Applied Sciences

21 pages, 3936 KiB

Open AccessArticle

Current Practices of Railway Ballastless Track Design Methods in China

by Peng Chen, Chen Hua, Haiyan Han, Hanbing Xiao, Xinghan Liu and Yanglong Zhong

Appl. Sci. 2025, 15(10), 5621; https://doi.org/10.3390/app15105621 (registering DOI) - 17 May 2025

With the development of railway transportation, diversified demands for track structures require the design methods to be safer, more flexible and efficient. At present, the limit state method is regarded as a more scientific design method compared to the allowable stress method, but [...] Read more.

With the development of railway transportation, diversified demands for track structures require the design methods to be safer, more flexible and efficient. At present, the limit state method is regarded as a more scientific design method compared to the allowable stress method, but its optimization effects await further research. Taking a new type of prefabricated track slab as an example, the differences between the two methods are deeply analyzed using finite element simulation and formula calculation. The development prospect for the track design methods is proposed, providing reference for new structures. The results show the following: (1) There are significant differences in the calculation principles between the two methods. Unlike the single safety factor K of the allowable stress method, the partial factors of the limit state method make it more reasonable. (2) The working conditions of different train speeds and temperature gradients are the main factors influencing the design results, and the latter plays a main control role. (3) Under current specification, the reinforcement and slab thickness can be reduced by approximately 6.5% and 3.4%, respectively, according to the limit state method, but the values its coefficient still need to be studied further to achieve efficiency. Full article

(This article belongs to the Section Civil Engineering)

17 pages, 2088 KiB

Open AccessArticle

Organochlorine Contaminants in Maize Fertilized with Meat and Bone Meal Derived from Animal By-Products

by Arkadiusz Stępień, Katarzyna Wojtkowiak, Ewelina Kolankowska and Renata Pietrzak-Fiećko

Appl. Sci. 2025, 15(10), 5620; https://doi.org/10.3390/app15105620 (registering DOI) - 17 May 2025

Abstract

Despite the fact that organochlorine pesticides (OCPs) were banned many years ago, their residues are still present in the natural environment and pose a potential health risk to humans and animals. This study was undertaken to evaluate the effect of meat and bone [...] Read more.

Despite the fact that organochlorine pesticides (OCPs) were banned many years ago, their residues are still present in the natural environment and pose a potential health risk to humans and animals. This study was undertaken to evaluate the effect of meat and bone meal (1.0, 2.0 and 3.0 t ha⁻¹ MBM) derived from animal by-products and used as fertilizer on the content of γ-HCH (γ-hexachlorocyclohexane), DDT (1,1,1-Trichloro-bis-2,2 [4-chlorophenyl]-ethane) and its metabolites (DDD, dichlorodiphenyldichloroethane and DDE, dichlorodiphenyldichloroethylene) in MBM, soil, and maize grain. A long-term small-area field experiment with MBM applied to maize grown in monoculture was conducted at the Agricultural Experiment Station in Tomaszkowo, Poland (53°71′ N, 20°43′ E) from 2014 to 2017. The concentration of γ-HCH in soil decreased gradually, whereas the levels of DDT and its metabolites continued to increase in successive years of the experiment. A minor increase in DDT accumulation in maize grain was also observed, particularly in treatments supplied with mineral fertilizers. Meat and bone meal affected grain contamination levels, and the highest MBM rates decreased the content of DDT metabolites in grain. The results of the study suggest that MBM could be a secondary source of OCPs in the agricultural environment and that their availability to plants varies depending on soil parameters and weather conditions. Full article

(This article belongs to the Special Issue Biological Control and Pesticides in Agriculture: Current Status and Applications)

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12 pages, 5198 KiB

Open AccessArticle

TMD Damping for Structures with Uncertain Modal Parameters

by Felix Weber

Appl. Sci. 2025, 15(10), 5619; https://doi.org/10.3390/app15105619 (registering DOI) - 17 May 2025

Abstract

The optimum tuning of the natural frequency and damping ratio of TMDs for structural modal parameters and various optimization criteria are well-known from the literature. However, when the eigenfrequency and modal mass of the target structural mode are uncertain due to estimation and [...] Read more.

The optimum tuning of the natural frequency and damping ratio of TMDs for structural modal parameters and various optimization criteria are well-known from the literature. However, when the eigenfrequency and modal mass of the target structural mode are uncertain due to estimation and measurement errors, significant life loads, temperature, and other time-varying effects, the existing TMD tuning rules are not necessarily optimal. An often-adopted method is to select the TMD damping ratio that is greater than optimal value to make the TMD less sensitive to variations of the target eigenfrequency and uncertainty in the modal mass. This heuristic approach is quantitatively investigated by the presented research. Computations are made for different TMD mass ratios, different uncertainties in target eigenfrequency and modal mass, different levels of increased TMD damping, and assuming harmonic excitation. The results demonstrate that there is no simple rule when increased TMD damping is advantageous. Therefore, beneficial TMD increase factors are given as functions of TMD mass ratio and deviations between actual and nominal modal structural properties. These data can be used by engineers for real TMD projects with uncertain modal parameters. Full article

(This article belongs to the Special Issue Acoustics and Vibrations Analyses of Materials at Different Scales: Experimental and Numerical Approaches: Volume III)

19 pages, 8867 KiB

Open AccessArticle

Proof-of-Concept of a Monopulse Antenna Architecture Enabling Radar Sensors in Unmanned Aircraft Collision Avoidance Systems for UAS in U-Space Airspaces

by Javier Ruiz Alapont, Miguel Ferrando-Bataller and Juan V. Balbastre

Appl. Sci. 2025, 15(10), 5618; https://doi.org/10.3390/app15105618 (registering DOI) - 17 May 2025

Abstract

In this paper, we propose and prove an innovative radar antenna concept suitable for collision avoidance (CA) systems installed onboard small, unmanned aircraft (UA). The proposed architecture provides 360° monopulse coverage around the host platform, enabling the detection and accurate position estimation of [...] Read more.

In this paper, we propose and prove an innovative radar antenna concept suitable for collision avoidance (CA) systems installed onboard small, unmanned aircraft (UA). The proposed architecture provides 360° monopulse coverage around the host platform, enabling the detection and accurate position estimation of airborne, non-cooperative intruders using lightweight, low-profile antennas. These antennas can be manufactured using low-cost 3D printing techniques and are easily integrated into the UA airframe without compromising airworthiness. We present a Detect and Avoid (DAA) concept of operations (ConOps) aligned with the SESAR U-space ConOps, Edition 4. In this ConOps, the Remain Well Clear (RWC) and CA functions are treated separately: RWC is the responsibility of ground-based U-space services, while CA is implemented as an airborne safety net using onboard equipment. Based on this framework, we derive operation-centric design requirements and propose an antenna architecture based on a fixed circular array of sector waveguides. This solution overcomes key limitations of existing radar antennas for UAS CA systems by providing a wider field of view, higher power handling, and reduced mechanical complexity and cost. We prove the proposed concept through a combination of simulations and measurements conducted in an anechoic chamber using a 24 GHz prototype. Full article

(This article belongs to the Special Issue Recent Advances and Applications of Autonomous Aerial Vehicles)

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18 pages, 498 KiB

Open AccessArticle

The Impact of Microwaves and Ultrasound on the Hydrolysis of Banana Peels and the Growth of Fodder Yeasts

by Andrea Maria Patelski, Urszula Dziekońska-Kubczak, Maria Balcerek, Katarzyna Pielech-Przybylska, Jarosław Domański, Joanna Berłowska and Piotr Dziugan

Appl. Sci. 2025, 15(10), 5617; https://doi.org/10.3390/app15105617 (registering DOI) - 17 May 2025

Abstract

This study evaluates the feasibility of using banana peels as a substrate for cultivating fodder yeast biomass. Banana peels (BPs), representing approximately 38% of the total fruit weight, are rich in cellulose and hemicellulose, thus presenting a significant opportunity for valorisation. The study [...] Read more.

This study evaluates the feasibility of using banana peels as a substrate for cultivating fodder yeast biomass. Banana peels (BPs), representing approximately 38% of the total fruit weight, are rich in cellulose and hemicellulose, thus presenting a significant opportunity for valorisation. The study investigates the effects of microwave and ultrasound treatments on the hydrolysis efficiency of banana peels and the subsequent cultivation of yeast. Two yeast strains, Scheffersomyces stipitis and Meyerozyma guilliermondii, were cultivated in hydrolysates prepared using various methods, including acid–thermal, enzymatic, microwave, and ultrasound treatments. The results demonstrate that enzymatic hydrolysis following microwave or ultrasound pretreatment significantly enhances sugar release, supporting higher biomass yields. The maximum biomass concentration achieved was 7.68 g DM/L, with crude protein content reaching up to 45.46% DM. These results indicate that banana peels can be effectively utilised for single-cell protein production, providing a sustainable alternative for animal feed. The study underscores the potential of integrating microwave and ultrasound technologies in bioprocessing to enhance the efficiency and environmental sustainability of yeast cultivation. Full article

(This article belongs to the Special Issue Recent Trends in the Valorization of Natural Products and Food Wastes)

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17 pages, 3877 KiB

Open AccessArticle

ProLinker–Generator: Design of a PROTAC Linker Base on a Generation Model Using Transfer and Reinforcement Learning

by Yanlin Luo, Danyang Song, Chengwei Zhang and An Su

Appl. Sci. 2025, 15(10), 5616; https://doi.org/10.3390/app15105616 (registering DOI) - 17 May 2025

Abstract

In PROTAC molecules, the design of the linker directly affects the formation efficiency and stability of the target protein–PROTAC–E3 ligase ternary complex, making it a critical factor in determining degradation activity. However, current linker data are limited, and the accessible chemical space remains [...] Read more.

In PROTAC molecules, the design of the linker directly affects the formation efficiency and stability of the target protein–PROTAC–E3 ligase ternary complex, making it a critical factor in determining degradation activity. However, current linker data are limited, and the accessible chemical space remains narrow. The length, conformation, and chemical composition of linkers play a decisive role in drug performance, highlighting the urgent need for innovative linker design. In this study, we propose ProLinker-Generator, a GPT-based model aimed at generating novel and effective linkers. By integrating transfer learning and reinforcement learning, the model expands the chemical space of linkers and optimizes their design. During the transfer learning phase, the model achieved high scores in validity (0.989) and novelty (0.968) for the generated molecules. In the reinforcement learning phase, it further guided the generation of molecules with ideal properties within our predefined range. ProLinker-Generator demonstrates the significant potential of AI in linker design. Full article

(This article belongs to the Special Issue Development and Application of Computational Chemistry Methods)

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14 pages, 3971 KiB

Open AccessArticle

Design, Characteristic Analysis and Modeling of a Tailored Soft Robot for Phosphorite Grabbing

by Yang Zhang, Junjie Lu, Zixin Huang and Bing Feng

Appl. Sci. 2025, 15(10), 5615; https://doi.org/10.3390/app15105615 (registering DOI) - 17 May 2025

Abstract

The grabbing of phosphorite rocks is an important process in the mining industry. Traditional grabbing technology based on rigid robots faces challenges such as heavy weight, low flexibility, and insufficient safety. This study presents the structural design, characteristic analysis, and modeling of a [...] Read more.

The grabbing of phosphorite rocks is an important process in the mining industry. Traditional grabbing technology based on rigid robots faces challenges such as heavy weight, low flexibility, and insufficient safety. This study presents the structural design, characteristic analysis, and modeling of a novel tailored soft robot for phosphorite grabbing (TSRPG). The TSRPG is designed with soft, flexible materials, providing flexible movement and high safety in complex environments. The design inspiration of the robot comes from humans using their thumb and index finger to hold things, and the structural design mainly focuses on the flexibility and grabbing function of the robot. The grabbing function of the TSRPG is exhibited by several actual grabbing experiments. In addition, through characteristic analysis, we explore the robot’s motion properties under various input air pressure conditions. A mathematical model of the TSRPG is developed to depict its characteristics based on the nonlinear ARX model. The developed mathematical model provides a base for promoting the practical application of the TSRPG. Full article

21 pages, 2325 KiB

Open AccessArticle

Hardware-in-Loop Modules for Testing Automated Ventilator Controllers

by David Berard, Benjamin Alexander, David Owen, Isiah Mejia, Jose M. Gonzalez, Sofia I. Hernandez Torres and Eric J. Snider

Appl. Sci. 2025, 15(10), 5614; https://doi.org/10.3390/app15105614 (registering DOI) - 17 May 2025

Abstract

Automated ventilator controllers have the potential to simplify oxygen and carbon dioxide management for trauma. In the pre-hospital or military medicine environment, trauma care can be required for prolonged periods by personnel with limited ventilator management training. As such, there is a need [...] Read more.

Automated ventilator controllers have the potential to simplify oxygen and carbon dioxide management for trauma. In the pre-hospital or military medicine environment, trauma care can be required for prolonged periods by personnel with limited ventilator management training. As such, there is a need for closed-loop control systems that can adapt ventilator management to a complex, ever-changing medical environment. Here, we present a novel hardware-in-loop test platform for the independent troubleshooting and evaluation of oxygen and carbon dioxide automated ventilator management capabilities. The oxygen management system provides an analogue blood oxygen signal that is responsive to the fraction of inspired oxygen and the peak inspiratory pressure ventilator settings. A tested oxygenation controller successfully reached the target oxygen saturation within 5 min. The carbon dioxide removal system integrates with commercial ventilator technology and mimics carbon dioxide generation, lung compliance, and airway resistance while providing an end-tidal carbon dioxide level that is responsive to changes in the tidal volume and respiratory rate settings. A test mechanical ventilator controller was able to regulate EtCO₂ regardless of the starting value within 10 min. This highlights the system’s functionality and provides proof-of-concept demonstrations for how the hardware-in-loop test platforms can be used for evaluating closed-loop controller technologies. Full article

(This article belongs to the Special Issue Application of Decision Support Systems in Biomedical Engineering)

36 pages, 7096 KiB

Open AccessArticle

Stock Market Bubble Warning: A Restricted Boltzmann Machine Approach Using Volatility–Return Sequences

by Mauricio A. Valle, Jaime Lavín and Felipe Urbina

Appl. Sci. 2025, 15(10), 5613; https://doi.org/10.3390/app15105613 (registering DOI) - 17 May 2025

Abstract

Combining unsupervised learning with Restricted Boltzmann Machines and supervised learning with Balanced Random Forest and Feedforward Neural Networks, we propose a warning system for the early detection of stock bubbles by analyzing daily returns and the volatility of a market index. We complement [...] Read more.

Combining unsupervised learning with Restricted Boltzmann Machines and supervised learning with Balanced Random Forest and Feedforward Neural Networks, we propose a warning system for the early detection of stock bubbles by analyzing daily returns and the volatility of a market index. We complement our method by detecting states of high volatility and very low returns, which are market states that immediately follow a stock market’s bubble-bursting point. We trained our detection model using the S&P500 as an empirical case study, using successive samples of well-known crises from 1987 to 2022. Our results achieve area-under-the-curve (AUC) rates of over 70% and false-positive rates of less than 20%. Our model’s generative nature enables the creation of synthetic samples to analyze market periods prone to forming a bubble. The model successfully alerts periods of bubbles and instability in the stock market. Capital markets’ interconnectedness enables the model to be trained with various shocks from other stock markets, providing further detection learning possibilities and improved detection rates. Our work helps investors, regulators, and practitioners in their stock market investment, supervision, and monitoring tasks. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

34 pages, 9619 KiB

Open AccessArticle

Heat Transfer Intensification in a Heat Exchanger Tube with Continuous V-Rib Twisted Tapes Installed

by Yuexiang Du, Khwanchit Wongcharee, Varesa Chuwattanakul, Paisarn Naphon, Naoki Maruyama, Masafumi Hirota and Smith Eiamsa-ard

Appl. Sci. 2025, 15(10), 5612; https://doi.org/10.3390/app15105612 (registering DOI) - 17 May 2025

Abstract

This article reports the effect of twisted tapes with continuous V-ribs on the thermal performance index characteristics of a heat exchanger tube. Numerical and experimental studies were conducted to investigate the influence of V-rib attack angles (β = 15°, 30°, and 45°) [...] Read more.

This article reports the effect of twisted tapes with continuous V-ribs on the thermal performance index characteristics of a heat exchanger tube. Numerical and experimental studies were conducted to investigate the influence of V-rib attack angles (β = 15°, 30°, and 45°) in forward and backward arrangements. This investigation employed 0.9 mm thick, continuous V-rib twisted tapes (CVRTs) made from aluminum sheets formed with a twist ratio of y/w = 4.0. The experimental results indicated that a continuous V-rib twisted tape (CVRT) was more effective in heat transfer improvement than a typical twisted tape (TT). This was due to swirl and longitudinal vortex flows that helped increase flow mixing and reduce boundary layer thickness. Decreased V-rib attack angles (β) led to greater heat transfer enhancement, pressure drop, and thermal performance index values due to the greater turbulent mixing of fluid. The numerical result revealed that a continuous V-rib twisted tape created strong longitudinal vortex flow, especially with higher attack angles. The Turbulent Kinetic Energy (TKE) and core fluid temperature increased with the insertion of CVRTs. Local Nusselt numbers also remained relatively high for heat exchanger tubes with CVRTs. The experimental study illustrated that a tube with a CVRT installed augmented heat transfer. In the experimentally studied cases, a backward arrangement had more heat transfer, a greater friction factor, and a better thermal performance index. Compared to a plain tube, a tube with CVRT installed, having β = 15°, 30°, and 45°, showed 76.8, 71.6, and 66.2% improved heat transfer, respectively. CVRTs with these three β-values, respectively, exhibited higher thermal performance than a TT. Among the investigated CVRTs, the backward-arranged tape with β = 15° offered the maximum thermal performance index, 1.13 at Re = 6000. The results are congruent with the simulation outcomes, hence supporting the CFD analysis. Full article

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

38 pages, 1572 KiB

Open AccessReview

Overview of Dual Two-Level Inverter Configurations for Open-End Winding Machines: Enhancing Power Quality and Efficiency

by Mohammed Zerdani, Sid Ahmed El Mehdi Ardjoun and Houcine Chafouk

Appl. Sci. 2025, 15(10), 5611; https://doi.org/10.3390/app15105611 (registering DOI) - 17 May 2025

Abstract

Today, power electronic-based converters are at the core of many modern systems, such as smart grids and electric vehicles. In this context, the Dual Two-Level Inverter (DTLI) supplying an open-end winding machine offers an innovative and promising solution for marine propulsion, aeronautics, and [...] Read more.

Today, power electronic-based converters are at the core of many modern systems, such as smart grids and electric vehicles. In this context, the Dual Two-Level Inverter (DTLI) supplying an open-end winding machine offers an innovative and promising solution for marine propulsion, aeronautics, and electric vehicles. This configuration provides several advantages, including a reduced DC bus voltage, enhanced fault tolerance, and improved overall system performance. However, ensuring optimal energy efficiency and high-power quality remains a major challenge given the increasing demands for performance and sustainability. This paper presents a state-of-the-art review of the main DTLI configurations and their impact on system performance. Three architectures are analyzed, highlighting their benefits and limitations. This study aims to demonstrate the influence of the DC bus voltage ratio and pulse width modulation strategies on power quality and energy efficiency. The objective is to enhance the understanding of the DTLI’s potential and to guide its integration into other electrical systems. Full article

(This article belongs to the Special Issue Challenges for Power Electronics Converters, 2nd Edition)

11 pages, 1662 KiB

Open AccessArticle

Engagement-Oriented Dynamic Difficulty Adjustment

by Qingwei Mi and Tianhan Gao

Appl. Sci. 2025, 15(10), 5610; https://doi.org/10.3390/app15105610 (registering DOI) - 17 May 2025

Abstract

As an emerging and lively research field, game designers are employing Dynamic Difficulty Adjustment (DDA) in Game Artificial Intelligence (Game AI) to improve player experience. Traditional DDA methods focus little on player churn, which cannot always lead to enhanced player engagement. Hence, we [...] Read more.

As an emerging and lively research field, game designers are employing Dynamic Difficulty Adjustment (DDA) in Game Artificial Intelligence (Game AI) to improve player experience. Traditional DDA methods focus little on player churn, which cannot always lead to enhanced player engagement. Hence, we propose the Engagement-oriented Dynamic Difficulty Adjustment (EDDA) to meet the urgent need for a highly general and customizable solution in the game industry. EDDA directly considers players’ churn trend to ensure player engagement during gameplay. Its real-time monitoring algorithm and common parameter set are effective in quantifying and preventing player churn. We developed a prototype system integrating seven major game genres to verify the difficulty, gameplay time, and scores of the Game Engagement Questionnaire (GEQ) in multiple dimensions. EDDA has the largest mean and median of all genres in the above metrics with the highest confidence level and effect size, which demonstrates its generality and availability in improving player experience. It is fair to say that EDDA not only provides game designers with targeted player churn monitoring and intervention means, but also offers a deeper level of thinking for the generalized application of DDA and other Game AI technologies. Full article

(This article belongs to the Special Issue Applications of Artificial Intelligence and Machine Learning in Games: 2nd Edition)

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26 pages, 7906 KiB

Open AccessArticle

Comparative Evaluation of Feed-Forward Neural Networks for Predicting Uniaxial Compressive Strength of Seybaplaya Carbonate Rock Cores

by Jose W. Naal-Pech, Leonardo Palemón-Arcos and Youness El Hamzaoui

Appl. Sci. 2025, 15(10), 5609; https://doi.org/10.3390/app15105609 (registering DOI) - 17 May 2025

Abstract

Accurate estimation of the uniaxial compressive strength (UCS) of carbonate rocks underpins safe design and stability assessment in karst-influenced geotechnical projects. This work presents a comprehensive evaluation of four feed-forward artificial neural network (ANN) architectures—radial basis function (RBF), Bayesian regularized (BR), scaled conjugate [...] Read more.

Accurate estimation of the uniaxial compressive strength (UCS) of carbonate rocks underpins safe design and stability assessment in karst-influenced geotechnical projects. This work presents a comprehensive evaluation of four feed-forward artificial neural network (ANN) architectures—radial basis function (RBF), Bayesian regularized (BR), scaled conjugate gradient (SCG), and Levenberg–Marquardt (LM)—to predict UCS from three readily measured variables: water content, interconnected porosity, and real density. Fifty core specimens from the Seybaplaya quarry in Campeche, Mexico, were split into training and testing subsets under uniform preprocessing. Each model’s predictive performance was assessed over 30 independent runs using mean absolute error, root mean squared error, and coefficient of determination, with statistical differences tested via nonparametric hypothesis testing. The RBF network achieved the highest median R² and significantly outperformed the other variants, while the BR model demonstrated robust generalization. SCG and LM converged faster and efficiently but with slightly lower accuracy. Sensitivity analysis identified interconnected porosity as the primary predictor of UCS. These results establish RBF-based ANNs with appropriate regularization and feature importance assessment as a novel, practical, and reliable framework for UCS prediction in heterogeneous carbonate formations. Full article

(This article belongs to the Special Issue Research and Applications of Artificial Neural Network)

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17 pages, 5821 KiB

Open AccessArticle

NuCap: A Numerically Aware Captioning Framework for Improved Numerical Reasoning

by Yuna Jeong and Yong-Suk Choi

Appl. Sci. 2025, 15(10), 5608; https://doi.org/10.3390/app15105608 (registering DOI) - 17 May 2025

Abstract

Despite advances in image captioning, existing models struggle to generate captions that include accurate numerical information, especially the number of objects. One reason for this issue is that the dataset used for training has a limited number of samples with numerical information about [...] Read more.

Despite advances in image captioning, existing models struggle to generate captions that include accurate numerical information, especially the number of objects. One reason for this issue is that the dataset used for training has a limited number of samples with numerical information about the image. To address this issue, we propose a new framework, the Numerically Aware Captioning (NuCap) model, to enhance numerical reasoning in caption generation. We extract dual features by combining a region-attended object encoder for finer-grained object features and a spatially attended grid encoder for encoding spatially distributed global features. We also propose a number-focused cross-entropy loss component to increase sensitivity to numerical tokens, and introduce CountCOCO, a dataset for structured understanding of numerical information. Experiments show that our method achieves statistically significant counting performance improvements over state-of-the-art image captioning models while maintaining similar captioning performance. Despite the significant improvement in numerical reasoning power, our proposed approach has significantly fewer parameters and lower inference latency than large-scale vision language models, demonstrating both computational efficiency and stability. NuCap is an image captioning model that can represent specific numerical information in a given image, making it more suitable for applications that require precise object enumeration, such as automated surveillance, store monitoring, and scientific documentation. Full article

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18 pages, 2232 KiB

Open AccessArticle

Optimal Selection of Gravity Field Model Order for Spaceborne GNSS Receivers: A Study on System Resources and Real-Time Orbit Determination Accuracy

by Chongao Zhou, Jing Hu, Xiangyu Li, Meng Wang and Xianyang Liu

Appl. Sci. 2025, 15(10), 5607; https://doi.org/10.3390/app15105607 (registering DOI) - 17 May 2025

Abstract

In this study, different data types are employed according to the objectives of each experiment. Simulated orbit data are used for analyzing the effects of atmospheric drag modeling in order to ensure controlled and consistent comparisons. In contrast, real on-orbit data from the [...] Read more.

In this study, different data types are employed according to the objectives of each experiment. Simulated orbit data are used for analyzing the effects of atmospheric drag modeling in order to ensure controlled and consistent comparisons. In contrast, real on-orbit data from the Gaofen-7 satellite are used for evaluating gravity field models with the aim of validating the accuracy and adaptability of the proposed method in real orbital environments. By examining the effects of various gravity field orders on orbit determination accuracy, computation time, and other factors using spaceborne GNSS navigation receivers, the study concludes that setting the gravity field model order to 60 is the best option for LEO satellites at 500 km altitude. With this setup, the orbit determination accuracies in the radial, tangential, and normal directions are 0.420 m, 0.191 m, and 0.225 m, respectively, for a three-dimensional position accuracy of 0.522 m. The computation time is 286 ms. Full article

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18 pages, 2225 KiB

Open AccessReview

Defects in Silicon Carbide as Quantum Qubits: Recent Advances in Defect Engineering

by Ivana Capan

Appl. Sci. 2025, 15(10), 5606; https://doi.org/10.3390/app15105606 (registering DOI) - 16 May 2025

Abstract

This review provides an overview of defects in silicon carbide (SiC) with potential applications as quantum qubits. It begins with a brief introduction to quantum qubits and existing qubit platforms, outlining the essential criteria a defect must meet to function as a viable [...] Read more.

This review provides an overview of defects in silicon carbide (SiC) with potential applications as quantum qubits. It begins with a brief introduction to quantum qubits and existing qubit platforms, outlining the essential criteria a defect must meet to function as a viable qubit. The focus then shifts to the most promising defects in SiC, notably the silicon vacancy (V_Si) and divacancy (V_C-V_Si). A key challenge in utilizing these defects for quantum applications is their precise and controllable creation. Various fabrication techniques, including irradiation, ion implantation, femtosecond laser processing, and focused ion beam methods, have been explored to create these defects. Designed as a beginner-friendly resource, this review aims to support early-career experimental researchers entering the field of SiC-related quantum qubits. Providing an introduction to defect-based qubits in SiC offers valuable insights into fabrication strategies, recent progress, and the challenges that lie ahead. Full article

(This article belongs to the Special Issue Quantum Communication and Applications)

16 pages, 1279 KiB

Open AccessArticle

Microstructure of Mortar with Ballast Waste as a Cement Replacement

by Santiago Yagüe-García and Rosario García-Giménez

Appl. Sci. 2025, 15(10), 5605; https://doi.org/10.3390/app15105605 (registering DOI) - 16 May 2025

Abstract

The use of ballast in tracks generates waste that, in most cases, is destined for landfill. The proposal to use this waste as a replacement in OPC in different proportions valorizes the waste and allows its participation in the Circular Economy. To this [...] Read more.

The use of ballast in tracks generates waste that, in most cases, is destined for landfill. The proposal to use this waste as a replacement in OPC in different proportions valorizes the waste and allows its participation in the Circular Economy. To this end, two samples of ballast waste with substitution ratios (10, 15, and 20%) were studied for one year using pozzolanic activity, XRD, SEM/EDX, and CT scanning analysis. The shortest setting times corresponded to the ballast waste substitutions with the highest percentage, which is related to particle size and the presence of amorphous material, thereby reducing the setting time. The workability of mortars with a substitution indicates that the average consistency decreases as the substitution percentage increases, while the loss of fluidity grows with a higher substitution percentage. Porosity is linked to the formation of C-S-H gels and the presence of ettringite, which fills the pores between particles. Tortuosity can be considered low, which hinders the transport of aqueous solutions, making the substituted cements studied more resistant to hydration processes. Full article

(This article belongs to the Section Materials Science and Engineering)

15 pages, 3448 KiB

Open AccessArticle

Predictive Current Control of a Five-Phase Drive Using a Lead-Pursuit Strategy and Virtual Voltage Vectors

by Federico Barrero, Mario Bermúdez, Manuel R. Arahal and Ignacio González-Prieto

Appl. Sci. 2025, 15(10), 5604; https://doi.org/10.3390/app15105604 (registering DOI) - 16 May 2025

Abstract

Modern electric machines are attracting the greatest interest from the research community due to their current increasing number of applications, including electric vehicles and wind power generators. Their use requires the development of complex regulators, where predictive controllers appear as interesting and viable [...] Read more.

Modern electric machines are attracting the greatest interest from the research community due to their current increasing number of applications, including electric vehicles and wind power generators. Their use requires the development of complex regulators, where predictive controllers appear as interesting and viable alternatives in recent research works. Although these controllers have an easy formulation and high flexibility to incorporate different control objectives in multidimensional systems, they have limitations that require attention and limit their application: a high computational cost and current harmonic content. This work presents a novel controller that focuses on these limitations, where the additional degree of freedom introduced in the predictive controller through the lead-pursuit guidance law concept is combined with the use of virtual voltage vectors to reduce the harmonic content in a controlled drive. The effectiveness of the proposed controller is explored using a five-phase drive and several figures of merit, such as the root mean square error in current tracking, the total harmonic distortion in the stator currents, and the number of switching commutations per cycle. Different predictive controllers are compared with the proposal in terms of speed regulation, stator current control, and steady-state performance, where the results obtained are analyzed to show the interest, improvements, and limitations of the proposal. Full article

(This article belongs to the Special Issue Electric Power Applications II)

21 pages, 18601 KiB

Open AccessArticle

Predicting Clay Swelling Pressure: A Comparative Analysis of Advanced Symbolic Regression Techniques

by Esteban Díaz and Roberto Tomás

Appl. Sci. 2025, 15(10), 5603; https://doi.org/10.3390/app15105603 (registering DOI) - 16 May 2025

Abstract

Swelling pressure is a key geotechnical property that influences the behaviour and stability of engineering structures built on expansive clayey soils. This pressure can be measured directly through laboratory tests or estimated using indirect methods. This paper analyses a dataset of undisturbed clay [...] Read more.

Swelling pressure is a key geotechnical property that influences the behaviour and stability of engineering structures built on expansive clayey soils. This pressure can be measured directly through laboratory tests or estimated using indirect methods. This paper analyses a dataset of undisturbed clay samples from southeastern Spain using advanced symbolic regression techniques, namely: deep symbolic regression (PhySO), high-performance symbolic regression (PySR), multi-objective symbolic regression (MOSR), and physics-guided symbolic regression (PGSR). These methods provide interpretable results as equations, unlike standard machine learning models. All generated equations showed high performance (R² > 0.91 and MAE < 23 kPa) and simplicity, making them suitable for practical engineering applications. PySR yielded the best overall metrics (R² = 0.933, MAE = 20.49 kPa), particularly excelling in high-pressure ranges, while PhySO demonstrated the most balanced performance, especially for low to medium pressures. MOSR minimized edge-case bias, and PGSR, despite lower overall performance, remained competitive. The plasticity index (PI) was identified as the most influential factor in all models, followed by the percentage of fines. The use of undisturbed samples enhanced the reliability of the findings, and the resulting equations enable a flexible estimation of swelling pressure based on commonly available geotechnical parameters. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Geotechnical Engineering)

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19 pages, 1252 KiB

Open AccessArticle

Doctrina: Blockchain 5.0 for Artificial Intelligence

by Khikmatullo Tulkinbekov and Deok-Hwan Kim

Appl. Sci. 2025, 15(10), 5602; https://doi.org/10.3390/app15105602 (registering DOI) - 16 May 2025

Abstract

The convergence of blockchain technology with artificial intelligence presents a promising paradigm shift in data management and trust within AI ecosystems. Starting from the initial cryptocurrency-oriented versions, the blockchain potential is improved up to the highly scalable and programmable versions available currently. Even [...] Read more.

The convergence of blockchain technology with artificial intelligence presents a promising paradigm shift in data management and trust within AI ecosystems. Starting from the initial cryptocurrency-oriented versions, the blockchain potential is improved up to the highly scalable and programmable versions available currently. Even though the integration of real-world applications offers a promising future for distributed computing, there are limitations on executing AI models on blockchain due to high external library dependencies, storage, and cost constraints. Addressing this issue, this study explores the transformative potential of integrating blockchain with AI within the paradigm of blockchain 5.0. We propose the next-generation novel blockchain architecture named Doctrina that allows executing AI models directly on blockchain. Compared to the existing approaches, Doctrina allows sharing and using AI services in a fully distributed and privacy-preserved manner. Full article

(This article belongs to the Special Issue Recent Advances in Parallel Computing and Big Data)

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14 pages, 8971 KiB

Open AccessArticle

Polysaccharide Hydrogels Based on Cellulose and Chitosan for Drug Sustained-Release Applications

by Xueyan Jin, Hong Xu, Zhiping Mao, Xueling Feng and Yi Zhong

Appl. Sci. 2025, 15(10), 5601; https://doi.org/10.3390/app15105601 (registering DOI) - 16 May 2025

Abstract

This study developed a novel water-soluble Cellulose Acetoacetate (CAA)-chitosan (CS) composite hydrogel drug delivery system. In this system, CAA and CS molecules are cross-linked via dynamic enamine bonds, forming a three-dimensional network structure suitable for drug encapsulation and controlled release. The primary objective [...] Read more.

This study developed a novel water-soluble Cellulose Acetoacetate (CAA)-chitosan (CS) composite hydrogel drug delivery system. In this system, CAA and CS molecules are cross-linked via dynamic enamine bonds, forming a three-dimensional network structure suitable for drug encapsulation and controlled release. The primary objective was to address the challenges associated with the short half-life and significant fluctuations in therapeutic concentration of cytokine drugs, such as interleukin-2 (IL-2). A hydrogel system with a three-dimensional spatial network structure was successfully constructed via dynamic enamine bonds cross-linking between the acetoacetate groups in CAA molecules and the amino groups in CS. This system exhibits the following characteristics: (1) Dynamic covalent bonds impart adjustable mechanical properties to the hydrogel, enabling precise control over gelation time and mechanical performance; (2) A hierarchical pore structure (average pore size of 100–200 μm) provides a three-dimensional confined space for efficient drug encapsulation, achieving an IL-2 encapsulation efficiency of 83.3 ± 3.1%; (3) In vitro release studies demonstrated that the cumulative release of IL-2 within 72 h ranged from 18.4% to 34.7%, indicating sustained-release behavior. Cell viability assays confirmed that the hydrogel maintained the survival rate of L929 cells above 85% (as determined by the CCK-8 method), and live/dead staining revealed no apparent cytotoxicity. Overall, this three-dimensional network hydrogel based on dynamic covalent bonds represents a promising strategy for low-dose, long-lasting cytokine delivery. Full article

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14 pages, 1560 KiB

Open AccessStudy Protocol

Analysis and Verification Results of Manual Inspection of Pavement Condition Index

by Szu-Han Lu, Jyh-Dong Lin and Yi-Shian Chiou

Appl. Sci. 2025, 15(10), 5600; https://doi.org/10.3390/app15105600 (registering DOI) - 16 May 2025

Abstract

The aim of this study is to establish an analysis of certification indicators for the Pavement Condition Index (PCI) to address previously unaccredited issues. In the management of road infrastructure, the PCI serves as a crucial indicator for assessing road pavement conditions. However, [...] Read more.

The aim of this study is to establish an analysis of certification indicators for the Pavement Condition Index (PCI) to address previously unaccredited issues. In the management of road infrastructure, the PCI serves as a crucial indicator for assessing road pavement conditions. However, the lack of standardized detection and accreditation mechanisms in the past may have led to variations in the reliability of detection results among different personnel. This study observes the accuracy and precision of the data obtained by different inspectors. The analysis is based on repeated manual inspections conducted by four inspectors across 12 road units on Zhongda Road, using the ASTM D6433-23 (2023) standard. To ensure the reliability of the inspection results, the Coefficient of Variation (CV) is used to measure repeatability, while the Mean Relative Error (MRE) is used to evaluate accuracy. Training was introduced between inspection phases to assess performance improvement. The results showed that the average CV decreased from 27.2% to 7.5% and the average MRE reduced from 45.3% to 5.9% after training. These findings demonstrate that targeted training significantly enhances the repeatability and accuracy of manual PCI assessments. This study concludes with recommendations to set a CV threshold of ≤0.1 and an MRE threshold of ≤10% as practical benchmarks for manual PCI Quality Control. These standards can serve as validation criteria for future automated inspection systems. Full article

14 pages, 400 KiB

Open AccessArticle

Characterization of Dietary Constituents, Phytochemicals, and Antioxidant Capacity of Carpobrotus edulis Fruit: Potential Application in Nutrition

by Carlota R. Marques, Carla Sousa, Carla Moutinho, Carla Matos and Ana Ferreira Vinha

Appl. Sci. 2025, 15(10), 5599; https://doi.org/10.3390/app15105599 - 16 May 2025

Abstract

Carpobrotus edulis (chorão-da-praia) is an edible and medicinal plant native to South Africa, currently distributed worldwide. Due to the urge for novel foods, invasive species can be considered valuable food supplies to accomplish the current goals of the 2030 Agenda. In this study, [...] Read more.

Carpobrotus edulis (chorão-da-praia) is an edible and medicinal plant native to South Africa, currently distributed worldwide. Due to the urge for novel foods, invasive species can be considered valuable food supplies to accomplish the current goals of the 2030 Agenda. In this study, C. edulis fruits harvested in northern Portugal’s Atlantic coast were evaluated for proximate analysis (AOAC methods), mineral contents (ICP-MS), and fatty acid composition (GC-FID). Total phenolics, flavonoids, and antioxidant activity (DPPH and FRAP assays) were carried out by colorimetric methods. The fruits exhibited high amounts of carbohydrates (60.5%), ash (10.9%), and total crude protein (22.8%). A low content of total fat (4.5%) was observed. Linoleic acid (C18:2n6c) was the predominant unsaturated fatty acid (52.08%) among the 11 identified fatty acids. The highest amounts of total phenolics (311.7 mg GAE/g) and flavonoid (50.43 mg CE/g) contents were observed in hydroalcoholic fruit extracts. The high concentration of bioactive compounds in the C. edulis fig is directly reflected in its antioxidant properties, enhancing the usefulness of this invasive species in food and pharmaceutical industries. Full article

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

24 pages, 1731 KiB

Open AccessArticle

A Magnetotelluric Signal Acquisition and Monitoring System Based on a Cloud Platform

by Qi Luo, Weibin Sun, Rujun Chen, Xiaoli Mi and Hongchun Yao

Appl. Sci. 2025, 15(10), 5598; https://doi.org/10.3390/app15105598 - 16 May 2025

Abstract

This study designed and implemented an magnetotelluric signal acquisition and monitoring system (CMT) based on an Internet of Things (IoT) cloud platform. By integrating magnetotelluric monitoring stations, control terminals, and cloud servers, a real-time and efficient monitoring network was constructed. The hardware part [...] Read more.

This study designed and implemented an magnetotelluric signal acquisition and monitoring system (CMT) based on an Internet of Things (IoT) cloud platform. By integrating magnetotelluric monitoring stations, control terminals, and cloud servers, a real-time and efficient monitoring network was constructed. The hardware part of the system adopts a multi-module collaborative design, including signal conditioning circuits, FPGA control modules, DSP processing units, and embedded subsystems, achieving high-precision acquisition and processing of magnetotelluric signals. The software part employs a layered architecture, developing acquisition software, terminal control software, and a cloud platform monitoring system, which support multi-protocol communication, data parsing, and remote interaction. Through server stress testing, consistency testing, and cloud platform functional verification, the results showed that the system performs well under pressure even with limited server hardware bandwidth, with controllable consistency errors compared to the commercial device MTU-5A, and has stable field acquisition performance. The study validated the system’s advantages in real-time performance, reliability, and scalability, providing a feasible technical solution for the field of magnetotelluric monitoring. In the future, the system will be applied to geothermal monitoring. Full article

30 pages, 6438 KiB

Open AccessArticle

Landslide Susceptibility Analysis Based on Dataset Construction of Landslides in Yiyang Using GIS and Machine Learning

by Chengxun Hou, Huanhua Liu, Xuan Wang, Jinqi Hu, Youde Tang and Xunwen Yao

Appl. Sci. 2025, 15(10), 5597; https://doi.org/10.3390/app15105597 (registering DOI) - 16 May 2025

Abstract

This study aims to explore the methodology for assessing landslide susceptibility by using machine learning techniques based on a geographic information system (GIS) in an effort to develop landslide susceptibility maps and assess landslide risk in the Yiyang region. A landslide dataset in [...] Read more.

This study aims to explore the methodology for assessing landslide susceptibility by using machine learning techniques based on a geographic information system (GIS) in an effort to develop landslide susceptibility maps and assess landslide risk in the Yiyang region. A landslide dataset in Yiyang was constructed after 16 landslide predisposing factors were identified across four categories, topography, geology, environment, and hydrometeorology, through factor state determination and multicollinearity analysis. A Blending ensemble model was created and achieved higher prediction accuracy by fusing predictions from Random Forest, CatBoost, and XGBoost with logistic regression used as the meta-learner, thus deriving the importance coefficients of the landslide predisposing factors and their contribution rates. The Blending ensemble model achieved high predictive accuracy with an AUC value of 0.8784, demonstrating balanced and stable performance characteristics. With the addition of the rainfall factor, the AUC value of the Blending ensemble model has increased by 0.1199. In combination with the information value method, this model was applied to assess landslide susceptibility and rainfall-induced landslide risks in Yiyang City, demonstrating its validity. In addition, experimental validation confirmed the prediction and evaluation accuracy of the GIS-based Blending ensemble model. Results showed that the frequency ratio (FR) of historical landslide occurrences in high-susceptibility and extremely high-susceptibility zones in Yiyang City exceeded 1, indicating strong consistency between the landslide risk classification and actual distribution of historical landslides. The landslide susceptibility maps created for Anhua County, Heshan District, and Taojiang County in Yiyang City may provide support for the early warning and prevention of landslides and land-use planning in this region. The proposed methodology may be of reference value for improving natural disaster prevention and risk management. Full article

22 pages, 1641 KiB

Open AccessArticle

The Effect of Germination Duration on the Biochemical Indicators and Functional-Technological Properties of Triticale Grain

by Gulnazym Ospankulova, Indira Temirova, Dana Toimbayeva, Saule Saduakhasova, Sayagul Tazhina, Dina Khamitova, Marat Muratkhan, Akmaral Aldiyeva and Aibek Zhumalin

Appl. Sci. 2025, 15(10), 5596; https://doi.org/10.3390/app15105596 - 16 May 2025

Abstract

Germination is a biotechnological process that activates enzymatic reactions and alters the chemical content of grain, improving its nutritional and functional value. However, the duration of the germination process significantly affects grain composition and properties. Prolonged and uncontrolled germination can lead to undesirable [...] Read more.

Germination is a biotechnological process that activates enzymatic reactions and alters the chemical content of grain, improving its nutritional and functional value. However, the duration of the germination process significantly affects grain composition and properties. Prolonged and uncontrolled germination can lead to undesirable changes, such as excessive enzymatic activity, microbial contamination of sprouted grains, and loss of dry matter. While short-term germination is preferable for producing various food products, including whole-grain porridge, this article analyzed the impact of short-term germination of triticale grain (for 18, 20, 22, and 24 h) on its biochemical indicators and functional-technological properties. This research established that changes in biochemical values accompany the germination of triticale grain. The most significant increase in protein content was observed after 20 h of germination (GT 20), which increased by 4.43%. In contrast, after 24 h (GT 24), a decrease of 3.27% was noted compared to the original content in the whole grain (WGT). The contents of fats, carbohydrates, and ash tended to decrease. Germination promoted an increase in the amount of essential amino acids and improved the amino acid profile, particularly during the 20 and 22 h germination intervals. At 24 h of germination, the highest increase in total phenolic compounds (28.6%) and antioxidant activity (20.8%) was recorded. B-group vitamins, thiamine, and riboflavin, were detected in the sprouts only after 22 and 24 h of germination. The highest thiamine content (0.17 mg/kg) was observed at the 22nd hour, and the highest riboflavin content (2.51 mg/kg) was observed at the 24th hour. Niacin content showed a steady increase throughout the germination period. The maximum magnesium (0.200%) and molybdenum (0.589%) contents were recorded after 24 h of germination, while the calcium content increased at all germination intervals. The functional and technological properties of sprouted triticale grain improved, while the pasting (gelatinization) properties tended to decrease. Thus, it has been established that short-term germination enhances the biochemical indicators and functional-technological properties of triticale grains, indicating their potential for use in the production of whole-grain porridge. Full article

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13 pages, 4984 KiB

Open AccessArticle

Evaluation of Manufacturing Accuracy in Merlon Fracture Models Fabricated by Vat Photopolymerization 3D-Printing Technologies

by Hee-jung Lee, Chang-sub Jeong, Joon-mo Moon, Ji-myung Bae, Eun-joo Choi and Seung-han Oh

Appl. Sci. 2025, 15(10), 5595; https://doi.org/10.3390/app15105595 - 16 May 2025

Abstract

This study evaluates the manufacturing accuracy of Merlon fracture models produced using two vat-photopolymerization-based three-dimensional (3D) printers: digital light processing (DLP) and liquid-crystal display (LCD). The Merlon fracture model is used to assess dimensional precision and machining accuracy. The root mean square (RMS) [...] Read more.

This study evaluates the manufacturing accuracy of Merlon fracture models produced using two vat-photopolymerization-based three-dimensional (3D) printers: digital light processing (DLP) and liquid-crystal display (LCD). The Merlon fracture model is used to assess dimensional precision and machining accuracy. The root mean square (RMS) values, wall and bottom thicknesses, and field-emission scanning electron microscopy images are analyzed. The DLP-based printers exhibit lower RMS values and superior accuracy compared with LCD-based printing and subtractive milling. Polymer-based slurries for permanent dental applications exhibit better dimensional stability than those for temporary restorations. This study also highlights the significant impact of postprocessing and cleaning procedures on the final model accuracy. These findings suggest that optimizing the postprocessing parameters is crucial for enhancing the precision of 3D-printed dental restorations. The Merlon fracture model is a viable method for evaluating additive manufacturing accuracy, contributing to the improved clinical application of vat photopolymerization in dental prosthetics. Full article

(This article belongs to the Special Issue Advances in Additive Manufacturing: Novel Technologies and Processes)

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26 pages, 4511 KiB

Open AccessArticle

VDGA-Based Resistorless Mixed-Mode Universal Filter and Dual-Mode Quadrature Oscillator

by Orapin Channumsin, Jetwara Tangjit, Tattaya Pukkalanun and Worapong Tangsrirat

Appl. Sci. 2025, 15(10), 5594; https://doi.org/10.3390/app15105594 - 16 May 2025

Abstract

This study introduces an electronically tunable resistorless mixed-mode universal filter and dual-mode quadrature oscillator configuration utilizing merely two voltage differencing gain amplifiers and two grounded capacitors. The suggested filter can perform all generic biquadratic filter functions in all four modes: voltage mode, trans-admittance [...] Read more.

This study introduces an electronically tunable resistorless mixed-mode universal filter and dual-mode quadrature oscillator configuration utilizing merely two voltage differencing gain amplifiers and two grounded capacitors. The suggested filter can perform all generic biquadratic filter functions in all four modes: voltage mode, trans-admittance mode, current mode, and trans-impedance mode, while utilizing the same design. The pole frequency and the quality factor can be tuned electronically and orthogonally by means of the transconductances of the voltage differencing gain amplifier. The dual-mode quadrature oscillator featuring both voltage and current outputs can also be obtained from the proposed filter core. It additionally provides separate electronic control of the oscillation condition and frequency. Several PSPICE simulations with the TSMC 0.18 μm CMOS model confirm the feasibility of the proposed configurations. Both proposed circuits were experimentally evaluated using commercially available integrated circuit LM13600s. Both simulation and experimental results have validated the performance of the design. Full article

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

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14 pages, 1028 KiB

Open AccessArticle

A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients

by Michele Tepedino, Rosa Esposito, Maurizio Delvecchio, Domenico Ciavarella, Giuseppe Rofrano and Francesco Masedu

Appl. Sci. 2025, 15(10), 5593; https://doi.org/10.3390/app15105593 - 16 May 2025

Abstract

Background: Skeletal age estimation plays a fundamental role in orthopedic treatments. Since the most reliable methods are based on ionizing radiation, this study aimed to use machine learning techniques to explore a skeletal age assessment method not based on additional radiographies. Methods: [...] Read more.

Background: Skeletal age estimation plays a fundamental role in orthopedic treatments. Since the most reliable methods are based on ionizing radiation, this study aimed to use machine learning techniques to explore a skeletal age assessment method not based on additional radiographies. Methods: Patients aged between 6 and 16 years old whose clinical records included orthopantomography, radiographs of the second phalanx of the third finger, and biometric data were enrolled for the study. The radiographs were analyzed to estimate the maturation degree of the left lower first premolars, the midpalatal suture, and the second phalanx of the third finger. Both an explicative data analysis and a multivariate analysis were performed. Results: The sample comprised 111 subjects. The multivariate analysis revealed an explanatory role for sex (p < 0.01) and chronological age (p < 0.01). The ordinal tool showed how the use of height (p = 0.02) and weight (p = 0.03) was explicative of skeletal age against a loss of statistical significance corresponding to the use of body mass index (p = 0.6). The median palatine suture (p = 0.01) was explicative. Conclusions: The combined evaluation of weight, height, sex, chronological age, and grade of maturation of the midpalate suture provides an explicative tool for assessing skeletal age without additional radiographic exams, besides a routine orthopantomography. Full article

(This article belongs to the Special Issue Orthodontics: Advanced Techniques, Methods and Materials)

16 pages, 8572 KiB

Open AccessArticle

Fracture Behavior and Cracking Mechanism of Rock Materials Containing Fissure-Holes Under Brazilian Splitting Tests

by Hengjie Luan, Kun Liu, Decheng Ge, Wei Han, Yiran Zhou, Lujie Wang and Sunhao Zhang

Appl. Sci. 2025, 15(10), 5592; https://doi.org/10.3390/app15105592 - 16 May 2025

Abstract

Fractures and voids are widely distributed in slope rock masses. These defects promote crack initiation and propagation, ultimately leading to rock mass failure. Investigating their damage evolution mechanisms and strength characteristics is of significant importance for slope hazard prevention. A numerical simulation study [...] Read more.

Fractures and voids are widely distributed in slope rock masses. These defects promote crack initiation and propagation, ultimately leading to rock mass failure. Investigating their damage evolution mechanisms and strength characteristics is of significant importance for slope hazard prevention. A numerical simulation study of Brazilian splitting tests on disk samples containing prefabricated holes and fractures was conducted using the Finite Element Method with Cohesive Zone Modeling (FEM-CZM) in ABAQUS by embedding zero-thickness cohesive elements within the finite element model. This 2021 study analyzed the effects of fracture angle and length on tensile strength and crack propagation characteristics. The results revealed that when the fracture angle is small, cracks initiate near the fracture and propagate and intersect radially as the load increases, ultimately leading to specimen failure, with the crack coalescence pattern exhibiting local closure. As the fracture angle increases, the initiation location of the crack shifts. With an increase in fracture length, the crack initiation position may transfer to other parts of the fracture or near the hole, and longer fractures may result in more complex coalescence patterns and local closure phenomena. During the tensile and stable failure stages, the load–displacement curves of samples with different fracture angles and lengths exhibit similar trends. However, the fracture angle has a notable impact on the curve during the shear failure stage, while the fracture length significantly affects the peak value of the curve. Furthermore, as displacement increases, the proportion of tensile failure undergoes a process of rapid decline, slow rise, and then rapid decline again before stabilizing, with the fracture angle having a significant influence on the proportion of tensile failure. Lastly, as the fracture angle and length increase, the number of damaged cohesive elements shows an upward trend. This study provides novel perspectives on the tensile behavior of fractured rock masses through the FEM-CZM approach, contributing to a fundamental understanding of the strength characteristics and crack initiation mechanism of rocks under tensile loading conditions. Full article

(This article belongs to the Special Issue Cross-Scale Cracks in Rock Mass Under Multi-Phase and Multi-Field Coupling)

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