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22 pages, 6727 KB

Open AccessArticle

Efficient Signal Denoising Methods Using Randomized HSVD and Wavelet Thresholding

by Saifon Chaturantabut and Jatupat Chanakul

AppliedMath 2026, 6(9), 149; https://doi.org/10.3390/appliedmath6090149 (registering DOI) - 6 Sep 2026

This work introduces efficient signal denoising methods based on wavelet thresholding (WT) and Hankel matrix-based Singular Value Decomposition (HSVD) with a randomized algorithm. The sequential hybrid frameworks of these techniques are investigated—both WT followed by HSVD (WT-HSVD) and HSVD followed by WT (HSVD-WT)—across [...] Read more.

This work introduces efficient signal denoising methods based on wavelet thresholding (WT) and Hankel matrix-based Singular Value Decomposition (HSVD) with a randomized algorithm. The sequential hybrid frameworks of these techniques are investigated—both WT followed by HSVD (WT-HSVD) and HSVD followed by WT (HSVD-WT)—across varying noise levels. Numerical tests are performed through different benchmark signals, including dual harmonic, damped sine, and dual frequency signals, as well as a natural phonocardiogram recording. Different types of corrupted noises, including white Gaussian, colored (brown), and impulsive noises, are considered in the numerical tests. For moderate and high noise levels, hybrid frameworks can significantly improve the final accuracy of the denoised signals, as measured by reconstruction error metrics and Signal-to-Noise Ratio. These hybrid frameworks are also shown to be advantageous in compensating for suboptimal parameter selections that may occur when using either method individually. Furthermore, to mitigate the computational burden inherent to exact SVD, this work employs a randomized Singular Value Decomposition (rSVD) algorithm. Depending on the signal size, the proposed hybrid frameworks with rSVD achieve a 30% to 80% reduction in CPU execution time while maintaining denoised signal reconstruction accuracy across test cases. Full article

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33 pages, 464 KB

Open AccessArticle

Shannon Capacity and Related Graph Invariants for Lexicographic Products

by Igal Sason

Entropy 2026, 28(9), 994; https://doi.org/10.3390/e28090994 (registering DOI) - 5 Sep 2026

Abstract

This paper studies the Shannon capacity of lexicographic products of finite simple graphs, together with the Lovász theta function and the fractional Haemers number. The Shannon capacity is proved to be supermultiplicative under lexicographic products in either order, and these products are compared [...] Read more.

This paper studies the Shannon capacity of lexicographic products of finite simple graphs, together with the Lovász theta function and the fractional Haemers number. The Shannon capacity is proved to be supermultiplicative under lexicographic products in either order, and these products are compared with the strong product. We explicitly construct three countably infinite families of lexicographic powers based on the Schläfli graph, the McLaughlin graph, and its second subconstituent; in each family, pairing each member with its complement yields strict supermultiplicativity and arbitrarily large multiplicative gaps. Bounds and exact-capacity criteria for lexicographic products are derived, and the resulting upper bounds are shown to be incomparable. The capacities of lexicographic products involving Kneser graphs, their complements, and q-analogues of Kneser graphs are determined. It is also shown that a lexicographic product with a complete outer factor preserves the Shannon capacity of an arbitrary inner factor. The capacities of iterated lexicographic powers are determined, including those of self-complementary graphs that are vertex-transitive or strongly regular. Elementary, self-contained proofs are also given for three known results: the multiplicativity of the Lovász theta function and the fractional Haemers number under lexicographic products, and the equality of the fractional and ordinary Lovász theta functions. Finally, an open problem concerning the Shannon capacities of lexicographic and strong products is posed. Full article

(This article belongs to the Section Information Theory, Probability and Statistics)

24 pages, 967 KB

Open AccessReview

Arrhythmic Mitral Valve Prolapse as a Regional Stretch-Induced Cardiomyopathy with Fibro-Inflammatory Signature: A Conceptual Review

by Mili Dave, Shaaf Ahmad, Kirkwood Adams, Adam Akerman, Jinny Ha, Ross J. Simpson, Jr. and Faisal F. Syed

J. Cardiovasc. Dev. Dis. 2026, 13(9), 437; https://doi.org/10.3390/jcdd13090437 (registering DOI) - 5 Sep 2026

Abstract

Mitral valve prolapse (MVP) affects 1–3% of the general population and is largely considered benign. However, a small subset of MVP patients develops complex ventricular arrhythmias (VAs) and sudden cardiac death, including patients with nonsignificant mitral regurgitation (MR). This subgroup of arrhythmic MVP [...] Read more.

Mitral valve prolapse (MVP) affects 1–3% of the general population and is largely considered benign. However, a small subset of MVP patients develops complex ventricular arrhythmias (VAs) and sudden cardiac death, including patients with nonsignificant mitral regurgitation (MR). This subgroup of arrhythmic MVP (aMVP) is variably associated with features such as mitral annular disjunction, bileaflet myxomatous prolapse, and regional myocardial fibrosis, with arrhythmic risk disproportionate to hemodynamic burden. The EHRA defines aMVP as MVP with complex VAs (frequent premature ventricular contractions, non-sustained or sustained ventricular tachycardia, ventricular fibrillation, or aborted sudden cardiac arrest) in the absence of another defined arrhythmic substrate. This narrative review reframes aMVP as a regional, stretch-induced cardiomyopathy with a distinct fibro-inflammatory signature. We further characterize a two-hit pathogenesis in which abnormal valvular mechanics create regional myocardial stress, while patient-specific vulnerability shapes variable fibro-inflammatory, fibrotic, and electromechanical responses. This narrative review synthesizes contemporary evidence across multimodal cardiac imaging, electrophysiology, surgical outcomes, mechanotransduction biology, and pharmacology, emphasizing a modifiable fibro-inflammatory trajectory underlying the intermediate risk aMVP phenotype and supporting a clinical shift from device-based rescue to substrate-directed prevention. Expanding on this model, we evaluate substrate-modifying pharmacotherapies for mechanistic fit, human cardiac evidence, and trial feasibility. Among these, mineralocorticoid receptor antagonists (MRAs) and sodium–glucose cotransporter 2 (SGLT2) inhibitors demonstrate the strongest convergence of antifibrotic potential and trial readiness. Full article

(This article belongs to the Special Issue Ventricular Arrhythmias: Mechanisms and Management)

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27 pages, 9352 KB

Open AccessArticle

Spatiotemporal Evolution of Waterlogging Intensity During Winter Oilseed Rape Growth Stages and Its Relationship with Yield Losses in the Middle-Lower Yangtze River Region

by Long Qian, Huayue Meng, Yunying Luo and Kai Duan

Agriculture 2026, 16(17), 1925; https://doi.org/10.3390/agriculture16171925 (registering DOI) - 5 Sep 2026

Abstract

Understanding the spatiotemporal evolution of waterlogging intensity across winter oilseed rape (WOSR) growth stages and its quantitative relationship with yield losses is critical for agricultural water management in the Middle-Lower Yangtze River Region (MLYRR). Here, a daily-scale agrometeorological index (SAPEI) was introduced to [...] Read more.

Understanding the spatiotemporal evolution of waterlogging intensity across winter oilseed rape (WOSR) growth stages and its quantitative relationship with yield losses is critical for agricultural water management in the Middle-Lower Yangtze River Region (MLYRR). Here, a daily-scale agrometeorological index (SAPEI) was introduced to quantify waterlogging intensity during four WOSR growth stages from 1961 to 2020. Waterlogging intensity increased significantly over the past six decades in most areas, particularly during the overwintering stage (38 stations, 57% of all stations), with the 2000s representing the historical high levels for most provinces, followed by those in the 1990s. The northeastern and southernmost MLYRR were identified as highly waterlogging-prone regions, and the overwintering stage exhibited substantially larger daily waterlogging intensity than other stages. The yield-reducing impact of severe waterlogging (SAPEI > 1.0) was greater than general waterlogging (SAPEI > 0.5), with larger absolute regression coefficients of waterlogging indices. The flowering–maturing stage, followed by the overwintering stage, was the most waterlogging-sensitive period, and it was also selected as the sole explanatory variable in up to 14 districts in stepwise regression. A marked spatial mismatch was found between waterlogging proneness and crop sensitivity, suggesting that drainage scheduling should account for crop waterlogging sensitivity rather than waterlogging intensity alone. These findings provide guidance for targeted WOSR drainage planning in key regions of the MLYRR under climate change. Full article

(This article belongs to the Section Agricultural Water Management)

23 pages, 6940 KB

Open AccessArticle

Formation and Properties of Electrospun Zein Nanofibers from Glacial Acetic Acid Solutions: Effects of Process Variables and Surfactants

by Shumin Wang, Xiaolin Liang, Hanyu Chai, Shaohua Lin, Yankun Fu, Xiaofei Liu, Hongyu Li and Pengjie Wang

Foods 2026, 15(17), 3156; https://doi.org/10.3390/foods15173156 (registering DOI) - 5 Sep 2026

Abstract

Electrospun zein nanofibers are promising bio-based materials, but producing uniform ultrafine fibers with desirable performance remains challenging. This study examined the effects of process variables and three surfactants on zein fiber formation, diameter, and material properties. Zein solutions (30–40%, w/v) [...] Read more.

Electrospun zein nanofibers are promising bio-based materials, but producing uniform ultrafine fibers with desirable performance remains challenging. This study examined the effects of process variables and three surfactants on zein fiber formation, diameter, and material properties. Zein solutions (30–40%, w/v) were prepared in glacial acetic acid, and 2% (w/w, based on zein) triethyl benzyl ammonium chloride (TEBAC), sodium dodecyl sulfate (SDS), or span-80 was incorporated into the 30% zein solution. Zein concentration and feed rate yielded fiber diameters of 208.22–1001.90 nm. Surfactants reduced surface tension and increased conductivity, promoting jet stretching and generating uniform fibers with diameters near 100 nm. SDS produced the smallest fibers (98.92 ± 15.20 nm). TEBAC increased tensile strength from 11.08 to 63.26 MPa and improved dimensional retention in water, whereas SDS and span-80 increased elongation at break but reduced strength and stiffness. All surfactants increased wettability and altered intermolecular interactions and secondary structure of zein, although they reduced thermal stability. Overall, surfactants acted as both electrospinning aids and structure-directing modifiers, with TEBAC providing the best balance of fineness, strength, and aqueous stability. These ultrafine, robust, and water-stable nanofibers are promising as functional coating layers for high-moisture food packaging and as carriers for antioxidants or antimicrobial agents. Full article

(This article belongs to the Special Issue Recent Research on Function and Structure of Plant-Based Food Protein)

20 pages, 3576 KB

Open AccessArticle

Drivers of Spatial and Temporal Variability in Oil and Gas Emissions: Temporally Resolved Inventories for the Permian Basin Across Multiple Spatial Scales

by Qining Chen, Sewar Jennifer Almasalha, Shannon Stokes, Lea Hildebrandt Ruiz and David T. Allen

Atmosphere 2026, 17(9), 870; https://doi.org/10.3390/atmos17090870 (registering DOI) - 5 Sep 2026

Abstract

Emission inventories at fine spatial and temporal scales were developed for light alkanes, volatile organic compounds (VOCs), and nitrogen oxides (NO_x) from upstream and midstream oil and gas operations in the Permian Basin oil and gas production region for 2022–2024. The [...] Read more.

Emission inventories at fine spatial and temporal scales were developed for light alkanes, volatile organic compounds (VOCs), and nitrogen oxides (NO_x) from upstream and midstream oil and gas operations in the Permian Basin oil and gas production region for 2022–2024. The inventories were spatially aggregated at basin, county, and 12 km by 12 km grid cell levels, and temporally resolved at hourly resolution, with underlying methods capable of generating inventories at other spatial and temporal scales. Spatial and temporal variability in emissions in the Permian were compared at various spatial scales with inventories for the Marcellus oil and gas production region, developed using the same methods. Emission sources that drive spatial and temporal variability differ by regional production characteristics, the level of spatial aggregation, and emitted species. Temporal variability in emissions decreases as the scale of spatial aggregation increases. Among counties with at least 10 active producing wells, maximum-to-annual-average hourly emission rate ratios reached 2.5 for methane, 2.8 for VOCs, and 2.3 for NO_x. At the 12 km by 12 km grid cell level, the corresponding maximum ratios were 33.7, 26.5, and 13.9. These ratios illustrate the magnitude of short-term emission variability and the extent to which peak hourly emissions can exceed annual average estimates, with potential implications for episodic air-quality impact assessment. Compared with the gas-dominated Marcellus Basin, the oil-dominated Permian Basin shows lower temporal variability in hydrocarbon emissions due to fewer episodic gas production related sources (e.g., liquid unloadings) and a greater contribution from near-continuous oil production related sources (e.g., associated gas venting and tank flash). In contrast, NOₓ emissions exhibit higher temporal variability in the Permian due to more frequent preproduction activities associated with new well development. The spatially and temporally resolved emission inventories by source category and chemical species can be further combined with chemical transport modeling and air quality modeling to support assessment of regional air quality events, such as localized and episodic ozone formation. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

14 pages, 640 KB

Open AccessArticle

Community-Based HPV Self-Sampling to Enhance Access to Cervical Cancer Prevention: A Continuum-of-Care Model from Urban Nepal

by Shreekrishna Maharjan, Anamika Maharjan, Kushala K. Bista, Pranali G. Patel, Jitendra Pariyar, Pema Lhaki and Sadeep Shrestha

Curr. Oncol. 2026, 33(9), 539; https://doi.org/10.3390/curroncol33090539 (registering DOI) - 5 Sep 2026

Abstract

Cervical cancer remains the leading cause of cancer-related mortality among women in Nepal, where national screening coverage is approximately 16%. This study evaluated the feasibility of a community-based, door-to-door self-sampling strategy for high-risk human papillomavirus (hrHPV) detection in an urban municipality of central [...] Read more.

Cervical cancer remains the leading cause of cancer-related mortality among women in Nepal, where national screening coverage is approximately 16%. This study evaluated the feasibility of a community-based, door-to-door self-sampling strategy for high-risk human papillomavirus (hrHPV) detection in an urban municipality of central Nepal and assessed hrHPV prevalence, genotype distribution, screening outcomes, and associated demographic factors. A cross-sectional study was conducted between September 2023 and May 2024 in Ward No. 3 of Lalitpur Metropolitan City. Women aged 30–60 years were recruited through trained community health workers, provided education and home-based self-sampling kits, and completed a demographic questionnaire. Dry cervical swabs from 418 participants were tested for hrHPV. Women with positive results underwent visual inspection with acetic acid (VIA), followed by colposcopy, biopsy when indicated, and thermal ablation for confirmed precancerous lesions. Overall participation was 64.1%, and hrHPV prevalence was 10.3%. Non-16/18 hrHPV genotypes predominated (55.8%), followed by HPV16 (20.9%). Women aged > 50 years were more likely to be hrHPV- and VIA-positive (OR = 7.39, p = 0.02). Six pre-cancer cases were identified: five cervical intraepithelial neoplasia (CIN1) and one CIN3 case. Community-based hrHPV self-sampling was found to be feasible and achieved effective linkage to triage and treatment, supporting its consideration for strengthening cervical cancer screening in Nepal. Full article

(This article belongs to the Special Issue Global Strategies and Equity Challenges in Cervical Cancer Prevention and Elimination)

19 pages, 323 KB

Open AccessArticle

Associations of Diabetes-Related Distress, Disordered-Eating Risk, and Self-Perceived Health with Glycemic Outcomes in Adolescents with Type 1 Diabetes: An Exploratory Cross-Sectional Study

by Marta García-Poblet, Isabel Sospedra, Brisa Florencia Formilan, Esther Soler-Climent, Manuel Antonio Alberola-Chazarra and José Miguel Martínez-Sanz

Nutrients 2026, 18(17), 2916; https://doi.org/10.3390/nu18172916 (registering DOI) - 5 Sep 2026

Abstract

Background/Objectives: Adolescents with type 1 diabetes mellitus (T1DM) are particularly vulnerable to psychological distress, disordered-eating (DE) risk and negative self-perceived health status (SPHS), which may compromise metabolic control and self-care. Although these factors have been studied individually, the usefulness of brief and clinically [...] Read more.

Background/Objectives: Adolescents with type 1 diabetes mellitus (T1DM) are particularly vulnerable to psychological distress, disordered-eating (DE) risk and negative self-perceived health status (SPHS), which may compromise metabolic control and self-care. Although these factors have been studied individually, the usefulness of brief and clinically feasible screening tools to detect these dimensions remains underexplored. This study aimed to: (1) examine associations between distress, DE risk and SPHS; (2) explore their relationships with glycemic control, clinical profile and self-care; and (3) assess the influence of age and diabetes duration on these outcomes. Methods: A cross-sectional study was conducted in 37 adolescents with T1DM in Spain. Sociodemographic, anthropometric and clinical variables were obtained from medical records. Distress, DE risk and self-care were assessed using validated questionnaires, while SPHS was measured using single-item question. Pearson and Spearman correlations were performed. Results: Distress was present in 48.6% of participants and DE risk in 29.7%, while 67.6% reported positive SPHS. Distress correlated with higher HbA1c and lower TIR. DE risk correlated with BMI. Lower SPHS was associated with higher HbA1c. Age and diabetes duration were associated with greater glycemic variability, and diabetes duration also correlated with higher glucose and TyG-based insulin resistance indexes. No significant associations were found for self-care behaviors. Conclusions: Distress, DE risk and SPHS, assessed through feasible screening tools, showed meaningful associations with metabolic outcomes in adolescents with T1DM. Integrating brief psychological screening tools into routine care may facilitate early identification of psychological vulnerability profiles in this population during routine practice. Full article

(This article belongs to the Special Issue Research on the Psychological Factors Shaping Physical Health and Nutrition)

30 pages, 2409 KB

Open AccessArticle

Ultrasonic Monitoring of Gas-Induced Geomechanical Evolution in Coal Reservoirs Using Coda Wave Interferometry

by Gilbert Yaw Bimpong, Long Fan and Zakiya Konda Nurudeen

Acoustics 2026, 8(3), 64; https://doi.org/10.3390/acoustics8030064 (registering DOI) - 5 Sep 2026

Abstract

Continuous monitoring of gas-induced changes in coal is important for carbon dioxide storage, coalbed methane recovery, and underground mine safety. Conventional ultrasonic monitoring primarily relies on direct-wave velocities, which may exhibit limited sensitivity to subtle, distributed changes within the coal microstructure. This study [...] Read more.

Continuous monitoring of gas-induced changes in coal is important for carbon dioxide storage, coalbed methane recovery, and underground mine safety. Conventional ultrasonic monitoring primarily relies on direct-wave velocities, which may exhibit limited sensitivity to subtle, distributed changes within the coal microstructure. This study evaluates coda wave interferometry (CWI) for monitoring the response of an anthracite coal specimen to helium (He) and carbon dioxide (CO₂) injection under controlled triaxial loading with an axial-to-confining stress ratio of 2:1, with confining stress held 1.0 MPa above the gas pressure in every test so that the effective confining stress was constant at 1.0 MPa and the stages differ only in the gas present. Gas was introduced at nominal injection pressures of 2.5, 5.5, and 12.5 MPa. Ultrasonic waveforms were recorded continuously for 5 h during the CO₂ experiments and 7 h during the He experiments. P- and S-wave velocities, and their fractional changes (dv/v), were calculated from Akaike Information Criterion-based arrival picks, while coda-derived relative velocity changes (δv/v) were estimated by the CWI stretching method over a 300–600 µs coda window. All six gas–pressure conditions were imposed sequentially on a single specimen, which was vented, degassed, and reconditioned between successive runs. CO₂ exhibited slower upstream-pressure dissipation than He, a response consistent with sorptive retention and adsorption-induced modification of the coal pore structure. Direct-wave velocities captured pronounced mechanical changes at low and intermediate injection pressures but showed limited sensitivity during the 12.5 MPa CO₂ experiment. In contrast, CWI detected a persistent negative δv/v trend at 5.5 MPa and a progressive negative trend at 12.5 MPa. Although adsorption was not measured independently, the contrasting He and CO₂ responses demonstrate that CWI can complement direct-wave analysis by detecting subtle, distributed changes associated with coupled mechanical and gas–coal interactions. Full article

32 pages, 6311 KB

Open AccessArticle

Latent Conditional Diffusion-Based Data Augmentation for Small-Sample Hyperspectral Prediction of Forest Soil Organic Carbon

by Jian Tang, Weilin Li, Yuanyuan Shi, Yun Deng and Junyu Zhao

Sensors 2026, 26(17), 5657; https://doi.org/10.3390/s26175657 (registering DOI) - 5 Sep 2026

Abstract

Accurate forest soil organic carbon (SOC) monitoring is essential for forest soil quality assessment and carbon-sink evaluation. Visible-near-infrared (Vis–NIR) hyperspectral sensing provides rapid and information-rich measurements for SOC prediction, but obtaining sufficiently large labeled soil-spectral datasets remains difficult because field sampling, sample preparation, [...] Read more.

Accurate forest soil organic carbon (SOC) monitoring is essential for forest soil quality assessment and carbon-sink evaluation. Visible-near-infrared (Vis–NIR) hyperspectral sensing provides rapid and information-rich measurements for SOC prediction, but obtaining sufficiently large labeled soil-spectral datasets remains difficult because field sampling, sample preparation, and reference SOC determination are labor and time intensive. This study developed a latent conditional diffusion-based data augmentation framework for SOC prediction from hyperspectral sensor data. A total of 248 forest red-soil samples from Guangxi, China, were measured using laboratory Vis–NIR reflectance spectroscopy over 350–2500 nm and divided by the Kennard-Stone algorithm into a 174-sample modeling set and a fixed 74-sample validation set. Four generative models, including VAE, GAN, WGAN-GP, and the proposed hyperspectral latent conditional denoising diffusion implicit model (HsDDIM), were evaluated using spectral visualization, t-SNE distributions, maximum mean discrepancy (MMD), Fréchet Inception Distance (FID), and downstream prediction performance. Unlike joint spectral-label generation, HsDDIM treats SOC as an external condition and generates spectra in the latent space under specified SOC conditions; the SOC condition itself is not generated by the diffusion process. Among the compared augmentation strategies, HsDDIM showed the closest distributional agreement with the real spectral samples according to MMD and FID, with values of 0.0806 and 0.5281, respectively. Without augmentation, FD1-SVR achieved the best validation result (R² = 0.83, RMSE = 4.71 g kg⁻¹). After 300% HsDDIM augmentation, 1D-CNN achieved R² = 0.91, RPD = 3.39, and RMSE = 3.40 g kg⁻¹. These results suggest that the SOC-conditioned latent DDIM framework can improve small-sample hyperspectral SOC prediction under the present fixed-validation protocol. Full article

(This article belongs to the Section Environmental Sensing)

29 pages, 5139 KB

Open AccessArticle

Explainable Ceramic-Form Classification and Visual Retrieval of Chinese Ceramic Cultural Heritage Using DINOv2 and Morphological Feature Fusion

by Zengcheng Wang, Wuxin Liu, Yaxin Li and Bin Dong

Appl. Sci. 2026, 16(17), 8850; https://doi.org/10.3390/app16178850 (registering DOI) - 5 Sep 2026

Abstract

The continued digitization of open museum collections provides new opportunities for the intelligent organization and visual discovery of cultural heritage. However, morphological similarity between ceramic forms, intra-class variation, and changing photographic conditions remain challenges for automated classification, model interpretation, and similar-object retrieval. This [...] Read more.

The continued digitization of open museum collections provides new opportunities for the intelligent organization and visual discovery of cultural heritage. However, morphological similarity between ceramic forms, intra-class variation, and changing photographic conditions remain challenges for automated classification, model interpretation, and similar-object retrieval. This study uses 3305 Chinese ceramic objects from the open collection of The Metropolitan Museum of Art (The Met) to develop an explainable and traceable workflow for ceramic-form classification and visual retrieval. Museum metadata were standardized into 13 form categories, from which 2755 objects were used to establish a seven-class primary classification task. Explicit morphological features, handcrafted visual features, ResNet50 representations, DINOv2 representations, and morphology–deep feature fusion were evaluated under a unified data split and evaluation protocol. Explainable artificial intelligence (XAI) methods were further used to examine spatial model responses and feature attributions of explicit morphological variables, while different representations were evaluated for content-based visual retrieval. The results show that deep visual representations effectively support ceramic-form classification, with DINOv2 demonstrating comparatively stable performance across multiple random seeds. Morphology–deep feature fusion did not provide a consistent classification advantage over DINOv2-only, but the fused representation showed clearer complementary value in visual retrieval, achieving the highest Precision@5 (0.819) and mean average precision at 10 (mAP@10; 0.773). XAI analyses further indicated that structurally meaningful spatial responses and explicit geometric descriptors contributed to form discrimination. By linking classification, interpretation, and retrieval outputs to Object IDs and original collection records, the proposed workflow provides a practical computational approach for ceramic-form organization, similar-object discovery, and traceable visual retrieval in digital museum collections. Full article

(This article belongs to the Special Issue Artificial Intelligence Technologies in Cultural Heritage)

53 pages, 17342 KB

Open AccessReview

AI-Assisted MOS Gas Sensors: Sensing Materials, MEMS Platforms, Dynamic Operation, and Intelligent Applications

by Jin Li, Tongheng Cheng, Haoqing Li, Junwen Wei, Yukun Wu, Yuhua Hu, Ziqi Luo, Bo Tang and Fei Wang

AI Sens. 2026, 2(3), 12; https://doi.org/10.3390/aisens2030012 (registering DOI) - 5 Sep 2026

Abstract

Metal oxide semiconductor (MOS) gas sensors are widely used for low-cost chemical detection, but their practical performance is still limited by high operating temperature, insufficient selectivity, signal drift, and device-to-device variation. Recent advances in microelectromechanical systems (MEMS), dynamic sensing protocols, and artificial intelligence [...] Read more.

Metal oxide semiconductor (MOS) gas sensors are widely used for low-cost chemical detection, but their practical performance is still limited by high operating temperature, insufficient selectivity, signal drift, and device-to-device variation. Recent advances in microelectromechanical systems (MEMS), dynamic sensing protocols, and artificial intelligence (AI) provide new opportunities to improve MOS gas sensing from both hardware and data-processing perspectives. MEMS micro-hotplates enable miniaturized devices, low-power heating, rapid thermal control, temperature-modulated operation, and compatibility with integrated readout and interface circuits, while AI methods extract multivariate, nonlinear, and temporal information from cross-sensitive sensor responses. This review summarizes the fundamentals of MOS sensing materials, MEMS micro-hotplate platforms, material–device integration strategies, and AI-assisted data-processing methods ranging from classical statistical analysis to deep learning. Representative strategies are discussed, including single-sensor feature extraction, sensor-array recognition, temperature-modulated sensing, drift compensation, and AI-guided material design. Application studies in food quality assessment, agriculture, medical diagnostics, environmental monitoring, and public safety are further reviewed to show how sensing tasks evolve from odor-fingerprint discrimination to nonlinear feature interpretation, dynamic response analysis, domain adaptation, and deployable intelligent monitoring. Particular attention is given to the role of high-consistency integration of MOS sensing layers on MEMS platforms, since reproducible material loading, morphology, electrode coverage, and thermal coupling are essential for reliable datasets and transferable AI models. Finally, key challenges are discussed, including dataset heterogeneity, long-term drift, edge deployment, and material–device reproducibility. This review highlights that future AI-assisted MOS/MEMS gas sensors require coordinated design of sensing materials, device platforms, fabrication processes, operating protocols, and data-driven models. Full article

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26 pages, 15695 KB

Open AccessArticle

Impacts of Urbanization on Compound Heat and Drought Events in the Beijing–Tianjin–Hebei Region Based on Explainable Machine Learning

by Ping Jiang, Jianjun Wu, Lei Zhou, Ruimeng Tang, Jianhua Yang and Minghui Lu

Land 2026, 15(9), 1649; https://doi.org/10.3390/land15091649 (registering DOI) - 5 Sep 2026

Abstract

Compound heat and drought events (CHDEs) are occurring more frequently due to climate change. However, the role of urbanization as a key driver of climate change in modulating these events remains poorly quantified. Hence, this study evaluates the impacts of urbanization on CHDE [...] Read more.

Compound heat and drought events (CHDEs) are occurring more frequently due to climate change. However, the role of urbanization as a key driver of climate change in modulating these events remains poorly quantified. Hence, this study evaluates the impacts of urbanization on CHDE frequency, duration, and severity using a daily scale analytical framework, and further quantifies the key influencing factors contributing to these impacts using explainable machine learning. The results revealed that: (1) the urban expansion rates ranged from 0.06% to 22.92% per decade in the Beijing–Tianjin–Hebei (BTH) region. Concurrently, the frequency, duration, and severity of CHDEs exhibited overall upward trends, with rates of 0.11, 1.45, and 0.06 per decade, respectively. (2) Urban stations exhibited more apparent upward trends in the frequency, duration, and severity of CHDEs than rural stations. Urbanization contributed to these increases in CHDEs, with its greatest contribution to duration (44.0%), followed by severity (39.1%) and frequency (33.6%). (3) The explainable machine learning analysis revealed that the attributes of CHDEs are driven by multiple urban and climatic factors under urbanization. While enhanced Tmean and UHI consistently intensified CHDEs, changes in urban underlying surfaces manifest complex non-linear relationships with CHDE attributes. Notably, BV and UrbF amplified the duration and severity of CHDEs more strongly than frequency. These findings suggest that urbanization may primarily amplify the duration and severity of CHDEs through enhanced thermal conditions and surface modification, highlighting the need to prioritize heat mitigation and urban land-use regulation in climate adaptation planning. Full article

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29 pages, 11025 KB

Open AccessArticle

Nucleosome Assembly Protein 1 in Dinoflagellate Cells Without Architectural Nucleosomes

by Kosmo Ting Hin Yan, Alvin Chun Man Kwok, Shaoping Wen, Fang Zhang and Joseph Tin Yum Wong

Int. J. Mol. Sci. 2026, 27(17), 7931; https://doi.org/10.3390/ijms27177931 (registering DOI) - 5 Sep 2026

Abstract

Nucleosome assembly protein 1 (NAP1) is highly conserved across eukaryotes, yet its biochemical function, particularly its proposed role as a histone chaperone, remains unresolved. Dinoflagellates, including Karenia brevis (Kb) and Crypthecodinium cohnii (Cc), lack architectural nucleosomes and express core [...] Read more.

Nucleosome assembly protein 1 (NAP1) is highly conserved across eukaryotes, yet its biochemical function, particularly its proposed role as a histone chaperone, remains unresolved. Dinoflagellates, including Karenia brevis (Kb) and Crypthecodinium cohnii (Cc), lack architectural nucleosomes and express core histones at unusually low levels, yet retain abundant NAP1 transcripts encoding two to three distinct homologs. Confocal immunolocalization of K. brevis showed strong nuclear signals for both homologs, between chromosomes and at the nucleolus, with higher nuclear-to-cytoplasmic ratios in G₂ than in G₁ (the two gap phases of the cell cycle); labeling at chromosome-territory margins and at the nuclear cortex is consistent with an association with the telomeric nucleosomes anchored to the nuclear envelope. Recombinant KbNAP1Bp reproduced the canonical yeast NAP1 fold, recovered H2A-immunoreactive material in immunoprecipitation, and preferentially retarded larger DNA fragments in gel mobility assays, whereas KbNAP1Ap did none of these under the conditions tested. In C. cohnii, the anti-NAP1-reactive protein peaked at S–G₂, and exposure to a CcNAP1.1-antisense oligodeoxynucleotide (ODN) was associated with an S–G₂ delay. These findings uncouple NAP1 abundance from the availability of a canonical nucleosomal substrate and suggest evolutionary repurposing toward non-nucleosomal roles in chromosome-territory organization. They help define the minimal functional core of this conserved chaperone family and caution against treating NAP1 abundance as a proxy for nucleosome assembly activity. Full article

(This article belongs to the Section Molecular Microbiology)

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18 pages, 16515 KB

Open AccessArticle

Construction and Characterization of an Attenuated Vaccine Vector Based on Cucumber Mosaic Virus RNA2

by Zhao Wang, Shanshan Liu, Mingjing Zhu, Jiagan Zhang, Xueyuan Wang, Zhifei Liu, Kaiqiang Hao, Shuyuan Tian, Xuefeng Yuan and Chengming Yu

Life 2026, 16(9), 1489; https://doi.org/10.3390/life16091489 (registering DOI) - 5 Sep 2026

Abstract

Plant viruses are major plant pathogens and account for nearly half of emerging plant diseases worldwide. To date, few effective management measures are available for the efficient control of plant viral diseases. Cross-protection based on attenuated vaccine is an effective strategy to prevent [...] Read more.

Plant viruses are major plant pathogens and account for nearly half of emerging plant diseases worldwide. To date, few effective management measures are available for the efficient control of plant viral diseases. Cross-protection based on attenuated vaccine is an effective strategy to prevent plant viral diseases. The primary requirement for the development of attenuated vaccines is a vector with excellent characteristics, such as low pathogenicity, genetic stability, and the capacity for stable insertion of exogenous fragments. In this study, the cucumber mosaic virus (Fny strain) was genetically modified to serve as an attenuated vaccine vector. Based on pre-termination of the 2b protein-coding region and deletion of the 3′ UTR in CMV RNA2, six RNA2 mutants, designated R2-2bPTI, R2-2bPTII, R2-2bPTIII, R2-2bPTIV, R2-2bPTV, and R2-2bPTVI, were constructed. Experiments with different lengths tobacco phytoene desaturase (PDS) fragment insertion evaluated the capacity of each mutant to accommodate exogenous fragment. Based on the R2-2bPTIV, a viral fragment insertion mutant R2-2bPTIV-TMPYTVPX targeting cucumber mosaic virus (CMV), tobacco mosaic virus (TMV), potato virus Y (PVY), tobacco vein banding mosaic virus (TVBMV), and potato virus X (PVX) was constructed. This mutant provided effective cross-protection against these targeted virulent viruses. This study developed a series of CMV-based vaccine vector, providing materials and data for the development of plant viral diseases attenuated vaccines. Full article

(This article belongs to the Special Issue Plant Virus-Host Interactions: From Pathogenesis to Integrated Disease Management)

19 pages, 4126 KB

Open AccessArticle

Spatial Mineralogical and Geochemical Variations Across Mafic Dike–Country Rock Contacts in the Permian Nam Duk Formation, Thailand

by Vimoltip Singtuen, Juthatip Khonman and Burapha Phajuy

Minerals 2026, 16(9), 918; https://doi.org/10.3390/min16090918 (registering DOI) - 5 Sep 2026

Abstract

The emplacement of mafic dikes into carbonate-bearing sedimentary successions commonly produces localized mineralogical and geochemical variations in adjacent country rocks. However, the spatial distribution of these variations remains poorly documented in the Permian sedimentary successions of Thailand. The study investigates spatial mineralogical and [...] Read more.

The emplacement of mafic dikes into carbonate-bearing sedimentary successions commonly produces localized mineralogical and geochemical variations in adjacent country rocks. However, the spatial distribution of these variations remains poorly documented in the Permian sedimentary successions of Thailand. The study investigates spatial mineralogical and geochemical variations across intrusive rocks and adjacent sedimentary rocks in the Permian Nam Duk Formation, Phetchabun Province, Thailand. Petrographic observations and whole-rock geochemical analyses (XRF and ICP-MS), supported by qualitative XRD phase identification, were integrated to characterize mineral assemblages and whole-rock geochemistry. The intrusive rocks display porphyritic textures dominated by plagioclase and hornblende, whereas the adjacent country rocks are characterized by quartz, calcite, feldspar, clay minerals, and secondary alteration phases. Spatial variations in mineral assemblages are accompanied by changes in contents of some major oxides (SiO₂, Al₂O₃, Fe₂O₃, MgO, and CaO) and selected trace and rare earth elements. The sedimentary country rocks generally contain higher total REE concentrations, particularly La and Ce, whereas the contact-proximal sample shows values closer to the mafic dike. Site A shows the clearest spatial variations across the exposed mafic dike–country rock contact, whereas site B exhibits compositional variability associated with strongly altered porphyritic andesite and heterogeneous sedimentary rocks. The integrated results document localized mineralogical and geochemical variations across the investigated intrusive–sedimentary rock systems, although primary lithological heterogeneity and secondary alteration may also contribute to these patterns. Full article

(This article belongs to the Special Issue Mineralogical and Geochemical Characterization of Geological Materials, 3rd Edition)

17 pages, 4156 KB

Open AccessArticle

Sucnr1 Mediates Leukocyte–Endothelial Cell Interactions Induced by Tnfα

by Sandra Coll, Ana Jarén, Cristina Bauset, Dulce C. Macias-Ceja, Dolores Ortiz-Masiá, Jesús Cosín-Roger, María D. Barrachina and Sara Calatayud

Int. J. Mol. Sci. 2026, 27(17), 7930; https://doi.org/10.3390/ijms27177930 (registering DOI) - 5 Sep 2026

Abstract

Succinate is a metabolite involved in chronic inflammatory diseases, regulating macrophages, dendritic cells, and lymphocytes via its receptor SUCNR1 and through intracellular pathways. Our aim was to analyze whether the succinate–SUCNR1 axis modulates the leukocyte–endothelium interactions (L/EI) that mediate the formation of inflammatory [...] Read more.

Succinate is a metabolite involved in chronic inflammatory diseases, regulating macrophages, dendritic cells, and lymphocytes via its receptor SUCNR1 and through intracellular pathways. Our aim was to analyze whether the succinate–SUCNR1 axis modulates the leukocyte–endothelium interactions (L/EI) that mediate the formation of inflammatory foci in response to a ubiquitous pro-inflammatory cytokine (TNFα). L/EI were analyzed in murine cremasteric venules in vivo and between human umbilical endothelial cells (HUVECs) and peripheral blood mononuclear cells (PBMCs) in vitro. We observed that TNFα increased the expression of SUCNR1 and that the L/EI, the proinflammatory cytokines’ upregulation and the NF-κB activation that induced this cytokine were reduced in Sucnr1^−/− mice in comparison with WT mice. Intrascrotal injection of exogenous succinate did not induce significant proinflammatory effects per se but, combined with TNFα, allowed a Sucnr1-independent upregulation of pro-inflammatory cytokines. In vitro, the SUCNR1 antagonist NF-56-EJ40 prevented the interactions of PBMCs with TNFα-treated HUVECs. HUVECs incubated with exogenous succinate presented higher L/EI but a limited response to TNFα. SUCNR1 contributes to TNFα-induced leukocyte–endothelial interactions. However, exogenous administration of high concentrations of this succinate exerts a complex pattern of effects that may include anti-inflammatory actions. Full article

(This article belongs to the Special Issue Inflammation in Chronic Disease: Molecular Mechanisms and Signaling Pathways)

30 pages, 11935 KB

Open AccessArticle

DDGF-Net: A Novel Dual-Domain Generative-Discriminative Fusion Network for Gearbox Fault Diagnosis Under Strong Noise Conditions

by Ruihan Ma, Xuanyue Wang, Jiajun Cheng, Tao Xie, Shuo Li and Chaoge Wang

Machines 2026, 14(9), 1013; https://doi.org/10.3390/machines14091013 (registering DOI) - 5 Sep 2026

Abstract

In industrial scenarios, strong background noise can easily overwhelm the weak impulsive signatures of gearbox faults, leading to time-domain waveform distortion and frequency-domain spectral aliasing, which in turn degrades the feature extraction capability of conventional diagnostic models and significantly reduces their diagnostic accuracy [...] Read more.

In industrial scenarios, strong background noise can easily overwhelm the weak impulsive signatures of gearbox faults, leading to time-domain waveform distortion and frequency-domain spectral aliasing, which in turn degrades the feature extraction capability of conventional diagnostic models and significantly reduces their diagnostic accuracy and robustness. To overcome this limitation, a dual-domain generative–discriminative fusion network (DDGF-Net) is proposed for robust gearbox fault diagnosis under strong noise interference. The proposed framework consists of three collaborative components. Firstly, an improved conditional variational autoencoder (CVAE) integrating soft-threshold shrinkage and spectral consistency constraints is designed to perform joint time–frequency denoising and signal reconstruction, thereby preserving subtle fault characteristics while effectively suppressing noise. Secondly, parallel time-domain and frequency-domain encoding branches are constructed to extract transient fault impulses and fault characteristic frequencies, respectively, compensating for the inadequacy of single-domain feature representations. Thirdly, a lightweight bidirectional cross-attention mechanism is introduced to overcome the limitations of conventional fixed-weight fusion strategies, enabling dynamic adjustment of the interaction weights between dual-domain features according to the instantaneous noise intensity, thus maximizing the complementary value of cross-domain features. Extensive comparative experiments conducted on the Southeast University(SEU) gearbox dataset demonstrate that DDGF-Net achieves superior diagnostic performance and noise robustness over eight representative methods, particularly under strong noise interference, thereby validating its effectiveness and superiority in harsh diagnostic scenarios. Full article

(This article belongs to the Special Issue Trustworthy and Intelligent Systems for Machine Health Monitoring and Predictive Maintenance)

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36 pages, 787 KB

Open AccessArticle

Lexicon-Enhanced Fine-Grained Sentiment Classification for Online Social-Behavior Analysis

by Stavroula Kridera, Alaa Mohasseb and Andreas Kanavos

Appl. Sci. 2026, 16(17), 8849; https://doi.org/10.3390/app16178849 (registering DOI) - 5 Sep 2026

Abstract

Online social networks generate large volumes of textual data that reflect users’ opinions, affective expressions, and broader patterns of engagement and social behavior. However, natural language processing approaches frequently examine sentiment, trust-related signals, and behavioral indicators independently, limiting their ability to represent the [...] Read more.

Online social networks generate large volumes of textual data that reflect users’ opinions, affective expressions, and broader patterns of engagement and social behavior. However, natural language processing approaches frequently examine sentiment, trust-related signals, and behavioral indicators independently, limiting their ability to represent the multidimensional nature of online interaction. This study conducts a systematic comparative evaluation of lexicon-enhanced fine-grained sentiment classification using linguistic, message-level statistical, and lexicon-derived affective information across a common experimental framework. The empirical analysis combines TF–IDF features, word-count information, and sentiment indicators derived from TextBlob, SentiStrength, and VADER, while the broader multi-level organization is used to relate the resulting affective evidence to online social-behavior analysis. Fifteen classical machine learning algorithms and seven deep learning architectures are evaluated on a real-world Twitter dataset containing 41,157 COVID-19-related tweets labeled across five sentiment-intensity classes. The experimental evaluation considers four feature configurations and seven performance metrics, complemented by Friedman and post hoc Wilcoxon signed-rank tests. The results show that TextBlob provides modest improvements, SentiStrength produces broader and more consistent gains, and VADER yields the strongest overall performance. AdaBoost combined with VADER achieves the best results, with 93.16% accuracy, 93.20% macro F1, 93.27% balanced accuracy, and an MCC of 0.913, while the Dense Neural Network is the strongest deep learning model. These results demonstrate that lexicon-derived affective features can substantially strengthen fine-grained sentiment classification, although their effectiveness depends strongly on the learning algorithm used to exploit them. The empirical contribution of this study is confined to fine-grained sentiment classification, while trust-related and attachment-related dimensions are retained as higher-order interpretive constructs rather than directly predicted or empirically validated outcomes. Full article

(This article belongs to the Special Issue New Trends in Natural Language Processing, 2nd Edition)

33 pages, 1533 KB

Open AccessArticle

Integrating Universal Design for Learning, Challenge-Based Learning, and Generative AI in Teacher Education: A Participatory Action Research Study

by Arasay Padrón Alvarez and Odiel Estrada-Molina

Educ. Sci. 2026, 16(9), 1452; https://doi.org/10.3390/educsci16091452 (registering DOI) - 5 Sep 2026

Abstract

Teacher education incorporates generative artificial intelligence (GenAI) without developed inclusive pedagogical frameworks. This study contextually evaluates the Integrated Inclusive AI Challenge Model (MIIA-R). A concurrent mixed-methods design based on Participatory Action Research comprised three phases in a postgraduate programme and examined participation, engagement, [...] Read more.

Teacher education incorporates generative artificial intelligence (GenAI) without developed inclusive pedagogical frameworks. This study contextually evaluates the Integrated Inclusive AI Challenge Model (MIIA-R). A concurrent mixed-methods design based on Participatory Action Research comprised three phases in a postgraduate programme and examined participation, engagement, and pedagogical creativity in designing inclusive GenAI-mediated proposals. The sample included 83 students, 80 proposals, and 178 learning artefacts. An independent rater blinded to the hypotheses re-evaluated a stratified subsample (ICC = 0.84; weighted κ = 0.74–0.78). Although the overall rubric score exceeded the functional threshold (M = 3.29), this reflected proposal feasibility (M = 4.18) and curricular coherence (M = 3.62), while UDL integration (M = 2.88) and pedagogical use of GenAI (M = 2.39) remained below it; therefore, Hypothesis 1 received partial and limited support. Pedagogical creativity followed a non-linear trajectory and correlated with GenAI tool diversity in the final phase (ρ = 0.527, p < 0.001). Profile differences were significant, H(3) = 18.34, p < 0.001, ε² = 0.37; Dunn tests showed that multimodal integrated use differed from generative-only and no or minimal use, but not from guided instrumental use. The MIIA-R supported feasible proposals but not consistently deep inclusive, AI-mediated pedagogical integration. Full article

17 pages, 732 KB

Open AccessSystematic Review

Guidelines on Immunization of People with Chronic Neurological Disorders: A Systematic Review

by Giuseppina Lo Moro, Andreea Mihaela Butnaru, Carola Toffanin, Anastasia Cataldo, Simona Mazzeo, Manuela Martella, Giacomo Scaioli, Fabrizio Bert and Roberta Siliquini

Vaccines 2026, 14(9), 777; https://doi.org/10.3390/vaccines14090777 (registering DOI) - 5 Sep 2026

Abstract

Background: People with chronic neurological disorders may be vulnerable to severe outcomes from vaccine-preventable infections. However, immunization recommendations for these patients may be difficult to identify and apply. This systematic review aimed to identify and describe official guidelines on preventive active immunization for [...] Read more.

Background: People with chronic neurological disorders may be vulnerable to severe outcomes from vaccine-preventable infections. However, immunization recommendations for these patients may be difficult to identify and apply. This systematic review aimed to identify and describe official guidelines on preventive active immunization for individuals with chronic neurological disorders. Methods: This systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 and registered in the PROSPERO International prospective register of systematic reviews (CRD420251005848). Bibliographic databases (PubMed, Embase, Scopus) and grey literature sources were searched to identify official national or international clinical practice guidelines or comparable structured guidance documents providing recommendations relevant to chronic neurological disorders. The search was restricted to countries with a Human Development Index greater than 0.8, to allow comparison across broadly comparable healthcare and socioeconomic contexts. Data were extracted on document characteristics, neurological conditions addressed, vaccines covered, and vaccination-related recommendations. Results: Overall, 12 unique documents were included. Four were vaccination-focused documents including recommendations for neurological disorders, four were disease-management guidelines including vaccination-related recommendations, and four specifically addressed vaccination in selected neurological diseases. Guidance was unevenly distributed across countries, neurological conditions, and document types. Influenza and COVID-19 vaccination were the most consistently addressed vaccines. Multiple sclerosis was the condition with the most detailed guidance, especially regarding vaccination before disease-modifying therapies, live attenuated vaccines, vaccine timing in relation to immunosuppression or relapse, and protection of close contacts. Conclusions: Official immunization guidance for people with chronic neurological disorders remains limited and heterogeneous. Future guidelines should provide clearer and regularly updated recommendations to support vaccination assessment, treatment-sensitive planning, and multidisciplinary coordination. Full article

(This article belongs to the Special Issue Vaccines for the Vulnerable Population)

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11 pages, 2813 KB

Open AccessArticle

Prevalence of Babesia bigemina and Theileria orientalis in Domestic Cattle (Bos taurus) Across the Three Geo-Climatic Zones of Sri Lanka

by W. M. Gihani K. Weerasekara, W. M. Chathushka Dhananjaya, W. A. Bhagya Wanasinghe, Viskam Wijewardana, Richard Thiga Kangethe and Thilini A. N. Mahakapuge

Int. J. Mol. Sci. 2026, 27(17), 7929; https://doi.org/10.3390/ijms27177929 (registering DOI) - 5 Sep 2026

Abstract

Theileria orientalis and Babesia bigemina are hemoprotozoan parasites that adversely affect domestic cattle (Bos taurus) productivity and health worldwide. Rapid climatic changes in different geo-climatic zones observed over the past few years may have altered the distribution and transmission of tick-borne [...] Read more.

Theileria orientalis and Babesia bigemina are hemoprotozoan parasites that adversely affect domestic cattle (Bos taurus) productivity and health worldwide. Rapid climatic changes in different geo-climatic zones observed over the past few years may have altered the distribution and transmission of tick-borne pathogens and vectors. Though these parasites are reported in Sri Lanka in surveillance records, there is a limited understanding of their current distribution pattern. The present study aimed to determine the prevalence and genetic characterization of B. bigemina and T. orientalis in cattle from three geo-climatic zones of Sri Lanka during the period from January 2025 to March 2026. Out of 384 samples collected from animals (wet, n = 124; dry, n = 208; and intermediate, n = 52 zones) in Sri Lanka, the overall prevalence of 60.2% for T. orientalis and 7.6% for B. bigemina was revealed using PCR-based detection methods. The highest prevalence of T. orientalis was observed in the wet zone (86.3%), while the highest prevalence of B. bigemina was 17.3% in the intermediate zone. Co-infections were detected in 5.7% of cattle across all three zones. These results indicate the dominance of T. orientalis compared with B. bigemina in cattle in Sri Lanka. The observation of co-infections highlights the importance of vector control against vector-borne diseases in Sri Lanka. Full article

(This article belongs to the Section Molecular Biology)

16 pages, 1665 KB

Open AccessReview

Food Intelligent Quality and Safety Analysis: From Data-Driven to Data–Mechanism Hybrid-Driven Paradigm

by Zheng-Yong Zhang, Rui Zhang, Wen-Qi Yan and Min Sha

Foods 2026, 15(17), 3155; https://doi.org/10.3390/foods15173155 (registering DOI) - 5 Sep 2026

Abstract

In recent years, numerous studies have reported on intelligent analytical applications for food quality and safety. To identify the underlying patterns and development trends in this field, this paper presents a comprehensive review from the perspectives of both data-driven and mechanism-driven paradigms. Under [...] Read more.

In recent years, numerous studies have reported on intelligent analytical applications for food quality and safety. To identify the underlying patterns and development trends in this field, this paper presents a comprehensive review from the perspectives of both data-driven and mechanism-driven paradigms. Under the data-driven paradigm, detection modalities may involve either single-modal or multimodal approaches. By integrating measured detection data with appropriate intelligent learning algorithms, specific tasks for food quality or safety assessment can be achieved. Research efforts in this area encompass the development of detection techniques, optimization of measurement parameters, construction of high-dimensional spectral features, design of feature extraction methods, selection and tuning of algorithms, and formulation of multimodal data fusion strategies. This paradigm is characterized by high computational speed and superior prediction or classification efficiency. Nevertheless, it is constrained by several limitations, including poor model interpretability, limited extrapolation and generalization capabilities, and a heavy reliance on high-quality annotated data. In contrast, the data–mechanism hybrid-driven paradigm integrates physical laws and other prior knowledge as constraints that are deeply embedded into neural network training. By combining data-driven mining capabilities with theoretical prior knowledge, this approach achieves improved predictive performance and decision-making reliability. This paradigm offers notable advantages, such as enhanced interpretability, greater trustworthiness, improved data efficiency, and reduced computational costs. It is particularly well-suited for small-sample or data-sparse scenarios, and thus represents a promising and important direction for future research in this domain. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence, Machine Learning and Deep Learning in Food Safety Analysis and Quality Control)

14 pages, 692 KB

Open AccessArticle

Comparative Biochemistry of Wild and In Vitro-Propagated Melilotus officinalis: Phytochemical Composition, Antioxidant, and Antimicrobial Properties

by Gulmira Zhakupova, Ângela Liberal, Assem Sagandyk, Tayse F. F. da Silveira, Tania Pires, Aigerym Akhmetzhanova, Aknur Muldasheva, Anastassiya Tyurina and Lillian Barros

Life 2026, 16(9), 1488; https://doi.org/10.3390/life16091488 (registering DOI) - 5 Sep 2026

Abstract

Melilotus officinalis (L.) Lam. (yellow sweet clover) is a medicinally valuable Fabaceae species with recognized antioxidant and antimicrobial properties, yet the impact of cultivation system on its secondary metabolism remains poorly characterized for Central Asian populations. This study compared wild and in vitro-grown [...] Read more.

Melilotus officinalis (L.) Lam. (yellow sweet clover) is a medicinally valuable Fabaceae species with recognized antioxidant and antimicrobial properties, yet the impact of cultivation system on its secondary metabolism remains poorly characterized for Central Asian populations. This study compared wild and in vitro-grown Melilotus officinalis from northern Kazakhstan (Astana city), examining phenolic composition, organic acids, antioxidant capacity, and antimicrobial activity as functions of cultivation system. Hydroethanolic extracts were analyzed by HPLC-DAD-ESI-Orbitrap MS/MS and UFLC-PDA, while antioxidant activity was assessed by TBARS and ABTS assays and antimicrobial activity by broth microdilution against eight bacterial and two fungal strains. Thirteen phenolic compounds were tentatively identified, revealing higher total flavonoid content in in vitro plants, dominated by apigenin di-C-pentoside isomers and vicenin-3, whereas wild plants showed greater diversity of phenolic acids and flavonols, including kaempferol and quercetin glycosides. Despite lower total phenolics, wild extracts more effectively inhibited lipid peroxidation, while ABTS radical scavenging was comparable between sources, and antimicrobial effects were strain-specific. Oxalic acid was approximately three-fold higher in in vitro material, a biochemical feature relevant for downstream use. These findings indicate that cultivation system substantially shapes the secondary metabolite profile and bioactivity of this regionally important medicinal species. Full article

(This article belongs to the Section Plant Science)

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22 pages, 12511 KB

Open AccessArticle

Sensorless Contact Force Estimation and Adaptive Variable-Damping Compliant Control for Biomimetic Robotic Arm

by Yanwei Xie, Jiawen He and Yi Zhang

Biomimetics 2026, 11(9), 637; https://doi.org/10.3390/biomimetics11090637 (registering DOI) - 5 Sep 2026

Abstract

To address contact force estimation and compliant control for biomimetic robotic arms interacting with uncertain environments, an adaptive variable-damping impedance control method based on a fuzzy-controlled forgetting-factor strong tracking Kalman filter (FSKF) is proposed. The proposed method improves the conventional strong tracking Kalman [...] Read more.

To address contact force estimation and compliant control for biomimetic robotic arms interacting with uncertain environments, an adaptive variable-damping impedance control method based on a fuzzy-controlled forgetting-factor strong tracking Kalman filter (FSKF) is proposed. The proposed method improves the conventional strong tracking Kalman filter (SKF) by introducing a fuzzy control strategy to adaptively adjust the forgetting factor, thereby enhancing the filtering performance and improving the accuracy of contact force estimation. The estimated contact force is subsequently incorporated into an adaptive variable-damping impedance controller to achieve simultaneous contact force estimation and compliant control of the biomimetic robotic arm. During biomimetic robotic arm motion, the proposed controller utilizes the estimated contact force to adaptively regulate the damping coefficient, compensating for force-tracking errors caused by environmental uncertainties and thereby improving both force and position tracking performance. The simulation and experimental results demonstrate that the proposed adaptive variable-damping impedance controller has better force and position tracking accuracy compared with the conventional impedance controller. Compared with traditional methods, the estimation accuracy based on FSKF has improved by about 7.3%. These results demonstrate the potential of the proposed method for prosthetic systems and other applications involving compliant robot–environment interaction. Full article

(This article belongs to the Special Issue Human-Inspired Grasp Control in Robotics 2026)

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21 pages, 11564 KB

Open AccessArticle

Determining Jadeite and Omphacite in Fei Cui by Na/(Na+Ca) Atomic Ratio with a Semi-Quantitative FTIR Screening Method

by Ming Zhu, Taafee Long, Biqian Xing, Zurong Mo, Lu Yu and Mingqi Meng

Minerals 2026, 16(9), 917; https://doi.org/10.3390/min16090917 (registering DOI) - 5 Sep 2026

Abstract

Jadeite and omphacite, both pyroxene-group minerals, are the two most dominant component minerals in fei cui (a rock-origin gemstone that may be dominated by jadeite, omphacite, kosmochlor, or their intermediate compositions), and classifying jadeitic vs. omphacitic domains is key to identification, grading, and [...] Read more.

Jadeite and omphacite, both pyroxene-group minerals, are the two most dominant component minerals in fei cui (a rock-origin gemstone that may be dominated by jadeite, omphacite, kosmochlor, or their intermediate compositions), and classifying jadeitic vs. omphacitic domains is key to identification, grading, and evaluation. However, determining their proportion quantitatively often needs destructive analyses, which is not suitable for high-value fei cui samples. In this study, 29 fei cui samples were selected to obtain electron probe micro-analysis (EPMA) data and infrared reflectance spectra. We found that six characteristic peaks and the intensity ratio (I_B/I_C) near 1085–1066 cm⁻¹ and 963–946 cm⁻¹ showed strong linear correlations with the Na/(Na+Ca) atomic ratio in the jadeite–omphacite series of the studied fei cui, upon which an infrared spectroscopy semi-quantitative screening method was then developed. In this method, the I_B/I_C ratio from infrared spectra was derived to provisionally estimate the Na/(Na+Ca) atomic ratio according to statistical models; for jadeite (Na/(Na+Ca) atomic ratio > 0.8), its I_B/I_C ratio > 1.68, whereas for omphacite (Na/(Na+Ca) atomic ratio ≤ 0.8), its I_B/I_C ratio ≤ 1.68. This finding has implications for provisionally discriminating jadeitic from omphacitic domains non-destructively. Furthermore, by FTIR mapping using micro-FTIR, heatmaps based on the calculated I_B/I_C ratio at each scanned spot allow observation of the spatial distribution of jadeite-dominant and omphacite-dominant domains classified as jadeitic or omphacitic according to the Na/(Na+Ca) ratio, providing a semi-quantitative estimate of their mapped areal proportion on the polished surface. The method and its application were reinforced by micro-XRF mapping; Na and Ca elemental heatmaps show the same distribution in the same region, and would satisfy the increasing demand in fei cui testing. Full article

(This article belongs to the Special Issue Formation Study of Gem Deposits)

20 pages, 2144 KB

Open AccessArticle

Towards an Integrated Digital Product Management Framework

by Roman Adamik, Nikola Staffenova, Milan Kubina, Daniela Fedorova and Lenka Kyrisova

Adm. Sci. 2026, 16(9), 429; https://doi.org/10.3390/admsci16090429 (registering DOI) - 5 Sep 2026

Abstract

Product management plays a key role in the development and management of digital products, but the current professional literature does not provide a unified and practically usable framework that systematically integrates product strategy, product manager responsibilities, and the product development process. The aim [...] Read more.

Product management plays a key role in the development and management of digital products, but the current professional literature does not provide a unified and practically usable framework that systematically integrates product strategy, product manager responsibilities, and the product development process. The aim of the article is to analyze the role of the product manager, identify the main steps of the product management process, including the methods and analyses used, and propose an integrated framework based on empirical findings. The research was conducted using a qualitative approach through semi-structured interviews with product managers and practitioners. The results showed that the role of the product manager and its associated responsibilities vary significantly between organizations, while the product management process itself shows a high degree of similarity. Four main phases of the process were identified: product discovery, product ownership, product launch and commercialization, and product optimization. The differences were mainly reflected in the methods used, the analyses conducted, and the interpretation of selected product management concepts. The contribution of the article lies in proposing an integrated product management framework that connects relevant knowledge from literature with empirical findings and provides organizations with a systematic approach to managing the development of digital products. Full article

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