Applied Sciences

14 pages, 945 KiB

Open AccessArticle

Enhancing Far-Field Speech Recognition with Mixer: A Novel Data Augmentation Approach

by Tong Niu, Yaqi Chen, Dan Qu and Hengbo Hu

Appl. Sci. 2025, 15(7), 4073; https://doi.org/10.3390/app15074073 - 7 Apr 2025

Viewed by 296

Recent advancements in end-to-end (E2E) modeling have notably improved automatic speech recognition (ASR) systems; however, far-field speech recognition (FSR) remains challenging due to signal degradation from factors such as low signal-to-noise ratio, reverberation, and interfering sounds. This requires richer training data and multi-channel [...] Read more.

Recent advancements in end-to-end (E2E) modeling have notably improved automatic speech recognition (ASR) systems; however, far-field speech recognition (FSR) remains challenging due to signal degradation from factors such as low signal-to-noise ratio, reverberation, and interfering sounds. This requires richer training data and multi-channel speech enhancement. To address this gap, we introduce Mixer, a novel data augmentation technique designed to further enhance the performance of large-scale pre-trained models for FSR. Mixer interpolates and mixes feature representations of speech samples and their corresponding losses, extending the MixSpeech framework to intermediate layers of Whisper. Additionally, we propose Mixer-C, which further leverages multi-channel information by combining speech from different microphone channels using a channel selector. Experimental results demonstrate that Mixer significantly outperforms existing methods, including SpecAugment, achieving a relative word error rate (WER) reduction of 3.6% compared to the baseline. Furthermore, Mixer-C offers an additional WER improvement of 2.2%, showcasing its efficacy in improving FSR accuracy. Full article

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

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18 pages, 9039 KiB

Open AccessArticle

An Intelligent Monitoring System for the Driving Environment of Explosives Transport Vehicles Based on Consumer-Grade Cameras

by Jinshan Sun, Jianhui Tang, Ronghuan Zheng, Xuan Liu, Weitao Jiang and Jie Xu

Appl. Sci. 2025, 15(7), 4072; https://doi.org/10.3390/app15074072 - 7 Apr 2025

Viewed by 264

Abstract

With the development of industry and society, explosives are widely used in social production as an important industrial product and require transportation. Explosives transport vehicles are susceptible to various objective factors during driving, increasing the risk of transportation. At present, new transport vehicles [...] Read more.

With the development of industry and society, explosives are widely used in social production as an important industrial product and require transportation. Explosives transport vehicles are susceptible to various objective factors during driving, increasing the risk of transportation. At present, new transport vehicles are generally equipped with intelligent driving monitoring systems. However, for old transport vehicles, the cost of installing such systems is relatively high. To enhance the safety of older explosives transport vehicles, this study proposes a cost-effective intelligent monitoring system using consumer-grade IP cameras and edge computing. The system integrates YOLOv8 for real-time vehicle detection and a novel hybrid ranging strategy combining monocular (fast) and binocular (accurate) techniques to measure distances, ensuring rapid warnings and precise proximity monitoring. An optimized stereo matching workflow reduces processing latency by 23.5%, enabling real-time performance on low-cost devices. Experimental results confirm that the system meets safety requirements, offering a practical, application-specific solution for improving driving safety in resource-limited explosive transport environments. Full article

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34 pages, 788 KiB

Open AccessArticle

Study About the Performance of Ascon in Arduino Devices

by Ventura Sarasa Laborda, Luis Hernández-Álvarez, Luis Hernández Encinas, José Ignacio Sánchez García and Araceli Queiruga-Dios

Appl. Sci. 2025, 15(7), 4071; https://doi.org/10.3390/app15074071 - 7 Apr 2025

Viewed by 225

Abstract

In 2023, the Ascon cipher suite was selected as the winner of the National Institute of Standards and Technology (NIST) standardization process for lightweight cryptography, and has emerged as the leading candidate for cryptographic algorithms in resource-constrained environments. This cipher suite provides authenticated [...] Read more.

In 2023, the Ascon cipher suite was selected as the winner of the National Institute of Standards and Technology (NIST) standardization process for lightweight cryptography, and has emerged as the leading candidate for cryptographic algorithms in resource-constrained environments. This cipher suite provides authenticated encryption with associated data and hash functionality. NIST’s Ascon proposal consists of two symmetric ciphers, Ascon-128 and Ascon-128a, a hash function, Ascon-HASH, an extendible output function, Ascon-XOF, and a new cipher variant, Ascon-80pq, with increased resistance to quantum attacks. This study presents an overview of the mathematical background, security principles and key properties of the Ascon cipher suite. In addition, a comprehensive performance evaluation of Ascon on various Arduino platforms, such as Arduino DUE, Arduino Mega2560, Arduino Nano Every and Arduino Nano ESP32, is performed. A detailed comparative analysis of these implementations is also provided. Full article

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15 pages, 769 KiB

Open AccessArticle

A Method for Adapting Stereo Matching Algorithms to Real Environments

by Adam L. Kaczmarek

Appl. Sci. 2025, 15(7), 4070; https://doi.org/10.3390/app15074070 - 7 Apr 2025

Viewed by 168

Abstract

This study challenges the commonly used testbeds and benchmarks for testing stereo matching algorithms. Although the algorithms listed in the rankings based on these testbeds score exceptionally high, stereo matching technology still suffers from major drawbacks; as such, it is much less popular [...] Read more.

This study challenges the commonly used testbeds and benchmarks for testing stereo matching algorithms. Although the algorithms listed in the rankings based on these testbeds score exceptionally high, stereo matching technology still suffers from major drawbacks; as such, it is much less popular in commercial use than other technologies for 3D scanning, such as structured-light 3D scanners. One of the main problems is that the poor quality of the results is either blamed on an inappropriate stereo camera calibration or a bad stereo matching algorithm. However, this study shows that both of these steps need to be considered together. In this paper, a solution is proposed by integrating the problem of camera calibration with the execution of a stereo matching algorithm. This approach makes it possible to restore stereo matching as a technology that is competitive with other methods of 3D image acquisition. Full article

(This article belongs to the Section Robotics and Automation)

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14 pages, 1019 KiB

Open AccessArticle

Enhanced Blockchain-Based Data Poisoning Defense Mechanism

by Song-Kyoo Kim

Appl. Sci. 2025, 15(7), 4069; https://doi.org/10.3390/app15074069 - 7 Apr 2025

Viewed by 231

Abstract

This paper deals with a new secured execution environment which adapts blockchain technology to defend artificial intelligence (AI) models against data poisoning (DP) attacks. The Blockchain Governance Game (BGG) is a theoretical framework for analyzing the network to provide the decision-making moment for [...] Read more.

This paper deals with a new secured execution environment which adapts blockchain technology to defend artificial intelligence (AI) models against data poisoning (DP) attacks. The Blockchain Governance Game (BGG) is a theoretical framework for analyzing the network to provide the decision-making moment for taking preliminary cybersecurity actions before DP attacks. This innovative method for conventional decentralized network securities is adapted into a DP defense for AI models in this paper. The core components in the DP defense network, including the Predictor and the BGG engine, are fully implemented. This research concerns the first blockchain-based DP defense mechanism which establishes an innovative framework for DP defense based on the BGG. The simulation in the paper demonstrates realistic DP attack situations targeting AI models. This new controller is newly designed to provide sufficient cybersecurity performance measures even with minimal data collection and limited computing power. Additionally, this research will be helpful for those considering using blockchain to implement a DP defense mechanism. Full article

(This article belongs to the Special Issue Approaches to Cyber Attacks and Malware Detection)

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20 pages, 5341 KiB

Open AccessArticle

Real-Time DTM Generation with Sequential Estimation and OptD Method

by Wioleta Błaszczak-Bąk, Waldemar Kamiński, Michał Bednarczyk, Czesław Suchocki and Andrea Masiero

Appl. Sci. 2025, 15(7), 4068; https://doi.org/10.3390/app15074068 - 7 Apr 2025

Viewed by 184

Abstract

Data acquisition and simultaneous generation of real-time digital terrain models (DTMs) is a demanding task, due to the vast amounts of observations collected by modern technologies and measurement instruments in a short time. Existing methods for generating DTMs with large datasets require significant [...] Read more.

Data acquisition and simultaneous generation of real-time digital terrain models (DTMs) is a demanding task, due to the vast amounts of observations collected by modern technologies and measurement instruments in a short time. Existing methods for generating DTMs with large datasets require significant time and high computing power. Furthermore, these methods often fail to consider fragmentary DTM generation to maintain model continuity by addressing overlaps. Additionally, storing the resulting datasets, generated 3D models, and backup copies consumes excessive memory on computer and server disks. In this study, a novel concept of generating DTMs based on real-time data acquisition using the principles of sequential estimation is proposed. Since DTM generation occurs simultaneously with data acquisition, the proposed algorithm also incorporates data reduction techniques to manage the large dataset. The reduction is achieved using the Optimum Dataset Method (OptD). The effect of the research is the characteristics file that stores information about the DTM. The results demonstrate that the proposed methodology enables the creation of 3D models described by mathematical functions in each sequence and allows for determining the height of any terrain point efficiently. Experimental validation was conducted using airborne LiDAR data. The results demonstrate that data reduction using OptD retains critical terrain features while reducing dataset size by up to 98%, significantly improving computational efficiency. The accuracy of the generated DTM was assessed using root mean square error (RMSE) metrics, with values ranging from 0.041 m to 0.121 m, depending on the reduction level. Additionally, statistical analysis of height differences (ΔZ) between the proposed method and conventional interpolation techniques confirmed the reliability of the new approach. Compared to existing DTM generation methods, the proposed approach offers real-time adaptability, improved accuracy representation per model fragment, and reduced computational overhead. Full article

(This article belongs to the Special Issue Applications of Digital Photogrammetry and 3D Laser Scanning in Geomatics)

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24 pages, 2521 KiB

Open AccessArticle

Research on Structural Mechanics Stress and Strain Prediction Models Combining Multi-Sensor Image Fusion and Deep Learning

by Yifeng Shan, Mengzhe Zhen and Heinz D. Fill

Appl. Sci. 2025, 15(7), 4067; https://doi.org/10.3390/app15074067 - 7 Apr 2025

Viewed by 216

Abstract

The integration of multi-sensor imaging and deep learning techniques has emerged as a pivotal innovation in advancing structural mechanics, particularly in the prediction of stress and strain distributions. This study falls within the thematic scope of multi-sensor imaging and fusion methods, emphasizing their [...] Read more.

The integration of multi-sensor imaging and deep learning techniques has emerged as a pivotal innovation in advancing structural mechanics, particularly in the prediction of stress and strain distributions. This study falls within the thematic scope of multi-sensor imaging and fusion methods, emphasizing their crucial role in assessing material behavior under complex conditions. Traditional methodologies, such as finite element methods and classical constitutive models, often fall short in capturing the intricacies of heterogeneous materials and nonlinear stress–strain relationships. These limitations necessitate a more robust computational framework capable of addressing material variability and computational efficiency challenges. To this end, we propose the Stress–Strain Adaptive Predictive Model (SSAPM), which synergizes mechanistic modeling with data-driven corrections. Leveraging hybrid representations, adaptive optimization strategies, and modular architectures, SSAPM ensures precision by embedding physics-informed constraints and reduced-order modeling for computational scalability. Experimental validations underscore the model’s capability to generalize across diverse structural scenarios, outperforming conventional approaches in accuracy and efficiency. This work establishes a transformative pathway for incorporating multi-sensor data fusion into structural analysis, advancing the predictive power and applicability of stress–strain models. Full article

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12 pages, 17471 KiB

Open AccessArticle

Calibration of a Low-Cost 8×8 Active Phased Array Antenna

by Xiaoliang Sun, Jorge Calatayud-Maeso, Alfonso-Tomás Muriel-Barrado, José-Manuel Fernández-González and Manuel Sierra-Castañer

Appl. Sci. 2025, 15(7), 4066; https://doi.org/10.3390/app15074066 - 7 Apr 2025

Viewed by 281

Abstract

This paper presents the calibration process involved in a planar active phased array antenna operating in the K-band (17.7–20.2 GHz). The array consists of eight columns, each containing a 1 × 8 subarray of patch antennas. To enhance the antenna bandwidth, a double-stacked [...] Read more.

This paper presents the calibration process involved in a planar active phased array antenna operating in the K-band (17.7–20.2 GHz). The array consists of eight columns, each containing a 1 × 8 subarray of patch antennas. To enhance the antenna bandwidth, a double-stacked patch structure is employed. We analyze the challenges encountered when measuring active antennas. Additionally, we discuss the solutions and calibration techniques used to improve the array performance. Finally, we present the results of the optimal calibration approach, comparing simulated and measured data, both with and without calibration, to evaluate the improvements achieved. Full article

(This article belongs to the Special Issue Multi-Band/Broadband Antenna Design, Optimization and Measurement)

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20 pages, 4243 KiB

Open AccessArticle

Importance Measure for Fuzzy Structural Systems from the Probabilistic Perspective and Its Solving Algorithms

by Guijie Li, Miaomiao Zhu and Sanyuan Li

Appl. Sci. 2025, 15(7), 4065; https://doi.org/10.3390/app15074065 - 7 Apr 2025

Viewed by 144

Abstract

To effectively determine the influences of fuzzy uncertainties on structural systems in engineering, according to the fuzzy failure probability (FFP) model, which is based on the probabilistic perspective, the importance measure (IM) technique is extended to fuzzy uncertain structural systems. A novel IM [...] Read more.

To effectively determine the influences of fuzzy uncertainties on structural systems in engineering, according to the fuzzy failure probability (FFP) model, which is based on the probabilistic perspective, the importance measure (IM) technique is extended to fuzzy uncertain structural systems. A novel IM framework, i.e., the fuzzy-failure-probability-based IM (FFP-IM), is established. By transforming the fuzzy failure probability into the expected value of the function for the failure domain, the proposed FFP-IM index can be represented as the variance-based IM of that index function. Then, an efficient solution algorithm for the proposed FFP-IM index is established based on the state-dependent parameter method. Ultimately, the Ishigami function, alongside three practical engineering examples, validates the proposed FFP-IM’s rationality and applicability. Furthermore, these examples illustrate the solution algorithm’s superior computational efficiency and accuracy. Full article

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22 pages, 4637 KiB

Open AccessArticle

Generalized Singular Value Decomposition-Based Secure Beam Hybrid Precoding for Millimeter Wave Massive Multiple-Input Multiple-Output Systems

by Boqing Chen, Lijun Yang and Meng Wu

Appl. Sci. 2025, 15(7), 4064; https://doi.org/10.3390/app15074064 - 7 Apr 2025

Viewed by 147

Abstract

The precoder obtained using the traditional singular value decomposition (SVD) method for legitimate user’s channel, while achieving the highest spectral efficiency for the legitimate user, cannot defend against eavesdropping attacks, thus posing a security vulnerability. This paper investigates the millimeter wave (mmWave) secure [...] Read more.

The precoder obtained using the traditional singular value decomposition (SVD) method for legitimate user’s channel, while achieving the highest spectral efficiency for the legitimate user, cannot defend against eavesdropping attacks, thus posing a security vulnerability. This paper investigates the millimeter wave (mmWave) secure beam hybrid precoding technology and proposes a generalized singular value decomposition (GSVD)-based secure beam hybrid precoding algorithm, termed GSVD-Sparsity, leveraging the sparsity of the mmWave beamspace channel. The algorithm selects the most powerful paths from the legitimate user’s beamspace channel representation and utilizes their corresponding angle information to construct a radio frequency (RF) precoder. It then constructs a hybrid precoder that closely approximates the optimal digital precoder derived from the GSVD-based scheme in a fully digital system. The simulation results indicate that, compared to the SVD-based scheme that focuses on spectral efficiency, the GSVD-based precoding scheme can form secure beams in a fully digital system. Under the condition that the legitimate user experiences a certain loss in the received signal-to-noise ratio (SNR), the eavesdropper is unable to correctly reconstruct the original constellation diagram, ensuring the scheme has strong anti-eavesdropping capabilities. In a hybrid precoding system, the low-complexity GSVD-Sparsity algorithm can achieve a spectral efficiency close to that of the GSVD-based scheme in a fully digital system while maintaining anti-eavesdropping capabilities. Full article

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10 pages, 938 KiB

Open AccessArticle

Fractal Dimension of the Condylar Bone Structure in Patients with Unilateral Condylar Hyperplasia: Cross-Sectional Retrospective Study

by Adriana Assunta De Stefano, Ludovica Musone, Martina Horodynski, Roberto Antonio Vernucci and Gabriella Galluccio

Appl. Sci. 2025, 15(7), 4063; https://doi.org/10.3390/app15074063 - 7 Apr 2025

Viewed by 175

Abstract

Unilateral condylar hyperplasia (UCH) is one of the causes of facial asymmetry, and it is characterized by increased growth in one of the mandibular condyles. In UCH, it is important to determine whether the metabolic activity of the hyperplastic condyle is still active. [...] Read more.

Unilateral condylar hyperplasia (UCH) is one of the causes of facial asymmetry, and it is characterized by increased growth in one of the mandibular condyles. In UCH, it is important to determine whether the metabolic activity of the hyperplastic condyle is still active. Fractal dimension (FD) analysis could be a non-invasive method to identify active metabolic activity. The aim of this study is to compare the FD of the hyperplastic condyle with the contralateral one in patients with facial asymmetry and positive bone scintigraphy and to compare the FD of the right and left condyles in symmetrical patients. A cross-sectional retrospective study of fifteen patients with facial asymmetry and positive bone scintigraphy and fifteen symmetrical patients was conducted. Clinical data and scintigraphy results were collected from medical records, and CBCT scans were used for the application of FD by pre-processing the images according to White and Rudolph and using ImageJ^® (1.54p) software and the box-counting method. Wilcoxon’s t test was used to analyze the differences in FD between the hyperplastic and contralateral condyles in patients with UCH and between the right and left condyles in symmetrical patients. A p-value of <0.05 was considered statistically significant. The FD of the hyperplastic condyles was significantly higher than the contralateral one in the axial and coronal plane (p = 0.001). The analysis of FD of the mandibular condyle can be a useful non-invasive method to identify active UCH in patients with facial asymmetry. Full article

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

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29 pages, 3807 KiB

Open AccessArticle

Optimal Dispatch of Multi-Coupling Systems Considering Molten Salt Thermal Energy Storage Retrofit and Cost Allocation Under Rapid Load Variations

by Niancheng Zhou, Zhenyu Xu, Yuan Chi, Yao Zou, Fei Xu and Xuhui Dai

Appl. Sci. 2025, 15(7), 4062; https://doi.org/10.3390/app15074062 - 7 Apr 2025

Viewed by 175

Abstract

With the rapid growth of renewable energy generation capacity, integrating thermal power units and renewable energy units at the point of common coupling (PCC) as a coupling system (CS) can significantly enhance the operational reliability and economic efficiency of modern power systems. To [...] Read more.

With the rapid growth of renewable energy generation capacity, integrating thermal power units and renewable energy units at the point of common coupling (PCC) as a coupling system (CS) can significantly enhance the operational reliability and economic efficiency of modern power systems. To better reflect the coordinated operational capability of thermal power units with molten salt thermal storage retrofit (TPUMSTSR) in multi-coupling system (MCS) scheduling, this study proposes a multi-stage optimization-based dispatch method for MCSs. First, rapid load variation (RLV) technology and thermal storage retrofitting are combined to establish a thermal power unit operation model incorporating molten salt thermal storage (MSTS) retrofits under RLVs. Based on this, a three-stage economic dispatch optimization method is proposed to maximize the daily comprehensive generation revenue of MCSs while dynamically allocating peak regulation (PR) revenue costs across different time periods to relax and simplify nonlinear objectives and constraints in the optimization process. Finally, a simulation study is conducted on an MCS in northeast China. The results demonstrate that the proposed flexibility retrofit scheme and optimization algorithm enable a more coordinated and economically efficient dispatch strategy. Full article

(This article belongs to the Special Issue Advances and Challenges in Power Systems with High Penetration of Renewable Energies)

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19 pages, 9083 KiB

Open AccessArticle

Sealing of Unconformity Structure and Hydrocarbon Accumulation in the Baikouquan Formation of the Mahu Sag

by Zexin Wan, Menglin Zheng, Xiaolong Wang, Yiyao Bao, Zhiyuan An, Qilin Xiao and Yunqiao Chen

Appl. Sci. 2025, 15(7), 4061; https://doi.org/10.3390/app15074061 - 7 Apr 2025

Viewed by 204

Abstract

Unconformity stratigraphic traps are widely developed in the Mahu Sag, on the northwestern margin of the Junggar Basin. It is of great significance for subsequent oil and gas exploration to explore the role of conglomerate accumulation mode and unconformity inner structure in the [...] Read more.

Unconformity stratigraphic traps are widely developed in the Mahu Sag, on the northwestern margin of the Junggar Basin. It is of great significance for subsequent oil and gas exploration to explore the role of conglomerate accumulation mode and unconformity inner structure in the formation of oil and gas reservoirs. Therefore, this study uses oil and gas geophysical technology combined with geological theory to identify the P/T unconformity structure in the study area, determine the development characteristics and accumulation control of the unconformity structure, and explore the accumulation mode of stratigraphic oil and gas reservoirs. The results show the following: (1) Based on the different logging response characteristics of the upper, middle, and lower layers of the unconformity structure, five types of unconformity structure are divided according to different lithologic combinations. (2) Through experimental and numerical simulation analysis, it was verified that fracture pressure and thickness are important indicators for evaluating the sealing property of unconformity structure. P/T unconformity structure provides good floor conditions for the Baikouquan Formation reservoir, further confirming its key role in the process of oil and gas accumulation and storage. (3) Based on the analysis of actual cases, the accumulation model of stratigraphic oil and gas reservoirs under the control of unconformity structure is summarized as cross-layer accumulation above the source, fault communication source reservoir, unconformity lateral transmission and distribution, and mudstone lateral docking. The research results provide technical support and important reference values for the exploration and development of unconformity-related oil and gas reservoirs in the Junggar Basin. Full article

(This article belongs to the Section Earth Sciences)

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18 pages, 6383 KiB

Open AccessStudy Protocol

The Impact of Hollow Wear on the Stability of High-Speed Railway Vehicles

by Ling Zhang, Junping Hu, Chen Wang and Zechao Liu

Appl. Sci. 2025, 15(7), 4060; https://doi.org/10.3390/app15074060 - 7 Apr 2025

Viewed by 205

Abstract

Hollow wear on wheels is a common form of surface damage often observed in high-velocity vehicles. It is widely recognized that hollow wear of the wheel tread degrades the dynamic performance of rail vehicles, especially in the issue commonly referred to as “operational [...] Read more.

Hollow wear on wheels is a common form of surface damage often observed in high-velocity vehicles. It is widely recognized that hollow wear of the wheel tread degrades the dynamic performance of rail vehicles, especially in the issue commonly referred to as “operational stability”, and leads to abnormal wheel–rail contact interactions. However, the evaluation criteria for vehicle stability are not uniform, which affects the assessment of wheel conditions and the timing of wheel re-profiling during maintenance. Therefore, numerical simulations were conducted by matching the measured worn wheel profiles with standard rails, and three different methods were employed to evaluate vehicle stability in this article. The numerical results revealed that the wheel equivalent conicity exhibits a nonlinear characteristic caused by hollow wear, which means that the nominal equivalent conicity is unable to accurately represent the geometric contact relationship between the wheel and rail. Under identical wheel wear conditions, a certain difference was observed in the critical speed of the vehicle determined by the velocity-reducing method and the bifurcation configuration method. Both methods were capable of reflecting the impact of wheel hollow wear on vehicle stability at the critical speed. Compared to the velocity-reducing method, the bifurcation configuration method can better reflect the transition process of a vehicle from stable running to hunting instability. Furthermore, the lateral vibration acceleration values measured above the bogie frame indicated that slight wheel wear is insensitive to increased speed. However, when the wear was severe, the lateral vibration acceleration of the bogie was found to increase sharply, exceeding the established stability criteria. This phenomenon was consistent with the safety alarms that occurred during actual vehicle operation, indicating that the vehicle had failed to meet stability requirements. Full article

(This article belongs to the Special Issue New Insights into Railway Vehicle Dynamics)

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12 pages, 2582 KiB

Open AccessArticle

Evaluation of Deflection Errors in Traffic Speed Deflectometer Measurements on Inverted Asphalt Pavement Structures

by Kai Wang, Jiaojiao Wei, Xiaoqiang Hou and Chaoyang Wu

Appl. Sci. 2025, 15(7), 4059; https://doi.org/10.3390/app15074059 - 7 Apr 2025

Viewed by 229

Abstract

This study developed a dynamic model for the Traffic Speed Deflectometer (TSD) on inverted asphalt pavement structures. It is aimed at evaluating the deflection slope and quantifying measurement errors. First, the reliability of the ABAQUS model in simulating the dynamic response of asphalt [...] Read more.

This study developed a dynamic model for the Traffic Speed Deflectometer (TSD) on inverted asphalt pavement structures. It is aimed at evaluating the deflection slope and quantifying measurement errors. First, the reliability of the ABAQUS model in simulating the dynamic response of asphalt pavements was validated by comparing with previous studies. The deflection slope curves of inverted and semi-rigid base pavements with varying thicknesses were compared, revealing that the inverted pavement exhibited complex deflection slope trends in TSD measurements. A significant decrease in peak deflection was observed at 0.15 m from the load gap center with increasing surface thickness. The deflection velocity measurement value of the TSD calibration sensor (S3500) on the inverted asphalt pavement is not zero, which causes the road surface deflection to be lower than the actual deflection, with an error as high as 80.1%, which overestimated the pavement’s structural capacity. These findings suggest that the sensor configuration and measurement strategy of TSD should be reconsidered when applied to inverted asphalt pavement structures. The results provide useful insights that may support the refinement of TSD application strategies. Full article

(This article belongs to the Special Issue Pavement Engineering: System, Rehabilitation, and Sustainable Strategies for Long-Term Management)

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11 pages, 1434 KiB

Open AccessArticle

Development of a Simple HPLC Method for the Analysis of Ergosterol and UV-Enriched Vitamin D₂ in Mushroom Powders

by Judit Bajzát, András Misz, József Rácz, Máté Vágvölgyi, Csaba Csutorás and Csaba Vágvölgyi

Appl. Sci. 2025, 15(7), 4058; https://doi.org/10.3390/app15074058 - 7 Apr 2025

Viewed by 223

Abstract

In this study, a straightforward and cost-effective HPLC-UV method was developed for the rapid determination of vitamin D₂ and ergosterol in mushrooms. These bioactive components are known to play a significant role in the nutritional value of mushrooms, particularly in the production [...] Read more.

In this study, a straightforward and cost-effective HPLC-UV method was developed for the rapid determination of vitamin D₂ and ergosterol in mushrooms. These bioactive components are known to play a significant role in the nutritional value of mushrooms, particularly in the production of mushroom-based food supplements. The method, designed for routine analysis, involves a simple sample preparation process combining saponification and solid–liquid extraction, followed by HPLC-UV detection. High recovery rates (97–99%) were achieved by the method, with limits of detection (LOD) and quantitation (LOQ) of 0.1 mg/kg dry weight and 0.5 mg/kg dry weight, respectively. The enrichment of vitamin D₂ content in mushroom powders through UV irradiation was also investigated. In Agaricus bisporus, vitamin D₂ levels increased from an initial 1.92 mg/kg to 4.66 mg/kg following heat treatment at 100 °C, and reached a maximum of 28.13 mg/kg when heat treatment was combined with UV irradiation. In contrast, Lentinula edodes exhibited an initial vitamin D₂ content of 7–8.5 mg/kg, with the highest levels achieved through UV treatment alone, which also preserved ergosterol content. These findings highlight species-specific differences in vitamin D₂ conversion and present an effective approach for enhancing the nutritional profile of mushroom-based products, while providing a reliable analytical tool for quality control. Full article

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

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30 pages, 6442 KiB

Open AccessReview

Macroissues with Microplastics: A Review on Distribution, Environmental Impacts, Pollutant Interactions, Toxicity, Analytical Methodology and Mitigation Strategies

by Aleksandra Anić-Vučinić, Dunja Turk and Anja Bek

Appl. Sci. 2025, 15(7), 4057; https://doi.org/10.3390/app15074057 - 7 Apr 2025

Viewed by 442

Abstract

Although plastic has many desirable properties and numerous social benefits, it is a serious ecological problem due to massive application and difficult decomposing. Various environmental and anthropogenic impacts indicate that plastic breaks down into small particles that are ubiquitous in the environment. Microplastics [...] Read more.

Although plastic has many desirable properties and numerous social benefits, it is a serious ecological problem due to massive application and difficult decomposing. Various environmental and anthropogenic impacts indicate that plastic breaks down into small particles that are ubiquitous in the environment. Microplastics (MPs) are detected in oceans and seas, freshwater, wastewater, glaciers, soils, air, sediments, precipitation, plants, animals, humans, food and drinking water worldwide. Traces of MPs have been found even in remote and sparsely populated areas, indicating far-reaching movement through environmental compartments. Inadequate waste management and wastewater treatment is considered the major source of MP pollution. MPs are persistent contaminants that can adversely affect the ecological balance of the environment and may damage the health of living organisms, including humans. This review emphasizes the current global problems of MP pollution. It covers different areas of MPs, which include basic characteristics, interactions with other pollutants, occurrence and impacts in the environment, toxic effects on living organisms, sampling, sample pre-treatment and analytical methodology for the identification and quantification of MPs in different matrices as well as potential reduction and remediation strategies and the possibilities for effective control of MPs in the environment. Various interesting and useful previously published knowledge collected in this review can serve as a valuable foundation for further MP research. Full article

(This article belongs to the Special Issue Waste Recycling Materials and Technologies: Latest Advances and Prospects)

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19 pages, 282 KiB

Open AccessArticle

Mental Health, Overweight, and Physical Exercise in Young Portuguese Adults: A Cross-Sectional Study

by Tânia Gonçalves, Diogo Monteiro, Rui Matos, Pedro Duarte-Mendes, Nuno Couto, Raul Antunes, Susana Diz, Nuno Amaro and Miguel Jacinto

Appl. Sci. 2025, 15(7), 4056; https://doi.org/10.3390/app15074056 - 7 Apr 2025

Viewed by 229

Abstract

The aim of this study was to see if there are any associations between mental health, Body Mass Index (BMI), and physical exercise (PE) in young Portuguese adults. The sample consisted of 414 people aged between 18 and 25 years old. A sociodemographic [...] Read more.

The aim of this study was to see if there are any associations between mental health, Body Mass Index (BMI), and physical exercise (PE) in young Portuguese adults. The sample consisted of 414 people aged between 18 and 25 years old. A sociodemographic questionnaire designed for this study and the Mental Health Inventory were used. To analyze the results, the total sample was divided according to the criteria “BMI ≥ 5 kg/m²”; “BMI < 25 kg/m²”; “does not practice PE”; and “practices PE”, and sample groups were formed with these names. It was found that there was an association between the dimensions of the Mental Health Inventory and the average time spent practicing PE in the total sample (r from 0.099 to 0.160) and in individuals with a BMI < 25 kg/m² (r = 0.154 and 0.169). In individuals with a BMI ≥25 kg/m², there was an association between the ‘BMI’ and depression variables (r = −0.174). In all groups, associations were found between the variables of age and BMI (r from 0.120 to 0.216). There was also a significant effect of group (non-exercise vs. exercise groups) on the dependent variables, Λ = 0.972, F(5, 408) = 2.329, p = 0.042, η²p = 0.28. This study confirms the association between PE and mental health and suggests that BMI may have an influence on the appearance of depressive symptoms in young Portuguese adults. Full article

(This article belongs to the Special Issue Current Advances in Performance Analysis and Technologies for Sports)

18 pages, 4644 KiB

Open AccessArticle

An Assisted Numerical Simulation Diagnosis Method for Atherosclerosis Based on Hemodynamics

by Lei Guo, Ye Lu and Shusheng Zhang

Appl. Sci. 2025, 15(7), 4055; https://doi.org/10.3390/app15074055 - 7 Apr 2025

Viewed by 230

Abstract

The mechanism of atherosclerosis lesions was investigated based on a fluid–structure interaction method according to the geometric reconstruction of human arteries by medical imaging. Numerical simulation, mechanical analysis, and dynamic simulation were used to establish a model of the mechanical characteristics of arterial [...] Read more.

The mechanism of atherosclerosis lesions was investigated based on a fluid–structure interaction method according to the geometric reconstruction of human arteries by medical imaging. Numerical simulation, mechanical analysis, and dynamic simulation were used to establish a model of the mechanical characteristics of arterial blood transport, analyze the fluid properties of arterial blood flow under the influence of vascular lesion process, and study the mechanism of arterial lesion formation and development. The results indicated that the clinically important areas of secondary flow were generated at stenosis and bifurcation sites, which were prone to lesions during a cardiac cycle. The low flow rate and shear stress levels of blood in this region led to the adhesion and precipitation of lesion-inducing factors on the intimal tissue, creating a hydrodynamic environment suitable for lesion development. According to the research reported here in, early clinical detection and follow-up of atherosclerosis can be performed by collecting data on wall shear stress and blood flow pressure difference. Full article

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17 pages, 1224 KiB

Open AccessArticle

Filtered Operator-Based Nonlinear Control for DC–DC Converter-Driven Triboelectric Nanogenerator System

by Ryusei Shimane, Chengyao Liu and Mingcong Deng

Appl. Sci. 2025, 15(7), 4054; https://doi.org/10.3390/app15074054 - 7 Apr 2025

Viewed by 184

Abstract

In recent years, with the growing interest in the Internet of Things (IoT) and decarbonization, energy harvesting has been attracting attention. Energy harvesting is a technology that converts ambient energy such as light, heat, and vibration into electrical power, and it is also [...] Read more.

In recent years, with the growing interest in the Internet of Things (IoT) and decarbonization, energy harvesting has been attracting attention. Energy harvesting is a technology that converts ambient energy such as light, heat, and vibration into electrical power, and it is also known as environmental power generation. A triboelectric nanogenerator is a type of energy harvesting device that converts mechanical energy, such as vibration, into electrical energy using the triboelectric effect and electrostatic induction. The advantages of this device include low cost and high durability. Due to the principle of triboelectric nanogenerators, a stable output voltage cannot be obtained, so auxiliary circuits such as DC–DC converters are required to obtain the desired voltage. In this paper, a DC–DC converter is utilized, controlled by a system based on operator theory, with a filter incorporated to enhance tracking performance, ensuring that the output voltage follows the target value. Full article

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14 pages, 1518 KiB

Open AccessArticle

Decoding Lung Cancer Radiogenomics: A Custom Clustering/Classification Methodology to Simultaneously Identify Important Imaging Features and Relevant Genes

by Destie Provenzano, John P. Lichtenberger, Sharad Goyal and Yuan James Rao

Appl. Sci. 2025, 15(7), 4053; https://doi.org/10.3390/app15074053 - 7 Apr 2025

Viewed by 233

Abstract

Background: This study evaluated a custom algorithm that sought to perform a radiogenomic analysis on lung cancer genetic and imaging data, specifically by using machine learning to see whether a custom clustering/classification method could simultaneously identify features from imaging data that correspond to [...] Read more.

Background: This study evaluated a custom algorithm that sought to perform a radiogenomic analysis on lung cancer genetic and imaging data, specifically by using machine learning to see whether a custom clustering/classification method could simultaneously identify features from imaging data that correspond to genetic markers. Methods: CT imaging data and genetic mutation data for 281 subjects with NSCLC were collected from the CPTAC-LUAD and TCGA-LUSC databases on TCIA. The algorithm was run as follows: (1) genetic clusters were initialized using random clusters, binary matrix factorization, or k-means; (2) image classification was run on CT data for these genetic clusters; (3) misclassified subjects were re-classified based on the image classification algorithm; and (4) the algorithm was run until an accuracy of 90% or no improvement after 10 runs. Input genetic mutations were evaluated for potential medical treatments and severity to provide clinical relevance. Results: The image classification algorithm was able to achieve a >90% accuracy after nine algorithm runs and grouped subjects from a starting five clusters to four final clusters, where final image classification accuracy was better than every initial clustered accuracy. These clusters were stable across all three test runs. A total of thirty-eight genes from the top hundred across each subject were identified with specific severity or treatment data; twelve of these genes are listed. Conclusion: This small pilot study presented a potential way to identify genetic patterns from image data and presented a methodology that could group images with no labels or only partial labels for future problems. Full article

(This article belongs to the Special Issue Recent Advances in and Applications of Medical Image Processing and Analysis)

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29 pages, 9451 KiB

Open AccessArticle

Optimizing Thermal Performance of Mini Heat Exchangers: An Experimental Analysis Using a Full Factorial Design

by Sergio da Silva Franco, Álvaro Augusto Soares Lima, Alvaro Antonio Villa Ochoa, José Ângelo Peixoto da Costa, Gustavo de Novaes Pires Leite, Márcio Vilar, Kilvio Alessandro Ferraz and Paula Suemy Arruda Michima

Appl. Sci. 2025, 15(7), 4052; https://doi.org/10.3390/app15074052 - 7 Apr 2025

Viewed by 296

Abstract

This study seeks to investigate the heat dissipation process in a minichannel heat exchanger, commonly employed for cooling electronic components. The analysis centers on two key factors: global thermal resistance (G_TR) and the heat transfer coefficient. The innovation of this [...] Read more.

This study seeks to investigate the heat dissipation process in a minichannel heat exchanger, commonly employed for cooling electronic components. The analysis centers on two key factors: global thermal resistance (G_TR) and the heat transfer coefficient. The innovation of this study resides in the development and analysis of a mini heat exchanger optimized using chemometric methods to achieve efficient thermal dissipation. Various conditions, including the power source, volumetric flow rate, and ambient temperature, were varied at both low and high levels to assess their impact on these variables and establish the optimal conditions for heat dissipation. The cooling of electronic components, such as processors, remains a topic of ongoing research, as the miniaturization of components through nanotechnology requires enhanced heat dissipation within increasingly smaller spaces. This experimental study identifies the optimal conditions for both G_TR and the heat transfer coefficient within the examined parameters. G_TR is minimized with a power of 30 W, an ambient temperature of 29 °C, and a flow rate of 2.50 L·min⁻¹. The results indicate that electrical power was the most significant variable affecting G_TR, while ambient temperature also played a determining role in the heat transfer coefficient. Full article

(This article belongs to the Special Issue Thermal and Thermomechanical Management in Electronic Systems)

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16 pages, 4102 KiB

Open AccessArticle

Mechanical Performance of Group Stud Connectors in Steel–Concrete Composite Beams with Straddle Monorail

by Lei-Ting Jiao, Zhen-Hao Wu, Yong-Fei Zhao, Ji-Zhi Zhao and Shu-Ke Wang

Appl. Sci. 2025, 15(7), 4051; https://doi.org/10.3390/app15074051 - 7 Apr 2025

Viewed by 224

Abstract

A steel–concrete composite beam with a straddle monorail is a lightweight and easily installable structure. The mechanical performance of group stud connectors and their arrangement are key design parameters that govern the beam’s overall performance. This study investigates the behavior of group stud [...] Read more.

A steel–concrete composite beam with a straddle monorail is a lightweight and easily installable structure. The mechanical performance of group stud connectors and their arrangement are key design parameters that govern the beam’s overall performance. This study investigates the behavior of group stud connectors by conducting push-out tests on four specimens, comprising three full-scale models and one 1:3 scaled model. Variables such as the number of connectors, arrangement, and specimen size were explored. The results indicated that all the specimens exhibited ductile failure due to stud shearing. The strain distribution analysis revealed higher strain at the edges and lower in the middle, persisting as the load increased. The group stud effect resulted in a 23.4% to 27.2% reduction in shear capacity for the full-scale specimens and 16.5% for the scaled specimen. The reduction was proportional to the density of the studs, but the size effects were less significant. This study provides valuable insights into the mechanical behavior of group stud connectors and offers design recommendations for practical applications. Full article

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16 pages, 4584 KiB

Open AccessArticle

Development of Ultra-Fast Surface Acoustic Wave-Based NO₂ Sensor Incorporating a Monolayered Graphene: MoS₂ Sensing Material and a Microheater for Spacecraft Applications

by Faisal Nawaz, Hyunho Lee, Wen Wang and Keekeun Lee

Appl. Sci. 2025, 15(7), 4050; https://doi.org/10.3390/app15074050 - 7 Apr 2025

Viewed by 243

Abstract

A surface acoustic wave-based NO₂ sensor and its interface electronics, utilizing monolayered two-dimensional sensing materials, were developed for internal pollution monitoring in spacecraft. The sensor system consists of a two-port SAW delay line with monolayered graphene/MoS₂ flakes in the cavity region [...] Read more.

A surface acoustic wave-based NO₂ sensor and its interface electronics, utilizing monolayered two-dimensional sensing materials, were developed for internal pollution monitoring in spacecraft. The sensor system consists of a two-port SAW delay line with monolayered graphene/MoS₂ flakes in the cavity region between two interdigital transducers, along with the interface electronics. A microheater was integrated adjacent to the sensor to maintain a stable temperature field on the sensor surface, thereby enhancing sensitivity, response/recovery times, and selectivity. The monolayered graphene/MoS₂ sensing material, with its high surface-to-volume ratio, excellent mobility, and moderate bonding force with target molecules, enables the rapid response and recovery times of less than 2.5 and 8 s, respectively—among the fastest reported in SAW gas sensor technology. The developed sensor combines the conductivity changes, the mass loading effect, and a synergistic effect that promotes carrier separation caused by a built-in potential barrier between the two monolayers, providing exceptionally high sensitivity of 578 Hz/ppm. Additionally, the sensor’s interface electronics were engineered to mitigate the effects of external factors, such as temperature and humidity, ensuring a stable and reliable performance under varying harsh conditions. Full article

(This article belongs to the Section Surface Sciences and Technology)

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19 pages, 5298 KiB

Open AccessArticle

A Health Status Identification Method for Rotating Machinery Based on Multimodal Joint Representation Learning and a Residual Neural Network

by Xiangang Cao and Kexin Shi

Appl. Sci. 2025, 15(7), 4049; https://doi.org/10.3390/app15074049 - 7 Apr 2025

Viewed by 227

Abstract

Given that rotating machinery is one of the most commonly used types of mechanical equipment in industrial applications, the identification of its health status is crucial for the safe operation of the entire system. Traditional equipment health status identification mainly relies on conventional [...] Read more.

Given that rotating machinery is one of the most commonly used types of mechanical equipment in industrial applications, the identification of its health status is crucial for the safe operation of the entire system. Traditional equipment health status identification mainly relies on conventional single-modal data, such as vibration or acoustic modalities, which often have limitations and false alarm issues when dealing with real-world operating conditions and complex environments. However, with the increasing automation of coal mining equipment, the monitoring of multimodal data related to equipment operation has become more prevalent. Existing multimodal health status identification methods are still imperfect in extracting features, with poor complementarity and consistency among modalities. To address these issues, this paper proposes a multimodal joint representation learning and residual neural network-based method for rotating machinery health status identification. First, vibration, acoustic, and image modal information is comprehensively utilized, which is extracted using a Gramian Angular Field (GAF), Mel-Frequency Cepstral Coefficients (MFCCs), and a Faster Region-based Convolutional Neural Network (RCNN), respectively, to construct a feature set. Second, an orthogonal projection combined with a Transformer is used to enhance the target modality, while a modality attention mechanism is introduced to take into consideration the interaction between different modalities, enabling multimodal fusion. Finally, the fused features are input into a residual neural network (ResNet) for health status identification. Experiments conducted on a gearbox test platform validate the proposed method, and the results demonstrate that it significantly improves the accuracy and reliability of rotating machinery health state identification. Full article

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28 pages, 4025 KiB

Open AccessArticle

Blockchain-Based UAV-Assisted Mobile Edge Computing for Dual Game Resource Allocation

by Shanchen Pang, Yu Tang, Xue Zhai, Siyuan Tong and Zhenghao Wan

Appl. Sci. 2025, 15(7), 4048; https://doi.org/10.3390/app15074048 - 7 Apr 2025

Viewed by 347

Abstract

UAV-assisted mobile edge computing combines the flexibility of UAVs with the computing power of MEC to provide low-latency, high-performance computing solutions for a wide range of application scenarios. However, due to the highly dynamic and heterogeneous nature of the UAV environment, the optimal [...] Read more.

UAV-assisted mobile edge computing combines the flexibility of UAVs with the computing power of MEC to provide low-latency, high-performance computing solutions for a wide range of application scenarios. However, due to the highly dynamic and heterogeneous nature of the UAV environment, the optimal allocation of resources and system reliability still face significant challenges. This paper proposes a two-stage optimization (DSO) algorithm for UAV-assisted MEC, combining Stackelberg game theory and auction mechanisms to optimize resource allocation among servers, UAVs, and users. The first stage uses a Stackelberg game to allocate resources between servers and UAVs, while the second stage employs an auction algorithm for UAV-user resource pricing. Blockchain smart contracts automate task management, ensuring transparency and reliability. The experimental results show that compared with the traditional single-stage optimization algorithm (SSO), the equal allocation algorithm (EAA) and the dynamic resource pricing algorithm (DRP), the DSO algorithm proposed in this paper has significant advantages by improving resource utilization by 7–10%, reducing task latency by 3–5%, and lowering energy consumption by 4–8%, making it highly effective for dynamic UAV environments. Full article

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16 pages, 3144 KiB

Open AccessArticle

Optimizing Computational Process of High-Order Taylor Discontinuous Galerkin Method for Solving the Euler Equations

by Meng Zhang and Kyosuke Yamamoto

Appl. Sci. 2025, 15(7), 4047; https://doi.org/10.3390/app15074047 - 7 Apr 2025

Viewed by 151

Abstract

Solving the Euler equations often requires expensive computations of complex, high-order time derivatives. Although Taylor Discontinuous Galerkin (TDG) schemes are renowned for their accuracy and stability, directly evaluating third-order tensor derivatives can significantly reduce computational efficiency, particularly for large-scale, intricate flow problems. To [...] Read more.

Solving the Euler equations often requires expensive computations of complex, high-order time derivatives. Although Taylor Discontinuous Galerkin (TDG) schemes are renowned for their accuracy and stability, directly evaluating third-order tensor derivatives can significantly reduce computational efficiency, particularly for large-scale, intricate flow problems. To overcome this difficulty, this paper presents an optimized numerical procedure that combines Taylor series time integration with the Discontinuous Galerkin (DG) approach. By replacing cumbersome tensor derivatives with simpler time derivatives of the Jacobian matrix and finite difference method inside the element to calculate the high-order time derivative terms, the proposed method substantially decreases the computational cost while maintaining accuracy and stability. After verifying its fundamental feasibility in one-dimensional tests, the optimized TDG method is applied to a two-dimensional forward-facing step problem. In all numerical tests, the optimized TDG method clearly exhibits a computational efficiency advantage over the conventional TDG method, therefore saving a great amount of time, nearly 70%. This concept can be naturally extended to higher-dimensional scenarios, offering a promising and efficient tool for large-scale computational fluid dynamics simulations. Full article

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17 pages, 2419 KiB

Open AccessArticle

Bubble Temperature Effect on the Heat Transfer Performance of R449a During Flow Boiling Inside a Horizontal Smooth Tube

by Andrea Lucchini, Bharath Nagaraju, Igor Matteo Carraretto, Luigi Pietro Maria Colombo, Domenico Mazzeo, Luca Molinaroli and Paola Grazia Pittoni

Appl. Sci. 2025, 15(7), 4046; https://doi.org/10.3390/app15074046 - 7 Apr 2025

Viewed by 202

Abstract

Since the Montreal Protocol (dated 1987), the reduction of the environmental impact has been one of the main goals in the HVAC sector, which has led to the replacement of widely used fluids with new environmentally friendly ones. Nevertheless, only new fluids with [...] Read more.

Since the Montreal Protocol (dated 1987), the reduction of the environmental impact has been one of the main goals in the HVAC sector, which has led to the replacement of widely used fluids with new environmentally friendly ones. Nevertheless, only new fluids with suitable heat transfer features can be used. The refrigerant mixture R449a, one of the fourth-generation refrigerants, was tested during flow boiling inside a horizontal smooth tube. The experiments were carried out at six different mass fluxes G ∈ [175;400] kg·m⁻²·s⁻¹ and four different bubble temperatures T_b ∈ [2.5;10] °C, while the nominal values for inlet and outlet quality were selected as x_Ti = 0.1 and x_To = 0.9, respectively. The results highlighted that, as the bubble temperature increases, it has an opposite effect on the pressure drop per unit length and the heat transfer coefficient: the former decreases while the latter grows. The comparison between experimental results and the correlations showed that the Zhang and Webb formula provides the best prediction of pressure drop, while the models provided by Bertsch yield the most reliable predictions for the heat transfer coefficient. Nevertheless, for both quantities, other correlations with similar performances are available. Full article

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19 pages, 1301 KiB

Open AccessReview

An Overview of Shared Mobility Operational Models in Europe

by Luka Vidan, Marko Slavulj, Ivan Grgurević and Matija Sikirić

Appl. Sci. 2025, 15(7), 4045; https://doi.org/10.3390/app15074045 - 7 Apr 2025

Viewed by 340

Abstract

Climate change is an urgent issue, and the current mindset of private ownership, particularly of private vehicles, needs to shift. Shared mobility is rapidly emerging as a key part of the solution to contemporary transportation challenges, driven by technological advancements and the growing [...] Read more.

Climate change is an urgent issue, and the current mindset of private ownership, particularly of private vehicles, needs to shift. Shared mobility is rapidly emerging as a key part of the solution to contemporary transportation challenges, driven by technological advancements and the growing demand for more sustainable travel options. This paper provides a comprehensive analysis of shared mobility operational models in Europe, focusing on carsharing and its current research on fleet optimization, bikesharing, and scooter sharing. The study draws on three scientific literature databases, with searches centered on keywords relevant to Shared Mobility. This study contributes to the literature by defining each Shared Mobility modality and examining the different operational models. Full article

(This article belongs to the Special Issue Sustainable Urban Mobility)

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21 pages, 481 KiB

Open AccessArticle

Adaptive Cluster-Based Normalization for Robust TOPSIS in Multicriteria Decision-Making

by Vitor Anes and António Abreu

Appl. Sci. 2025, 15(7), 4044; https://doi.org/10.3390/app15074044 - 7 Apr 2025

Viewed by 221

Abstract

In multicriteria decision-making (MCDM), methods such as TOPSIS are essential for evaluating and comparing alternatives across multiple criteria. However, traditional normalization techniques often struggle with datasets containing outliers, large variances, or heterogeneous measurement units, which can lead to skewed or biased rankings. To [...] Read more.

In multicriteria decision-making (MCDM), methods such as TOPSIS are essential for evaluating and comparing alternatives across multiple criteria. However, traditional normalization techniques often struggle with datasets containing outliers, large variances, or heterogeneous measurement units, which can lead to skewed or biased rankings. To address these challenges, this paper proposes an adaptive, cluster-based normalization approach, demonstrated through a real-world logistics case study involving the selection of a host city for an international event. The method groups alternatives into clusters based on similarities in criterion values and applies logarithmic normalization within each cluster. This localized strategy reduces the influence of outliers and ensures that scaling adjustments reflect the specific characteristics of each group. In the case study—where cities were evaluated based on cost, infrastructure, safety, and accessibility—the cluster-based normalization method yielded more stable and balanced rankings, even in the presence of significant data variability. By reducing the influence of outliers through logarithmic normalization and allowing predefined cluster profiles to reflect expert judgment, the method improves fairness and adaptability. These features strengthen TOPSIS’s ability to deliver accurate, balanced, and context-aware decisions in complex, real-world scenarios. Full article

(This article belongs to the Special Issue Fuzzy Control Systems: Latest Advances and Prospects)

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