, social, economic, and transportation variables. Results reveal a polycentric retail structure, with high-density clusters in Yingze and Xiaodian districts and under-supply in Jiancaoping and Jinyuan. Population density, nighttime light (NTL) intensity, and school distribution emerged as the strongest drivers, while topography constrained expansion. By integrating GIS-based spatial statistics with GeoDetector, the study demonstrates a transferable framework for analyzing urban retail spatial patterns. The findings extend retail geography to transition cities and provide practical guidance for optimizing retail allocation, enhancing service equity, and supporting spatial decision-making for sustainable urban development. Full article

(This article belongs to the Topic Spatial Decision Support Systems for Urban Sustainability)

26 pages, 6543 KB

Open AccessArticle

Explainable Federated Learning for Multi-Class Heart Disease Diagnosis via ECG Fiducial Features

by Tanjila Alam Sathi, Rafsan Jany, AKM Azad, Salem A. Alyami, Naif Alotaibi, Iqram Hussain and Md Azam Hossain

Diagnostics 2025, 15(24), 3110; https://doi.org/10.3390/diagnostics15243110 (registering DOI) - 7 Dec 2025

Abstract

Background/Objectives: Cardiovascular disease (CVD) remains a leading cause of mortality and disability worldwide, with timely diagnosis critical for preventing long-term functional impairment. Electrocardiograms (ECGs) provide essential biomarkers of cardiac function, but their interpretation is often complex, particularly across multi-institutional datasets. Methods: This study [...] Read more.

Background/Objectives: Cardiovascular disease (CVD) remains a leading cause of mortality and disability worldwide, with timely diagnosis critical for preventing long-term functional impairment. Electrocardiograms (ECGs) provide essential biomarkers of cardiac function, but their interpretation is often complex, particularly across multi-institutional datasets. Methods: This study presents an explainable federated learning framework with long short-term memory (FL-LSTM) for multi-class heart disease classification, capable of distinguishing arrhythmia, ischemia, and healthy states while preserving patient privacy. Results: The model was trained and evaluated on three heterogeneous ECG datasets, achieving 92% accuracy, 99% AUC, and 91% F1 score, outperforming existing federated approaches. Model interpretability is provided via SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME), highlighting clinically relevant ECG biomarkers such as P-wave height, R-wave height, QRS complex, RR interval, and QT interval. Conclusions: By integrating temporal modeling, federated learning, and interpretable AI, the framework enables secure and collaborative cardiac diagnosis while supporting transparent clinical decision-making in distributed healthcare settings. Full article

(This article belongs to the Special Issue AI and Digital Health for Disease Diagnosis and Monitoring, 2nd Edition)

24 pages, 28659 KB

Open AccessArticle

Experimental Measurement and Numerical Computation of Permeability for Additively-Manufactured Heat Pipe Wicks

by Manfredo Guilizzoni, Luigi Vitali, Giovanni Brambati, Roberta Caruana, Emmanuel Caplanne and Stefano Foletti

Energies 2025, 18(24), 6399; https://doi.org/10.3390/en18246399 (registering DOI) - 7 Dec 2025

Abstract

Heat pipe (HP) performance depends on several interacting physical phenomena, such as phase change and liquid transport within the wick. The latter is strongly affected by the permeability of the porous material, whose accurate evaluation is essential for a reliable prediction of the [...] Read more.

Heat pipe (HP) performance depends on several interacting physical phenomena, such as phase change and liquid transport within the wick. The latter is strongly affected by the permeability of the porous material, whose accurate evaluation is essential for a reliable prediction of the heat transfer capability. This work investigates the permeability of an additively manufactured aluminum wick by comparing two experimental and two numerical methods, using acetone and ethanol as working fluids. In the first experimental approach, the analytical capillary rise curve was fitted to data obtained through infrared thermography and by monitoring the fluid level decrease in an input reservoir. In the second, the mass flow rate through the samples was directly measured under an imposed pressure difference. Numerical simulations were performed using the Finite Volume Method in OpenFOAM and the Lattice Boltzmann Method in Palabos on computational domains reconstructed from microtomographic scans of a real wick. The permeability values, determined through the Darcy–Forchheimer formulation, were then used to estimate the maximum heat transport capability based on the capillary limit model for representative HP geometries. The results show that all four methods provide consistent permeability estimates, with deviations below

30 %

in the porosity range relevant to real HPs. Full article

(This article belongs to the Special Issue Computational Fluid Dynamics (CFD) Study for Heat Transfer)

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