Applied Sciences

12 pages, 2038 KiB

Open AccessCommunication

Total Synthesis of Surfactant-Mimetic Nanocolloids via Regioselective Silica Deposition on Bottlebrush Polymers

by Junyi Zeng, Linlin Li, Li Ai, Kai Song, Heng Zhai and Chenglin Yi

Appl. Sci. 2025, 15(15), 8766; https://doi.org/10.3390/app15158766 - 7 Aug 2025

Viewed by 416

Molecular-mimetic nanocolloids (MMNCs) are promising for advanced materials, yet self-assembly fabrication faces challenges in purity and programmability. We report a total synthesis strategy for surfactant-mimetic nanocolloids (SMNCs), an amphiphilic MMNC subclass. SMNCs consist of a ~5 nm silica nanoparticle head and a bottlebrush [...] Read more.

Molecular-mimetic nanocolloids (MMNCs) are promising for advanced materials, yet self-assembly fabrication faces challenges in purity and programmability. We report a total synthesis strategy for surfactant-mimetic nanocolloids (SMNCs), an amphiphilic MMNC subclass. SMNCs consist of a ~5 nm silica nanoparticle head and a bottlebrush polymer tail. Regioselective silica deposition on linear-block-brush polymers via the modified sol–gel method enables precise control. This strategy is versatile and can be adapted to synthesize other MMNCs with different components. It offers a more controlled alternative to self-assembly methods, advancing MMNC synthesis and enabling their broader use in emerging technologies. Full article

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30 pages, 1329 KiB

Open AccessArticle

The Multi-Branch Deep-Learning-Based Approach to Heart Dysfunction Classification

by Krzysztof Hryniów, Bartosz Puszkarski and Marcin Iwanowski

Appl. Sci. 2025, 15(15), 8765; https://doi.org/10.3390/app15158765 - 7 Aug 2025

Viewed by 362

Abstract

Cardiovascular diseases (CVDs), which remain globally one of the most common causes of death, are usually diagnosed based on the electrocardiogram (ECG) signal. To support human experts, modern deep-learning models are used for CVD classification problems as an early warning. This article proposes [...] Read more.

Cardiovascular diseases (CVDs), which remain globally one of the most common causes of death, are usually diagnosed based on the electrocardiogram (ECG) signal. To support human experts, modern deep-learning models are used for CVD classification problems as an early warning. This article proposes a novel multi-branch architecture focused on processing various modalities of the ECG signal in parallel branches, replacing typical single-input architectures. Each branch is given separate input in the form of the raw signal, domain knowledge, the wavelet transform of the signal, or the signal with drift removed. The proposed method is based on deep-learning core models that can incorporate various modern neural networks. It was thoroughly tested on N-BEATS, LSTM, and GRU neural networks. The proposed architecture allows the retention of the speed of the neural network. At the same time, the combination of independently computed branches improves model performance, which finally exceeds the performance obtained by classical single-branch architectures. Full article

(This article belongs to the Special Issue Advances in Electrocardiogram (ECG) Signal Processing and Its Applications)

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13 pages, 645 KiB

Open AccessArticle

Pedagogical Qualities of Artificial Intelligence-Assisted Teaching: An Exploratory Analysis of a Personal Tutor in a Voluntary Business Higher-Education Course

by Nikša Alfirević, Marko Hell and Darko Rendulić

Appl. Sci. 2025, 15(15), 8764; https://doi.org/10.3390/app15158764 - 7 Aug 2025

Viewed by 350

Abstract

There is minimal research concerning the role of custom-trained artificial intelligence (AI) tools in higher education, with a lack of research concerning the pedagogical qualities of an AI-based personal tutor. To fill this literature gap, we examined how a custom GPT personal tutor [...] Read more.

There is minimal research concerning the role of custom-trained artificial intelligence (AI) tools in higher education, with a lack of research concerning the pedagogical qualities of an AI-based personal tutor. To fill this literature gap, we examined how a custom GPT personal tutor shapes key teaching and learning qualities. Using the mixed-methods approach, we aimed to demonstrate preliminary and exploratory empirical evidence concerning the contribution of custom-trained AI tutors to building up students’ competencies. Our research analyzed the subjective assessments of students related to the GPT tutor’s contribution to improving their competencies. Both the qualitative and quantitative empirical results confirmed the positive contribution. In addition, we triangulated the results to evaluate the potential of custom-trained AI chatbots in higher education, focusing on undergraduate business courses. However, the results of this study cannot be generalized to the entire student population of business schools, since the participation in the AI-assisted tutor program was voluntary, attracting only intrinsically motivated students. Full article

(This article belongs to the Special Issue Adaptive E-Learning Technologies and Experiences)

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18 pages, 2435 KiB

Open AccessArticle

Leveraging IGOOSE-XGBoost for the Early Detection of Subclinical Mastitis in Dairy Cows

by Rui Guo and Yongqiang Dai

Appl. Sci. 2025, 15(15), 8763; https://doi.org/10.3390/app15158763 - 7 Aug 2025

Viewed by 342

Abstract

Subclinical mastitis in dairy cows poses a significant challenge to the dairy industry, leading to reduced milk yield, altered milk composition, compromised animal health, and substantial economic losses for dairy farmers. A model based on the XGBoost algorithm, optimized with an Improved GOOSE [...] Read more.

Subclinical mastitis in dairy cows poses a significant challenge to the dairy industry, leading to reduced milk yield, altered milk composition, compromised animal health, and substantial economic losses for dairy farmers. A model based on the XGBoost algorithm, optimized with an Improved GOOSE Optimization Algorithm (IGOOSE), is presented in this work as an innovative approach for predicting subclinical mastitis in order to overcome these problems. The Dairy Herd Improvement (DHI) records of 4154 cows served as the model’s original foundation. A total of 3232 samples with 21 characteristics made up the final dataset, following extensive data cleaning and preprocessing. To overcome the shortcomings of the original GOOSE algorithm in intricate, high-dimensional problem spaces, three significant enhancements were made. First, an elite inverse strategy was implemented to improve population initialization, enhancing the algorithm’s balance between global exploration and local exploitation. Second, an adaptive nonlinear control factor was added to increase the algorithm’s stability and convergence speed. Lastly, a golden sine strategy was adopted to reduce the risk of premature convergence to suboptimal solutions. According to experimental results, the IGOOSE-XGBoost model works better than other models in predicting subclinical mastitis, especially when it comes to recognizing somatic cell scores, which are important markers of the illness. This study provides a strong predictive framework for managing the health of dairy cows, allowing for the prompt identification and treatment of subclinical mastitis, which enhances the efficiency and quality of milk supply. Full article

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21 pages, 12399 KiB

Open AccessArticle

Preventive Diagnosis of Biological Colonization and Salt-Related Decay on the Frescoes of the “Oratorio dell’Annunziata” (Riofreddo, Latium, Italy) to Improve Conservation Plans

by Flavia Bartoli, Annalaura Casanova Municchia, Marco Tescari, Ilaria Ciccone, Paolo Rosati, Alessandro Lazzara and Maria Catrambone

Appl. Sci. 2025, 15(15), 8762; https://doi.org/10.3390/app15158762 - 7 Aug 2025

Viewed by 297

Abstract

The frescoed Annunziata Oratory chapel in Riofreddo (Italy), a unique testimony to the pontificate of Martin V, sheds light on the trade routes of Ninfa in the first half of the 15th century. Despite having undergone several restorations in the past (the most [...] Read more.

The frescoed Annunziata Oratory chapel in Riofreddo (Italy), a unique testimony to the pontificate of Martin V, sheds light on the trade routes of Ninfa in the first half of the 15th century. Despite having undergone several restorations in the past (the most recent in the 2010s), the Oratory presents serious conservation issues. At first glance, there are no evident signs of biological colonization; rather, the most obvious damage is attributed to detachments and saline efflorescence. Biological colonization at several points was identified using various diagnostic field and laboratory techniques such as ATPase point analysis, field stereoscopy in visible and UV light, culture-based and molecular approaches, Raman spectroscopy, and SEM analysis, biological colonization at several points was identified. The characterization of salt efflorescence was carried out using ion chromatography analysis. The presence of bacteria, fungi and algae, which are also linked to saline efflorescence, was observed. A clear correlation between the biological colonization and salt efflorescence composition was highlighted by our results, as well as the potential sources of microorganisms and salts via the capillary rise of groundwater. This early diagnostic approach regarding the presence of lithobionts and salt efflorescence demonstrates the complex interplay between environmental factors and microbial colonization, which can lead to biodeterioration processes. Full article

(This article belongs to the Special Issue Application of Biology to Cultural Heritage III)

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Graphical abstract

21 pages, 1811 KiB

Open AccessArticle

Exploring Residual Clays for Low-Impact Ceramics: Insights from a Portuguese Ceramic Region

by Carla Candeias, Sónia Novo and Fernando Rocha

Appl. Sci. 2025, 15(15), 8761; https://doi.org/10.3390/app15158761 - 7 Aug 2025

Viewed by 254

Abstract

This study investigates the potential of residual clays from a traditional ceramic-producing region in southern Portugal as raw materials for red ceramic applications. This work aims to support more sustainable ceramic practices through the local valorization of naturally available, underutilized clay resources. A [...] Read more.

This study investigates the potential of residual clays from a traditional ceramic-producing region in southern Portugal as raw materials for red ceramic applications. This work aims to support more sustainable ceramic practices through the local valorization of naturally available, underutilized clay resources. A multidisciplinary approach was employed to characterize clays, integrating mineralogical (XRD), chemical (XRF), granulometric, and thermal analyses (TGA/DTA/TD), as well as technological tests on plasticity, extrusion moisture, shrinkage, and flexural strength. These assessments were designed to capture both the intrinsic properties of the clays and their behavior across key ceramic processing stages, such as shaping, drying, and firing. The results revealed a broad diversity in mineral composition, particularly in the proportions of kaolinite, smectite, and illite, which strongly influenced plasticity, water demand, and thermal stability. Clays with higher fine fractions and smectitic content exhibited excellent plasticity and workability, though with increased sensitivity to drying and firing conditions. Others, with coarser textures and illitic or feldspathic composition, demonstrated improved dimensional stability and lower shrinkage. Thermal analyses confirmed expected dehydroxylation and sintering behavior, with the formation of mullite and spinel-type phases contributing to densification and strength in fired bodies. This study highlights that residual clays from varied geological settings can offer distinct advantages when matched appropriately to ceramic product requirements. Some materials showed strong potential for direct application in structural ceramics, while others may serve as additives or tempering agents in formulations. These findings reinforce the value of integrated characterization for optimizing raw material use and support a more circular, resource-conscious approach to ceramic production. Full article

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21 pages, 1187 KiB

Open AccessArticle

Identification of Bottlenecks in Passenger Handling Processes Using Data-Driven Tools

by Edina Jenčová, Tatiana Gajdušková, Martin Jezný and Pavol Hudák

Appl. Sci. 2025, 15(15), 8760; https://doi.org/10.3390/app15158760 - 7 Aug 2025

Viewed by 237

Abstract

The paper focuses on the identification of “bottlenecks” in the passenger handling process at the airports. In the current era of digital transformation and the emergence of Industry 4.0 and 5.0 concepts, optimizing passenger flows through data-driven tools is becoming an essential part [...] Read more.

The paper focuses on the identification of “bottlenecks” in the passenger handling process at the airports. In the current era of digital transformation and the emergence of Industry 4.0 and 5.0 concepts, optimizing passenger flows through data-driven tools is becoming an essential part of intelligent airport management. While many solutions focus on high-end software or AI-based systems, this study demonstrates the value of preparatory models built in widely accessible platforms such as Microsoft Excel. A simulation model was developed to analyze check-in and security screening, integrating discrete event simulation (DES), queueing theory, and elements of Monte Carlo simulation. The model enables the segmentation of the handling process into key events, including probabilistically generated arrivals and service durations. Although the model is built in a basic environment, it serves as a prototype platform for potential integration into broader digitalization strategies, offering a preparatory framework for future implementation in more sophisticated systems. Full article

(This article belongs to the Special Issue The Wide Range Use of Innovative Technologies in Industry 4.0/5.0 and IoT)

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17 pages, 4935 KiB

Open AccessArticle

Steel Surface Defect Detection Algorithm Based on Improved YOLOv8 Modeling

by Miao Peng, Sue Bai and Yang Lu

Appl. Sci. 2025, 15(15), 8759; https://doi.org/10.3390/app15158759 - 7 Aug 2025

Viewed by 329

Abstract

Detecting steel defects is a vital process in industrial production, but traditional methods suffer from poor feature extraction and low detection accuracy. To address these issues, this research introduces an improved model, EB-YOLOv8, based on YOLOv8. First, the multi-scale attention mechanism EMA is [...] Read more.

Detecting steel defects is a vital process in industrial production, but traditional methods suffer from poor feature extraction and low detection accuracy. To address these issues, this research introduces an improved model, EB-YOLOv8, based on YOLOv8. First, the multi-scale attention mechanism EMA is integrated into the backbone and neck sections to reduce noise during gradient descent and enhance model stability by encoding global information and weighting model parameters. Second, the weighted fusion splicing module, Concat_BiFPN, is used in the neck network to facilitate multi-scale feature detection and fusion. This improves detection precision. The results show that the EB-YOLOv8 model increases detection accuracy on the NEU-DET dataset by 3.1%, reaching 80.2%, compared to YOLOv8. Additionally, the average precision on the Severstal steel defect dataset improves from 65.4% to 66.1%. Overall, the proposed model demonstrates superior recognition performance. Full article

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25 pages, 3159 KiB

Open AccessArticle

CLIP-BCA-Gated: A Dynamic Multimodal Framework for Real-Time Humanitarian Crisis Classification with Bi-Cross-Attention and Adaptive Gating

by Shanshan Li, Qingjie Liu, Zhian Pan and Xucheng Wu

Appl. Sci. 2025, 15(15), 8758; https://doi.org/10.3390/app15158758 - 7 Aug 2025

Viewed by 309

Abstract

During humanitarian crises, social media generates over 30 million multimodal tweets daily, but 20% textual noise, 40% cross-modal misalignment, and severe class imbalance (4.1% rare classes) hinder effective classification. This study presents CLIP-BCA-Gated, a dynamic multimodal framework that integrates bidirectional cross-attention (Bi-Cross-Attention) and [...] Read more.

During humanitarian crises, social media generates over 30 million multimodal tweets daily, but 20% textual noise, 40% cross-modal misalignment, and severe class imbalance (4.1% rare classes) hinder effective classification. This study presents CLIP-BCA-Gated, a dynamic multimodal framework that integrates bidirectional cross-attention (Bi-Cross-Attention) and adaptive gating within the CLIP architecture to address these challenges. The Bi-Cross-Attention module enables fine-grained cross-modal semantic alignment, while the adaptive gating mechanism dynamically weights modalities to suppress noise. Hierarchical learning rate scheduling and multidimensional data augmentation further optimize feature fusion for real-time multiclass classification. On the CrisisMMD benchmark, CLIP-BCA-Gated achieves 91.77% classification accuracy (1.55% higher than baseline CLIP and 2.33% over state-of-the-art ALIGN), with exceptional recall for critical categories: infrastructure damage (93.42%) and rescue efforts (92.15%). The model processes tweets at 0.083 s per instance, meeting real-time deployment requirements for emergency response systems. Ablation studies show Bi-Cross-Attention contributes 2.54% accuracy improvement, and adaptive gating contributes 1.12%. This work demonstrates that dynamic multimodal fusion enhances resilience to noisy social media data, directly supporting SDG 11 through scalable real-time disaster information triage. The framework’s noise-robust design and sub-second inference make it a practical solution for humanitarian organizations requiring rapid crisis categorization. Full article

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13 pages, 1663 KiB

Open AccessArticle

Effect of Sodium Sulfate Treatment on the Modulation of Aliphatic Glucosinolates in Eruca sativa Mill Organs at Flowering Stage

by Eleonora Pagnotta, Laura Righetti, Gabriele Micheletti, Carla Boga, Annamaria Massafra, Luisa Ugolini, Lorena Malaguti, Roberto Matteo, Federica Nicoletti, Roberto Colombo, Agostino Fricano and Laura Bassolino

Appl. Sci. 2025, 15(15), 8757; https://doi.org/10.3390/app15158757 - 7 Aug 2025

Viewed by 289

Abstract

Glucosinolates are secondary metabolites of the Brassicales, playing a role in plant protection and as health-promoting compounds. Here, Na₂SO₄ was used to modulate the aliphatic glucosinolate content in different organs of Eruca sativa Mill. In flowers, which accumulate the highest [...] Read more.

Glucosinolates are secondary metabolites of the Brassicales, playing a role in plant protection and as health-promoting compounds. Here, Na₂SO₄ was used to modulate the aliphatic glucosinolate content in different organs of Eruca sativa Mill. In flowers, which accumulate the highest amount of glucosinolates, Na₂SO₄ increased the concentration of glucoraphanin, in roots of glucoerucin and in apical leaves it doubled the amount of dimeric 4-mercaptobutyl glucosinolate. The biosynthetic gene Branched-Chain Aminotransferase 4 was also induced in roots at the highest salt concentration, while in leaves all tested genes biosynthetic genes were downregulated or unaffected. Cytochromes P450 83A1 monooxygenase was downregulated at the highest salt concentration in all organs. Overall, E. sativa is a reliable source of glucosinolates, which can be modulated with Na₂SO₄. Full article

(This article belongs to the Section Agricultural Science and Technology)

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12 pages, 7558 KiB

Open AccessArticle

High Resolution Imaging Using Micro-Objectives Fabricated by 2-Photon-Polymerization

by Fabian Thiemicke, Mostafa Agour, Ralf B. Bergmann and Claas Falldorf

Appl. Sci. 2025, 15(15), 8756; https://doi.org/10.3390/app15158756 - 7 Aug 2025

Viewed by 260

Abstract

We experimentally demonstrate high-resolution imaging using micro-objectives fabricated by two-photon polymerization (2PP) lithography, highlighting its potential as a flexible and precise fabrication method. The 2PP manufacturing process offers the ability to develop micro-optics with customized geometries and material properties, including tailored refractive indices. [...] Read more.

We experimentally demonstrate high-resolution imaging using micro-objectives fabricated by two-photon polymerization (2PP) lithography, highlighting its potential as a flexible and precise fabrication method. The 2PP manufacturing process offers the ability to develop micro-optics with customized geometries and material properties, including tailored refractive indices. This flexibility introduces new degrees of freedom in optical system design and expands the applicability of micro-optics to advanced imaging tasks where other materials and fabrication methods are insufficient. For our study, bi-convex micro-optics with different geometries with radii of curvature of <15

μ

m and minimized contact areas (<1

μ

m^{2}

) to ensure easy release from the substrate were fabricated with 2PP and investigated for their optical performance. With these micro-optics, the tracks with a pitch of 320 nm and the pits and lands as small as 130 nm were successfully resolved on a BluRay disc surface, demonstrating for the first time the high-resolution imaging capabilities of bi-convex spherical micro lenses. Full article

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23 pages, 4240 KiB

Open AccessArticle

Heliocentric Orbital Repositioning of a Sun-Facing Diffractive Sail with Controlled Binary Metamaterial Arrayed Grating

by Alessandro A. Quarta

Appl. Sci. 2025, 15(15), 8755; https://doi.org/10.3390/app15158755 - 7 Aug 2025

Viewed by 274

Abstract

This paper investigates the performance of a spacecraft equipped with a diffractive sail in a heliocentric mission scenario that requires phasing along a prescribed elliptical orbit. The diffractive sail represents an evolution of the more traditional reflective solar sail, which converts solar radiation [...] Read more.

This paper investigates the performance of a spacecraft equipped with a diffractive sail in a heliocentric mission scenario that requires phasing along a prescribed elliptical orbit. The diffractive sail represents an evolution of the more traditional reflective solar sail, which converts solar radiation pressure into thrust using a large reflective surface typically coated with a thin metallic film. In contrast, the diffractive sail proposed by Swartzlander leverages the properties of an advanced metamaterial-based film to generate a net transverse thrust even when the sail is Sun-facing, i.e., in a configuration that can be passively maintained by a suitably designed spacecraft. Specifically, this study considers a sail membrane covered with a set of electro-optically controlled diffractive panels. These panels employ a (controlled) binary metamaterial arrayed grating to steer the direction of photons exiting the diffractive film. This control technique has recently been applied to achieve a circle-to-circle interplanetary transfer using a Sun-facing diffractive sail. In this work, an optimal control law is employed to execute a rapid phasing maneuver along an elliptical heliocentric orbit with specified characteristics, such as those of Earth and Mercury. The analysis also includes a limiting case involving a circular heliocentric orbit. For this latter scenario, a simplified and elegant control law is proposed based on a linearized form of the equations of motion to describe the heliocentric dynamics of the diffractive sail-based spacecraft during the phasing maneuver. Full article

(This article belongs to the Special Issue 5th Anniversary of Aerospace Science and Engineering Section—Recent Advances in Aerospace)

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26 pages, 19284 KiB

Open AccessArticle

CFD Design Performance Analysis for a High-Speed Propeller

by Marian Ristea, Adrian Popa and Octavian-Narcis Volintiru

Appl. Sci. 2025, 15(15), 8754; https://doi.org/10.3390/app15158754 - 7 Aug 2025

Viewed by 249

Abstract

It is recognized that boats which intervene in dangerous situations are characterized by high maneuverability, have good governance properties, and must be equipped with high-speed propellers. This paper proposes a computerized analysis, using Computational Fluid Dynamics modeling, of a high-speed propeller, in open [...] Read more.

It is recognized that boats which intervene in dangerous situations are characterized by high maneuverability, have good governance properties, and must be equipped with high-speed propellers. This paper proposes a computerized analysis, using Computational Fluid Dynamics modeling, of a high-speed propeller, in open water, from the perspective of velocity and pressure manifested on the propeller blades. The use of numerical methods allows to determine the thrust forces on the propellers, to highlight the areas in the propeller blade where the maximum and minimum pressures occur, to identify the cavitation zone and to visualize the degree of turbulence of the fluid flow on the propeller blades in rotational motion. The analysis proves to be an efficient procedure in determining the characteristics of a high-speed propeller before deciding its production/manufacture. The Shear Stress Transport method was used for fluid turbulence analysis and the “Thrust–Propeller RPM” diagram and “Torque–propeller RPM” diagram finalized this study, the mentioned diagrams being the most important in choosing an efficient propeller for a given boat. Full article

(This article belongs to the Special Issue Recent Advances and Emerging Trends in Computational Fluid Dynamics)

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10 pages, 462 KiB

Open AccessArticle

Mutation Rates and Fitness Genes in Staphylococcus aureus Treated with the Medicinal Plant Synadenium glaucescens

by Zaituni Msengwa, Martin Saxtorph Bojer, Frank Rwegoshora, James Mwesongo, Magesa Mafuru, Faith Philemon Mabiki, Beda John Mwang’onde, Madundo Mkumbukwa Mtambo, Lughano Jeremy Kusiluka, Henrik Christensen, Robinson Hammerthon Mdegela and John Elmerdahl Olsen

Appl. Sci. 2025, 15(15), 8753; https://doi.org/10.3390/app15158753 - 7 Aug 2025

Viewed by 312

Abstract

Extracts, fractions and the pure compound epifriedelanol of the medicinal plant Synadenium glaucescens have antibacterial properties. Herbal products are generally considered less prone to resistance development than conventional antimicrobials, as they contain multiple compounds, which makes bacteria less likely to develop resistance. However, [...] Read more.

Extracts, fractions and the pure compound epifriedelanol of the medicinal plant Synadenium glaucescens have antibacterial properties. Herbal products are generally considered less prone to resistance development than conventional antimicrobials, as they contain multiple compounds, which makes bacteria less likely to develop resistance. However, data supporting this notion are lacking. This study evaluated the development of resistance in Staphylococcus aureus subjected to extract, fractions and epifriedelanol of S. glaucescens. It also identified S. aureus fitness genes contributing to intrinsic resistance to extract of S. glaucescens. Fluctuation and gradient concentration assays were used to determine mutation rates and growth adaptation, respectively, which were lower following exposure to growth in crude extract than the pure compound epifriedelanol. By subjecting 1920 single gene mutants from the Nebraska Transposon Mutant Library to growth in the presence of extract of S. glaucescens, 12 genes were identified as important for natural resistance in S. aureus JE2; however, only mutation in the hemB gene decreased the minimum inhibitory concentration by greater than 4-fold (64-fold). In conclusion, purifying active antimicrobial compounds from S. glaucescens and using them as antibacterial substances as an alternative to crude extract increased the risk of resistance development. Further, the gene hemB appears to have a significant role in the natural resistance to the extracts obtained from S. glaucescens in this study. Full article

(This article belongs to the Special Issue Advances in Natural Antimicrobial Compounds: Discovery, Synthesis, Characterization, and Application)

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41 pages, 1488 KiB

Open AccessReview

Advances in Computational Fluid Dynamics of Mechanical Processes in Food Engineering: Mixing, Extrusion, Drying, and Process Optimization

by Arkadiusz Szpicer, Weronika Bińkowska, Adrian Stelmasiak, Iwona Wojtasik-Kalinowska, Anna Czajkowska, Sylwia Mierzejewska, Zdzisław Domiszewski, Tomasz Rydzkowski, Joanna Piepiórka-Stepuk and Andrzej Półtorak

Appl. Sci. 2025, 15(15), 8752; https://doi.org/10.3390/app15158752 - 7 Aug 2025

Viewed by 475

Abstract

Mechanical processes such as mixing, extrusion, and drying are key operations in food engineering, with a significant impact on product quality and process efficiency. The increasing complexity of food materials—due to non-Newtonian properties, multiphase structures, and thermal–mechanical interactions—requires advanced modeling approaches for process [...] Read more.

Mechanical processes such as mixing, extrusion, and drying are key operations in food engineering, with a significant impact on product quality and process efficiency. The increasing complexity of food materials—due to non-Newtonian properties, multiphase structures, and thermal–mechanical interactions—requires advanced modeling approaches for process analysis and optimization. Computational Fluid Dynamics (CFD) has become a vital tool in this context. This review presents recent progress in the use of CFD for simulating key mechanical operations in food processing. Applications include the analysis of fluid flow, heat and mass transfer, and mechanical stresses, supporting improvements in mixing uniformity, energy efficiency during drying, and optimization of extrusion components (e.g., shaping dies). The potential for integrating CFD with complementary models for system-wide optimization is also discussed, including challenges related to scale-up and product consistency. Current limitations are outlined, and future research directions are proposed. Full article

(This article belongs to the Special Issue Fifth Anniversary of 'Food Science and Technology' Section—Recent Advances in Food)

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15 pages, 9399 KiB

Open AccessArticle

Analysis of 3D-Printed Zirconia Implant Overdenture Bars

by Les Kalman and João Paulo Mendes Tribst

Appl. Sci. 2025, 15(15), 8751; https://doi.org/10.3390/app15158751 - 7 Aug 2025

Viewed by 231

Abstract

Dental implant components are typically fabricated using subtractive manufacturing, often involving metal materials that can be costly, inefficient, and time-consuming. This study explores the use of additive manufacturing (AM) with zirconia for dental implant overdenture bars, focusing on mechanical performance, stress distribution, and [...] Read more.

Dental implant components are typically fabricated using subtractive manufacturing, often involving metal materials that can be costly, inefficient, and time-consuming. This study explores the use of additive manufacturing (AM) with zirconia for dental implant overdenture bars, focusing on mechanical performance, stress distribution, and fit. Solid and lattice-structured bars were designed in Fusion 360 and produced using LithaCon 210 3Y-TZP zirconia (Lithoz GmbH, Vienna, Austria) on a CeraFab 8500 printer. Post-processing included cleaning, debinding, and sintering. A 3D-printed denture was also fabricated to evaluate fit. Thermography and optical imaging were used to assess adaptation. Custom fixtures were developed for flexural testing, and fracture loads were recorded to calculate stress distribution using finite element analysis (ANSYS R2025). The FEA model assumed isotropic, homogeneous, linear-elastic material behavior. Bars were torqued to 15 Ncm on implant analogs. The average fracture loads were 1.2240 kN (solid, n = 12) and 1.1132 kN (lattice, n = 5), with corresponding stress values of 147 MPa and 143 MPa, respectively. No statistically significant difference was observed (p = 0.578; α = 0.05). The fracture occurred near high-stress regions at fixture support points. All bars demonstrated a clinically acceptable fit on the model; however, further validation and clinical evaluation are still needed. Additively manufactured zirconia bars, including lattice structures, show promise as alternatives to conventional superstructures, potentially offering reduced material use and faster production without compromising mechanical performance. Full article

(This article belongs to the Special Issue Recent Advances in Digital Dentistry and Oral Implantology)

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32 pages, 2266 KiB

Open AccessArticle

A Cellular Automata-Based Crossover Operator for Binary Chromosome Population Genetic Algorithms

by Doru Constantin and Costel Bălcău

Appl. Sci. 2025, 15(15), 8750; https://doi.org/10.3390/app15158750 - 7 Aug 2025

Viewed by 220

Abstract

In this paper, we propose a crossover operator for genetic algorithms with binary chromosomes populations based on the cellular automata (

CGACell

). After presenting the fundamental elements regarding cellular automata with specific examples for one- and two- dimensional cases, the the most [...] Read more.

In this paper, we propose a crossover operator for genetic algorithms with binary chromosomes populations based on the cellular automata (

CGACell

). After presenting the fundamental elements regarding cellular automata with specific examples for one- and two- dimensional cases, the the most widely used crossover operators in applications with genetic algorithms are described, and the crossover operator based on cellular automata is defined. Specific forms of the crossover operator based on the ECA and 2D CA cases are described and exemplified. The

CGACell

crossover operator is used in the genetic structure to improved the KNN algorithm in terms of the parameter represented by the number of nearest neighbors selected by the data classification method. Validity and practical performance testing are performed on image data classification problems by optimizing the nearest-neighbors-based algorithm. The experimental study on the proposed crossover operator, by comparing a GA algorithm based on

CGACell

with GA algorithms based on other crossover methods, including classical GAs and permutation-based, heuristic, and hybrid methods, attests to good qualitative performance in terms of correctness percentages in the recognition of new images, as well as in classification and recognition applications of facial image classes corresponding to several persons. Full article

(This article belongs to the Special Issue Applications of Genetic and Evolutionary Computation)

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16 pages, 1826 KiB

Open AccessArticle

Epigenetic Signatures of Dental Stem Cells: Insights into DNA Methylation and Noncoding RNAs

by Rosanna Guarnieri, Agnese Giovannetti, Giulia Marigliani, Michele Pieroni, Tommaso Mazza, Ersilia Barbato and Viviana Caputo

Appl. Sci. 2025, 15(15), 8749; https://doi.org/10.3390/app15158749 - 7 Aug 2025

Viewed by 312

Abstract

Tooth development (odontogenesis) is regulated by interactions between epithelial and mesenchymal tissues through signaling pathways such as Bone Morphogenetic Protein (BMP), Wingless-related integration site (Wnt), Sonic Hedgehog (SHH), and Fibroblast Growth Factor (FGF). Mesenchymal stem cells (MSCs) derived from dental tissues—including dental pulp [...] Read more.

Tooth development (odontogenesis) is regulated by interactions between epithelial and mesenchymal tissues through signaling pathways such as Bone Morphogenetic Protein (BMP), Wingless-related integration site (Wnt), Sonic Hedgehog (SHH), and Fibroblast Growth Factor (FGF). Mesenchymal stem cells (MSCs) derived from dental tissues—including dental pulp stem cells (DPSCs), periodontal ligament stem cells (PDLSCs), and dental follicle progenitor cells (DFPCs)—show promise for regenerative dentistry due to their multilineage differentiation potential. Epigenetic regulation, particularly DNA methylation, is hypothesized to underpin their distinct regenerative capacities. This study reanalyzed publicly available DNA methylation data generated with Illumina Infinium HumanMethylation450 BeadChip arrays (450K arrays) from DPSCs, PDLSCs, and DFPCs. High-confidence CpG sites were selected based on detection p-values, probe variance, and genomic annotation. Principal Component Analysis (PCA) and hierarchical clustering identified distinct methylation profiles. Functional enrichment analyses highlighted biological processes and pathways associated with specific methylation clusters. Noncoding RNA analysis was integrated to construct regulatory networks linking DNA methylation patterns with key developmental genes. Distinct epigenetic signatures were identified for DPSCs, PDLSCs, and DFPCs, characterized by differential methylation across specific genomic contexts. Functional enrichment revealed pathways involved in odontogenesis, osteogenesis, and neurodevelopment. Network analysis identified central regulatory nodes—including genes, such as PAX6, FOXC2, NR2F2, SALL1, BMP7, and JAG1—highlighting their roles in tooth development. Several noncoding RNAs were also identified, sharing promoter methylation patterns with developmental genes and being implicated in regulatory networks associated with stem cell differentiation and tissue-specific function. Altogether, DNA methylation profiling revealed that distinct epigenetic landscapes underlie the developmental identity and differentiation potential of dental-derived mesenchymal stem cells. This integrative analysis highlights the relevance of noncoding RNAs and regulatory networks, suggesting novel biomarkers and potential therapeutic targets in regenerative dentistry and orthodontics. Full article

(This article belongs to the Special Issue Advances in Orthodontic Diagnosis and Treatment: Methods and Applications)

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16 pages, 4106 KiB

Open AccessArticle

Optical Sensing Technologies for Cryo-Tank Composite Structural Element Analysis and Maintenance

by Monica Ciminello, Carmine Carandente Tartaglia and Pietro Caramuta

Appl. Sci. 2025, 15(15), 8748; https://doi.org/10.3390/app15158748 - 7 Aug 2025

Viewed by 240

Abstract

This article focuses on activities addressed in the European project hydrogen lightweight & innovative tank for zero-emission aircraft, H2ELIOS. The authors propose a preliminary approach oriented to the design of a structural health monitoring SHM system conceived for a cryo-tank liquid hydrogen storage [...] Read more.

This article focuses on activities addressed in the European project hydrogen lightweight & innovative tank for zero-emission aircraft, H2ELIOS. The authors propose a preliminary approach oriented to the design of a structural health monitoring SHM system conceived for a cryo-tank liquid hydrogen storage for medium range vehicles. The system was ideated to be installed on board and operating during service, to provide early detection and localization of potential damage, critical both in terms of safety and maintenance. The use of optical fibers for strain measurement is justified, on one hand, by the capability of pure silica fiber to prevent hydrogen darkening effects and, on the other hand, by the absence of metal components, which eliminates the risk of embrittlement. In detail, distributed and fiber Bragg grating FBG sensors designed for this specific application have demonstrated reliable monitoring capabilities, even after exposure to hydrogen and at cryogenic temperatures. Furthermore, another key contribution of this preliminary activity is the analysis of thermoplastic material faults by correlating damage characteristics with static and dynamic response. This is due to the fact that the investigated physics strongly depend on the nature of occurring damage. Achievements lie in the demonstrated ability to assess the health status of the reference composite structure, establishing the first steps for a future qualification of the proprietary system, made of commercial and original hardware and software. Full article

(This article belongs to the Special Issue Recent Advances in Optical Sensors)

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24 pages, 3567 KiB

Open AccessArticle

Investigation of the Load-Bearing Capacity of Resin-Printed Components Under Different Printing Strategies

by Brigitta Fruzsina Szívós, Vivien Nemes, Szabolcs Szalai and Szabolcs Fischer

Appl. Sci. 2025, 15(15), 8747; https://doi.org/10.3390/app15158747 - 7 Aug 2025

Viewed by 329

Abstract

This study examines the influence of different printing orientations and infill settings on the strength and flexibility of components produced using resin-based 3D printing, particularly with masked stereolithography (MSLA). Using a common photopolymer resin and a widely available desktop MSLA printer, we produced [...] Read more.

This study examines the influence of different printing orientations and infill settings on the strength and flexibility of components produced using resin-based 3D printing, particularly with masked stereolithography (MSLA). Using a common photopolymer resin and a widely available desktop MSLA printer, we produced and tested a series of samples with varying tilt angles and internal structures. To understand their mechanical behavior, we applied a custom bending test combined with high-precision deformation tracking through the GOM ARAMIS digital image correlation system. The results obtained clearly show that both the angle of printing and the density of the internal infill structure play a significant role in how much strain the printed parts can handle before breaking. Notably, a 75° orientation provided the best deformation performance, and infill rates between 60% and 90% offered a good balance between strength and material efficiency. These findings highlight how adjusting print settings can lead to stronger parts while also saving time and resources—an important consideration for practical applications in engineering, design, and manufacturing. Full article

(This article belongs to the Special Issue Sustainable Mobility and Transportation (SMTS 2025))

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21 pages, 2428 KiB

Open AccessArticle

Robust Human Pose Estimation Method for Body-to-Body Occlusion Using RGB-D Fusion Neural Network

by Jae-hyuk Yoon and Soon-kak Kwon

Appl. Sci. 2025, 15(15), 8746; https://doi.org/10.3390/app15158746 - 7 Aug 2025

Viewed by 340

Abstract

In this study, we propose a novel approach for human pose estimation (HPE) in occluded scenes by progressively fusing features extracted from RGB-D images, which contain RGB and depth images. Conventional bottom-up human pose estimation models that rely solely on RGB inputs often [...] Read more.

In this study, we propose a novel approach for human pose estimation (HPE) in occluded scenes by progressively fusing features extracted from RGB-D images, which contain RGB and depth images. Conventional bottom-up human pose estimation models that rely solely on RGB inputs often produce erroneous skeletons when parts of a person’s body are obscured by another individual, because they struggle to accurately infer body connectivity due to the lack of 3D topological information. To address this limitation, we modify the traditional OpenPose that is a bottom-up HPE model to take a depth image as an additional input, thereby providing explicit 3D spatial cues. Each input modality is processed by a dedicated feature extractor. Each input modality is processed by a dedicated feature extractor. In addition to the two existing modules for each stage—joint connectivity and joint confidence map estimations for the color image—we integrate a new module for estimating joint confidence maps for the depth image into the initial few stages. Subsequently, the confidence maps derived from both depth and RGB modalities are fused at each stage and forwarded to the next, ensuring that 3D topological information from the depth image is effectively utilized for both joint localization and body part association. Subsequently, the confidence maps derived from both depth and RGB modalities are fused at each stage and forwarded to the next to ensure that 3D topological information is effectively utilized for estimating both joint localization and their connectivity. The experimental results on the NTU 120+ RGB-D Dataset verify that our proposed approach achieves a 13.3% improvement in average recall compared to the original OpenPose model. The proposed method can enhance the performance of the bottom-up HPE models for the occlusion scenes. Full article

(This article belongs to the Special Issue Advanced Pattern Recognition & Computer Vision)

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18 pages, 40844 KiB

Open AccessArticle

The Stabilization Mechanism of a Stable Landslide Dam on the Eastern Margin of the Tibetan Plateau, China: Insights from Field Investigation and Numerical Simulation

by Liang Song, Yanjun Shang, Yunsheng Wang, Tong Li, Zhuolin Xiao, Yuchao Zhao, Tao Tang and Shicheng Liu

Appl. Sci. 2025, 15(15), 8745; https://doi.org/10.3390/app15158745 - 7 Aug 2025

Viewed by 191

Abstract

As a globally renowned alpine gorge region and seismically active zone, the eastern margin of the Qinghai–Tibet Plateau (QTP) is highly prone to landslide dam formation. Considering unstable landslide dams often pose catastrophic risks to downstream areas, current research on landslide dams along [...] Read more.

As a globally renowned alpine gorge region and seismically active zone, the eastern margin of the Qinghai–Tibet Plateau (QTP) is highly prone to landslide dam formation. Considering unstable landslide dams often pose catastrophic risks to downstream areas, current research on landslide dams along QTP primarily focuses on the breach mechanisms of unstable dams, while studies on the formation mechanisms of stable landslide dams—which can provide multiple benefits to downstream regions—remain limited. This paper selected the Conaxue Co landslide dam on the eastern margin of the QTP as one case example. Field investigation, sampling, numerical simulation, and comprehensive analysis were carried out to disclose its formation mechanisms. Field investigation shows that the Conaxue Co landslide dam was formed by a high-speed long-runout landslide blocking the river, with its structure exhibiting a typical inverse grading pattern characterized by coarse-grained rock overlying fine-grained layers. The inverse grading structure plays a critical role in the stability of the Conaxue Co landslide dam. On one hand, the coarse, hard rock boulders in the upper dam mitigate fluvial erosion of the lower fine-grained sediments. On the other hand, the fine-grained layer in the lower dam acts as a relatively impermeable aquitard, preventing seepage of dammed lake water. Additionally, the step-pool system formed in the spillway of the Conaxue Co landslide dam contributes to the protection of the dam structure by dissipating 68% of the river’s energy (energy dissipation rate η = 0.68). Understanding the formation mechanisms of the Conaxue Co landslide dam can provide critical insights into managing future landslide dams that may form in the QTP, both in emergency response and long-term strategies. Full article

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42 pages, 6539 KiB

Open AccessArticle

Multimodal Sparse Reconstruction and Deep Generative Networks: A Paradigm Shift in MR-PET Neuroimaging

by Krzysztof Malczewski

Appl. Sci. 2025, 15(15), 8744; https://doi.org/10.3390/app15158744 - 7 Aug 2025

Viewed by 579

Abstract

A novel multimodal super-resolution framework is introduced, combining GAN-based synthesis, perceptual constraints, and joint low-rank sparsity regularization to noticeably enhance MR-PET image quality. The architecture integrates modality-specific ResNet encoders, a transformer-based attention fusion block, and a multi-scale PatchGAN discriminator. Training is guided by [...] Read more.

A novel multimodal super-resolution framework is introduced, combining GAN-based synthesis, perceptual constraints, and joint low-rank sparsity regularization to noticeably enhance MR-PET image quality. The architecture integrates modality-specific ResNet encoders, a transformer-based attention fusion block, and a multi-scale PatchGAN discriminator. Training is guided by a hybrid loss function incorporating adversarial, pixel-wise, perceptual (VGG19), and structured Hankel constraints. The proposed method outperforms all baselines in PSNR, SSIM, LPIPS, and diagnostic confidence metrics. Clinical PET metrics, such as SUV recovery and lesion detectability, show substantial improvement. A thorough analysis of computational complexity, dataset composition, training reproducibility, and motion compensation is provided. These findings are visually supported by processed scan panels and benchmark tables. This framework advances reproducible and interpretable hybrid neuroimaging with strong clinical and technical validation. Full article

(This article belongs to the Special Issue Advances in Machine Learning and Data Mining: Emerging Trends and Applications)

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19 pages, 3382 KiB

Open AccessArticle

LiDAR as a Geometric Prior: Enhancing Camera Pose Tracking Through High-Fidelity View Synthesis

by Rafael Muñoz-Salinas, Jianheng Liu, Francisco J. Romero-Ramirez, Manuel J. Marín-Jiménez and Fu Zhang

Appl. Sci. 2025, 15(15), 8743; https://doi.org/10.3390/app15158743 - 7 Aug 2025

Viewed by 284

Abstract

This paper presents a robust framework for monocular camera pose estimation by leveraging high-fidelity, pre-built 3D LiDAR maps. The core of our approach is a render-and-match pipeline that synthesizes photorealistic views from a dense LiDAR point cloud. By detecting and matching keypoints between [...] Read more.

This paper presents a robust framework for monocular camera pose estimation by leveraging high-fidelity, pre-built 3D LiDAR maps. The core of our approach is a render-and-match pipeline that synthesizes photorealistic views from a dense LiDAR point cloud. By detecting and matching keypoints between these synthetic images and the live camera feed, we establish reliable 3D–2D correspondences for accurate pose estimation. We evaluate two distinct strategies: an Online Rendering and Tracking method that renders views on the fly, and an Offline Keypoint-Map Tracking method that precomputes a keypoint map for known trajectories, optimizing for computational efficiency. Comprehensive experiments demonstrate that our framework significantly outperforms several state-of-the-art visual SLAM systems in both accuracy and tracking consistency. By anchoring localization to the stable geometric information from the LiDAR map, our method overcomes the reliance on photometric consistency that often causes failures in purely image-based systems, proving particularly effective in challenging real-world environments. Full article

(This article belongs to the Special Issue Image Processing and Computer Vision Applications)

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20 pages, 4671 KiB

Open AccessArticle

Creep Characteristics and Fractional-Order Constitutive Modeling of Gangue–Rock Composites: Experimental Validation and Parameter Identification

by Peng Huang, Yimei Wei, Guohui Ren, Erkan Topal, Shuxuan Ma, Bo Wu and Qihe Lan

Appl. Sci. 2025, 15(15), 8742; https://doi.org/10.3390/app15158742 - 7 Aug 2025

Viewed by 181

Abstract

With the increasing depth of coal resource extraction, the creep characteristics of gangue backfill in deep backfill mining are crucial for the long-term deformation of rock strata. Existing research predominantly focuses on the instantaneous deformation response of either the backfill alone or the [...] Read more.

With the increasing depth of coal resource extraction, the creep characteristics of gangue backfill in deep backfill mining are crucial for the long-term deformation of rock strata. Existing research predominantly focuses on the instantaneous deformation response of either the backfill alone or the strata movement, lacking systematic studies that reflect the long-term time-dependent deformation characteristics of the strata-backfill system. This study addresses gangue–roof composite specimens with varying gangue particle sizes. Utilizing physical similarity ratio theory, graded loading confined compression creep experiments were designed and conducted to investigate the effects of gangue particle size and moisture content on the creep behavior of the gangue–roof composites. A fractional-order creep constitutive model for the gangue–roof composite was established, and its parameters were identified. The results indicate the following: (1) The creep of the gangue–roof composite exhibits two-stage characteristics (initial and steady-state). Instantaneous strain decreases with increasing particle size but increases with higher moisture content. Specimens reached their maximum instantaneous strain under the fourth-level loading, with values of 0.358 at a gangue particle size of 10 mm and 0.492 at a moisture content of 4.51%. (2) The fractional-order creep model demonstrated a goodness-of-fit exceeding 0.98. The elastic modulus and fractional-order coefficient showed nonlinear growth with increasing particle size, revealing the mechanism of viscoplastic attenuation in the gangue–roof composite. The findings provide theoretical support for predicting the time-dependent deformation of roofs in deep backfill mining. Full article

(This article belongs to the Section Civil Engineering)

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22 pages, 2152 KiB

Open AccessArticle

Tele-Assessment of Executive Functions in Young Adults with ADHD: A Pilot Study

by Agnese Capodieci, Valeria Olla, Chiara Tonasso, Marianna Campana, Annalisa Morsiani, Agnese Zambelli and Giulia Guidetti

Appl. Sci. 2025, 15(15), 8741; https://doi.org/10.3390/app15158741 - 7 Aug 2025

Viewed by 483

Abstract

ADHD is a childhood neurodevelopmental disorder, but it can persist into adolescence and adulthood and become detrimental to the individual’s well-being. It is known that many individuals with ADHD manifest executive functioning problems that affect their adaptive functioning. In the evaluation phase, it [...] Read more.

ADHD is a childhood neurodevelopmental disorder, but it can persist into adolescence and adulthood and become detrimental to the individual’s well-being. It is known that many individuals with ADHD manifest executive functioning problems that affect their adaptive functioning. In the evaluation phase, it is, therefore, useful to consider these aspects as well. The diagnosis of ADHD is purely clinical in adults: it is based on anamnesis and the completion of questionnaires on the history of symptoms and current symptomatology. In recent years, the tele-assessment has become a valuable and accessible tool for diagnostic framing and intervention planning; however, there are currently few tele-assessment tools that enable the in-depth analysis of young adults. In this study, a group of 34 young adults with ADHD was compared with 35 typically developing peers using a tele-assessment tool for executive functioning (TeleFE, Anastasis). This research can be considered a pilot study to evaluate the differences in these tasks between the two populations and open the possibility of standardizing the tool for young adults. The use of this tool to assess executive functioning in individuals with ADHD in this age group would enable clinicians to plan more individualized interventions. Full article

(This article belongs to the Special Issue Assistive Technology for Rehabilitation)

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36 pages, 2683 KiB

Open AccessSystematic Review

Physics-Informed Surrogate Modelling in Fire Safety Engineering: A Systematic Review

by Ramin Yarmohammadian, Florian Put and Ruben Van Coile

Appl. Sci. 2025, 15(15), 8740; https://doi.org/10.3390/app15158740 - 7 Aug 2025

Viewed by 377

Abstract

Surrogate modelling is increasingly used in engineering to improve computational efficiency in complex simulations. However, traditional data-driven surrogate models often face limitations in generalizability, physical consistency, and extrapolation—issues that are especially critical in safety-sensitive fields such as fire safety engineering (FSE). To address [...] Read more.

Surrogate modelling is increasingly used in engineering to improve computational efficiency in complex simulations. However, traditional data-driven surrogate models often face limitations in generalizability, physical consistency, and extrapolation—issues that are especially critical in safety-sensitive fields such as fire safety engineering (FSE). To address these concerns, physics-informed surrogate modelling (PISM) integrates physical laws into machine learning models, enhancing their accuracy, robustness, and interpretability. This systematic review synthesises existing applications of PISM in FSE, classifies the strategies used to embed physical knowledge, and outlines key research challenges. A comprehensive search was conducted across Google Scholar, ResearchGate, ScienceDirect, and arXiv up to May 2025, supported by backward and forward snowballing. Studies were screened against predefined criteria, and relevant data were analysed through narrative synthesis. A total of 100 studies were included, covering five core FSE domains: fire dynamics, wildfire behaviour, structural fire engineering, material response, and heat transfer. Four main strategies for embedding physics into machine learning were identified: feature engineering techniques (FETs), loss-constrained techniques (LCTs), architecture-constrained techniques (ACTs), and offline-constrained techniques (OCTs). While LCT and ACT offer strict enforcement of physical laws, hybrid approaches combining multiple strategies often produce better results. A stepwise framework is proposed to guide the development of PISM in FSE, aiming to balance computational efficiency with physical realism. Common challenges include handling nonlinear behaviour, improving data efficiency, quantifying uncertainty, and supporting multi-physics integration. Still, PISM shows strong potential to improve the reliability and transparency of machine learning in fire safety applications. Full article

(This article belongs to the Special Issue Intelligent Systems and Tools for Optimal Design in Mechanical Engineering and Their Practical Applications)

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16 pages, 1707 KiB

Open AccessArticle

An Overview of Analog and Digital RF Generator Techniques, Suitable for Space-Based AOTF Applications

by Jurgen Vanhamel

Appl. Sci. 2025, 15(15), 8739; https://doi.org/10.3390/app15158739 - 7 Aug 2025

Viewed by 272

Abstract

The use of Acousto-Optical Tunable Filters (AOTFs) is well known in ground- and space-based applications. These devices are used in several optical instruments and payloads for monitoring and other purposes. To make use of the filter capability of the AOTF, a dedicated Radio [...] Read more.

The use of Acousto-Optical Tunable Filters (AOTFs) is well known in ground- and space-based applications. These devices are used in several optical instruments and payloads for monitoring and other purposes. To make use of the filter capability of the AOTF, a dedicated Radio Frequency (RF) chain, consisting of an RF generator and RF amplifier, is needed. An RF generator can be designed in several ways. However, the design of these steering devices for space applications comes with several difficulties and limitations. The mechanical stress due to shock and vibration, the temperature variation, as well as the vacuum environment and radiation levels in which these devices have to perform limits the selection of possible techniques. This paper aims at giving an in-depth overview of space-qualified RF generator techniques using Commercial-Off-The-Shelf available components that usable in the harsh environment of space and applicable in driving AOTFs. Several analog as well as digital generator principles are discussed, substantiated by test results. Full article

(This article belongs to the Special Issue Recent Advances in Space Instruments and Sensing Technology)

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26 pages, 7949 KiB

Open AccessArticle

Sigmoidal Mathematical Models in the Planning and Control of Rigid Pavement Works

by Jose Manuel Palomino Ojeda, Lenin Quiñones Huatangari, Billy Alexis Cayatopa Calderon, Manuel Emilio Milla Pino, José Luis Piedra Tineo, Marco Antonio Martínez Serrano and Rosario Yaqueliny Llauce Santamaria

Appl. Sci. 2025, 15(15), 8738; https://doi.org/10.3390/app15158738 - 7 Aug 2025

Viewed by 197

Abstract

The objective of the research was to use sigmoidal mathematical models for the planning and control of rigid pavement works. A dataset was constructed using 140 technical files, which were then analyzed to extract the valued work schedules. These schedules contained the variables [...] Read more.

The objective of the research was to use sigmoidal mathematical models for the planning and control of rigid pavement works. A dataset was constructed using 140 technical files, which were then analyzed to extract the valued work schedules. These schedules contained the variables time and cost per month. Subsequently, two groups were created from the dataset: a training group comprising 80% of the data and a test group comprising the remaining 20%. Subsequently, the variables were normalized and adjusted with the proposed logistic, Von Bertalanffy, and Gompertz models using Python 3.11.13. Following the implementation of training and validation procedures, the logistic model was identified as the optimal fit, as indicated by the following metrics: R² = 0.9848, MSE = 0.0026, RMSE = 0.0506, and MAE = 0.0278. The implementation of the aforementioned model facilitates the establishment of an early warning system with a high degree of effectiveness. This system enables the evaluation of the discrepancy between the actual progress and the planned progress with an R² greater than 98%, thereby serving as a robust instrument for the adjustment and revalidation of activities before and following their execution. Full article

(This article belongs to the Section Civil Engineering)

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20 pages, 7704 KiB

Open AccessArticle

Laser Scanning and Photogrammetry for Graphic Analysis and Heritage Documentation: The Lopera Tower, a 14th-Century Castilian Fortress

by Juan Francisco Molina Rozalem, Jesús Rodríguez Medina and Ignacio Acosta

Appl. Sci. 2025, 15(15), 8737; https://doi.org/10.3390/app15158737 - 7 Aug 2025

Viewed by 366

Abstract

Spain is among the European countries with the greatest number of preserved castles and defensive structures—some estimates place the total at around 10,000, the majority of which date back to the medieval period. Yet, surprisingly, many of these fortifications remain uncatalogued and in [...] Read more.

Spain is among the European countries with the greatest number of preserved castles and defensive structures—some estimates place the total at around 10,000, the majority of which date back to the medieval period. Yet, surprisingly, many of these fortifications remain uncatalogued and in an advanced state of ruin. This study focuses on a small fortress that has been overlooked by historiography and neglected by public authorities, yet which still stands after seven centuries: the Tower of Lopera, a castle belonging to the so-called Banda Morisca (the frontier of Al-Andalus in the 14th century). Using a combination of digital documentation techniques—namely, portable laser scanning, photogrammetry (via drone and camera), and digital image processing software—we have been able to digitize, geometrize, and document both the surviving architectural remains and their immediate physical environment. Rather than pursuing the latest technological innovations, this methodology prioritizes practical and realistic solutions based on the resources typically available to cultural heritage administrations. Our work serves two main objectives: to demonstrate the viability of applying such tools to this typology of architectural heritage and to conduct a detailed graphic and geometric analysis of the structure. Given the abundance of similar abandoned fortresses in Spain, the findings presented here could inform future heritage documentation strategies on a broader, potentially national, scale. Full article

(This article belongs to the Special Issue Intelligent Techniques and 3D Virtual Reconstruction for Architectural Heritage)

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