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27 pages, 10006 KB  
Article
Physics-Informed Digital Twin of a Milling System for Vibration Prediction and Surface Roughness Modeling
by Muhamad Aditya Royandi, Wei-Zhu Lin, Jui-Pin Hung, Yu-Sheng Lai and Zheng-Mou Su
Machines 2026, 14(5), 579; https://doi.org/10.3390/machines14050579 (registering DOI) - 21 May 2026
Abstract
The application of digital twin (DT) technology to intelligent machining shows promise, but its effectiveness in predicting vibration and assessing surface quality has not been thoroughly validated for widespread industrial use. This study presents a physics-informed predictive digital twin framework operating in an [...] Read more.
The application of digital twin (DT) technology to intelligent machining shows promise, but its effectiveness in predicting vibration and assessing surface quality has not been thoroughly validated for widespread industrial use. This study presents a physics-informed predictive digital twin framework operating in an offline or near-real-time predictive configuration for vibration prediction and surface roughness modeling in milling processes. Impact hammer testing was conducted to extract the dominant modal properties of the spindle–tool assembly, which were embedded into a Simulink-based dynamic framework to predict tool vibration under varying cutting conditions. Full-immersion slot milling experiments on AL6061 were performed for validation. Within all datasets, including training phase and validation phase, the predicted vibration amplitudes exhibit a coefficient of determination R2=0.94 with measured values. The overall MAPE and RMSE are about 10.39% and 0.234, respectively. Power-law regression-based surface roughness prediction models were subsequently established using cutting parameters and both measured and DT-predicted vibration features through logarithmic transformation and least-squares fitting. The results show that the roughness prediction model using vibration features predicted by the digital twin model achieved a correlation coefficient of approximately R2=0.84, with MAPE = 9.57% and RMSE = 0.16 μm, which is comparable to the predictive model based on experimentally measured vibration. These results indicate that, within the investigated machining conditions, the digital twin can provide vibration features suitable for surface roughness prediction, demonstrating its potential as a virtual sensing approach. This work advances digital twin applications from process monitoring toward predictive, quality-oriented machining systems and provides a foundation for adaptive parameter updating in intelligent manufacturing environments. Full article
(This article belongs to the Special Issue Intelligent Fault Diagnosis and Predictive Maintenance Systems: Advanced Methods for Industrial Equipment and Dynamic Operating Conditions)
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36 pages, 3657 KB  
Article
Hierarchical Sparse Neural Networks for Structure-Aware Ransomware Detection Under Distribution Shift
by Isaac Kofi Nti
Future Internet 2026, 18(5), 273; https://doi.org/10.3390/fi18050273 (registering DOI) - 21 May 2026
Abstract
Behavioral ransomware detection often achieves high accuracy under standard evaluation settings, but such results may not generalize under distribution shift or when previously unseen ransomware families are encountered. This study evaluates detection performance on the MLRan dataset, which contains 4880 samples from 64 [...] Read more.
Behavioral ransomware detection often achieves high accuracy under standard evaluation settings, but such results may not generalize under distribution shift or when previously unseen ransomware families are encountered. This study evaluates detection performance on the MLRan dataset, which contains 4880 samples from 64 ransomware families, using four evaluation protocols: stratified, temporal, family-disjoint, and open-set. The family-disjoint and open-set protocols were constructed at the family level to limit overlap between learned and held-out ransomware families. The study proposes the Hierarchical Sparse Neural Network (HSNN), a taxonomy-aligned model that uses group-level and branch-level gating to support structured interpretability and modality-level analysis. Compared with the FlatMLP baseline, HSNN achieved a slightly lower average macro-F1 score (0.9839 vs. 0.9860) but showed better calibration and lower model complexity. Specifically, HSNN reduced expected calibration error by 34.1% and parameter count by 42%. HSNN also showed slightly lower variability across random seeds and stable gate patterns. Under the open-set family protocol, HSNN achieved one of the strongest macro-F1 scores (0.9930 vs. 0.9913 for FlatMLP) using a maximum-softmax novelty baseline. Feature analysis indicates that string-based artifacts remain strong predictors, while the hierarchical structure distributes importance across multiple behavioral modalities. These results position HSNN as a competitive alternative to dense neural baselines when calibration, compactness, and structured interpretability are considered alongside macro-F1 performance. Full article
(This article belongs to the Special Issue Machine Learning and Internet of Things in Industry 4.0—2nd Edition)
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14 pages, 3344 KB  
Article
Persistent Near-Linear Relationship Between Global Stress and Mean Atomic Bond Strain in Metallic Glasses Despite Significant Local Nonaffine Displacements
by Tittaya Thaiyanurak and Donghua Xu
Materials 2026, 19(10), 2176; https://doi.org/10.3390/ma19102176 (registering DOI) - 21 May 2026
Abstract
Mean atomic bond strain (MABS), based on the globally averaged bond length, has recently emerged as a new strain metric that retains clear physical meaning even as severe atomic neighborhood reconstruction occurs. It has been shown to exhibit a nearly perfect linear relationship [...] Read more.
Mean atomic bond strain (MABS), based on the globally averaged bond length, has recently emerged as a new strain metric that retains clear physical meaning even as severe atomic neighborhood reconstruction occurs. It has been shown to exhibit a nearly perfect linear relationship with global stress throughout the elastic and plastic deformation in single-crystal face-centered cubic (FCC) metals, contradicting conventional expectations based on nonlinear dislocation activity. Whether this near-linear relationship holds in other materials stands out as an important and intriguing question. In this study, we examine the MABS–stress relationship in representative unary, binary, and ternary metallic glasses (MGs), where neither a crystal structure nor dislocations are present. Large-scale molecular dynamics simulations of uniaxial tensile tests and statistical analysis of millions of atomic bonds are performed. Irrespective of their differing compositions, all the MGs exhibit a persistent near-linear relationship between total MABS (all bonds included) and global stress up to fracture, even in the presence of significant local nonaffine displacements (shear transformation zones and shear bands), with the Pearson correlation coefficient consistently exceeding 0.99. Unlike the nonaffine displacements, the spatial distribution of individual atomic bond strain does not localize under the uniaxial loading. In the MGs containing more than one element, MABS computed for a single bond type may not correlate as linearly with global stress as total MABS. The results demonstrate that the persistent near-linear total MABS–stress relationship over the entire deformation process, recently discovered in single-crystal FCC metals, also applies to MGs despite their vastly different atomic structures. This strengthens the candidacy of total MABS as a universal stress descriptor across materials classes and deformation regimes. With further development and implementation in atomistic simulations and constitutive modeling, the MABS concept has the potential to reshape our understanding of materials mechanics and generate new insights into the design of stronger, tougher, and more thermally and chemically stable materials. Full article
(This article belongs to the Special Issue Quality, Microstructure and Properties of Metal Alloys (Third Edition))
29 pages, 3491 KB  
Article
Generalized AUC Maximization Core Vector Machine: A Multi-Kernel Learning Approach for Fast Imbalanced Classification
by Yichen Sun, Min Wu, Erhao Zhou, Shitong Wang and Kai Zhu
Electronics 2026, 15(10), 2228; https://doi.org/10.3390/electronics15102228 (registering DOI) - 21 May 2026
Abstract
Imbalanced classification remains a fundamental challenge in machine learning, where the Area Under the ROC Curve (AUC) is widely used for threshold-independent ranking evaluation, especially in AUC maximization studies. Existing AUC maximization methods suffer from two critical limitations: they rely on single fixed [...] Read more.
Imbalanced classification remains a fundamental challenge in machine learning, where the Area Under the ROC Curve (AUC) is widely used for threshold-independent ranking evaluation, especially in AUC maximization studies. Existing AUC maximization methods suffer from two critical limitations: they rely on single fixed kernels that fail to capture complex data structures, and they incur prohibitive computational costs due to pairwise constraint construction. To address these issues, we propose the Generalized AUC Maximization Core Vector Machine (GAM-CVM), a fast imbalanced classification framework integrating multi-kernel learning with core vector machine optimization. Multiple affinity graphs are constructed from complementary perspectives and fused via cross-diffusion into a unified kernel matrix that respects the intrinsic data manifold. This fused kernel is embedded into a generalized AUC objective with a flexible ranking margin. Given the fused kernel matrix, the optimization stage of GAM-CVM achieves asymptotic linear time complexity with respect to the number of sample pairs under a fixed approximation accuracy by reformulating the learning objective as a center-constrained minimum enclosing ball problem. Extensive experiments demonstrate that GAM-CVM achieves the best overall average ranking and significantly outperforms most competing methods while maintaining the lowest optimization-stage running time. Full article
(This article belongs to the Special Issue Multimodal Learning for Multimedia Content Analysis and Understanding)
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15 pages, 3990 KB  
Article
Integrative Structural, Physiological, and Transcriptomic Analyses Reveal Key Determinants of Anthracnose Resistance in Rubber Tree (Hevea brasiliensis)
by Ling Xia, Peichun Li, Wenxiu Li, Meng Wang, Xiaoyu Liang and Yu Zhang
Forests 2026, 17(5), 629; https://doi.org/10.3390/f17050629 (registering DOI) - 21 May 2026
Abstract
Anthracnose, caused by Colletotrichum spp., is a major foliar disease limiting rubber tree (Hevea brasiliensis) productivity. To uncover resistance mechanisms, we compared resistant and susceptible germplasm using an integrated framework combining leaf structural analysis, physiological defense profiling, and transcriptome sequencing. Resistant [...] Read more.
Anthracnose, caused by Colletotrichum spp., is a major foliar disease limiting rubber tree (Hevea brasiliensis) productivity. To uncover resistance mechanisms, we compared resistant and susceptible germplasm using an integrated framework combining leaf structural analysis, physiological defense profiling, and transcriptome sequencing. Resistant germplasm exhibited lower stomatal density and more compact mesophyll, likely restricting pathogen entry and within-leaf spread. Following inoculation, resistant accessions showed stronger antioxidant responses, with higher activities of superoxide dismutase (SOD) and peroxidase (POD), and elevated phenylpropanoid-related enzymes, including polyphenol oxidase (PPO) and phenylalanine ammonia-lyase (PAL), peaking at 24–48 h post inoculation. These responses were accompanied by enhanced reactive oxygen species (ROS) accumulation (H2O2) but reduced lipid peroxidation (malondialdehyde), indicating efficient oxidative stress regulation. Microscopic observation revealed delayed infection progression and postponed differentiation of infection structures in resistant germplasm. Transcriptomic analysis further demonstrated that differentially expressed genes were mainly enriched in pathways related to signal transduction and secondary metabolism, particularly phenylpropanoid metabolism and related secondary metabolic pathways. Together, these results suggest that anthracnose resistance is mediated by coordinated structural barriers, redox homeostasis, and transcriptional regulation of defense networks. This study provides a mechanistic framework for resistance-oriented breeding and the utilization of resistant germplasm in rubber tree. Full article
(This article belongs to the Special Issue Adaptive Physiology of Forest Plants: Mechanisms, Strategies, and Responses to Environmental Challenges)
17 pages, 1446 KB  
Article
A Point Cloud Registration Method Based on Triangular Mesh Features
by Wenguang Wang, Jinshuo Zhao, Changshun Yuan and Haoran Wang
Appl. Sci. 2026, 16(10), 5167; https://doi.org/10.3390/app16105167 (registering DOI) - 21 May 2026
Abstract
To address the issue where conventional initial registration methods combined with the Iterative Closest Point (ICP) algorithm are highly sensitive to initial parameters such as point cloud density and pose—often resulting in degraded accuracy or even misregistration—this paper proposes a Lidar point cloud [...] Read more.
To address the issue where conventional initial registration methods combined with the Iterative Closest Point (ICP) algorithm are highly sensitive to initial parameters such as point cloud density and pose—often resulting in degraded accuracy or even misregistration—this paper proposes a Lidar point cloud registration method integrating triangular mesh features. First, Crust Triangulation is employed to construct a triangular mesh from the input point cloud. Then, the keypoint extraction based on triangular meshes, termed KE-TM, is introduced. Subsequently, a Triangle Feature Histogram (TFH) is constructed as the feature descriptor. Based on this, an initial alignment method grounded in triangular meshes, referred to as TM-IA, is developed to achieve coarse registration of point clouds. Finally, the ICP algorithm is applied to refine the alignment. Comparative experiments conducted on incomplete Bunny point clouds demonstrate that the proposed KE-TM maintains a higher keypoint repeatability under reduced point cloud density. The combined TM-IA and ICP registration method can achieve rotation errors within 1° and translation errors within 1 mm under small initial pose deviations, while also maintaining robust performance under larger initial misalignments. Compared with traditional methods, the proposed method significantly reduces sensitivity to initial parameters and improves the accuracy. This method has certain practical significance for the precise alignment of 3D point clouds. Full article
17 pages, 403 KB  
Article
Student Professional Collaboration as a Contemporary Format for Knowledge Sharing and Conducting Research in the University Environment
by Rabiga Bazarbekova, Saule Yerkebayeva, Almash Turalbayeva, Azhara Yerkebayeva and Azhar Amangeldikyzy
Educ. Sci. 2026, 16(5), 813; https://doi.org/10.3390/educsci16050813 (registering DOI) - 21 May 2026
Abstract
This study aimed to describe the profile of professional collaboration among students in teacher-education programmes and to examine whether readiness for further collaboration is associated with prior experience. The work was conducted within a university grant at XXXXXXXXX and implemented as a descriptive–comparative [...] Read more.
This study aimed to describe the profile of professional collaboration among students in teacher-education programmes and to examine whether readiness for further collaboration is associated with prior experience. The work was conducted within a university grant at XXXXXXXXX and implemented as a descriptive–comparative study based on a posttest cross-sectional snapshot with no baseline measurement. Data were collected via Google Forms from 91 students of the Department of Primary Education (Years 1–4). The questionnaire covered collaboration experience (yes/no), frequency of participation in joint projects, perceived value of collaboration (1–5), perceived impact on the learning experience, readiness to participate in joint research/projects in the future (1–5), and open-ended questions on motivations, barriers, and expected university support. Prior collaboration experience was reported by 40.7% of respondents; participation was predominantly irregular (48.4% “never”, 44.0% “rarely”). Perceived value was high (M = 4.05, SD = 1.15; Me = 4), and most respondents reported a positive contribution to their learning experience (75.8%). Readiness for future participation was moderately high (levels 4–5: 52.7%). A Mann–Whitney test indicated higher readiness among students with prior collaboration experience (U = 1288, p = 0.016, r = 0.29). Thematic grouping of open-ended responses showed that knowledge sharing and mutual support were the dominant motivations, while organisational/time and communication barriers were most frequently mentioned; the most commonly requested support measures included regular joint events and support for student communities. Findings are interpreted as a descriptive snapshot rather than causal evidence. The results may inform the design of facilitated collaboration formats and subsequent monitoring of student readiness. Full article
28 pages, 892 KB  
Article
System Quality, Perceived Compulsion, and Tax Literacy as Determinants of Continuous Usage Intention: Evidence from Indonesia’s Mandatory Coretax Platform
by Adi Prasetyo Tedjakusuma, Waiphot Kulachai, Phakawanaporn Phisuthisuwan and Andri Dayarana K. Silalahi
Informatics 2026, 13(5), 76; https://doi.org/10.3390/informatics13050076 (registering DOI) - 21 May 2026
Abstract
Governments worldwide are mandating digital tax platforms, yet little is understood about what sustains taxpayer engagement beyond legally compelled minimum use. This study extends the Technology Acceptance Model (TAM) with perceived compulsion and tax literacy to examine continuous usage intention toward Coretax, Indonesia’s [...] Read more.
Governments worldwide are mandating digital tax platforms, yet little is understood about what sustains taxpayer engagement beyond legally compelled minimum use. This study extends the Technology Acceptance Model (TAM) with perceived compulsion and tax literacy to examine continuous usage intention toward Coretax, Indonesia’s mandatory Core Tax Administration System. Using survey data from 535 active users analysed with PLS-SEM, six of eight hypotheses are supported: system quality drives perceived ease of use, which amplifies perceived usefulness, and both usefulness and user satisfaction independently predict continuous usage intention. Contrary to predictions derived from self-determination theory, perceived compulsion positively influences satisfaction, suggesting institutional acceptance of a mandate redirects evaluative attention toward system performance rather than generating resistance. Tax literacy does not moderate the usefulness–continuance pathway but independently increases engagement intentions, pointing to literacy programmes as direct engagement levers rather than amplifiers. These findings extend TAM into mandatory post-adoption contexts and propose institutional acceptance as a boundary condition for coercion theory in IS research. Full article
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24 pages, 602 KB  
Review
Integrating Envirotyping and Phenomics for AI-Enabled Multi-Environment Genomic Prediction in Crop Breeding
by Xiongwei Liang, Shaopeng Yu, Yongfu Ju, Yingning Wang and Dawei Yin
Agronomy 2026, 16(10), 1019; https://doi.org/10.3390/agronomy16101019 (registering DOI) - 21 May 2026
Abstract
Genomic prediction is now routine in crop improvement, but its main bottleneck has shifted from marker density to environmental complexity. Breeders rarely need predictions for one fixed environment; they need to rank genotypes across target populations of environments that differ in weather, soils, [...] Read more.
Genomic prediction is now routine in crop improvement, but its main bottleneck has shifted from marker density to environmental complexity. Breeders rarely need predictions for one fixed environment; they need to rank genotypes across target populations of environments that differ in weather, soils, management, and stress timing. This makes genotype-by-environment interaction a primary breeding problem rather than a secondary statistical nuisance. This review examines how genomic, environmental, and phenomic information can be integrated to improve multi-environment prediction in crop breeding pipelines. The review is narrative rather than PRISMA-style, but the literature search and selection logic were structured and explicitly defined. Peer-reviewed English-language studies were identified through structured searches of Web of Science Core Collection and Scopus, supplemented by backward citation screening, with emphasis on literature published from January 2023 to March 2026. Four conclusions emerge. First, environmental information is most useful when it is developmentally aligned, biologically interpretable, and matched to the target population of environments. Second, strong structured statistical baselines remain highly competitive, especially in moderate-sized or highly unbalanced datasets, whereas gains from more flexible machine-learning and deep-learning approaches are most evident in large, sparse, heterogeneous, and multimodal settings. Third, phenomic markers often improve prediction for complex traits, especially yield, because they capture realized crop responses not fully represented by markers alone. Fourth, practical value depends less on isolated gains in predictive accuracy than on evaluation under realistic deployment scenarios, including untested genotype and untested environment settings. Progress therefore requires transparent reporting, benchmark design, stage-aware envirotyping, multimodal integration, uncertainty reporting, and cost-aware deployment. Full article
(This article belongs to the Special Issue Precision Assistance for Crop Genetic Improvement: Big Data, Artificial Intelligence and Machine Learning)
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34 pages, 2789 KB  
Article
Investigation of the Impact of Household Energy Storage on DSO Grid Load Symmetry and Photovoltaic Energy Utilization Efficiency
by Laurynas Šriupša, Mindaugas Vaitkūnas, Artūras Baronas, Gytis Svinkūnas, Julius Dosinas, Saulius Gudžius and Gytis Vilutis
Symmetry 2026, 18(5), 879; https://doi.org/10.3390/sym18050879 (registering DOI) - 21 May 2026
Abstract
In this study, we investigate the impact of electric energy storage (EES) on phase line power flow symmetry and photovoltaic (PV) energy utilization in prosumer three-phase four-wire integrated household systems. The analysis is based on high-time-resolution (1 s) experimental data collected from a [...] Read more.
In this study, we investigate the impact of electric energy storage (EES) on phase line power flow symmetry and photovoltaic (PV) energy utilization in prosumer three-phase four-wire integrated household systems. The analysis is based on high-time-resolution (1 s) experimental data collected from a real household grid and subsequent simulations of energy flows using MATLAB/Simulink software. Two converter operation strategies were evaluated: the conventional symmetric mode and the asymmetric mode developed by the authors based on an adaptive power flow management algorithm. For both strategies, the impact of EES capacity on imbalance in the distribution system operator (DSO) grid was investigated. The methodology analyzes energy flows in each phase line separately, allowing for a detailed assessment of the imbalance between phase line phenomena and their impact on local energy consumption. Key performance parameters used for the efficiency evaluation include the self-consumption and self-sufficiency rates, which quantify the share of locally generated energy consumed within the household and the degree of independence from the DSO grid. The results show that combining adaptive asymmetric inverter control with appropriately sized energy storage allows for more efficient on-site utilization of PV energy, which, at the same time, improves the load symmetry of the phase lines in the DSO grid. Full article
(This article belongs to the Special Issue Power Supply-Demand Asymmetry and Power Quality Issues in High-Renewable Energy Power Systems)
24 pages, 2529 KB  
Article
Predicting the Potential Geographic Distributions of Two Large Predatory Insects, Microstylum dux and M. oberthurii (Diptera: Asilidae), Under Climate Change: A Comprehensive Analysis Based on Optimised Biomod2 Ensemble Model
by Zhuoman Zhang, Zhendong Gao and Hu Li
Insects 2026, 17(5), 533; https://doi.org/10.3390/insects17050533 (registering DOI) - 21 May 2026
Abstract
Climate change profoundly impacts insect distribution and ecological functions. For the predatory robber flies Microstylum dux and M. oberthurii (Diptera: Asilidae), clarifying their distribution and climatic responses is vital for natural enemy conservation and biological control. Using a parameter−optimized biomod2 ensemble model, we [...] Read more.
Climate change profoundly impacts insect distribution and ecological functions. For the predatory robber flies Microstylum dux and M. oberthurii (Diptera: Asilidae), clarifying their distribution and climatic responses is vital for natural enemy conservation and biological control. Using a parameter−optimized biomod2 ensemble model, we predicted their potential distributions under current and future climates, and analyzed key variables, centroid shifts, and niche dynamics. Current suitable habitats concentrate in southeast China and are scarce in the northwest. Future total suitable area remains stable but structurally reorganizes, with highly suitable habitats expanding and moderately suitable ones contracting. Key drivers are precipitation of the coldest quarter (bio19) and mean diurnal range (bio2). Habitat centroids migrate westward or southwestward with fluctuating range expansion. M. dux is a niche specialist (niche width = 0.257), while M. oberthurii is a generalist (niche width = 0.539). Their niche overlap shows non−linear “divergence−convergence−divergence” dynamics. This study supports natural enemy conservation and biological control strategy formulation. Full article
(This article belongs to the Special Issue Insects Ecology and Biological Control Applications)
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20 pages, 5811 KB  
Article
A Multimodal Time Point Labeling Approach for Analyzing Mastication and Swallowing Dynamics
by Jingjing Liu, Yuxuan Cao, Jiale Kuang, Zhongren Wei, Boyu Liu, Xianghao Wu, Bolin Shi, Lei Zhao, Dongfu Xu, Xinyu Wang and Kui Zhong
Biosensors 2026, 16(5), 301; https://doi.org/10.3390/bios16050301 (registering DOI) - 21 May 2026
Abstract
Mastication and swallowing are complex physiological processes involving the coordinated activity of multiple tissues in the oral cavity, facial region, and laryngeal system. Some detection methods suffer from limitations such as insufficient information acquisition and inadequate temporal feature analysis. To address these issues, [...] Read more.
Mastication and swallowing are complex physiological processes involving the coordinated activity of multiple tissues in the oral cavity, facial region, and laryngeal system. Some detection methods suffer from limitations such as insufficient information acquisition and inadequate temporal feature analysis. To address these issues, this study proposes a conceptual method for analyzing the state of masticatory and swallowing movements. It integrates maxillofacial electromyographic (EMG) signals with laryngeal movement signals. The goal is to preliminarily explore state analysis of masticatory and swallowing movements over time. A designed gain-adjustable conditioning circuit processes and acquires these signals: maxillofacial EMG signals from EMG electrodes and laryngeal movement signals from flexible PVDF piezoelectric sensors. These two signal streams complement each other’s missing information, enabling comprehensive detection of the state of masticatory and swallowing movements. To address time-point labeling in mastication and swallowing, a sliding-window-based dispersion calculation method was employed to extract characteristic signal nodes, which were then accurately associated with their corresponding physiological motion states. We combined temporal features such as the zero point, onset of fluctuations, characteristic peaks, and baseline recovery from electromyographic (EMG) signals and laryngeal movement signals. This allowed us to establish a correspondence between key time points in the mastication and swallowing processes. The coefficient of determination (R2) for the pressure–voltage linear fit of the PVDF flexible piezoelectric sensor was 0.99446. The pressure resolution was approximately 0.08 kPa. Response times were no more than 15 ms for the EMG channel and no more than 10 ms for the PVDF pressure channel. These results indicate that this method is feasible for extracting oral movement time parameters in healthy subjects. Full article
(This article belongs to the Section Biosensor and Bioelectronic Devices)
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30 pages, 5964 KB  
Article
Single-Cell Landscape Change in Cervical Epithelial Cells and Microenvironment During the Transformation from CINIII to Cervical Squamous Cell Carcinoma
by Yaomei Ma, Su Zhang, Bei Liu, Yibo Liu, Yuchao He, Wenchen Gong, Wenshuai Chen, Lisha Qi, Ke Wang and Hua Guo
Cancers 2026, 18(10), 1674; https://doi.org/10.3390/cancers18101674 (registering DOI) - 21 May 2026
Abstract
Background: The rising incidence of CINIII, particularly in younger patients, has highlighted limitations of current surgical treatments, which can affect fertility and carry recurrence risks. This underscores an urgent clinical need for non-invasive therapies. Our study addresses this by investigating the cellular and [...] Read more.
Background: The rising incidence of CINIII, particularly in younger patients, has highlighted limitations of current surgical treatments, which can affect fertility and carry recurrence risks. This underscores an urgent clinical need for non-invasive therapies. Our study addresses this by investigating the cellular and molecular changes during CINIII progression to cervical squamous cell carcinoma (CSCC). Methods: We employed single-cell sequencing to meticulously analyze cell types and molecular mechanisms within cervical epithelial cells and their microenvironment throughout the CINIII-to-CSCC transition. Results: Key findings include the identification of Sox2 and its signaling pathway as markers for specific cervical stem cells (CCSCs) during malignant transformation. In the microenvironment, upregulated VWF, MMP2, and HTRA1 were observed in vascular endothelial cells, while TXNIP+ and ARL4D+ fibroblasts underwent transformation into myofibroblasts. Immune cell proportions notably increased, particularly macrophages, T cells, B cells, NK cells, mast cells, and neutrophils, contrasting with a decrease in non-immune cells. Furthermore, interaction analysis revealed that communication between macrophages and cervical epithelial cells was the most prominent. Conclusions: This research comprehensively details the complex cellular and molecular remodeling inherent in CINIII progression. By pinpointing specific pathways and cell populations, our findings establish a crucial framework for developing innovative, non-invasive drug therapies to delay disease progression and ultimately improve long-term reproductive outcomes for patients. Full article
(This article belongs to the Section Molecular Cancer Biology)
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16 pages, 8104 KB  
Article
Effect of Curdlan on the Structural Stability and Thermal Processing Properties of Mycelium-Based Gels Used in 4D-Printed Meat Analogs
by Xin Hu, Jingyu Wang, Haijin Tang, Xinlian Su, Lifang Zou and Baocai Xu
Gels 2026, 12(5), 453; https://doi.org/10.3390/gels12050453 (registering DOI) - 21 May 2026
Abstract
This study investigated the effects of curdlan (CUR) on the structural stability and thermal processing properties of Pleurotus eryngii mycelium–soy protein isolate–cassava starch gels used as bio-ink scaffolds for 4D-printed meat analogs. Bio-inks containing different CUR concentrations (0–5%, w/w) were [...] Read more.
This study investigated the effects of curdlan (CUR) on the structural stability and thermal processing properties of Pleurotus eryngii mycelium–soy protein isolate–cassava starch gels used as bio-ink scaffolds for 4D-printed meat analogs. Bio-inks containing different CUR concentrations (0–5%, w/w) were prepared, and their rheological properties, 3D printability, microstructure, and water distribution were systematically evaluated. The fermented meat analogs were then subjected to steaming and baking to assess cooking loss, dimensional shrinkage, and textural properties. The results showed that CUR significantly increased the yield stress and structural recovery of the bio-inks while maintaining high height retention (>87%), thereby providing a favorable scaffold for mycelial growth and subsequent product formation. During thermal processing, CUR effectively mitigated structural collapse, which may be attributed to its heat-induced thermally irreversible gelation and the formation of an internal supporting network that resisted matrix contraction and dehydration. In particular, the addition of 5% CUR reduced cooking loss from 12.83% to 7.35% during steaming and from 42.52% to 38.59% during baking, while reducing shrinkage to 9.29% and 18.00%, respectively. In addition, hardness, springiness, and chewiness were significantly improved after cooking. Overall, CUR functioned not only as a rheological modifier for extrusion printing but also as a heat-activated internal supporting network during cooking, owing to its thermally irreversible gelation. Full article
(This article belongs to the Special Issue Application of Composite Gels in Food Processing and Engineering)
18 pages, 4060 KB  
Article
Material and Dye Characterization of Ottoman Ceremonial Silk Caftans from the Topkapı Palace Museum
by Recep Karadag
Textiles 2026, 6(2), 64; https://doi.org/10.3390/textiles6020064 (registering DOI) - 21 May 2026
Abstract
Silk fabrics and caftans preserved in the Topkapı Palace Museum collection constitute a distinguished group of cultural heritage objects reflecting the advanced weaving technologies, refined metal-thread use, and sophisticated natural dyeing practices of Ottoman court textile production. In this study, selected ceremonial caftans [...] Read more.
Silk fabrics and caftans preserved in the Topkapı Palace Museum collection constitute a distinguished group of cultural heritage objects reflecting the advanced weaving technologies, refined metal-thread use, and sophisticated natural dyeing practices of Ottoman court textile production. In this study, selected ceremonial caftans attributed to five Ottoman sultans were examined through a multidisciplinary and multi-analytical approach to characterize their structural, chromatic, and chemical properties. Color characteristics were evaluated in the CIE L*a*b* color space, while yarn properties, weave structures, and production techniques were investigated by optical microscopy. The morphology and elemental composition of the metal threads were analyzed using scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM–EDX), and dyestuffs were identified by high-performance liquid chromatography with diode-array detection (HPLC–DAD). The results show that compound silk weaving structures were widely used in Ottoman court textiles, metal threads were predominantly silver-based and often gold-gilded, and dyestuffs with high fastness properties were preferentially selected. The revised manuscript situates these findings within a broader international literature on historical textile analysis and natural dye characterization, while using only a limited number of directly relevant studies from the authors’ previous work. The present study therefore provides new, object-specific and comparable data for the scientific documentation, material characterization, and conservation-oriented understanding of Ottoman textile heritage. Full article
(This article belongs to the Special Issue Textiles in Cultural Heritage: Technology, Dyes and Conservation)
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31 pages, 2920 KB  
Article
An Efficient Reliability Analysis Method for Steel Structures Based on Support Vector Machines and Hyperparameter Optimization
by Yingshun Fang, Chengshu Yang, Cunpeng Liu and Dalian Bai
Appl. Sci. 2026, 16(10), 5165; https://doi.org/10.3390/app16105165 (registering DOI) - 21 May 2026
Abstract
To address the challenge of exorbitant computational costs in the reliability analysis of complex steel structures, which stems from the impact of multiple sources of uncertainty throughout their entire lifecycle, this paper presents a comparative evaluation of the explicit reconstruction of the Limit [...] Read more.
To address the challenge of exorbitant computational costs in the reliability analysis of complex steel structures, which stems from the impact of multiple sources of uncertainty throughout their entire lifecycle, this paper presents a comparative evaluation of the explicit reconstruction of the Limit State Function (LSF) using SVM combined with Hyperparameter Optimization (HPO) for structural reliability analysis under constrained computational budgets. Although traditional Monte Carlo simulation (MCS) exhibits high accuracy, it requires a substantial number of finite element calculations, rendering it difficult to satisfy the efficiency requirements of engineering projects. Conversely, the first-order and second-order reliability methods (FORM/SORM) offer high computational efficiency but rely on explicit limit state functions, posing challenges for their direct application to complex structural systems. Thus, this study initially acquires response samples of the structure under various combinations of random variables through a limited number of finite element analyses (FEA). Subsequently, it employs an SVM to develop a highly accurate equivalent explicit limit state function, which serves as a substitute for the original implicit limit state function. Finally, it integrates Monte Carlo simulation to efficiently evaluate the structure’s failure probability and reliability index. Meanwhile, to tackle the problem of SVM model performance being highly susceptible to hyperparameters, this study presents a comparative analysis of four strategies: Bayesian Optimization (BO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Random Search (RS), aiming to identify the optimal parameter combination and improve the model’s generalization capability. Through verification with four progressive examples, including linear, nonlinear, truss, and multistory frame structures, the results demonstrate that the proposed method can accurately characterize the nonlinearity of structural responses. The obtained failure probabilities and reliability indices are in close agreement with those obtained from the direct Monte Carlo simulation (MCS) and existing research. Moreover, while maintaining computational accuracy, the method significantly reduces computational costs, thereby providing an efficient and practical solution for structural reliability analysis in engineering practice. Full article
20 pages, 3156 KB  
Article
Dual Lactiplantibacillus plantarum-Derived Postbiotics Reduce Pathogens and Preserve the Quality of Goldenberry (Physalis peruviana L.) During Storage
by Diana Molina, Pamela Reyes, Yuleissy Cuamacas, Evelyn Angamarca, Clara Ortega, Renato Centeno and Gabriela N. Tenea
Foods 2026, 15(10), 1830; https://doi.org/10.3390/foods15101830 (registering DOI) - 21 May 2026
Abstract
Microbial contamination of fresh fruits remains a major food safety concern due to the ability of pathogenic bacteria to persist on fruit surfaces during storage. This study evaluated the antimicrobial efficacy of ExAF-E1, a postbiotic formulation derived from Lactiplantibacillus plantarum strains UTNGt28L and [...] Read more.
Microbial contamination of fresh fruits remains a major food safety concern due to the ability of pathogenic bacteria to persist on fruit surfaces during storage. This study evaluated the antimicrobial efficacy of ExAF-E1, a postbiotic formulation derived from Lactiplantibacillus plantarum strains UTNGt28L and UTNGt2, against multidrug-resistant Escherichia coli L1PEag1 and Staphylococcus epidermidis L4MStp5 on goldenberry (Physalis peruviana L.). Fruits were artificially contaminated, treated, and stored for 7 days at room temperature (RT) and refrigerated (4 °C), with analyses conducted in quadruplicate. At RT, ExAF-E1 significantly reduced total aerobic counts (TAC) and pathogen loads (p < 0.05), achieving early reductions of ~0.4–0.5 log CFU/g in TAC and ~1.0–1.5 log CFU/g in pathogens, with inhibition maintained through day 7. In contrast, the commercial disinfectant (CD) showed transient reductions, with microbial levels not significantly different from the control at later stages (p > 0.05). Under refrigeration, ExAF-E1 produced greater and persistent reductions, reaching ~1.0–1.2 log CFU/g in TAC and ~1.5–2.5 log CFU/g in pathogens by day 7 (p < 0.05), whereas CD exhibited strong initial reductions followed by partial regrowth. Fruit quality parameters (pH, TA, TSS, TPC, AOX, AAC) were not significantly affected by treatments (p > 0.05). Ultrastructural analyses using transmission and scanning electron microscopy revealed disruption of bacterial cell envelope integrity, including membrane damage, cytoplasmic leakage, and morphological deformation. These findings demonstrate that ExAF-E1 provides rapid and sustained antimicrobial activity under both storage conditions while preserving fruit quality, supporting its application as a postharvest strategy for improving the microbial safety of fresh produce. Full article
(This article belongs to the Section Food Microbiology)
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28 pages, 2948 KB  
Article
Easy Synthesis of a Multifunctional Macrophotoinitiator with Pendant Moieties of Benzoin Methyl Ether Derivative for Use as Active Surface-Modifier of Inorganic Fillers
by Halyna Ohar, Maria Tokareva and Viktor Tokarev
Polymers 2026, 18(10), 1265; https://doi.org/10.3390/polym18101265 (registering DOI) - 21 May 2026
Abstract
A novel macromolecular photoinitiator (MPI) was synthesized from a copolymer of maleic anhydride and methyl methacrylate and subsequently functionalized with 3-hydroxy-2-methoxy-1,2-diphenylpropan-1-one moieties via a polymer-analogous acylation reaction. The structure and physicochemical properties of the MPI were characterized by IR, UV–Vis, NMR, DSC, and [...] Read more.
A novel macromolecular photoinitiator (MPI) was synthesized from a copolymer of maleic anhydride and methyl methacrylate and subsequently functionalized with 3-hydroxy-2-methoxy-1,2-diphenylpropan-1-one moieties via a polymer-analogous acylation reaction. The structure and physicochemical properties of the MPI were characterized by IR, UV–Vis, NMR, DSC, and TGA analyses. TiO2 nanoparticles were successfully functionalized with the MPI, yielding materials with enhanced surface activity and photoinitiating efficiency. The MPI-modified TiO2 facilitated efficient UV-induced polymerization of methyl methacrylate, as confirmed by DLS and SEM analyses. Compared with unmodified fillers, the resulting composites exhibited improved dispersion, accelerated polymerization rates, and enhanced mechanical properties. This hybrid strategy offers a promising approach for the development of high-performance polymer nanocomposites through the integration of surface-engineered inorganic fillers and photoreactive polymers. Full article
(This article belongs to the Section Polymer Chemistry)
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9 pages, 7113 KB  
Case Report
Non-Surgical Management of Scrotal Extramammary Paget Disease: A Case Report of a Cutaneous Malignancy Treated with Depth-Guided Superficial Radiation Therapy
by Douglas Jaxon Vadner and Sidney Smith
Reports 2026, 9(2), 163; https://doi.org/10.3390/reports9020163 (registering DOI) - 21 May 2026
Abstract
Background and Clinical Significance: Extramammary Paget disease (EMPD) is a rare cutaneous adenocarcinoma that frequently involves apocrine-rich regions and may extend beyond clinically apparent margins through adnexal structures. Surgical excision remains the standard of care; however, management can be challenging in elderly patients [...] Read more.
Background and Clinical Significance: Extramammary Paget disease (EMPD) is a rare cutaneous adenocarcinoma that frequently involves apocrine-rich regions and may extend beyond clinically apparent margins through adnexal structures. Surgical excision remains the standard of care; however, management can be challenging in elderly patients and in anatomically sensitive areas such as the scrotum, where morbidity and functional impairment are significant concerns. Despite increasing use of radiation-based therapies, optimal superficial radiation therapy (SRT) parameters, particularly with respect to depth of penetration, remain poorly standardized. Case Presentation: An 88-year-old male with a history of melanoma, non-melanoma skin cancer, and remote prostate cancer presented with biopsy-proven EMPD involving the scrotum and perineum. Imaging demonstrated no evidence of underlying or metastatic malignancy. Given lesion size (9 × 4 cm), anatomic location, and patient preference to avoid surgery, SRT was selected. The patient underwent treatment with 70 kV energy, delivering a total dose of 5440 cGy in 17 fractions (320 cGy per fraction) administered twice weekly. Energy selection was guided by the known propensity of EMPD for adnexal extension, with the aim of improving treatment coverage of potential subclinical disease. Conclusions: This case highlights the importance of incorporating tumor depth and adnexal involvement into treatment planning for EMPD. Depth-guided SRT may represent a viable non-surgical management strategy in carefully selected patients, particularly when surgical morbidity is a concern. These findings support a more individualized, mechanism-based approach to optimizing radiation therapy in cutaneous malignancies. Full article
(This article belongs to the Section Dermatology)
20 pages, 774 KB  
Review
Exercise-Related Glycemic Fluctuations in Type 1 Diabetes: Mechanisms and Integrated Insulin–Carbohydrate Strategies in the Context of Diabetes Technologies
by Filomena Mazzeo, Gabriele Ferrara, Fiorenzo Moscatelli, Antonietta Monda, Antonietta Messina, Maria Ruberto, Nicola Mancini, Raffaele Ivan Cincione, Gianluca Russo, Salvatore Allocca, Marco La Marra, Pasquale Perrone, Girolamo Di Maio, Maria Casillo, Giovanni Messina, Mario Ruggiero, Maria Giovanna Tafuri and Vincenzo Monda
Endocrines 2026, 7(2), 22; https://doi.org/10.3390/endocrines7020022 (registering DOI) - 21 May 2026
Abstract
Background/Objectives: Regular physical exercise is strongly recommended for individuals with type 1 diabetes mellitus (T1DM) because of its beneficial effects on cardiovascular fitness, insulin sensitivity, metabolic control, and overall health. Nevertheless, participation in physical activity remains limited, largely due to the fear [...] Read more.
Background/Objectives: Regular physical exercise is strongly recommended for individuals with type 1 diabetes mellitus (T1DM) because of its beneficial effects on cardiovascular fitness, insulin sensitivity, metabolic control, and overall health. Nevertheless, participation in physical activity remains limited, largely due to the fear of exercise-induced hypoglycemia and glycemic instability. Glycemic responses to exercise in T1DM are influenced by the interaction between exercise modality, circulating insulin levels, nutritional status, and diabetes technologies. Continuous aerobic exercise, resistance training, high-intensity interval exercise, and mixed intermittent activities elicit distinct metabolic and hormonal responses, resulting in heterogeneous glycemic trajectories. This narrative review aimed to provide a clinically oriented synthesis of the physiological mechanisms underlying exercise-related glycemic fluctuations in T1DM and to discuss integrated insulin- and carbohydrate-based strategies to support safer participation in physical activity in the context of modern diabetes technologies. Methods: A structured narrative review was conducted using PubMed/MEDLINE, Scopus, and complementary searches in Google Scholar to identify experimental studies, observational studies, systematic reviews, consensus statements, and clinical guidelines focused on exercise-related glycemic responses in individuals with T1DM. Only articles published in English were considered. Evidence was selected and synthesized according to relevance to exercise modality, insulin therapy strategies, carbohydrate management, and diabetes technologies, including continuous glucose monitoring, continuous subcutaneous insulin infusion, and automated insulin delivery systems. The final narrative synthesis was based on 44 selected studies, reviews, consensus statements, and guidance documents considered most relevant to the objectives of this narrative review. Results: Available evidence indicates that continuous moderate-intensity aerobic exercise is most consistently associated with progressive glucose declines and increased risk of hypoglycemia, particularly when performed in the presence of elevated insulin on board. In contrast, resistance exercise and short-duration high-intensity or anaerobic exercise more frequently induce stable glycemia or transient hyperglycemia through adrenergic stimulation and increased hepatic glucose output. Mixed and intermittent exercise modalities often produce more variable responses depending on exercise sequencing, nutritional status, and insulin exposure. Across studies, integrated adjustment of basal and prandial insulin doses together with individualized carbohydrate supplementation emerged as the most effective strategy to reduce exercise-related glycemic instability. Continuous glucose monitoring and insulin pump technologies improved glucose trend awareness and management flexibility; however, physical exercise remains a challenging condition for current automated insulin delivery algorithms and still requires active user-driven decision-making. Conclusions: Exercise management in T1DM should be based on an individualized interpretation of exercise modality, glucose trends, insulin exposure, and nutritional context rather than on fixed glucose thresholds alone. Combining anticipatory insulin adjustments, tailored carbohydrate strategies, and appropriate use of diabetes technologies may substantially reduce glycemic variability and improve confidence toward physical activity participation. Structured education and individualized clinical guidance remain essential to translate physiological knowledge into effective real-world exercise management. Full article
(This article belongs to the Special Issue Recent Advances in Type 1 Diabetes)
33 pages, 2908 KB  
Review
Synergistic Effects of Air Pollutants and Extreme Temperature on Asthma: A Narrative Review of Mechanisms and Evidence
by Guanlin Li, Junliang Chen, Ao Wang, Shunjie Hao, Charles Obinwanne Okoye, Yueru Qiao, Yu Cheng, Hui Liang, Linjing Deng and Xunfeng Chen
Toxics 2026, 14(5), 452; https://doi.org/10.3390/toxics14050452 (registering DOI) - 21 May 2026
Abstract
Global climate change and air pollution jointly threaten respiratory health. Asthma, a prevalent chronic inflammatory airway disease, is exacerbated by both traditional air pollutants such as particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO [...] Read more.
Global climate change and air pollution jointly threaten respiratory health. Asthma, a prevalent chronic inflammatory airway disease, is exacerbated by both traditional air pollutants such as particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and emerging contaminants like microplastics (MPs) and per- and polyfluoroalkyl substances (PFAS), with effects amplified under extreme temperature conditions. In reality, individuals face complex combined exposures, yet the synergistic effects of these factors on asthma pathogenesis remain poorly understood. This narrative review synthesizes epidemiological and toxicological evidence. It aims to elucidate both the individual and the notably synergistic effects of these factors on asthma pathogenesis. The central mechanistic pathway is initiated by oxidative stress, which activates key inflammatory signaling pathways, thereby driving immune imbalance and airway inflammation. Our review underscores that the combined exposure to traditional pollutants, emerging pollutants, and extreme temperatures may pose a greater threat than individual factors. These findings underscore the critical need for an integrated perspective in asthma research and public health policy. Moving beyond single-pollutant approaches, we advocate for combinatorial risk assessment and synergistic intervention strategies to effectively mitigate the growing burden of asthma in a changing climate. Full article
(This article belongs to the Special Issue Air Pollution Monitoring and Epidemiology)
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23 pages, 27231 KB  
Article
Enhanced Composite Multi-Scale Slope Entropy and Its Application to Fault Diagnosis of Rolling Bearing
by Wei Li, Jiazhu Li, Shuyu Wang, Yan Chen and Jian Chen
Electronics 2026, 15(10), 2219; https://doi.org/10.3390/electronics15102219 (registering DOI) - 21 May 2026
Abstract
The health status of rolling bearings is critical to the normal operation of rotating machinery. To effectively extract vibration signal features and accurately identify different fault types, a novel method based on enhanced composite multi-scale slope entropy (ECMSE) and a honey badger algorithm-optimized [...] Read more.
The health status of rolling bearings is critical to the normal operation of rotating machinery. To effectively extract vibration signal features and accurately identify different fault types, a novel method based on enhanced composite multi-scale slope entropy (ECMSE) and a honey badger algorithm-optimized kernel extreme learning machine (HBA–KELM) is proposed. Specifically, ECMSE integrates high-order differences into the composite multi-scale framework to capture high-frequency information while preserving low-frequency characteristics, thereby enhancing the discriminability of time-series representations. Meanwhile, an average coarse-graining strategy is incorporated to achieve a more comprehensive characterization of the signals. The extracted features are then input into the HBA–KELM classifier for fault identification. Experiments conducted on two public and private rolling bearing datasets demonstrate that our method achieves superior performance in distinguishing different fault types and damage levels compared with several existing approaches. Full article
(This article belongs to the Special Issue Intelligent Sensing Empowered by Artificial Intelligence)
17 pages, 7307 KB  
Article
Potential of RNAi Targeting Juvenile Hormone Acid Methyltransferase (JHAMT) for Controlling Dendroctonus valens LeConte (Coleoptera: Scolytidae)
by Qin Cao, Yue Sun, Dejun Kong, Jinbin Han, Jianrong Wei and Jigang Li
Forests 2026, 17(5), 628; https://doi.org/10.3390/f17050628 (registering DOI) - 21 May 2026
Abstract
Dendroctonus valens LeConte represents a major invasive pest species in China. Both larvae and adults primarily feed on the phloem of the tree trunk base and roots, disrupting nutrient transport and leading to host tree mortality, which poses a severe threat to forest [...] Read more.
Dendroctonus valens LeConte represents a major invasive pest species in China. Both larvae and adults primarily feed on the phloem of the tree trunk base and roots, disrupting nutrient transport and leading to host tree mortality, which poses a severe threat to forest ecosystems and the forestry economy. Juvenile hormone acid methyltransferase (JHAMT) is a key enzyme in insect juvenile hormone (JH) biosynthesis. In this study, we identified a JHAMT-encoding gene, DvJHAMT, in D. valens via bioinformatic analysis. RT-qPCR analysis revealed that DvJHAMT is predominantly expressed during the egg and larval stages. In the fourth-instar larvae, the highest expression levels were observed in the head and epidermis, suggesting a central regulatory role during this critical developmental period. To investigate its function via RNA interference (RNAi), a nanomaterial, star polycation (SPc), was employed for the transdermal delivery of dsRNA into the fourth-instar larvae. The results demonstrated that DvJHAMT knockdown significantly downregulated mRNA levels, resulting in marked decreases in larval survival, pupation, and eclosion rates. Notably, treatment with 0.7 µg dsDvJHAMT-SPc resulted in a 96.67% mortality rate and a reduced pupation rate of 41.67% at 34 days post-treatment. Furthermore, RNAi led to developmental deformities and significant weight loss in larvae. ELISA assays confirmed that DvJHAMT silencing led to reduced JHAMT enzyme activity and JH III titers in a dose-dependent manner. In conclusion, our findings demonstrate that DvJHAMT plays a vital role in JH biosynthesis and that its suppression exhibits potent lethal effects, suggesting that DvJHAMT is a promising candidate for RNAi-based management of D. valens. Full article
(This article belongs to the Special Issue Advances in Wood Borer Control and Management)
12 pages, 5084 KB  
Article
A Randomized Intercept Survey Trial to Test the Effectiveness of Multiple Traffic Light Labels on Online Grocery Shopping Behaviors in Bahrain
by Soye Shin, Ali Shubbar Jawad, Buthaina Yusuf Ajlan, Fatema Ahmed Mohammed Isa, Amna Ghassan Alawadhi, Reem Alsukait and Eric A. Finkelstein
Nutrients 2026, 18(10), 1645; https://doi.org/10.3390/nu18101645 (registering DOI) - 21 May 2026
Abstract
Background/Objectives: Multiple Traffic Light (MTL) front-of-pack (FOP) labels are being considered in Bahrain. We tested whether an adapted MTL label improves the nutritional quality of grocery purchases. Methods: In a two-arm randomized controlled intercept trial (January–May 2025), adults (≥21 years) responsible for household [...] Read more.
Background/Objectives: Multiple Traffic Light (MTL) front-of-pack (FOP) labels are being considered in Bahrain. We tested whether an adapted MTL label improves the nutritional quality of grocery purchases. Methods: In a two-arm randomized controlled intercept trial (January–May 2025), adults (≥21 years) responsible for household grocery shopping were recruited in high-footfall public venues and asked to complete a one-time shop on a tablet-based, purpose-built online grocery platform. The MTL label was adapted for Arabic reading direction and displayed per-serving nutrients and % recommended daily intake. Treatment effects were estimated using ordinary least squares regressions with robust standard errors and covariate adjustment. Results: Of 395 randomized participants, 360 were included in primary analyses (control n = 183; MTL n = 177). MTL exposure was not associated with a significant change in the primary outcome (basket weighted average MTL score per serving; β = 0.037; p = 0.64) or in per-serving calories and nutrients of concern (all p > 0.17). In the post-shop assessment, only 47.2% of participants correctly interpreted MTL labels, indicating modest objective label comprehension under the study conditions. Conclusions: These findings suggest that the impact of front-of-pack labels likely depends on both implementation features and consumer understanding, and that pairing labels with public communication and nutrition literacy initiatives may be necessary to maximize the effectiveness of labels in Bahrain and the wider Gulf region. Full article
(This article belongs to the Special Issue The Impact of Food Labeling on Food Choices and Eating Behaviors)
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20 pages, 455 KB  
Article
Lifestyle and Dietary Behaviors Are Associated with Body Mass Index in Romanian Young Adults
by Diana Crișan, Oleg Frumuzachi, Denisia Pașca, Laura Gavrilaș and Gianina Crișan
Nutrients 2026, 18(10), 1644; https://doi.org/10.3390/nu18101644 (registering DOI) - 21 May 2026
Abstract
Background/Objectives: Overweight and obesity are increasing globally. However, structured contemporary data on lifestyle behaviors and adiposity in Romanian young adults remain limited. Therefore, this study aimed to describe dietary and lifestyle habits, BMI, and overweight/obesity prevalence in Romanian adults aged 18–30 years and [...] Read more.
Background/Objectives: Overweight and obesity are increasing globally. However, structured contemporary data on lifestyle behaviors and adiposity in Romanian young adults remain limited. Therefore, this study aimed to describe dietary and lifestyle habits, BMI, and overweight/obesity prevalence in Romanian adults aged 18–30 years and to examine associations between these variables. Methods: This cross-sectional online questionnaire study included 1202 young Romanian adults. BMI was calculated from self-reported height and weight and analyzed continuously, as well as for overweight/obesity (BMI ≥25 kg/m2). Pre-specified exposures were compulsive eating, soft-drink intake, breakfast frequency, physical activity, and sleep duration. Multivariable linear regression with heteroscedasticity-consistent standard errors was used for BMI, and modified Poisson regression with robust variance was used for overweight/obesity. Composite dietary score, sex-interaction, and sensitivity analyses were also performed. Results: Mean age was 23.2 ± 3.3 years, mean BMI was 23.8 ± 4.2 kg/m2, and 32.4% of participants had overweight/obesity. Men had higher BMI and a higher prevalence of overweight/obesity than women. Compulsive eating and soft-drink intake showed dose-dependent associations with higher BMI and higher overweight/obesity prevalence. Short sleep duration (≤5 h/night) and daily breakfast consumption were associated with a higher and, respectively, lower prevalence of overweight/obesity. Physical activity showed no independent association after full adjustment, although this finding may be influenced by the use of a single self-reported item. Composite-score analyses supported the main findings. Conclusions: In Romanian young adults, compulsive eating and soft-drink intake were the most consistent behavioral correlates of adiposity, while breakfast regularity and short sleep showed threshold-type associations with overweight/obesity. These findings may inform the design of multicomponent prevention strategies, although longitudinal confirmation is needed. Full article
(This article belongs to the Section Nutrition and Public Health)
16 pages, 978 KB  
Article
Driving Waveform as a Design Variable for PFAS Plasma Degradation: Electron-Density-Driven Versus Reactive-Species-Driven Pathways
by Yejin Lee, Juncheol Kim, Hwanho Kim, Ki Ho Baek, Juyeon Choi, Yunchan Jang, Kwiyong Kim, Seunghun Lee, Sunghoon Jung, Oi Lun Li, Holak Kim, Joo Young Park and Sarnai Odsuren
Appl. Sci. 2026, 16(10), 5164; https://doi.org/10.3390/app16105164 (registering DOI) - 21 May 2026
Abstract
Per- and polyfluoroalkyl substances (PFASs) are persistent micropollutants whose carbon–fluorine bonds resist conventional advanced oxidation. Nonthermal plasmas have emerged as a promising option for PFAS degradation, but the relative contributions of reactive oxygen species (ROS) and electrons are still being investigated. Herein, we [...] Read more.
Per- and polyfluoroalkyl substances (PFASs) are persistent micropollutants whose carbon–fluorine bonds resist conventional advanced oxidation. Nonthermal plasmas have emerged as a promising option for PFAS degradation, but the relative contributions of reactive oxygen species (ROS) and electrons are still being investigated. Herein, we compared sinusoidal alternating-current (AC) and nanosecond-pulsed discharges―in an identical plasma reactor with the same input power (30 W)―through diagnostics including voltage–current characterization, optical emission spectroscopy with vibrational and rotational temperatures and Hα Stark broadening for electron density, and aqueous H2O2 quantification. AC discharges produced more aqueous H2O2, stronger ·OH emission, and higher vibrational and rotational temperatures, yet showed lower perfluorooctanoic acid (PFOA) removal (85% ± 2%) and lower defluorination (61% ± 1%) than the pulsed discharge (96% ± 2% and 80% ± 2%, respectively). Among the diagnostics examined, electron density tracked the removal trend, being higher under pulsed operation (1.2 × 1016 vs. 8.3 × 1015 under AC operation). A pseudo-first-order kinetic model based on electron density qualitatively reproduced the observed PFOA decay rate, suggesting that the waveform may serve as a design variable for tuning electron and ROS-mediated pathways in plasma–water reactors. Full article
(This article belongs to the Section Applied Physics General)
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