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16 pages, 2160 KB

Open AccessArticle

Development and Analysis of a Mobile Measurement System for Measuring Condensation and Thermal Conductivity

by Igor Štambuk, Roman Malarić, Hrvoje Hegeduš and Petar Mostarac

Electronics 2025, 14(22), 4491; https://doi.org/10.3390/electronics14224491 (registering DOI) - 17 Nov 2025

Hygrothermal assessment plays a critical role in the design and maintenance of healthy, energy-efficient buildings. Despite established knowledge of condensation mechanisms and mitigation strategies, condensation and moisture remains a persistent issue even in newly constructed structures. This ongoing challenge highlights the need for [...] Read more.

Hygrothermal assessment plays a critical role in the design and maintenance of healthy, energy-efficient buildings. Despite established knowledge of condensation mechanisms and mitigation strategies, condensation and moisture remains a persistent issue even in newly constructed structures. This ongoing challenge highlights the need for empirical validation of data critical to condensation occurrence. This study presents the development and evaluation of a mobile, on-site measurement system designed to collect data on surface condensation and thermal conductivity of building walls. The system is developed using a data acquiring and processing platform myRIO built around LabVIEW, enabling real-time detection of critical condensation conditions and deviations in thermal conductivity from measured values. Measurement results were validated with the Heat Flow Method (HFM) and theoretical calculations at the same site. Full article

(This article belongs to the Section Circuit and Signal Processing)

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16 pages, 3345 KB

Open AccessArticle

A Lightweight Model for Insulator Defect Detection Based on Vision–Language Modeling and Prior Knowledge in Power Systems

by Shanfeng Liu, Weijian Zhang, Shaoguang Yuan, Hua Bao, Wandeng Mao and Shengzhe Xi

Processes 2025, 13(11), 3714; https://doi.org/10.3390/pr13113714 (registering DOI) - 17 Nov 2025

Abstract

Insulators serve as critical insulating components in power transmission lines, and their defects are one of the primary causes of power outages in power grids. Power companies widely utilize unmanned aerial vehicle (UAV) inspections to collect image data of power transmission lines. However, [...] Read more.

Insulators serve as critical insulating components in power transmission lines, and their defects are one of the primary causes of power outages in power grids. Power companies widely utilize unmanned aerial vehicle (UAV) inspections to collect image data of power transmission lines. However, existing methods face two core challenges: at the data level, insulator defect samples are extremely scarce in massive image datasets, leading to severe data imbalance issues. At the algorithm level, deep learning-based defect detection methods rely on data-driven feature extraction, ignoring quantifiable prior knowledge such as insulator installation specifications and mechanical structure. This factor results in low localization efficiency and poor robustness in complex scenarios. To address these issues, this paper proposes an insulator defect detection method based on Vision–Language models and prior knowledge. It extracts prior knowledge about the physical characteristics of insulators, quantifies spatial structure and installation specifications as prior constraints, embeds prior knowledge into the vision–language model’s feature space to generate insulator defect samples, addresses the data imbalance issue, and detects insulator defects using an improved You Only Look Once (YOLO) algorithm. This approach reduces model parameters while maintaining detection accuracy, constructing a lightweight model for insulator defect detection. The experimental results show that, compared with PP-YOLOE-m and RT-DETR-R18 models, the method proposed in this paper can significantly improve the detection accuracy. The mean average precision indicator of the model in this paper has reached 95.7%. Full article

(This article belongs to the Special Issue AI-Driven Innovations for Enhancing Power System Stability and Operational Efficiency)

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24 pages, 2456 KB

Open AccessArticle

Low-Cost Eye-Tracking Fixation Analysis for Driver Monitoring Systems Using Kalman Filtering and OPTICS Clustering

by Jonas Brandstetter, Eva-Maria Knoch and Frank Gauterin

Sensors 2025, 25(22), 7028; https://doi.org/10.3390/s25227028 (registering DOI) - 17 Nov 2025

Abstract

Driver monitoring systems benefit from fixation-related eye-tracking features, yet dedicated eye-tracking hardware is costly and difficult to integrate at scale. This study presents a practical software pipeline that extracts fixation-related features from conventional RGB video. Facial and pupil landmarks obtained with MediaPipe are [...] Read more.

Driver monitoring systems benefit from fixation-related eye-tracking features, yet dedicated eye-tracking hardware is costly and difficult to integrate at scale. This study presents a practical software pipeline that extracts fixation-related features from conventional RGB video. Facial and pupil landmarks obtained with MediaPipe are denoised using a Kalman filter, fixation centers are identified with the OPTICS algorithm within a sliding window, and an affine normalization compensates for head motion and camera geometry. Fixation segments are derived from smoothed velocity profiles based on a moving average. Experiments with laptop camera recordings show that the combined Kalman and OPTICS pipeline reduces landmark jitter and yields more stable fixation centroids, while the affine normalization further improves referential pupil stability. The pipeline operates with minimal computational overhead and can be implemented as a software update in existing driver monitoring or advanced driver assistance systems. This work is a proof of concept that demonstrates feasibility in a low-cost RGB setting with a limited evaluation scope. Remaining challenges include sensitivity to lighting conditions and head motion that future work may address through near-infrared sensing, adaptive calibration, and broader validation across subjects, environments, and cameras. The extracted features are relevant for future studies on cognitive load and attention, although cognitive state inference is not validated here. Full article

(This article belongs to the Section Sensing and Imaging)

22 pages, 2042 KB

Open AccessArticle

Predictive Modeling of Tool Wear and Mass in Honing Processes Using Machine Learning and Grain Size Optimization

by Vlad Gheorghita

Appl. Sci. 2025, 15(22), 12207; https://doi.org/10.3390/app152212207 (registering DOI) - 17 Nov 2025

Abstract

The increasing demand for energy efficiency in manufacturing has driven the need for advanced modeling techniques to optimize the machining processes. The honing process, critical for achieving high-precision surface finishes in manufacturing, faces challenges in optimizing tool wear and material removal for enhanced [...] Read more.

The increasing demand for energy efficiency in manufacturing has driven the need for advanced modeling techniques to optimize the machining processes. The honing process, critical for achieving high-precision surface finishes in manufacturing, faces challenges in optimizing tool wear and material removal for enhanced sustainability and efficiency. This study develops a predictive modeling framework using machine learning techniques, including support vector regression (SVR), random forest (RF), and XGBoost, to forecast tool wear (h₁–h₈) and mass loss in honing processes. Experimental tests were conducted on EN-GJL-300 gray cast-iron workpieces using diamond abrasive blades (FEPA F120 and F240) under varied conditions (rotation speed, translation speed, and pressure). The models, trained with 5-fold cross-validation and hyperparameter tuning via GridSearchCV, achieved high accuracy, with SVR yielding R² values of 0.9609–0.9782 for wear predictions and XGBoost achieving R² of 0.9005 for mass predictions. Incorporating grain size as a predictor showed that finer grains (54 µm vs. 120 µm) reduced wear, thereby improving prediction reliability. The proposed models enable precise control of honing parameters, enhancing tool life and process efficiency, with implications for sustainable manufacturing in automotive and precision engineering applications. Full article

(This article belongs to the Special Issue Recent Advances in Control Strategies and Applications for Mechatronic Systems)

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32 pages, 4196 KB

Open AccessFeature PaperArticle

Innovative Alloy Design for Acid Stimulation Applications: From Lab to Field Validation, Combining High-Temperature Corrosion Testing and AI-Enhanced Corrosion Predictions

by Charbel Ramy, Razvan George Ripeanu, Salim Nassreddine, Maria Tănase, Elias Youssef Zouein, Constantin Cristian Muresan and Ayham Mhanna

Processes 2025, 13(11), 3713; https://doi.org/10.3390/pr13113713 (registering DOI) - 17 Nov 2025

Abstract

The oil and gas sector encounterssignificant material problems during acid stimulation, particularly under high temperatures, high pressures, and corrosive conditions with CO₂ and H₂S. This study focused on corrosion and erosion failures of tungsten carbide jetting nozzles in coiled tubing [...] Read more.

The oil and gas sector encounterssignificant material problems during acid stimulation, particularly under high temperatures, high pressures, and corrosive conditions with CO₂ and H₂S. This study focused on corrosion and erosion failures of tungsten carbide jetting nozzles in coiled tubing bottom hole assemblies. While tungsten carbide is durable, its high price, restricted machinability, and scarcity necessitate the search for viable alternatives. This study sought to identify and validate a low-cost, readily available, and easily machinable alloy with equivalent performance. A rigorous material selection approach took into account thermochemical stability, mechanical strength, and corrosion resistance under simulated downhole circumstances. Candidate alloys, both coated and uncoated, were subjected to extensive laboratory testing, including acid compatibility, high-temperature corrosion, erosion resistance, and mechanical integrity assessments. The majority failed due to pitting or surface deterioration. However, one coated alloy system was very resistant to chemical and thermal damage. To support long-term performance, a machine learning model relying on Gradient Boosting was created to forecast corrosion behavior using operational factors; demonstrating effective prediction characteristics compared with four other models. This AI-powered tool allows for accurate prediction of corrosion risks and aids decision-making by determining whether the material will maintain integrity under harsh acidic conditions. Field tests proved the selected alloy’s durability and jetting efficiency during many acid stimulation cycles. The corrosion and wear performance of coated 4145 material demonstrates a validated, cost-effective alternative to tungsten carbide with only four times lower corrosion resistance than carbide, outperforming other alloy combinations with up to 35 times higher corrosion rates. These results reveal tremendous opportunities for improving material design in corrosive energy applications. Full article

(This article belongs to the Special Issue Advances in Corrosion and Anticorrosion of Materials in Thermal Energy Storage Systems)

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24 pages, 4540 KB

Open AccessReview

From Field Effect Transistors to Spin Qubits: Focus on Group IV Materials, Architectures and Fabrications

by Nikolay Petkov and Giorgos Fagas

Nanomaterials 2025, 15(22), 1737; https://doi.org/10.3390/nano15221737 (registering DOI) - 17 Nov 2025

Abstract

In this review, we focus on group IV one-dimensional devices for quantum technology. We outline the foundational principles of quantum computing before delving into materials, architectures and fabrication routes, separately, by comparing the bottom-up and top-down approaches. We demonstrate that due to easily [...] Read more.

In this review, we focus on group IV one-dimensional devices for quantum technology. We outline the foundational principles of quantum computing before delving into materials, architectures and fabrication routes, separately, by comparing the bottom-up and top-down approaches. We demonstrate that due to easily tunable composition and crystal/interface quality and relatively less demanding fabrications, the study of grown nanowires such as core–shell Ge-Si and Ge hut wires has created a very fruitful field for studying unique and foundational quantum phenomena. We discuss in detail how these advancements have set the foundations and furthered realization of SETs and qubit devices with their specific operational characteristics. On the other hand, top-down processed devices, mainly as Si fin/nanowire field-effect transistor (FET) architectures, showed their potential for scaling up the number of qubits while providing ways for very large-scale integration (VLSI) and co-integration with conventional CMOS. In all cases we compare the fin/nanowire qubit architectures to other closely related approaches such as planar (2D) or III–V qubit platforms, aiming to highlight the cutting-edge benefits of using group IV one-dimensional morphologies for quantum computing. Another aim is to provide an informative pedagogical perspective on common fabrication challenges and links between common FET device processing and qubit device architectures. Full article

(This article belongs to the Special Issue Semiconductor Nanowires and Devices)

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30 pages, 1166 KB

Open AccessArticle

Modeling Blockchain Investment in Data-Intensive Supply Chains: A Game-Theoretic Analysis of Power Structures

by Zhengbo Li, Juan He and Qian Xue

Systems 2025, 13(11), 1029; https://doi.org/10.3390/systems13111029 (registering DOI) - 17 Nov 2025

Abstract

This study advances the hypothesis that supply chain power structure is a critical contingency factor for realizing investment value from integrating blockchain and big data. We develop a game-theoretic model of a two-tier supply chain to analyze investment decisions. The model examines cost–benefit [...] Read more.

This study advances the hypothesis that supply chain power structure is a critical contingency factor for realizing investment value from integrating blockchain and big data. We develop a game-theoretic model of a two-tier supply chain to analyze investment decisions. The model examines cost–benefit dynamics under supplier-led, manufacturer-led, and balanced power structures and proposes a coordination mechanism to align incentives. Results demonstrate that power structure determines pricing and profit distribution, allowing the dominant party to capture a larger benefit share. Furthermore, power structure systematically interacts with technological performance: profitability increases with customer heterogeneity satisfaction and demand enhancement but can be eroded by a high technology cost coefficient that triggers disproportionate investment. We identify a critical investment cost threshold for achieving Pareto improvement. Finally, the demand premium from enhanced transparency ensures economic viability even when adoption increases prices. These insights offer strategic frameworks for blockchain investment tailored to specific power distributions. Full article

(This article belongs to the Section Supply Chain Management)

9 pages, 4655 KB

Open AccessCase Report

Morphological and Motor Ability Adaptations Following a Short-Term Moderate-Intensity Strength Training Intervention in a Sedentary Adult Male with Asymmetrical Bilateral Spastic Cerebral Palsy: A Case Study

by Aleksandra Popović, Marko Kapeleti, Igor Zlatović, Milica Jankucić, Anastasija Kocić, Vladimir Mrdaković and Marija Macura

J. Funct. Morphol. Kinesiol. 2025, 10(4), 442; https://doi.org/10.3390/jfmk10040442 (registering DOI) - 17 Nov 2025

Abstract

Background: Cerebral palsy (CP) is a group of permanent disorders affecting movement, posture, and balance. Spasticity is the most common movement disorder in CP, and muscle weakness is its primary impairment. There is a lack of studies that have examined the effects of [...] Read more.

Background: Cerebral palsy (CP) is a group of permanent disorders affecting movement, posture, and balance. Spasticity is the most common movement disorder in CP, and muscle weakness is its primary impairment. There is a lack of studies that have examined the effects of short-term, moderate-intensity strength training (ST) in adults with CP, whereas recommendations suggest that long-term interventions are necessary for substantial improvements in strength in the CP population. This study investigated the effects of a 5-week, moderate-intensity ST intervention, that targets various upper and lower extremity muscles, on multiple morphological characteristics (MC) and motor abilities (MA) in a sedentary 30-year-old adult male with asymmetrical bilateral spastic CP level II. Methods: Body composition, maximal knee strength, maximal squat strength, leg explosive strength, and hip mobility were assessed before and after the ST intervention. Results: Changes in body composition were modest (0.6–6.4%). Maximal knee strength increased moderately on the less spastic side (40.7–65.9%) and substantially on the more spastic side (118.5–130.6%). Hip mobility showed a similar pattern, with small to moderate improvements (11.4–30.0%), while maximal squat strength and leg explosive strength increased moderately (29.5–46.3%). Conclusions: A short-term, moderate-intensity ST intervention produced meaningful improvements in MC and MA in this subject, especially on the more spastic side. The applied ST program was feasible and potentially efficient, and the results of this single-case study support its approach and methodology in necessary future studies on larger trials in an attempt to generalize these preliminary findings. This in turn may encourage practitioners to promote increased participation in physical activity among individuals with CP, given the short-term period of adaptations. The study discusses the potential of further refinement of the existing CP-specific ST guidelines and load programming aspects. Full article

(This article belongs to the Special Issue Innovative Physiotherapy Approaches and Functional Outcomes in Neurological and Developmental Disorders)

14 pages, 1245 KB

Open AccessArticle

Biochemical Characterization of R-Loop Degradation by Chloroplast-Localized RNase H1 from Arabidopsis thaliana

by Anastasia A. Gavrilova, Aleksandra A. Kuznetsova, Darya S. Novopashina, Chengxia Zheng, Qianwen Sun and Nikita A. Kuznetsov

Int. J. Mol. Sci. 2025, 26(22), 11125; https://doi.org/10.3390/ijms262211125 (registering DOI) - 17 Nov 2025

Abstract

R-loops are three-stranded nucleic acid structures implicated in genome regulation and stability. In Arabidopsis thaliana, the chloroplast-localized RNase H1 enzyme (AtRNH1C) is important for chloroplast development and genome integrity; however, its molecular activity has not been experimentally verified. In the present study, [...] Read more.

R-loops are three-stranded nucleic acid structures implicated in genome regulation and stability. In Arabidopsis thaliana, the chloroplast-localized RNase H1 enzyme (AtRNH1C) is important for chloroplast development and genome integrity; however, its molecular activity has not been experimentally verified. In the present study, we characterized the enzymatic activity of recombinant AtRNH1C toward model R-loops of various structures. Using a set of synthetic R-loop substrates, we demonstrate that AtRNH1C cleaves the RNA within DNA/RNA hybrids with a strong preference for purine-rich sequences, most notably at G↓X dinucleotides. Kinetic assays showed that the enzyme’s efficiency is highly dependent on the length of the hybrid duplex but is not affected by a G-quadruplex structure in the single-stranded DNA flap of the R-loop. The most rapid degradation was observed for an R-loop with an 11 nt DNA/RNA hybrid region. This study provides a comparative analysis of chloroplast-localized RNase H1 activity and elucidates its substrate preferences, suggesting that an R-loop with a heteroduplex length closest to the native size found in transcription elongation complexes is the most efficient substrate. These findings suggest that the enzymatic activity of AtRNH1C is sufficient to perform its function in maintaining chloroplast genome stability by the degradation of R-loops in DNA. Full article

(This article belongs to the Special Issue The Characterization and Application of Enzymes in Bioprocesses)

20 pages, 4998 KB

Open AccessArticle

Trace Aflatoxins Extraction in Pistachio, Maize and Rice Based on β-Cyclodextrin-Doped Cu-Carboxylated Graphene Oxide Nanocomposite

by Amr A. Yakout, Wael H. Alshitari, Hassan M. Albishri, Faten M. Ali Zainy and Adel M. Alshutairi

Toxins 2025, 17(11), 562; https://doi.org/10.3390/toxins17110562 (registering DOI) - 17 Nov 2025

Abstract

Aflatoxins remain among the most challenging food contaminants to monitor due to their structural diversity, low abundance, and the chemical complexity of cereal- and nut-based matrices. In this study, a multifunctional Cu/β-cyclodextrin@carboxylated graphene oxide (Cu/β-CD@CGO) nanocomposite was synthesized through a green, two-step procedure [...] Read more.

Aflatoxins remain among the most challenging food contaminants to monitor due to their structural diversity, low abundance, and the chemical complexity of cereal- and nut-based matrices. In this study, a multifunctional Cu/β-cyclodextrin@carboxylated graphene oxide (Cu/β-CD@CGO) nanocomposite was synthesized through a green, two-step procedure and employed as a high-affinity nanosorbent for trace extraction of AFB₁, AFB₂, AFG₁, and AFG₂. The architecture integrates three complementary components: β-cyclodextrin for inclusion-driven molecular recognition, copper nanoparticles that establish coordination interactions with lactone-bearing aflatoxins, and CGO nanosheets that supply extensive π-rich surfaces and abundant carboxyl functionalities. Comprehensive characterization (FTIR, Raman, XPS, SEM, EDX-mapping, and HRTEM) confirmed the formation of a uniform, porous hybrid network. Under optimized d-SPE conditions, the nanocomposite enabled quantitative recovery (92.0–108.5%) of aflatoxins from pistachio, maize, and rice extracts while achieving sub-ng kg⁻¹ detection limits and excellent reproducibility. The results demonstrate that the Cu/β-CD@CGO platform provides a robust, selective, and sustainable alternative to conventional immunoaffinity or polymeric sorbents, offering strong potential for routine surveillance of aflatoxins in complex food systems. Full article

(This article belongs to the Section Mycotoxins)

16 pages, 297 KB

Open AccessPerspective

Regenerative and Drug-Free Strategies for Chronic Musculoskeletal Pain: An Evidence-Based Perspective on Shockwave Therapy, High-Intensity Laser Therapy and Ultrasound-Guided Mechanical Needling with Sterile Water Injection

by Carl P. C. Chen and Areerat Suputtitada

Biomedicines 2025, 13(11), 2801; https://doi.org/10.3390/biomedicines13112801 (registering DOI) - 17 Nov 2025

Abstract

Chronic musculoskeletal pain (CMP) is the leading global cause of disability and a major contributor to healthcare burden. Its pathogenesis reflects regenerative failure, driven by extracellular matrix (ECM) fibrosis, calcific deposition, mitochondrial dysfunction, and neuroimmune sensitization. Conventional pharmacological therapies such as NSAIDs, corticosteroids, [...] Read more.

Chronic musculoskeletal pain (CMP) is the leading global cause of disability and a major contributor to healthcare burden. Its pathogenesis reflects regenerative failure, driven by extracellular matrix (ECM) fibrosis, calcific deposition, mitochondrial dysfunction, and neuroimmune sensitization. Conventional pharmacological therapies such as NSAIDs, corticosteroids, and opioids offer only transient symptomatic relief while exposing patients to systemic complications. In contrast, energy-based, drug-free regenerative interventions directly address underlying pathology and restore physiological function. This Perspective synthesizes recent evidence (2020–2025) on three modalities that together form a regenerative triad: extracorporeal shockwave therapy (ESWT), high-intensity laser therapy (HILT), and ultrasound-guided mechanical needling with sterile water injection (SWI). ESWT promotes mechanotransduction, angiogenesis, and ECM remodeling; HILT enhances mitochondrial bioenergetics and downregulates inflammatory pathways; and SWI disrupts fibrosis and calcification while restoring neurovascular dynamics. Evidence from randomized controlled trials and meta-analyses supports moderate-to-high certainty (GRADE B–A–) for ESWT and HILT. SWI, initially supported by large observational cohorts and comparative studies, is now reinforced by a randomized comparative trial and meta-analyses of lavage effects, justifying an upgrade from moderate (B) to moderate-to-high certainty (B–A–). Risk of bias assessment using Cochrane RoB 2.0 and the Newcastle–Ottawa Scale (NOS) indicates overall low-to-moderate concerns across modalities. Together, these interventions integrate mechanistic biology with translational rehabilitation practice. This Perspective outlines their mechanistic foundations, clinical evidence, and alignment with the WHO decade of healthy ageing, offering a drug-free, mechanism-based framework for sustainable CMP management. Full article

(This article belongs to the Special Issue Molecular Insights and Translational Approaches in Musculoskeletal Disorders)

17 pages, 2125 KB

Open AccessArticle

Sex-Specific Expression Patterns of MYH6 and MYH7 Gene Transcripts in Large Cohorts of Non-Failing and Failing Human Left Ventricular Tissues

by Zdenko Červenák, Ján Somorčík, Yashar Jalali, Žaneta Zajacová, Marian Baldovič, Andrea Gažová and Ján Kyselovič

J. Cardiovasc. Dev. Dis. 2025, 12(11), 447; https://doi.org/10.3390/jcdd12110447 (registering DOI) - 17 Nov 2025

Abstract

The transcriptional regulation of MYH6 and MYH7 genes has been extensively investigated in healthy versus failing hearts; however, their expression dynamics in healthy human hearts across age and sex, particularly in the context of cardiovascular risk factors such as hypertension, remain poorly characterised. [...] Read more.

The transcriptional regulation of MYH6 and MYH7 genes has been extensively investigated in healthy versus failing hearts; however, their expression dynamics in healthy human hearts across age and sex, particularly in the context of cardiovascular risk factors such as hypertension, remain poorly characterised. This study aimed to carry out a reanalysis of MYH6 and MYH7 transcript levels in a large cohort of non-failing human left ventricular samples, stratified by sex, age, and hypertensive status. Furthermore, we examined how age and sex influence gene expression differences between non-failing and failing hearts, the latter affected by dilated cardiomyopathy (DCM). Normalised expression values for MYH6 and MYH7 transcripts from both healthy and failing left ventricles were extracted using the GEO2R online analysis tool from the publicly available RNA-sequencing library GSE141910. This library provides transcriptomic profiles of left ventricular (LV) tissue from both healthy individuals and patients with cardiomyopathies. The Mann–Whitney U test was employed for pairwise comparisons between different groups stratified by sex, age, and hypertensive status. Statistical analysis demonstrates sex-specific differences in MYH6 and MYH7 expression in healthy left ventricles, with postmenopausal females (aged > 50 years) with hypertension emerging as a distinct group. Conversely, in end-stage DCM hearts, the expression levels of both myosin genes seemed to be primarily influenced by disease-related pathophysiological mechanisms rather than by sex or age. Comparison between healthy and failing hearts revealed a consistent and significant downregulation of MYH6 in all comparisons, irrespective of sex or age. On the other hand, MYH7 expression exhibited greater variability, particularly among males, with age and hypertensive status influencing its expression. The results underscore the importance of considering age, sex, and comorbidities in interpreting cardiac gene expression patterns and highlight potential regulatory divergence in contractile gene expression during cardiac remodelling. Full article

(This article belongs to the Section Basic and Translational Cardiovascular Research)

15 pages, 4821 KB

Open AccessArticle

Assessment of Antibiotic Resistance and Microbial Contamination in Commercial Veterinary Probiotic Products

by Shuo Guan, Chunguang Wang, Zongshu Zhang, Mengfan Wang, Xinghua Zhao and Tie Zhang

Biology 2025, 14(11), 1612; https://doi.org/10.3390/biology14111612 (registering DOI) - 17 Nov 2025

Abstract

Probiotics are widely used as feed additives in livestock production, yet the overall safety of commercially available veterinary probiotics remains insufficiently assessed. In this study, 33 probiotic products marketed in Northern China were systematically evaluated with respect to strain composition, label accuracy, antimicrobial [...] Read more.

Probiotics are widely used as feed additives in livestock production, yet the overall safety of commercially available veterinary probiotics remains insufficiently assessed. In this study, 33 probiotic products marketed in Northern China were systematically evaluated with respect to strain composition, label accuracy, antimicrobial resistance, and the diversity of resistance genes. A total of 32 Bacillus spp. were isolated, many of which showed resistance to multiple antibiotics. Labeling inaccuracies were prevalent: none of the products specified strain names and numbers, 33% (11/33) failed to report viable bacterial counts, 9% (3/33) lacked their claimed key ingredients, and 21% (7/33) contained isolated strains that did not match the label. High-throughput quantitative PCR (HT-qPCR) analysis further revealed that all 27 tested products harbored abundant antibiotic resistance genes (ARGs), with 241 ARGs and seven mobile genetic elements (MGEs) detected. The ARGs were primarily associated with tetracycline, aminoglycosides, β-lactams, and macrolide–lincosamide–streptomycin B (MLSB) antibiotics, and co-occurrence analysis showed a strong positive correlation between ARG and MGE abundance, with Clostridium and Enterococcus identified as potential hosts. These findings underscore significant quality and safety deficiencies in veterinary probiotics and highlight potential risks to animal, human, and environmental health, emphasizing the relevance of a One Health perspective in probiotic evaluation and regulation. Full article

(This article belongs to the Section Microbiology)

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12 pages, 838 KB

Open AccessArticle

Epidemiological Study of Lymphedema Prevalence and Comorbidities in Hospitalized Patients in the United States

by Nicolas Gérard, Ioannis T. Farmakis, Luca Valerio, Lukas Hobohm, Karsten Keller, Nils Kucher, Stefano Barco and Alexandru Grigorean

J. Clin. Med. 2025, 14(22), 8156; https://doi.org/10.3390/jcm14228156 (registering DOI) - 17 Nov 2025

Abstract

Background/Objective: Lymphedema is a disabling condition that is both underdiagnosed and undertreated. Epidemiological data on this disease is sparse. Methods: The prevalence of lymphedema was studied in hospitalized patients registered in the Nationwide Inpatient Sample (NIS) of the United States (US) from 2016 [...] Read more.

Background/Objective: Lymphedema is a disabling condition that is both underdiagnosed and undertreated. Epidemiological data on this disease is sparse. Methods: The prevalence of lymphedema was studied in hospitalized patients registered in the Nationwide Inpatient Sample (NIS) of the United States (US) from 2016 to 2020. ICD-10 codes related to lymphedema were utilized to identify eligible cases. We studied comorbidity burden and outcomes during hospitalizations, including in-hospital fatality, length of stay and total charges per hospitalization. Results: Lymphedema was present in 0.45% (n = 792,475) of all hospitalizations; with prevalence increasing from 0.40% in 2016 to 0.50% in 2020. Lymphedema-mentioning hospitalizations peaked in July. The median age was 67 (IQR: 57–77) years; A total of 60% were female. Most lymphedema-mentioning hospitalizations were emergency admissions (90%). The most frequent comorbidities were arterial hypertension (77%), obesity (58%), diabetes mellitus (42%), phlegmon (38%), renal disease (32%), chronic pulmonary disease (31%), and cancer (26%). The in-hospital fatality rate was 2.3%, the median length of stay was 5 (IQR: 3–8) days, and each hospitalization incurred a median of 36,304 (IQR: 20,431, 67,171) US dollars, roughly three times higher than the average hospitalization costs in the NIS in the same period. Conclusions: This represents the first comprehensive nationwide study of the epidemiological and economic burden of lymphedema among hospitalized patients in the US. The findings highlight that lymphedema, although underdiagnosed, affects a significant number of patients and is associated with a considerable burden of both comorbidities and costs. Full article

(This article belongs to the Section Vascular Medicine)

17 pages, 4599 KB

Open AccessArticle

Reproducible Thermo-Fluid–Solid-Coupled Modeling of Wet Milling of Al6061: Parametric Influence and Surface Integrity Assessment

by Yanping Xiao, Xuanzhong Wu, Xin Tong, Enqing Chen and Cheng Zhang

Metals 2025, 15(11), 1256; https://doi.org/10.3390/met15111256 (registering DOI) - 17 Nov 2025

Abstract

Wet milling of aluminum alloys involves complex interactions among thermal, fluid, and mechanical fields that strongly affect cutting temperature, stress distribution, and surface integrity. To achieve reproducible and physics-based predictions of these coupled phenomena, this study develops a three-dimensional thermo–fluid–solid-coupled Eulerian–Lagrangian (CEL) framework [...] Read more.

Wet milling of aluminum alloys involves complex interactions among thermal, fluid, and mechanical fields that strongly affect cutting temperature, stress distribution, and surface integrity. To achieve reproducible and physics-based predictions of these coupled phenomena, this study develops a three-dimensional thermo–fluid–solid-coupled Eulerian–Lagrangian (CEL) framework for the wet milling of Al6061. The model system in this study evaluated the effects of milling cutter feed rate and spindle speed, feed per tooth of the milling cutter, axial cutting depth, and coolant flow rate on equivalent stress and peak milling temperature., as well as their correlation with surface roughness metrics (Ra, Sa). Simulation results reveal that higher feed rates significantly raise T_peak (+12.9%) while reducing σ_eq (−22.7%) and deteriorating surface quality (Ra +104.2%, Sa +29.9%). Increasing spindle speed lowers both T_peak (−2.2%) and σ_eq (−8.5%) and improves surface finish (Ra −39.3%, Sa −16.6%). A greater depth of cut amplifies mechanical and thermal loads, increasing T_peak (+10.3%) and σ_eq (+17%). Enhanced coolant flow reduces T_peak (−23.5%) and σ_eq (−6.1%) and markedly improves surface quality (Ra −88.8%, Sa −51.3%). Research findings indicate that coolant coverage is the dominant factor determining surface integrity. Although experimental data for T_peak and σeq were not directly validated, this framework clearly articulates modeling assumptions, quantifies parameter sensitivities, and provides a reproducible methodology for future experimental-numerical verification. Full article

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18 pages, 1698 KB

Open AccessArticle

Diversity and Functional Potential of Yeasts Inhabiting Honey Bee Drones

by Vilija Lapinskaitė, Paulina Bartkutė, Juliana Lukša-Žebelovič, Živilė Strazdaitė-Žielienė and Elena Servienė

Microorganisms 2025, 13(11), 2614; https://doi.org/10.3390/microorganisms13112614 (registering DOI) - 17 Nov 2025

Abstract

The honey bee (Apis mellifera L.) is a eusocial insect widely known for its role in pollination and plant biodiversity. Diverse microorganisms, including both beneficial and pathogenic, colonize bees and play important roles in the overall hive health. Microorganisms with biocontrol properties [...] Read more.

The honey bee (Apis mellifera L.) is a eusocial insect widely known for its role in pollination and plant biodiversity. Diverse microorganisms, including both beneficial and pathogenic, colonize bees and play important roles in the overall hive health. Microorganisms with biocontrol properties are natural modulators of honey bee microflora. Since most studies have focused on the characterization of worker bee-associated microbes, there is a lack of information about the drones’ microbial environment. In this study, we identified cultivable yeasts from different stages of honey bee drones collected in Lithuania. Sealed larvae hosted the widest variety of yeasts. Metschnikowia species were detected across all developmental stages of drones. The assessment of functionality revealed that M. pulcherrima and M. fructicola exhibited the most pronounced biocontrol properties, accompanied by high levels of autoaggregation and hydrophobicity. Starmerella apis and M. reukaufii were distinguished by the highest autoaggregation capacity, exceeding 60%, and strong adherence to hydrocarbons. Starmerella genus yeasts demonstrated strong biofilm-forming ability. The novel information on the functionality of honey bee drone-inhabiting yeasts suggests their importance in maintaining the healthy microbiological environment of the hive. The isolated yeasts with beneficial traits may serve as candidates for future studies aimed at supporting honey bee health. Full article

(This article belongs to the Special Issue Diversity and Applications of Yeasts: Food, Plant and Human Health)

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16 pages, 2169 KB

Open AccessArticle

The Anti-Inflammatory and Skin Barrier Function Recovery Effects of Carica papaya Peel in Mice with Contact Dermatitis

by Seonah Park, Kyoungmin Sun, Yeojin Kim, Hyorhan Son, Jimi Lee, Soyeon Kim and Hyungwoo Kim

Int. J. Mol. Sci. 2025, 26(22), 11122; https://doi.org/10.3390/ijms262211122 (registering DOI) - 17 Nov 2025

Abstract

With growing concerns over the safety of synthetic substances, the development of plant-derived alternatives with minimal adverse effects has gained significant attention. Carica papaya L. peel contains a rich profile of bioactive compounds, including papain, flavonoids, and vitamin C, which exhibit potent antioxidant [...] Read more.

With growing concerns over the safety of synthetic substances, the development of plant-derived alternatives with minimal adverse effects has gained significant attention. Carica papaya L. peel contains a rich profile of bioactive compounds, including papain, flavonoids, and vitamin C, which exhibit potent antioxidant and anti-inflammatory properties. This study aimed to evaluate the effects of an ethanol extract of C. papaya peel (EECP) on inflammation and skin barrier dysfunction in a mouse model of contact dermatitis (CD) induced by 1-fluoro-2,4-dinitrofluorobenzene (DNFB). Mice were treated by applying EECP at three different levels (60, 80, and 600 μg) to dorsal skin for six days. Skin lesion severity, skin color, skin barrier function (SBF, as indicated by water content and water-holding capacity (WHC)), histopathological abnormalities, cytokine levels, filaggrin and Intercellular Adhesion Molecule-1 (ICAM-1) expression, and phosphorylation of MAPK (Mitogen-Activated Protein Kinase) signaling molecules were assessed. EECP treatment significantly alleviated the CD-associated dermal symptoms induced by DNFB, including skin fissures, scabbing, roughness, changes in color, water content, and WHC, as well as petechiae. EECP also prevented histopathological abnormalities such as epidermal hyperplasia, spongiotic changes, and immune cell infiltration. In addition, EECP suppressed the production of pro-inflammatory cytokines, viz. TNF-α, IFN-γ, IL-6, and MCP-1. In addition, EECP restored filaggrin expression and inhibited ERK (Extracellular signal-regulated kinases) phosphorylation and ICAM-1 expression in HaCaT cells. In summary, C. papaya peel demonstrated therapeutic potential by effectively suppressing inflammation and restoring SBF. These findings support the potential use of EECP as a safe and effective botanical candidate for the treatment of CD and the promotion of overall skin health Full article

(This article belongs to the Special Issue Molecular Mechanisms and Therapeutic Targeting of Inflammatory Complications)

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29 pages, 1027 KB

Open AccessArticle

Small Samples, Big Insights: A Methodological Comparison of Estimation Techniques for Latent Divergent Thinking Models

by Selina Weiss, Lara S. Elmdust and Benjamin Goecke

J. Intell. 2025, 13(11), 150; https://doi.org/10.3390/jintelligence13110150 (registering DOI) - 17 Nov 2025

Abstract

In psychology, small sample sizes are a frequent challenge—particularly when studying specific expert populations or using complex and cost-intensive methods like human scoring of creative answers—as they reduce statistical power, bias results, and limit generalizability. They also hinder the use of frequentist confirmatory [...] Read more.

In psychology, small sample sizes are a frequent challenge—particularly when studying specific expert populations or using complex and cost-intensive methods like human scoring of creative answers—as they reduce statistical power, bias results, and limit generalizability. They also hinder the use of frequentist confirmatory factor analysis (CFA), which depends on larger samples for reliable estimation. Problems such as non-convergence, inadmissible parameters, and poor model fit are more likely. In contrast, Bayesian methods offer a robust alternative, being less sensitive to sample size and allowing the integration of prior knowledge through parameter priors. In the present study, we introduce small-sample-size structural equation modeling to creativity research by investigating the relationship between creative fluency and nested creative cleverness with right-wing authoritarianism, starting with a sample size of N = 198. We compare the stability of results in frequentist and Bayesian SEM while gradually reducing the sample by n = 25. We find that common frequentist fit indexes degrade below N = 100, while Bayesian multivariate Rhat values indicate stable convergence down to N = 50. Standard errors for fluency loadings inflate 40–50% faster in frequentist SEM compared to Bayesian estimation, and regression coefficients linking RWA to cleverness remain significant across all reductions. Based on these findings, we discuss (1) the critical role of Bayesian priors in stabilizing small-sample SEM, (2) the robustness of the RWA-cleverness relationship despite sample constraints, and (3) practical guidelines for minimum sample sizes in bifactor modeling. Full article

(This article belongs to the Special Issue Analysis of a Divergent Thinking Dataset)

20 pages, 7285 KB

Open AccessArticle

Bending Characteristics of Hybrid Fiber Concrete Beams Reinforced with Steel–GFRP Hybrid Rebars

by Aref Abadel, Husain Abbas, Hussein Elsanadedy, Tarek Almusallam, Shehab Mourad and Yousef Al-Salloum

Buildings 2025, 15(22), 4146; https://doi.org/10.3390/buildings15224146 (registering DOI) - 17 Nov 2025

Abstract

The current study aims to investigate the effect of using hybrid bars on the bending characteristics of hybrid fiber-reinforced concrete (FRC) beams. For this purpose, a series of flexural tests on FRC beams were conducted. Four FRC beams were fabricated, each with a [...] Read more.

The current study aims to investigate the effect of using hybrid bars on the bending characteristics of hybrid fiber-reinforced concrete (FRC) beams. For this purpose, a series of flexural tests on FRC beams were conducted. Four FRC beams were fabricated, each with a section of 120 mm × 185 mm and an overall length of 1.5 m. The FRC beams’ tension reinforcement consisted of a hybrid configuration of steel and glass fiber-reinforced polymer (GFRP) rebars. The concrete mix included a hybrid fiber content of 1% by volume, with 0.75% for hooked-end steel fibers (SF) and 0.25% polypropylene fibers (PP). The simply supported FRC beams were tested under the action of two-point loads. The results demonstrated that the inclusion of hybrid fibers substantially improved the crack widening and propagation in FRC beams compared to normal concrete (NC) beams. The maximum load capabilities of the FRC beams surpassed those of the NC beams up to 13.2%. The GFRP bars further enhanced the beams’ load-carrying capacity with an observed increase of up to 42.5%, when compared to the steel-reinforced FRC beam (BFRC-3S). Additionally, hybrid reinforcement improved ductility, with increases of 39.1% and 167.1% when one or two GFRP bars were replaced by steel, respectively. Full article

(This article belongs to the Section Building Structures)

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32 pages, 2030 KB

Open AccessArticle

Time Perspective and ICT Use: A Descriptive Study with Secondary School Adolescents

by Duarte Gomes, Cristina Antunes and Ana Paula Monteiro

Societies 2025, 15(11), 315; https://doi.org/10.3390/soc15110315 (registering DOI) - 17 Nov 2025

Abstract

The literature addresses Time Perspective and technology use among adolescents in various ways. However, the existing body of research remains limited, with gaps in both descriptive and comparative dimensions. Accordingly, this study aimed to describe and compare Time Perspective, the Use of ICT [...] Read more.

The literature addresses Time Perspective and technology use among adolescents in various ways. However, the existing body of research remains limited, with gaps in both descriptive and comparative dimensions. Accordingly, this study aimed to describe and compare Time Perspective, the Use of ICT (Information and Communication Technologies) and Social Media, and Attitudes Towards Technology among adolescents, considering sex, type of course, and school year. The sample comprised 433 secondary school students aged between 14 and 19 years. Two instruments were employed: the Time Perspective Inventory (TPI) and the Media and Technology Usage and Attitudes Scale for Portuguese Youth (MTUAS-PY). Participants were generally more oriented towards the past; specifically, greater Future Orientation was observed among male students, while Past Orientation was more prevalent in regular-education courses, and a more Negative View of the Future was found among students in vocational courses. Smartphone Use emerged as the highest-scoring dimension within ICT and Social Media Use, whereas Accessibility and Ease received the highest scores in Attitudes Towards Technology. This study provides a nuanced overview of the secondary school adolescent population and identifies significant differences when considering academic tracks. These findings raise important considerations for future research, both in terms of factorial analysis and comparative approaches. Full article

30 pages, 5680 KB

Open AccessArticle

Surface and Vertical Nutrient Profiles in the Northwestern Black Sea: Trends, Comparisons, and Sample Preservation Assessment

by Dan Vasiliu, Andra Bucșe, Florina Rădulescu, Florentina Fediuc and Sorin Balan

J. Mar. Sci. Eng. 2025, 13(11), 2178; https://doi.org/10.3390/jmse13112178 (registering DOI) - 17 Nov 2025

Abstract

This study investigated the physicochemical properties and nutrient dynamics on the Romanian shelf of the northwestern Black Sea in July 2024, collecting data across 36 stations (13–1116 m depth) heavily influenced by Danube discharges. Vertical CTD profiling revealed a pronounced seasonal thermocline and [...] Read more.

This study investigated the physicochemical properties and nutrient dynamics on the Romanian shelf of the northwestern Black Sea in July 2024, collecting data across 36 stations (13–1116 m depth) heavily influenced by Danube discharges. Vertical CTD profiling revealed a pronounced seasonal thermocline and a deep-lying permanent halocline. The Cold Intermediate Layer (CIL) boundary, defined by the 8 °C isotherm, was absent, indicating warmer subsurface waters. Surface nutrient concentrations, particularly for nitrate (NO₃) and phosphate (PO₄), were considerably lower than peak eutrophication periods, approaching pre-1970s values, suggesting a positive trend due to reduced anthropogenic loading. They are also comparable to or lower than other coastal regions in the Black Sea. Vertical nutrient profiles confirmed the typical anoxic Black Sea structure, but with regional specifics: the PO₄ maximum was slightly deeper, and the NO₃ maximum position and concentration mirrored the pre-eutrophication period, further supporting reduced anthropogenic nitrogen input. Silicate (SiO₄) concentrations were consistently low throughout the water column, suggesting the northwest shelf functions as a SiO₄ sink compared to the southeastern Black Sea. Overall results indicate a shift towards a less eutrophic state on the Romanian shelf while highlighting the continued dominance of Danube-driven hydrodynamics. In addition to those investigations, this study assessed nutrient preservation techniques, finding that pasteurization was significantly superior to freezing for maintaining the stability of PO₄ and NOx (losses up to 20% and 47% for frozen samples, respectively) over six months. Though SiO₄ was stable under both methods, the freezing produced lower concentrations, possibly from incomplete depolymerization during thawing. These findings stress that pasteurization could be taken into consideration as a reliable preservation technique for long-term storage of nutrient samples. Full article

(This article belongs to the Section Chemical Oceanography)

23 pages, 5472 KB

Open AccessArticle

Research on the Process and Quality of Prepacked Braised Meat Products

by Mingxia Zhao, Lili Zhang, Li Liang, Shihao Sun, Shuxing Chen, Lishui Chen and Yuyu Zhang

Foods 2025, 14(22), 3937; https://doi.org/10.3390/foods14223937 (registering DOI) - 17 Nov 2025

Abstract

The processing technique critically determines the quality of prepackaged braised meat products. This study aimed to evaluate the effects of an innovative processing method against traditional methods on the product’s shelf-life and quality attributes. Results: no significant difference in shelf-life was observed between [...] Read more.

The processing technique critically determines the quality of prepackaged braised meat products. This study aimed to evaluate the effects of an innovative processing method against traditional methods on the product’s shelf-life and quality attributes. Results: no significant difference in shelf-life was observed between the experimental and control groups. However, the innovative method significantly improved product quality. The experimental group exhibited a redder and bluer color, significantly higher hardness (2–4 times, p < 0.01) and chewiness, alongside better moisture retention and meat yield. Sensory evaluation confirmed an overall preference for the experimental group (p < 0.05). Flavor profile analysis revealed a greater number and more stable retention of key flavor compounds (alcohols, ketones, and ethers) in the experimental group. The innovative processing method optimizes traditional techniques by significantly enhancing the physicochemical, textural, sensory, and flavor properties of prepackaged braised meat, without compromising shelf-life, providing a novel strategy for producing high-quality products. Full article

(This article belongs to the Special Issue Food Preservation: Traditional and Modern Processes and Strategies)

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16 pages, 1302 KB

Open AccessArticle

Preoperative Risk Factors and Phenotypic Clustering in Periprosthetic Joint Infection: A Matched Case–Control Study

by Tarek Omar Pacha, Sophia K. Klett, Gabi von Lewinski, Maximilian Koblenzer, Hür Özbek, Jorge Mayor, Jan D. Clausen, Axel Gänsslen, Schayan Faraj Tabrizi, Stephan Sehmisch and Gökmen F. Aktas

Life 2025, 15(11), 1762; https://doi.org/10.3390/life15111762 (registering DOI) - 17 Nov 2025

Abstract

Periprosthetic joint infection (PJI) remains one of the most serious complications after total joint arthroplasty. This retrospective 1:1 matched case–control study investigated preoperative predictors and patient phenotypes associated with PJI in 182 patients (91 cases, 91 controls) undergoing hip or knee arthroplasty between [...] Read more.

Periprosthetic joint infection (PJI) remains one of the most serious complications after total joint arthroplasty. This retrospective 1:1 matched case–control study investigated preoperative predictors and patient phenotypes associated with PJI in 182 patients (91 cases, 91 controls) undergoing hip or knee arthroplasty between 2013 and 2024. Variables with skewed distributions were log-transformed, and multivariable logistic regression with LASSO regularization identified independent risk factors. Unsupervised K-means clustering was applied to perioperative features to explore data-driven patient phenotypes. Preoperative anemia (OR 5.91, p = 0.026), higher ASA score (OR 1.77, p = 0.033), and surgical delay (OR 1.67, p = 0.024) independently predicted infection, while age and CRP showed non-significant trends. The resulting five-variable preoperative model achieved an AUC of 0.718 (optimism-corrected AUC of 0.661) for infection prediction. Clustering analysis revealed three phenotypes: anemia-dominated, elderly but short-procedure, and high surgery duration with significantly different infection rates (χ² = 23.5, p < 0.001) but similar mortality (p = 0.068). This integrative approach combining regression-based prediction and phenotype discovery enables clinically interpretable, preoperatively applicable risk stratification. The findings identify anemia, comorbidity burden, and surgical delay as key modifiable targets for preventive optimization before arthroplasty. External validation and recalibration to population-level incidence are warranted before clinical implementation. Full article

(This article belongs to the Special Issue Advanced Machine Learning for Disease Prediction and Prevention)

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17 pages, 3608 KB

Open AccessArticle

Specimen Size Effect on Expansive Soil Permeability: Laboratory and In-Situ Investigation

by Yanling Lin, Junping Yuan and Chen Ding

Appl. Sci. 2025, 15(22), 12205; https://doi.org/10.3390/app152212205 (registering DOI) - 17 Nov 2025

Abstract

The permeability characteristics of expansive soil have a significant impact on slope stability. This study investigates the permeability evolution of three expansive soils (B, GW, GB) with distinct swelling potentials (68%, 42%, and 28%) under repeated wet–dry cycles, combining laboratory falling-head tests and [...] Read more.

The permeability characteristics of expansive soil have a significant impact on slope stability. This study investigates the permeability evolution of three expansive soils (B, GW, GB) with distinct swelling potentials (68%, 42%, and 28%) under repeated wet–dry cycles, combining laboratory falling-head tests and in situ four-ring infiltrometer measurements. The results demonstrate that the permeability coefficient increases consistently with cycle number. The high-expansivity soil (B) exhibited the most pronounced change, with permeability increasing from 10⁻⁶ cm/s to 10⁻³ cm/s after five cycles, whereas the low-expansivity soil (GB) remained stable. A significant specimen size effect was observed in initial permeability, which stabilized beyond a critical infiltration area of 1102.7 cm². However, this size dependence diminished after three cycles due to extensive cracking and structural homogenization. Crack density analysis further confirmed microstructural stabilization at sample diameters between 32 and 38 cm, validating the adopted in situ seepage diameter of 37 cm. Linear regression revealed greater discrepancies between laboratory and in situ permeability values in high-swelling soils. Empirical formulas incorporating wet–dry cycles were developed to accurately predict in situ permeability, providing practical tools for engineering design and risk assessment. Full article

21 pages, 1147 KB

Open AccessArticle

AI-Based Steganography Method to Enhance the Information Security of Hidden Messages in Digital Images

by Nhi Do Ngoc Huynh, Jiajun Jiang, Chung-Hao Chen and Wen-Chao Yang

Electronics 2025, 14(22), 4490; https://doi.org/10.3390/electronics14224490 (registering DOI) - 17 Nov 2025

Abstract

With the increasing sophistication of Artificial Intelligence (AI), traditional digital steganography methods face a growing risk of being detected and compromised. Adversarial attacks, in particular, pose a significant threat to the security and robustness of hidden information. To address these challenges, this paper [...] Read more.

With the increasing sophistication of Artificial Intelligence (AI), traditional digital steganography methods face a growing risk of being detected and compromised. Adversarial attacks, in particular, pose a significant threat to the security and robustness of hidden information. To address these challenges, this paper proposes a novel AI-based steganography framework designed to enhance the security of concealed messages within digital images. Our approach introduces a multi-stage embedding process that utilizes a sequence of encoder models, including a base encoder, a residual encoder, and a dense encoder, to create a more complex and secure hiding environment. To further improve robustness, we integrate Wavelet Transforms with various deep learning architectures, namely Convolutional Neural Networks (CNNs), Bayesian Neural Networks (BNNs), and Graph Convolutional Networks (GCNs). We conducted a comprehensive set of experiments on the FashionMNIST and MNIST datasets to evaluate our framework’s performance against several adversarial attacks. The results demonstrate that our multi-stage approach significantly enhances resilience. Notably, while CNN architectures provide the highest baseline accuracy, BNNs exhibit superior intrinsic robustness against gradient-based attacks. For instance, under the Fast Gradient Sign Method (FGSM) attack on the MNIST dataset, our BNN-based models maintained an accuracy of over 98%, whereas the performance of comparable CNN models dropped sharply to between 10% and 18%. This research provides a robust and effective method for developing next-generation secure steganography systems. Full article

(This article belongs to the Special Issue Advanced Machine Learning, Pattern Recognition, and Deep Learning Technologies: Methodologies and Applications, 2nd Edition)

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16 pages, 1845 KB

Open AccessArticle

Verapamil Suppresses the Development of Resistance Against Anti-Tuberculosis Drugs in Mycobacteria

by Kunna Liu, Elise Buitenhek, Coenraad P. Kuijl, Yuval Mulla, Joen Luirink and Dirk Bald

Int. J. Mol. Sci. 2025, 26(22), 11124; https://doi.org/10.3390/ijms262211124 (registering DOI) - 17 Nov 2025

Abstract

The emergence of drug resistance remains a major challenge in the treatment of tuberculosis and other mycobacterial infections. To combat the rise in resistance, strategies that reduce the frequency of resistance mutations are urgently needed. Verapamil is a small-molecule compound that can enhance [...] Read more.

The emergence of drug resistance remains a major challenge in the treatment of tuberculosis and other mycobacterial infections. To combat the rise in resistance, strategies that reduce the frequency of resistance mutations are urgently needed. Verapamil is a small-molecule compound that can enhance the potency of companion drugs in combination regimen. Here, we investigate if verapamil can decrease the resistance frequency of antimycobacterial drugs. The results show that verapamil significantly reduces the resistance frequency of multiple antimycobacterial agents, including the DNA gyrase inhibitor moxifloxacin, the protein synthesis inhibitor streptomycin, and the RNA polymerase inhibitor rifampicin in Mycobacterium smegmatis. The presence of point mutations in the target was confirmed for moxifloxacin-resistant M. smegmatis. Suppression of resistance evolution against moxifloxacin by verapamil was also found in the slow-growing, pathogenic mycobacteria M. avium and M. tuberculosis. Real-time qPCR analysis in M. smegmatis showed that verapamil treatment downregulates the expression of multiple efflux pump genes and upregulates DNA repair genes. These findings suggest that verapamil exerts a dual role by interfering with efflux pump functionality and by reducing the probability of chromosomal mutations. The combination of these properties may underlie the promise of verapamil as adjuvant to enhance the effectiveness of current antimycobacterial chemotherapy. Full article

(This article belongs to the Special Issue Antibiotics Science: Molecular Insights, Detection Strategies, Resistance Challenges and Interdisciplinary Applications)

20 pages, 2302 KB

Open AccessSystematic Review

Global Prevalence of Isolated Systolic, Isolated Diastolic, and Systodiastolic Hypertension: A Systematic Review and Meta-Analysis

by Víctor Juan Vera-Ponce, Lupita Ana Maria Valladolid-Sandoval, Jhosmer Ballena-Caicedo and Fiorella E. Zuzunaga-Montoya

Cardiovasc. Med. 2025, 28(1), 3; https://doi.org/10.3390/cardiovascmed28010003 (registering DOI) - 17 Nov 2025

Abstract

Arterial hypertension (HTN) is a global public health problem with three distinct subtypes: isolated systolic hypertension (ISH), isolated diastolic hypertension (IDH), and systodiastolic hypertension (SDH), each with unique clinical implications. This systematic review and meta-analysis aimed to determine the global prevalence of ISH, [...] Read more.

Arterial hypertension (HTN) is a global public health problem with three distinct subtypes: isolated systolic hypertension (ISH), isolated diastolic hypertension (IDH), and systodiastolic hypertension (SDH), each with unique clinical implications. This systematic review and meta-analysis aimed to determine the global prevalence of ISH, IDH, and SDH and their variability. Following PRISMA guidelines, a search was conducted in SCOPUS, Web of Science, PubMed, and EMBASE. A random-effects model with the Freeman-Tukey transformation was used for the meta-analysis, and a meta-regression was performed to assess temporal trends. Twenty-seven studies from five continents were included, revealing pooled global prevalence rates of 10.72% for ISH, 5.07% for IDH, and 11.71% for SDH. Extreme heterogeneity was observed (I² = 100%), reflecting substantial methodological diversity. The meta-regression suggested an increasing trend for ISH over time, while non-significant decreasing trends were observed for IDH and SDH. In conclusion, all three HTN subtypes show clinically relevant prevalences, with ISH and SDH being nearly twice as common as IDH. The high heterogeneity underscores the urgent need for research standardization, and these findings highlight the importance of differentiating subtypes for more effective population-level screening and public health planning. Full article

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