Applied Sciences

18 pages, 5715 KB

Open AccessArticle

Spatiotemporal Characteristics of Oxygen Content in the Vegetation Growing Season of Qinghai Province Based on Vertical Gradients

by Ziqian Zhang, Weidong Ma, Fenggui Liu, Zemin Zhi and Wenjing Xu

Appl. Sci. 2025, 15(18), 10301; https://doi.org/10.3390/app151810301 - 22 Sep 2025

Abstract

To reveal the spatiotemporal variations in near-surface oxygen content during the growing season across different altitudinal gradients in Qinghai Province and to deepen the understanding of oxygen cycling in plateau ecosystems, this study analyzed daily observations from 12 monitoring stations spanning three elevation [...] Read more.

To reveal the spatiotemporal variations in near-surface oxygen content during the growing season across different altitudinal gradients in Qinghai Province and to deepen the understanding of oxygen cycling in plateau ecosystems, this study analyzed daily observations from 12 monitoring stations spanning three elevation ranges (1500–2500 m, 2500–3500 m, and 3500–4500 m) during the 2022–2023 growing seasons (March–July). The Mann–Kendall test was employed to detect temporal trends, variability indices such as standard deviation and coefficient of variation were used to quantify fluctuation intensity, Kernel density estimation (KDE) was applied to characterize distributional features, and the Kruskal–Wallis test was conducted to assess statistical significance. The results indicate that: (1) oxygen content showed a significant increasing trend at all three altitudinal gradients, with the strongest rise at low elevations and the weakest at high elevations; (2) fluctuation intensity exhibited clear spatial heterogeneity, with the most pronounced variability in summer at low elevations, a distinct peak in June at mid-elevations, and overall stability at high elevations; and (3) KDE analysis revealed a broader distribution and higher frequency of extreme oxygen values at low elevations, while mid- and high-elevations displayed more concentrated distributions. Both the Kruskal–Wallis test and post hoc comparisons confirmed highly significant differences among the three elevation ranges. These findings demonstrate that elevation is a key factor influencing the spatiotemporal distribution of near-surface oxygen content during the growing season in Qinghai Province. Differences are not only evident in absolute oxygen levels but also in fluctuation intensity and distributional characteristics. This study provides empirical evidence for understanding oxygen variability mechanisms on the plateau and offers theoretical and practical references for ecological management and health risk prevention in high-altitude regions. Full article

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14 pages, 3803 KB

Open AccessArticle

Analysis of the Relationship Between Production Process Determinants and Production Flow Control Methods

by Krzysztof Żywicki

Appl. Sci. 2025, 15(18), 10300; https://doi.org/10.3390/app151810300 - 22 Sep 2025

Abstract

Production flow control is a key area affecting the productivity of production systems. The use of an appropriate control method ensures that customer requirements are met while maintaining an acceptable level of production costs. In many cases, the choice of control method does [...] Read more.

Production flow control is a key area affecting the productivity of production systems. The use of an appropriate control method ensures that customer requirements are met while maintaining an acceptable level of production costs. In many cases, the choice of control method does not allow for significant improvements in production processes, as the known guidelines are not very detailed. This article presents research on the impact of factors related to products, production processes, and customer orders on, for example, the number of technological operations, the number of production stations, product demand (product, process, and order conditions—PPOC), and the effectiveness of production flow control methods. This research was conducted for selected product families (water and gas fittings) for which various production flow control solutions were developed. The most popular control methods were used: push–schedule, supermarket-type pull, sequential pull, mixed pull, and drum-buffer-rope. The criteria for evaluation were in-process stocks and lead time of materials in the production process. As a result of the ranking, relationships were identified by indicating how the values of PPOC factors affect the effectiveness of a given production flow control method. The results of this research can serve as guidelines for companies in selecting the most appropriate method of controlling production processes. Full article

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19 pages, 10875 KB

Open AccessArticle

CFD Analysis of Transition Models for Low-Reynolds Number Aerodynamics

by Enrico Giacomini and Lars-Göran Westerberg

Appl. Sci. 2025, 15(18), 10299; https://doi.org/10.3390/app151810299 - 22 Sep 2025

Abstract

Low Reynolds number flows are central to the performance of airfoils used in small unmanned aerial vehicles (UAVs), micro air vehicles (MAVs), and aerodynamic platforms operating in rarefied atmospheres. Consequently, a deep understanding of airfoil behavior and accurate prediction of aerodynamic performance are [...] Read more.

Low Reynolds number flows are central to the performance of airfoils used in small unmanned aerial vehicles (UAVs), micro air vehicles (MAVs), and aerodynamic platforms operating in rarefied atmospheres. Consequently, a deep understanding of airfoil behavior and accurate prediction of aerodynamic performance are essential for the optimal design of such systems. The present study employs Computational Fluid Dynamics (CFD) simulations to analyze the aerodynamic performance of a cambered plate at a Reynolds number of 10,000. Two Reynolds-Averaged Navier–Stokes (RANS) turbulence models,

γ

–

R e_{θ}

and

k - k_{L} - ω

, are utilized, along with the Unsteady Navier–Stokes (UNS) equations. The simulation results are compared against experimental data, with a focus on lift, drag, and pressure coefficients. The models studied perform moderately well at small angles of attack. The

γ

–

R e_{θ}

model yields the lowest lift and drag errors (below 0.17 and 0.04, respectively), while the other models show significantly higher discrepancies, particularly in lift prediction. The

γ

–

R e_{θ}

model demonstrates good overall accuracy, with notable deviation only in the prediction of the stall angle. In contrast, the

k - k_{L} - ω

model and the UNS equations capture the general flow trend up to stall but fail to provide reliable predictions beyond that point. These findings indicate that the

γ

–

R e_{θ}

model is the most suitable among those tested for low Reynolds number transitional flow simulations. Full article

(This article belongs to the Special Issue Computational Fluid Dynamics in Mechanical Engineering)

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43 pages, 8632 KB

Open AccessReview

Combating the Counterfeit: A Review on Hardware-Based Anticounterfeiting Technologies

by Suvadeep Choudhury, Filippo Costa, Giuliano Manara and Simone Genovesi

Appl. Sci. 2025, 15(18), 10298; https://doi.org/10.3390/app151810298 - 22 Sep 2025

Abstract

Counterfeiting poses a significant threat to global commerce, causing economic damage and jeopardizing consumer safety. This report addresses the critical need for advanced anti-counterfeiting measures. While often confused, authentication verifies an item’s genuineness, whereas anticounterfeiting is a broader strategy that includes authentication to [...] Read more.

Counterfeiting poses a significant threat to global commerce, causing economic damage and jeopardizing consumer safety. This report addresses the critical need for advanced anti-counterfeiting measures. While often confused, authentication verifies an item’s genuineness, whereas anticounterfeiting is a broader strategy that includes authentication to deter counterfeit production. This report explores such technologies, which are primarily based on tangible objects and can be used as an anticounterfeiting measure. Such technologies, referred subsequently as “hardware-based anticounterfeiting techniques”, provides a critical line of defence in the fight against imitation of goods. This review covers diverse methods: electronic, mechanical, chemical, and marking techniques. The report emphasizes that no single technique is sufficient, advocating for a multi-layered approach. By combining these hardware solutions with complementary measures like supply chain monitoring, we can create a more resilient defense against counterfeiting. Full article

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14 pages, 468 KB

Open AccessArticle

Exploring Three Methods for Sampling Oral Microbiota in Older People: A Comparative Study

by Sanne M. Pruntel, Hanneke de Valk, Arjan Vissink and Anita Visser

Appl. Sci. 2025, 15(18), 10297; https://doi.org/10.3390/app151810297 - 22 Sep 2025

Abstract

A variety of methods are described in the literature for sampling oral microbiota, including their advantages and disadvantages. The aim of this study was to assess which method (swab, paper point, and oral fluid collection) for sampling oral microbiota is most favourable for [...] Read more.

A variety of methods are described in the literature for sampling oral microbiota, including their advantages and disadvantages. The aim of this study was to assess which method (swab, paper point, and oral fluid collection) for sampling oral microbiota is most favourable for use on a geriatric population. The oral microbiota of geriatric patients who visited the Geriatric Department of the University Medical Center Groningen (The Netherlands), because of memory complaints, were assessed between April 2022 and April 2023. The samples were collected using three methods: swab, paper point, and oral fluid collection. The participants had to have at least one natural tooth. The samples were checked for 11 oral bacteria commonly associated with oral and general diseases. Of the 30 potentially eligible participants, 28 could be enrolled. A 100% bacteria match was achieved by all 3 sampling techniques between 64% of the cases (18/28) and a 91% match between another 25% (7/28). The swab had the highest positivity rate in this population, as it was easy to perform and usable on edentulous individuals, even on those with (severe) disabilities. Overall, the sampling methods showed comparable microbiota in most cases but differed in the complexity of use. The swab seemed to be the most favourable method among the geriatric participants. Full article

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36 pages, 7129 KB

Open AccessArticle

Sustainable Mass Timber Structures—Selected Issues in the Structural Shaping of Tall Buildings

by Hanna Michalak and Karolina Michalak

Appl. Sci. 2025, 15(18), 10296; https://doi.org/10.3390/app151810296 - 22 Sep 2025

Abstract

The subject of this article is tall buildings with a load-bearing layout made of mass timber, erected between 2009 and 2025. The aim of the study is to introduce a typology and to systematise and synthesise knowledge concerning the spatial and material–structural shaping [...] Read more.

The subject of this article is tall buildings with a load-bearing layout made of mass timber, erected between 2009 and 2025. The aim of the study is to introduce a typology and to systematise and synthesise knowledge concerning the spatial and material–structural shaping of the load-bearing systems of these buildings. Load-bearing systems were classified according to the type of elements into 1D, 2D, 3D, mixed and hybrid. It was found that the most common types of mass timber tall building construction are 1D, accounting for 47% of the buildings analysed, and 2D accounting for 23%, with the remaining 3D (4%), hybrid (3%) and mixed (1%) used infrequently. A research method based on a case study and data collection with an analysis of the available literature was used. A study of the spatial and material and structural solutions of 109 timber tall buildings was carried out. Conclusions are presented for the most sustainable in terms of material solution, i.e., with an above-ground part made entirely of mass timber in the buildings which represents 10% of the cases studied. Mass timber tall buildings have a low slenderness of 0.66–2.98 for heights up to 50 m and 2.41–4.97 for heights over 50 m. Full article

(This article belongs to the Special Issue Sustainable Materials and Innovative Solutions for Green Construction)

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16 pages, 535 KB

Open AccessArticle

Solving Construction Site Layout Planning as a Quadratic Assignment Problem Using the Advanced Jaya Algorithm

by Gülçağ Albayrak

Appl. Sci. 2025, 15(18), 10295; https://doi.org/10.3390/app151810295 - 22 Sep 2025

Abstract

Construction site layout planning (CSLP) plays a pivotal role in determining the overall efficiency and cost-effectiveness of construction projects. Material handling operations, which constitute a significant portion of indirect project costs, heavily depend on the spatial arrangement of temporary facilities such as site [...] Read more.

Construction site layout planning (CSLP) plays a pivotal role in determining the overall efficiency and cost-effectiveness of construction projects. Material handling operations, which constitute a significant portion of indirect project costs, heavily depend on the spatial arrangement of temporary facilities such as site offices, storage yards, and equipment zones. Poorly planned layouts can lead to excessive travel distances, increased material handling times, and operational delays, all of which contribute to inflated costs and reduced productivity. Therefore, optimizing the layout of construction sites to minimize transportation distances and enhance workflow is a critical task for project managers, contractors, and other stakeholders. The challenge in CSLP lies in the complexity of simultaneously satisfying multiple, often conflicting, requirements such as space constraints, safety regulations, and functional proximities. This complexity is compounded by the dynamic nature of construction activities and the presence of numerous facilities to be allocated within limited and irregularly shaped site boundaries. Mathematically, this problem can be formulated as a Quadratic Assignment Problem (QAP), a well-known NP-hard combinatorial optimization problem. The QAP seeks to assign a set of facilities to specific locations in a manner that minimizes the total cost, typically modeled as the sum of products of flows (e.g., material movement) and distances between assigned locations. However, due to the computational complexity of QAP, exact solutions become impractical for medium to large-scale site layouts. In recent years, metaheuristic algorithms have gained traction for effectively tackling such complex optimization problems. Among these, the Advanced Jaya Algorithm (A-JA), a recent population-based metaheuristic, stands out for its simplicity, parameter-free nature, and robust search capabilities. This study applies the A-JA to solve the CSLP modeled as a QAP, aiming to minimize the total weighted travel distance of material handling within the site. The algorithm’s performance is validated through two realistic case studies, showcasing its strong search capabilities and competitive results compared to traditional optimization methods. This promising approach offers a valuable decision-support tool for construction managers seeking to enhance site operational efficiency. Full article

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15 pages, 2733 KB

Open AccessArticle

AI-Enhanced Virus Detection in Biopharmaceutical Production Processes

by Wei He, Zhihao Xu, Ziyi Wang, Hang Lin, Li Xie and Hailin Yang

Appl. Sci. 2025, 15(18), 10294; https://doi.org/10.3390/app151810294 - 22 Sep 2025

Abstract

Ensuring viral safety is a fundamental requirement in the production of biopharmaceutical products. Transmission Electron Microscopy (TEM) has long been recognized as a critical tool for detecting viral particles in unprocessed bulk (UPB) samples, yet manual counting remains labor-intensive, time-consuming, and prone to [...] Read more.

Ensuring viral safety is a fundamental requirement in the production of biopharmaceutical products. Transmission Electron Microscopy (TEM) has long been recognized as a critical tool for detecting viral particles in unprocessed bulk (UPB) samples, yet manual counting remains labor-intensive, time-consuming, and prone to errors. To address these limitations, we propose an enhanced virus strain detection approach using the YOLOv11 deep learning framework, optimized with C3K2, SPPF, and C2PSA modules in the backbone, PANet in the neck, and Depthiwise Convolution (DWConv) in the head. To further improve feature fusion and detection of single-class virus particles, we integrated BiFPN and C3K2_IDWC modules. The resulting model (YOLOv11n + BiFPN + IDWC) achieves an mAP@0.5 of 0.995 with 33.6% fewer parameters compared to YOLOv11n, while increasing accuracy by 1.3%. Compared to YOLOv8n and YOLOv10n, our approach shows superior performance in both detection accuracy and computational efficiency. These results demonstrate that the model offers a robust and scalable solution for real-time virus detection and downstream process monitoring in the pharmaceutical industry. Full article

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37 pages, 8947 KB

Open AccessArticle

Experimental and Numerical Analysis on the Static and Dynamic Performance of Adhesive Bolts in Various Ground Conditions

by Tshepiso Mollo, Fhatuwani Sengani and Jeffrey Mahachi

Appl. Sci. 2025, 15(18), 10293; https://doi.org/10.3390/app151810293 - 22 Sep 2025

Abstract

This study evaluates adhesive bolts (chemical anchors) bonded with epoxy and vinyl ester resins for surface and tunnel excavations in tropical mining environments under static and dynamic loading. Over 300 pull-out tests in concrete and hard rock examined the effects of bolt length, [...] Read more.

This study evaluates adhesive bolts (chemical anchors) bonded with epoxy and vinyl ester resins for surface and tunnel excavations in tropical mining environments under static and dynamic loading. Over 300 pull-out tests in concrete and hard rock examined the effects of bolt length, curing time, and substrate condition on load capacity, failure mode, and bond–slip response. Epoxy anchors exhibited higher bond strength, including under early-age and thermally active conditions, while vinyl ester showed improved ductility and post-peak behaviour in fractured rock. Numerical modelling with Rocscience RS2 (Phase 2) and Unwedge simulated excavation responses for bolt lengths of 190–250 mm and spacings of 0.5–2.0 m. Tensile failure dominated at wider spacings, whereas closely spaced anchors enhanced confinement and redistributed stresses. The combined experimental–numerical evidence quantifies chemical-anchor performance in complex subsurface settings and supports their use for early-age support and long-term stability. Findings motivate integration of resin-grouted bolts into modern support designs, particularly in seismically sensitive or hydrothermally variable mines. Full article

(This article belongs to the Special Issue Latest Advances in Rock Mechanics and Geotechnical Engineering)

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15 pages, 269 KB

Open AccessArticle

Impacts of Conventional and Agri-Food Waste-Derived Fertilizers on Durum Wheat Yield, Grain Quality, and Soil Health: A Two-Year Field Study in Greece and Southern Italy

by Adele Muscolo, Kostantinos Zoukidis, Evangelous Vergos, Federica Alessia Marra, Ludovica Santoro, Mariateresa Oliva, Santo Battaglia, Angela Maffia and Carmelo Mallamaci

Appl. Sci. 2025, 15(18), 10292; https://doi.org/10.3390/app151810292 - 22 Sep 2025

Abstract

Sustainable fertilization strategies are critical under climate change and the European Green Deal, particularly for Mediterranean cereal systems. Organic fertilizers derived from agro-industrial residues offer promising alternatives to conventional mineral inputs. This study evaluated RecOrgFert, a novel fertilizer composed of sulfur–bentonite and citrus-processing [...] Read more.

Sustainable fertilization strategies are critical under climate change and the European Green Deal, particularly for Mediterranean cereal systems. Organic fertilizers derived from agro-industrial residues offer promising alternatives to conventional mineral inputs. This study evaluated RecOrgFert, a novel fertilizer composed of sulfur–bentonite and citrus-processing residues, in comparison with NPK (15-15-15) and horse manure across two years in Central Macedonia (Greece) and Apulia (Italy). Using a randomized complete block design, soil chemical and biological properties, plant growth, yield, and grain quality were assessed. RecOrgFert outperformed conventional fertilizers by enhancing soil fertility—raising organic matter 25–27% above control and further increasing it from 2023 to 2024 (up to +75% in Italy, +38% in Greece)—while improving cation exchange capacity, enzymatic activity, and soil water content. Wheat grown with RecOrgFert showed higher protein (up to 15.2%), antioxidant activity (DPPH > 37%, ABTS⁺ > 26%), and phenolic and flavonoid content, with yields comparable to NPK. The unique sulfur and orange-residue composition distinguish RecOrgFert from standard fertilizers, promoting nutrient cycling, microbial activity, and bioactive compound accumulation. It represents a novel, circular, and climate-smart solution aligned with EU sustainability and circular economy objectives. Full article

(This article belongs to the Special Issue Biological Activity, Chemical Characterization and Contaminants of Plants and Waste: 2nd Edition)

14 pages, 1581 KB

Open AccessArticle

Quantification of Caffeic Acid as Well as Antioxidant and Cytotoxic Activities of Ucuuba (Virola surinamensis) Co-Product Extract to Obtain New Functional and Nutraceutical Foods

by Lindalva Maria de Meneses Costa Ferreira, Rayanne Rocha Pereira, Kalene de Almeida Oliveira, Attilio Converti, Edilene Oliveira da Silva, José Otávio Carréra Silva-Júnior and Roseane Maria Ribeiro-Costa

Appl. Sci. 2025, 15(18), 10291; https://doi.org/10.3390/app151810291 - 22 Sep 2025

Abstract

Ucuuba (Virola surinamensis) is a fruit of Amazonian origin with anti-inflammatory, nutritional, and phenolic substances. This study aimed to prepare and characterize the ucuuba co-product extract as well as to evaluate its antioxidant and cytotoxic activities, proximate composition, and water activity. [...] Read more.

Ucuuba (Virola surinamensis) is a fruit of Amazonian origin with anti-inflammatory, nutritional, and phenolic substances. This study aimed to prepare and characterize the ucuuba co-product extract as well as to evaluate its antioxidant and cytotoxic activities, proximate composition, and water activity. For this purpose, the co-product and its extract were analyzed by Fourier-transform infrared (FTIR) spectroscopy, and their thermal behavior was investigated by thermogravimetry (TG). The ucuuba co-product extract was also evaluated for its contents of total polyphenols and flavonoids, antioxidant activity by the DPPH and ABTS assays, and cytotoxicity in normal J774.A1 macrophages by the MTT technique. The co-product proved to have important macronutrient contents from a nutritional point of view, i.e., 11.67 ± 0.731% fiber, 16.67 ± 0.36% lipids, 38.32 ± 0.19% proteins, and 30.56% carbohydrates, as well as low moisture content (6.73 ± 0.05%) and water activity (0.403). FTIR spectra showed characteristic absorption peaks of phenolic compounds. The ucuuba co-product (pressed seeds) and the extract obtained from the ucuuba seed co-product were stable at around 100 °C and showed two mass loss events typical of natural products. The extract contained total polyphenols and flavonoids amounting to 806.45 mg/100 g and 62 mg RE/100 g, respectively, and its antioxidant activity according to the DPPH and ABTS assays was 374.33 and 258.15 µM Trolox/g, respectively. Caffeic acid was identified as an abundant phenolic compound (5.17 µg/mL) by high-performance liquid chromatography (HPLC-DAD), and its quantification method was validated. Furthermore, there was no cytotoxicity in the macrophage cell line at concentrations up to 100 µg/mL. These results indicate that the ucuuba co-product could be reused to develop new functional and nutraceutical foods. Full article

(This article belongs to the Section Chemical and Molecular Sciences)

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10 pages, 1471 KB

Open AccessCommunication

Unsaturated Fatty Acid Oil-Based Microdroplets: A Promising Novel Class of Microdroplets

by Mitra Shojania Feizabadi, Ramiz Alejilat and Amy Ataalla

Appl. Sci. 2025, 15(18), 10290; https://doi.org/10.3390/app151810290 - 22 Sep 2025

Abstract

Droplet-based microfluidics has rapidly advanced applications in chemistry, biology, materials science, medicine, food science, and cosmetics. Using this technology, various oils have been employed for fluid encapsulation. This study is the first to investigate the use of an animal-based unsaturated fatty acid oil—emu [...] Read more.

Droplet-based microfluidics has rapidly advanced applications in chemistry, biology, materials science, medicine, food science, and cosmetics. Using this technology, various oils have been employed for fluid encapsulation. This study is the first to investigate the use of an animal-based unsaturated fatty acid oil—emu oil—for microdroplet formation. We characterized droplet generation in the presence and absence of a non-fluorinated surfactant at a defined concentration and examined the influence of geometrical parameters using T-junction microchannels with two different central channel widths. The results were compared with those obtained from a plant-based oil (olive oil) under parallel experimental conditions. Given the growing concerns regarding the environmental and health risks of fluorocarbon oils combined with fluorinated surfactants, which are widely used in microfluidics, emu oil represents a potentially safer alternative for microdroplet-based technologies across multiple fields. Full article

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18 pages, 1769 KB

Open AccessArticle

A Method for Determining the Soil Shear Strength by Eliminating the Heteroscedasticity and Correlation of the Regression Residual

by Heng Chi, Hengdong Wang, Yufeng Jia and Degao Zou

Appl. Sci. 2025, 15(18), 10289; https://doi.org/10.3390/app151810289 - 22 Sep 2025

Abstract

Due to cost and variability of geotechnical test results, the number of samples for geotechnical material parameters in one engineering project is limited, resulting in a certain degree of errors in the calculation of probability distribution, mean, and variance of mechanical parameters of [...] Read more.

Due to cost and variability of geotechnical test results, the number of samples for geotechnical material parameters in one engineering project is limited, resulting in a certain degree of errors in the calculation of probability distribution, mean, and variance of mechanical parameters of the geotechnical materials. To improve the reliability of geotechnical engineering design, reducing the variance of shear strength is one of the methods. Currently, the least squares method is widely used to regress the shear strength of soil; however, the regression residuals often exhibit heteroscedasticity and correlation, which undermine the validity of the variance estimates of soil shear strength parameters. This study aims to address this issue by applying the generalized least squares method to eliminate the heteroscedasticity and correlation of regression residuals. The results of triaxial consolidated drained (CD) tests on the coarse-grained soil; triaxial unconsolidated undrained(UU), CD, and consolidated undrained (CU) tests on gravelly clay; and triaxial CD tests on sand were analyzed to estimate the mean and variance of their shear strength. The results show that while the mean values of shear strength parameters remain largely unchanged, the generalized least squares method reduces the standard deviation of cohesion by an average of 30.575% and that of the internal friction angle by 14.21%. This reduction in variability enhances the precision of parameter estimation, which is critical for reliability-based design in geotechnical engineering, as it leads to more consistent safety assessments and optimized structural designs. The reliability analysis of an infinitely long slope stability shows that the reliability index of the soil slope calculated by the traditional method is either large or small. The generalized least squares method, which eliminates the heteroscedasticity and correlation of the regression residuals, should be adopted to regress the shear strength of soil. Full article

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22 pages, 2938 KB

Open AccessArticle

Real-Time Braille Image Detection Algorithm Based on Improved YOLOv11 in Natural Scenes

by Yu Sun, Wenhao Chen, Yihang Qin, Xuan Li and Chunlian Li

Appl. Sci. 2025, 15(18), 10288; https://doi.org/10.3390/app151810288 - 22 Sep 2025

Abstract

The development of Braille recognition technology is intrinsically linked to the educational rights of individuals with visual impairments. The key challenges in natural scene Braille detection include three core trade-offs: difficulty extracting small-target features under complex background interference, a balance between model accuracy [...] Read more.

The development of Braille recognition technology is intrinsically linked to the educational rights of individuals with visual impairments. The key challenges in natural scene Braille detection include three core trade-offs: difficulty extracting small-target features under complex background interference, a balance between model accuracy and real-time performance, and generalization across diverse scenes. To address these issues, this paper proposes an improved YOLOv11 algorithm that integrates a lightweight gating mechanism and subspace attention. By reconstructing the C3k2 module into a hybrid structure containing Gated Bottleneck Convolutions (GBC), the algorithm effectively captures weak Braille dot matrix features. A super-lightweight subspace attention module (ULSAM) enhances the attention to Braille regions, while the SDIoU loss function optimizes bounding box regression accuracy. Experimental results on a natural scene Braille dataset show that the algorithm achieves a Precision of 0.9420 and a Recall of 0.9514 with only 2.374 M parameters. Compared to the base YOLOv11, this algorithm improves the combined detection performance (Precision: 0.9420, Recall: 0.9514) by 3.2% and reduces computational complexity by 6.3% (with only 2.374 M parameters). Ablation experiments validate the synergistic effect of each module: the GBC structure reduces the model parameter count by 8.1% to maintain lightweight properties, and the ULSAM effectively lowers the missed detection rate of ultra-small Braille targets. This study provides core algorithmic support for portable Braille assistive devices, advancing the technical realization of equal information access for individuals with visual impairments. Full article

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13 pages, 677 KB

Open AccessArticle

Catalyst and Process Effects in the Solvent-Free Hydrogenation of p-Cymene to p-Menthane

by Ayyoub Selka and Mohamed Touaibia

Appl. Sci. 2025, 15(18), 10287; https://doi.org/10.3390/app151810287 - 22 Sep 2025

Abstract

The hydrogenation of p-cymene to p-menthane, a bio-based solvent, over four platinum-group catalysts, was thoroughly investigated in this study. The effect of the support material, pressure, and temperature were explored. Rhodium was the most effective metal, even under normal pressure conditions. [...] Read more.

The hydrogenation of p-cymene to p-menthane, a bio-based solvent, over four platinum-group catalysts, was thoroughly investigated in this study. The effect of the support material, pressure, and temperature were explored. Rhodium was the most effective metal, even under normal pressure conditions. Charcoal was a better metal support compared to alumina, offering better selectivity at lower pressure and outstanding recyclability. Hydrogen pressure had no effect on the selectivity; however, the conversion rate was maximal at higher pressure. At higher temperatures, the thermodynamically stable trans-isomer was favored, whereas at lower temperatures the cis-isomer became predominant. Remarkably, Rh/C achieved >99% conversion of p-cymene and maintained stable activity and selectivity over 66 recycling cycles, whereas the same metal-based catalyst on alumina was only recycled twice. These findings demonstrate that the solvent-free hydrogenation of p-cymene can be efficiently achieved using commercially available catalysts, with Rh/C emerging as a promising benchmark for sustainable and green catalytic processes. Full article

(This article belongs to the Special Issue Advanced Phytochemistry and Its Applications)

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12 pages, 2006 KB

Open AccessCommunication

Simultaneous 4G and 5G EMF Exposure and Field Uniformity in a Reverberation Chamber for Animal Studies

by DukSoo Kwon, Sangbong Jeon, Ae-Kyoung Lee, Hyung-Do Choi and Jung-Ick Moon

Appl. Sci. 2025, 15(18), 10286; https://doi.org/10.3390/app151810286 - 22 Sep 2025

Abstract

The design and validation of a reverberation chamber (RC) specifically constructed for conducting large-scale experimental animal carcinogenicity studies using RF electromagnetic fields (EMF) relevant to contemporary 4G and 5G mobile communication (900 MHz, 2.12 GHz, and 3.65 GHz) is proposed. The RC’s electric [...] Read more.

The design and validation of a reverberation chamber (RC) specifically constructed for conducting large-scale experimental animal carcinogenicity studies using RF electromagnetic fields (EMF) relevant to contemporary 4G and 5G mobile communication (900 MHz, 2.12 GHz, and 3.65 GHz) is proposed. The RC’s electric field (E-field) uniformity is evaluated under four practical loading conditions: empty, apparatus only, and two apparatus variations with 80 experimental animals (Sprague–Dawley rats) with approximate weights 400 g and 520 g, respectively. Measurement results show E-field uniformity better than 1.36 dB under all test conditions, with frequency-dependent variation becoming negligible once the RC is loaded with cage racks and 80 rats. Additionally, a predictive method is introduced to estimate composite E-field intensities under simultaneous multi-frequency exposures, potentially reducing experimental measurements. These findings confirm that the designed RC is capable of accurately evaluating RF EMF exposure in biological studies. Full article

(This article belongs to the Section Electrical, Electronics and Communications Engineering)

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42 pages, 1304 KB

Open AccessReview

Exploring Protein Misfolding and Aggregate Pathology in Neurodegenerative Diseases: From Molecular Mechanisms to Clinical Interventions

by Joel Theophilus Johnson, Fila Winifred Awosiminiala and Christian Kosisochukwu Anumudu

Appl. Sci. 2025, 15(18), 10285; https://doi.org/10.3390/app151810285 - 22 Sep 2025

Abstract

Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease are characterized by progressive neuronal loss, driven mainly by the misfolding, aggregation, and accumulation of each disease’s specific proteins. These pathogenic aggregates, including tau, α-synuclein, TDP-43, and huntingtin, disrupt cellular proteostasis and [...] Read more.

Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease are characterized by progressive neuronal loss, driven mainly by the misfolding, aggregation, and accumulation of each disease’s specific proteins. These pathogenic aggregates, including tau, α-synuclein, TDP-43, and huntingtin, disrupt cellular proteostasis and initiate cascades of neuroinflammation, oxidative stress, mitochondrial dysfunction, and synaptic failure. While protein aggregation has been a long-recognized hallmark of these disorders, growing evidence points towards a more complex interplay of initial molecular pathways with defects in RNA processing, stress granule pathology, and cell-type-specific vulnerability. Notably, such events may manifest differentially with respect to sex and are further modulated by age-related loss of the protein quality control processes like the ubiquitin–proteasome pathway, autophagy–lysosome pathway, and molecular chaperones. This review synthesizes current insights into the structural and functional dynamics of protein aggregation and its significance for neuronal well-being. It highlights the role of post-translational modifications, prion-like transmission, and aggregation kinetics in the regulation of toxicity. The review further discusses promising therapeutic strategies centered on restoring proteostasis, including small molecules that inhibit aggregation, protein clearance pathway enhancers, immunotherapy, antioxidant therapy, and diagnostic prospects such as the identification of reliable molecular signatures in bodily fluids that can reflect pathological changes even before clinical symptoms emerge. Advancements in single-cell transcriptomics and multi-omics platforms, which are changing our understanding of disease onset and progression and opening avenues for precision medicine and personalized treatments, were also discussed. Ultimately, deciphering the molecular logic that distinguishes physiological from pathological protein assemblies and understanding how cellular systems fail to adapt under stress will be key to the development of effective, disease-modifying therapies for these debilitating disorders. Full article

(This article belongs to the Special Issue Molecular Mechanisms, Diagnosis and Therapeutics of Neurodegenerative Diseases)

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22 pages, 1753 KB

Open AccessReview

Holoscopic 3D Imaging Systems: A Review of History, Recent Advances and Future Directions

by Yi Liu, Hongying Meng, Mohammad Rafiq Swash, Yiyuan Huang and Chen Yan

Appl. Sci. 2025, 15(18), 10284; https://doi.org/10.3390/app151810284 - 22 Sep 2025

Abstract

As the demand for high-quality visual experiences continues to grow, advanced imaging technologies offering higher realism and immersion are being increasingly integrated into various fields. Among them, glasses-free 3D imaging has gained significant attention for enhancing user experience without the need for wearable [...] Read more.

As the demand for high-quality visual experiences continues to grow, advanced imaging technologies offering higher realism and immersion are being increasingly integrated into various fields. Among them, glasses-free 3D imaging has gained significant attention for enhancing user experience without the need for wearable equipment. Holoscopic 3D imaging systems, known for their capability to reconstruct true volumetric images and provide natural depth perception, have emerged as a promising direction within this domain. Originating from early 20th-century optical theory, holoscopic imaging has evolved in response to diversified application scenarios and rapid advancements in micro-optics and computational imaging. This paper presents a representative historical overview of the development of holoscopic 3D systems, their unique features compared to other glasses-free 3D technologies, and their expanding presence in these applications. By analyzing representative use cases across sectors such as healthcare, education, cultural heritage, and media entertainment, this review offers a broader and more detailed perspective on the deployment of holoscopic 3D systems. Furthermore, this paper discusses current technical challenges and outlines future research directions, with a particular focus on the transformative potential of holoscopic 3D in the creative and entertainment industries. This study aims to provide both theoretical grounding and practical insights to support the next generation of holoscopic 3D imaging technologies. Full article

(This article belongs to the Special Issue State-of-the-Art 3D Imaging, Processing and Display Technologies)

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14 pages, 2435 KB

Open AccessArticle

Study on the Stability of Buildings During Excavation in Urban Core Areas

by Kang Liu, Huafeng Liu, Yuntai Gao, Zijian Wang, Yunchuan Wang, Qi Liu, Chaolin Jia, Zihang Huang and Bin Zhang

Appl. Sci. 2025, 15(18), 10283; https://doi.org/10.3390/app151810283 - 22 Sep 2025

Abstract

Excavations in urban cores, in close proximity to existing structures, can significantly influence the structural loading. This study, based on a specific section of the foundation pit for the Yaoziqiu area road network project, constructs a mechanical analysis model to assess the impact [...] Read more.

Excavations in urban cores, in close proximity to existing structures, can significantly influence the structural loading. This study, based on a specific section of the foundation pit for the Yaoziqiu area road network project, constructs a mechanical analysis model to assess the impact of foundation pit construction on adjacent buildings. The research examines how various factors, including the distance between the building and the pit, pile length, retaining wall thickness, and the depth of the retaining wall’s embedment, affect the deformation response of the structures. The results indicate that when the building is 5 m away from the foundation pit, the maximum pile foundation settlement is 13.45 mm. When the distance is 30 m, the settlement value is 6.91 mm, with a decrease of 6.54 mm. The effect of foundation pit excavation on pile foundation settlement is significantly reduced when the pile length exceeds 15 m. When the thickness of the retaining wall increases from 0.5 m to 0.7 m, the maximum settlement of the building foundation is reduced by 1.34 mm, a decrease of 8.38%. When the thickness increases from 0.9 m to 1.1 m, the maximum settlement of the building foundation is reduced by 0.6 mm, a decrease of 4.17%. When the embedded depth of the retaining structure increases from 10 m to 15 m, the maximum settlement is reduced by only 1.05 mm. When the embedded depth is increased to 25 m, the change in the settlement value of the building foundation is within 0.2 mm. This study offers a detailed quantitative analysis of the factors influencing structural deformation, providing specific guidance for developing risk minimization strategies in planning excavations near existing structures. Full article

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15 pages, 4604 KB

Open AccessArticle

A JPEG Reversible Data Hiding Algorithm Based on Block Smoothness Estimation and Optimal Zero Coefficient Selection

by Ya Yue, Minqing Zhang, Peizheng Lai and Fuqiang Di

Appl. Sci. 2025, 15(18), 10282; https://doi.org/10.3390/app151810282 - 22 Sep 2025

Abstract

To address the issues of image quality degradation and file size expansion encountered during reversible data hiding (RDH) of JPEG images, a JPEG reversible data hiding algorithm based on block smoothness estimation and optimal zero coefficient selection is proposed. Firstly, a block smoothness [...] Read more.

To address the issues of image quality degradation and file size expansion encountered during reversible data hiding (RDH) of JPEG images, a JPEG reversible data hiding algorithm based on block smoothness estimation and optimal zero coefficient selection is proposed. Firstly, a block smoothness estimation strategy is designed based on the number of zero coefficients and non-zero quantisation table values within DCT blocks, prioritising DCT blocks with higher smoothness for information embedding. Subsequently, under a given embedding payload, an optimal zero coefficient selection strategy is introduced. Blocks are partitioned into embedding regions and non-embedding regions based on a preset position threshold T. Within embedding regions, the frequency of zero coefficients at different positions across all blocks is statistically analysed, with embedding prioritised at positions exhibiting the highest zero coefficient frequency to enhance embedding efficiency. Concurrently, by setting positive and negative displacement gaps to constrain the modification range of non-zero coefficients, invalid shifts are minimised. This further enhances visual quality while controlling file expansion. Experimental results demonstrate that, compared to existing algorithms, the proposed method achieves a peak signal-to-noise ratio improvement of 0.75 to 3.62 dB under fixed embedding capacity. File expansion is reduced by 1038 to 2243 bits, whilst enabling fully reversible image restoration. Full article

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12 pages, 1899 KB

Open AccessArticle

Fractal Analysis of the Microstructure and Functional Properties of Milk Powders

by Katarzyna Kiełczewska, Michał Smoczyński, Elżbieta Haponiuk and Bogdan Dec

Appl. Sci. 2025, 15(18), 10281; https://doi.org/10.3390/app151810281 - 22 Sep 2025

Abstract

(1) Background: The impact of different drying methods on the functional properties and microstructure of milk powders was analyzed in this study. (2) Methods: Whole milk, skim milk, and buttermilk powders were obtained by freeze drying, spray drying, and roller drying. (3) Results: [...] Read more.

(1) Background: The impact of different drying methods on the functional properties and microstructure of milk powders was analyzed in this study. (2) Methods: Whole milk, skim milk, and buttermilk powders were obtained by freeze drying, spray drying, and roller drying. (3) Results: The examined powders differed in chemical composition, and these differences were attributed mainly to their fat content. The functional properties of the studied powders were determined mainly by the drying method and were less influenced by their composition. Loose and tapped bulk density was highest in roller-dried powders and lowest in freeze-dried powders. The flowability of milk powders was determined by calculating the Carr index and the Hausner ratio, and the results were used to classify the analyzed powders into the following groups: poorly flowing and cohesive (spray-dried samples), passable (roller-dried samples), and fair (freeze-dried samples). The volume of insoluble particles was highest in roller-dried powders and much lower in spray-dried powders, whereas freeze-dried powders were 99.8–99.9% soluble in water. Whole milk powder was characterized by low wettability (>180 s) regardless of the drying method. Powder morphology was influenced mainly by the drying method. (4) Conclusions: The fractal analysis demonstrated that spray-dried powders had the smallest fractal dimensions, which implies that their surface was least complex (most uniform). Regardless of the drying method, fractal dimensions were highest in whole milk powder, which could suggest that fat affects the microstructure of powders. The color parameters of milk powders were determined mainly by the drying method and were less influenced by the type of raw material used in powder production. Full article

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19 pages, 4057 KB

Open AccessArticle

Multi-Objective Optimization of PMSM Servo System Control Performance Based on Artificial Neural Network and Genetic Algorithm

by Futeng Li, Xianglong Li, Huan Hou and Xiyang Xie

Appl. Sci. 2025, 15(18), 10280; https://doi.org/10.3390/app151810280 - 22 Sep 2025

Abstract

With the rapid advancement of intelligent technologies, permanent magnet synchronous motor (PMSM) servo systems have seen increasing applications in industrial fields, accompanied by continuously rising control performance demands. Moreover, the adjustment of controller parameters is pivotal for the performance optimization of servo systems. [...] Read more.

With the rapid advancement of intelligent technologies, permanent magnet synchronous motor (PMSM) servo systems have seen increasing applications in industrial fields, accompanied by continuously rising control performance demands. Moreover, the adjustment of controller parameters is pivotal for the performance optimization of servo systems. This paper presents an optimization method for PMSM servo systems based on the coupling technique of the neural network surrogate model and intelligent optimization algorithm. A hybrid model is constructed by the proposed method, integrating a mathematical model based on transfer functions with an artificial neural network surrogate model, which is employed to compensate for the discrepancies between the mathematical model and the actual measured values. The accuracy and superiority of the hybrid model are comprehensively validated through training and validation loss analysis, fitting plot construction, and ablation experiments. Subsequently, based on the hybrid model, the qualitative and quantitative comparative analysis of the Pareto fronts of five commonly used multi-objective intelligent optimization algorithms is conducted. The optimal algorithm is determined through experimental validation of the optimization results to obtain the optimal result. The optimal result demonstrates that, compared to the initial result before optimization, the overshoot is reduced by 89.7%, and the settling time is reduced by 80.1%. Additionally, several other non-dominated solutions are available for selection, and all optimized results are superior to the initial result. This study provides a novel idea and method for the performance optimization of PMSM servo systems, contributing to the field with a robust and effective approach to enhance system control performance. Full article

(This article belongs to the Special Issue Mechatronic Systems Design and Optimization)

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5 pages, 160 KB

Open AccessEditorial

Special Issue: Trends and Prospects in Applied Electromagnetics

by Yating Yu and Baolin Nie

Appl. Sci. 2025, 15(18), 10279; https://doi.org/10.3390/app151810279 - 22 Sep 2025

Abstract

With the rapid advancement of information technology, humans are living in an increasingly intricate electromagnetic environment [...] Full article

(This article belongs to the Special Issue Trends and Prospects in Applied Electromagnetics)

18 pages, 5708 KB

Open AccessArticle

Investigation on Similitude Materials with Controlled Strength and Permeability for Physical Model Tests

by Yao Rong, Yangchen Wang, Yitian Yu, Yang Sun and Jingliang Dong

Appl. Sci. 2025, 15(18), 10278; https://doi.org/10.3390/app151810278 - 22 Sep 2025

Abstract

To meet the demand for simulative materials exhibiting suitable hydraulic characteristics in geomechanical model tests, this research developed a type of simulative material using iron powder, quartz sand, and barite powder as aggregates, white cement as binder, and silicone oil as additive. An [...] Read more.

To meet the demand for simulative materials exhibiting suitable hydraulic characteristics in geomechanical model tests, this research developed a type of simulative material using iron powder, quartz sand, and barite powder as aggregates, white cement as binder, and silicone oil as additive. An orthogonal experimental design L₁₆(4⁴) was employed to prepare 16 distinct mix proportions. Advanced statistical methods, including range analysis, residual analysis, Pearson correlation analysis, and multiple regression performed with SPSS 27.0.1, were applied to analyze the influence of four factors—aggregate-to-cement ratio (A), water–cement ratio (B), silicone oil content (C), and moisture content (D)—on physical and mechanical parameters such as density, uniaxial compressive strength, elastic modulus, angle of internal friction, and permeability coefficient. Range analysis results indicate that the aggregate-to-cement ratio serves as the primary controlling factor for density and elastic modulus; moisture content exerts the most significant effect on compressive strength and permeability; while the water–cement ratio is the dominant factor influencing the internal friction angle. Empirical formulas were established through multiple regression to quantitatively correlate mix proportions with material properties. The resulting similitude materials cover a wide range of mechanical and hydraulic parameters, satisfying the requirements of large-scale physical modeling with high similitude ratios. The proposed equations allow efficient inverse design of mixture ratios based on target properties, thereby supporting the rapid preparation of simulative materials for advanced model testing. Full article

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29 pages, 4444 KB

Open AccessArticle

Meta-Heuristic Optimization Model for Base Stress Distribution in Elastic Continuous Foundations with Large Eccentricity

by Seda Turan, İbrahim Aydoğdu and Engin Emsen

Appl. Sci. 2025, 15(18), 10277; https://doi.org/10.3390/app151810277 - 22 Sep 2025

Abstract

This study focuses on determining stress distribution in elastic continuous beam foundations subjected to large eccentricities primarily induced by the overturning moments generated when horizontal forces, like those from earthquakes and wind, act on the superstructure. Traditional linear static solutions provide an incorrect [...] Read more.

This study focuses on determining stress distribution in elastic continuous beam foundations subjected to large eccentricities primarily induced by the overturning moments generated when horizontal forces, like those from earthquakes and wind, act on the superstructure. Traditional linear static solutions provide an incorrect stress distribution when a foundation loses partial contact with the ground, as they erroneously calculate tensile stress in the uplifted regions. This research aims to formulate a mathematical model that accurately calculates the corrected stress distribution. An optimization problem is defined to minimize the discrepancy between the external effects (loads and moments) from the superstructure and the internal resistance effects from the redistributed base stress under the condition of partial foundation uplift. To solve this, meta-heuristic optimization methods, including Artificial Bee Colony (ABC), Tree Seed Algorithm (TSA), and Biogeography-Based Optimization (BBO), are employed to derive accurate mathematical formulas. The performance of these methods is evaluated under varying soil conditions and loading scenarios. The Tree Seed Method has consistently delivered the most accurate results, with near-zero optimization errors. The findings provide the applicability of algorithmic methods and their potential for improving stress distribution modeling in elastic foundations. Full article

(This article belongs to the Section Civil Engineering)

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19 pages, 1820 KB

Open AccessArticle

PROMPT-BART: A Named Entity Recognition Model Applied to Cyber Threat Intelligence

by Xinzhu Feng, Songheng He, Xinxin Wei, Runshi Liu, Huanzhou Yue and Xuren Wang

Appl. Sci. 2025, 15(18), 10276; https://doi.org/10.3390/app151810276 - 22 Sep 2025

Abstract

The growing sophistication of cyberattacks underscores the need for the automated extraction of machine-readable intelligence from unstructured Cyber Threat Intelligence (CTI), commonly achieved through Named Entity Recognition (NER). However, existing CTI-oriented NER research faces two major limitations: the scarcity of standardized datasets and [...] Read more.

The growing sophistication of cyberattacks underscores the need for the automated extraction of machine-readable intelligence from unstructured Cyber Threat Intelligence (CTI), commonly achieved through Named Entity Recognition (NER). However, existing CTI-oriented NER research faces two major limitations: the scarcity of standardized datasets and the lack of advanced models tailored to domain-specific entities. To address the dataset challenge, we present CTINER, the first STIX 2.1-aligned dataset, comprising 42,549 annotated entities across 13 cybersecurity-specific types. CTINER surpasses existing resources in both scale (+51.82% more annotated entities) and vocabulary coverage (+40.39%), while ensuring label consistency and rationality. To tackle the modeling challenge, we propose PROMPT-BART, a novel NER model built upon the BART generative framework and enhanced through three types of prompt designs. Experimental results show that PROMPT-BART improves F1 scores by 4.26–8.3% over conventional deep learning baselines and outperforms prompt-based baselines by 1.31%. Full article

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29 pages, 5920 KB

Open AccessArticle

Design of a Novel Integrated Solid–Liquid Separation and Mixing Pin Screw for CF-PLA Particle-Based 3D Printing: Fluid Simulation and Performance Evaluation

by Jun Wang, Xinke Liu, Guanjun Fu, Xipeng Luo, Hang Hu, Shuisheng Chen and Yizhe Huang

Appl. Sci. 2025, 15(18), 10275; https://doi.org/10.3390/app151810275 - 22 Sep 2025

Abstract

Particle-based 3D printing shows great potential in high-performance composite fabrication due to high raw material utilization and flexible material compatibility. However, constrained by conventional extrusion system structures, critical issues (non-uniform melt conveying, insufficient mixing efficacy, poor extrusion stability, etc.) remain. To address these, [...] Read more.

Particle-based 3D printing shows great potential in high-performance composite fabrication due to high raw material utilization and flexible material compatibility. However, constrained by conventional extrusion system structures, critical issues (non-uniform melt conveying, insufficient mixing efficacy, poor extrusion stability, etc.) remain. To address these, this study proposes a novel separate-type pin screw integrating solid–liquid separation (from split screws) and high-efficiency mixing (from pin screws) to improve CF/PLA composite extrusion efficiency and mixing homogeneity in particle-based 3D printing. Three-dimensional modeling, static strength/stiffness analysis, and POLYFLOW-based numerical simulation of particle melt conveying/mixing in the screw channel were conducted to analyze structural parameter effects on pressure field, shear rate, and mixing. Experiments assessed printer extrusion rate (different screws) and printed specimen mechanical properties. The simulation and experiment confirmed the optimized screw has better pressure distribution and mixing at 20 rpm, with optimal pin parameters: diameter 2 mm, height 1.6 mm, radial angle 60°, and axial spacing 10 mm. This work offers theoretical/structural support for particle-based 3D printing extrusion system optimization. Full article

(This article belongs to the Section Additive Manufacturing Technologies)

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5 pages, 168 KB

Open AccessEditorial

New Findings in Visual Communications on Visibility or Legibility in Different Media

by Klementina Možina and Maja Brozović

Appl. Sci. 2025, 15(18), 10274; https://doi.org/10.3390/app151810274 - 22 Sep 2025

Abstract

The visibility and legibility of graphic elements and typography in different colours are crucial for the rapid absorption and processing of information, the speed of which depends on typography and graphic design [...] Full article

(This article belongs to the Special Issue New Findings in Visual Communications on Visibility or Legibility in Different Media)

20 pages, 4063 KB

Open AccessArticle

Standard Reference Thermoelectric Modules Based on Metallic Combinations and Geometric Design

by EunA Koo, Hanhwi Jang, SuDong Park, Sang Hyun Park and Sae-byul Kang

Appl. Sci. 2025, 15(18), 10273; https://doi.org/10.3390/app151810273 - 22 Sep 2025

Abstract

To establish a reliable thermoelectric module evaluation, a Standard Reference Thermoelectric Module (SRTEM) was developed based on stability. Open-circuit voltage (V_oc) was selected as the key calibration parameter due to its consistent response to temperature differences (ΔT). The SRTEM consists of [...] Read more.

To establish a reliable thermoelectric module evaluation, a Standard Reference Thermoelectric Module (SRTEM) was developed based on stability. Open-circuit voltage (V_oc) was selected as the key calibration parameter due to its consistent response to temperature differences (ΔT). The SRTEM consists of eight p–n thermoelectric couples composed of metallic thermoelectric materials—Ni₉₀Cr₁₀ (chromel), Cu₅₅Ni₄₅ (constantan), Fe₆₄Ni₃₆ (invar), and pure Fe—selected based on their thermoelectric properties, structural compatibility, and contact resistance. Among the tested combinations, the chromel–constantan pair exhibited the highest V_oc of 55 mV at ΔT = 150 K. To increase V_oc and expand the usable calibration range, leg-shape modification and substrate replacement were investigated. Module simulation revealed that replacing the rectangular-leg geometry with a double-hourglass (2H/G) structure could increase V_oc by 20.2%. Furthermore, measurement of single-leg modules with substrates attached confirmed a 16.0% improvement in V_oc for the 2H/G shape over the rectangular shape, consistent with the predicted enhancement due to increased thermal resistance. In addition, replacing the alumina substrate with a higher thermal conductivity material, such as AlN, increased ΔT across the legs and yielded a further 9.1% improvement in V_oc. These results demonstrate the potential of the proposed SRTEM as a calibration standard for consistent thermoelectric module measurements. Full article

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17 pages, 6465 KB

Open AccessArticle

The Feasibility of Combining 3D Cine bSSFP and 4D Flow MRI for the Assessment of Local Aortic Pulse Wave Velocity

by Renske Merton, Daan Bosshardt, Gustav J. Strijkers, Aart J. Nederveen, Eric M. Schrauben and Pim van Ooij

Appl. Sci. 2025, 15(18), 10272; https://doi.org/10.3390/app151810272 - 21 Sep 2025

Abstract

Pulse wave velocity (PWV) is a key marker of aortic stiffness and cardiovascular risk, yet current methods typically offer only global or regional estimates and lack the possibility to measure local variations along the thoracic aorta. This study aimed to develop and evaluate [...] Read more.

Pulse wave velocity (PWV) is a key marker of aortic stiffness and cardiovascular risk, yet current methods typically offer only global or regional estimates and lack the possibility to measure local variations along the thoracic aorta. This study aimed to develop and evaluate a pipeline for assessing local aortic PWV using the flow–area (QA) method (PWV_QA) by combining high-resolution 4D MRI techniques. A 3D cine balanced steady-state free precession (bSSFP) sequence was used to capture dynamic changes in aortic geometry, while 4D flow MRI measured time-resolved blood flow. The QA method was applied during the reflection-free early systolic phase. Scan–rescan reproducibility was assessed in six healthy volunteers, and feasibility was additionally explored in Marfan syndrome patients. The mean ± SD values of the Pearson correlation coefficients for per-slice maximum area, velocity, flow, and PWV_QA were 0.99 ± 0.00, 0.82 ± 0.11, 0.96 ± 0.01, and 0.20 ± 0.35, respectively. The median (Q1–Q3) average PWV_QA was 6.6 (5.4–9.4) m/s for scan 1 and 9.1 (6.7–11.3) m/s for scan 2 (p = 0.16) in healthy volunteers and 7.1 (6.9–8.0) m/s in Marfan patients. Combining 4D bSSFP and 4D flow MRI is technically feasible, but the derived PWV_QA maps show high variability, particularly in the aortic root and descending aorta, requiring further optimization. Full article

(This article belongs to the Special Issue Biomedical Imaging Technologies for Cardiovascular Disease, 4th Edition)

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