Applied Sciences

22 pages, 6861 KiB

Open AccessArticle

A Numerical Investigation of Enhanced Microfluidic Immunoassay by Multiple-Frequency Alternating-Current Electrothermal Convection

by Qisheng Wu, Shaohua Huang, Shenghai Wang, Xiying Zhou, Yuxuan Shi, Xiwei Zhou, Xianwu Gong, Ye Tao and Weiyu Liu

Appl. Sci. 2025, 15(9), 4748; https://doi.org/10.3390/app15094748 - 24 Apr 2025

Abstract

Compared with traditional immunoassay methods, microfluidic immunoassay restricts the immune response in confined microchannels, significantly reducing sample consumption and improving reaction efficiency, making it worthy of widespread application. This paper proposes an exciting multi-frequency electrothermal flow (MET) technique by applying combined standing-wave and [...] Read more.

Compared with traditional immunoassay methods, microfluidic immunoassay restricts the immune response in confined microchannels, significantly reducing sample consumption and improving reaction efficiency, making it worthy of widespread application. This paper proposes an exciting multi-frequency electrothermal flow (MET) technique by applying combined standing-wave and traveling-wave voltage signals with different oscillation frequencies to a three-period quadra-phase discrete electrode array, achieving rapid immunoreaction on functionalized electrode surfaces within straight microchannels, by virtue of horizontal pumping streamlines and transverse stirring vortices induced by nonlinear electrothermal convection. Under the approximation of a small temperature rise, a linear model describing the phenomenon of MET is derived. Although the time-averaged electrothermal volume force is a simple superposition of the electrostatic body force components at the two frequencies, the electro-thermal-flow field undergoes strong mutual coupling through the dual-component time-averaged Joule heat source term, further enhancing the intensity of Maxwell–Wagner smeared structural polarization and leading to mutual influence between the standing-wave electrothermal (SWET) and traveling-wave electrothermal (TWET) effects. Through thorough numerical simulation, the optimal working frequencies for SWET and TWET are determined, and the resulting synthetic MET flow field is directly utilized for microfluidic immunoassay. MET significantly promotes the binding kinetics on functionalized electrode surface by simultaneous global electrokinetic transport along channel length direction and local chaotic stirring of antigen samples near the reaction site, compared to the situation without flow activation. The MET investigated herein satisfies the requirements for early, rapid, and precise immunoassay of test samples on-site, showing great application prospects in remote areas with limited resources. Full article

(This article belongs to the Special Issue Electrokinetic Phenomena in Microfluidics and Nanofluidics and Their Lab-on-a-Chip Applications)

13 pages, 438 KiB

Open AccessArticle

Supplement Use Among Athletes: Insights from Gyms in Sarajevo

by Denis Čaušević, Cristina Ioana Alexe, Nedim Čović, Elena Adelina Panaet, Ensar Abazović, Raul Marian Todor, Babina Rani, Gabriel Lupu and Dan Iulian Alexe

Appl. Sci. 2025, 15(9), 4747; https://doi.org/10.3390/app15094747 - 24 Apr 2025

Abstract

This study aimed to examine the habits, attitudes, and consumption patterns of food supplements (FS) among gym users in Sarajevo, Bosnia and Herzegovina, with respect to gender, age, and training experience. Understanding these behaviors is essential given the rising global trend in FS [...] Read more.

This study aimed to examine the habits, attitudes, and consumption patterns of food supplements (FS) among gym users in Sarajevo, Bosnia and Herzegovina, with respect to gender, age, and training experience. Understanding these behaviors is essential given the rising global trend in FS use, often without professional guidance, which can have implications for individual health and public awareness. By investigating local patterns, this study seeks to provide valuable insights into the motivations and risks associated with supplement consumption, contributing to evidence-based recommendations and policy-making in the field of fitness and nutrition. Methods: Cross-sectional data were collected from various fitness centers using an online questionnaire composed of 21 questions divided into three segments. A total of 614 participants (mean ± SD: 32.77 ± 9.82 years), including both male (67.8%) and female (32.2%) gym users, took part in the study. Results: Participants predominantly belonged to the 36–45 age group, with 70.0% (p < 0.001) reporting more than one year of regular gym attendance, and 40.4% indicating regular FS consumption (p < 0.05). Supplements were mainly used to support faster recovery (29.1%, p < 0.05) and muscle growth (25%, p < 0.05). Magnesium was the most commonly used supplement, equally favored across genders and age groups. Creatine, fish oil capsules, and multivitamins were also frequently consumed (p < 0.05). Self-prescription emerged as the predominant method of FS use (40.3%, p < 0.05), followed by advice from gym coaches (21.8%), with only 5.6% of participants receiving guidance from a nutritionist. Conclusions: The findings highlight a societal trend toward self-directed FS use, often influenced by informal sources, underscoring the importance of further research and the development of targeted, evidence-based educational strategies. Males reported higher FS consumption, with younger users more focused on muscle gain and older individuals prioritizing health maintenance. The reliance on non-expert recommendations raises concerns about the safety and effectiveness of FS usage in the fitness community. Full article

(This article belongs to the Special Issue Supplements for Health and Sports Performance)

14 pages, 891 KiB

Open AccessArticle

An Axial Compression Transformer for Efficient Human Pose Estimation

by Wen Tan, Haixiang Zhang and Xinyi Song

Appl. Sci. 2025, 15(9), 4746; https://doi.org/10.3390/app15094746 - 24 Apr 2025

Abstract

Transformer has a wide range of applications in human posture estimation. It can model the global dependence relationship of images through the self-attention mechanism to obtain key human body information. However, Transformer consumes a lot of computation. An axial compression pose transformer (ACPose) [...] Read more.

Transformer has a wide range of applications in human posture estimation. It can model the global dependence relationship of images through the self-attention mechanism to obtain key human body information. However, Transformer consumes a lot of computation. An axial compression pose transformer (ACPose) method is proposed to reduce part of the computational cost of Transformer by the axial compression of the input matrix, while maintaining the global receptive field by feature fusion. A Local Enhancement Module is constructed to avoid the loss of too much feature information in the compression process. In the COCO dataset experiment, there was a significant reduction in computational cost compared to those of state-of-the-art transformer-based algorithms. Full article

(This article belongs to the Collection Advances in Image Processing, Analysis and Recognition Technology)

30 pages, 721 KiB

Open AccessArticle

Verifiable Threshold Multi-Party Fully Homomorphic Encryption from Share Resharing

by Yuqi Xie, Ruwei Huang and Junbin Qiu

Appl. Sci. 2025, 15(9), 4745; https://doi.org/10.3390/app15094745 - 24 Apr 2025

Abstract

Threshold multi-party fully homomorphic encryption (TMFHE) schemes enable efficient computation to be performed on sensitive data while maintaining privacy. These schemes allow a subset of parties to perform threshold decryption of evaluation results via a distributed protocol without the need for a trusted [...] Read more.

Threshold multi-party fully homomorphic encryption (TMFHE) schemes enable efficient computation to be performed on sensitive data while maintaining privacy. These schemes allow a subset of parties to perform threshold decryption of evaluation results via a distributed protocol without the need for a trusted dealer, and provide a degree of fault tolerance against a set of corrupted parties. However, existing TMFHE schemes can only provide correctness and security against honest-but-curious parties. We construct a compact TMFHE scheme based on the Learning with Errors (LWE) problem. The scheme applies Shamir secret sharing and share resharing to support an arbitrary t-out-of-N threshold access structure, and enables non-interactive reconstruction of secret key shares using additive shares derived from the current set of online participants. Furthermore, the scheme implements commitment and non-interactive zero-knowledge (NIZK) proof techniques to verify the TMFHE operations. Finally, our experiments demonstrate that the proposed scheme achieves active security against malicious adversaries. It overcomes the limitation of existing TMFHE schemes that can only guarantee correct computation under passive semi-honest adversaries. Full article

17 pages, 3252 KiB

Open AccessArticle

Design of a Robotic Work Cell Using Hierarchical Systems Approach and Visual Components Software

by Kanstantsin Miatliuk, Krystian Koc, Atakan Eliacik, Paulo E. Miyagi and Marcosiris A. O. Pessoa

Appl. Sci. 2025, 15(9), 4744; https://doi.org/10.3390/app15094744 - 24 Apr 2025

Abstract

The use of Hierarchical Systems (HS) technology in the conceptual design of the RWC (Robotic Work Cell) is proposed in the work. In comparison with other widespread approaches, the conceptual model of the RWC constructed in the HS formal basis contains connected models [...] Read more.

The use of Hierarchical Systems (HS) technology in the conceptual design of the RWC (Robotic Work Cell) is proposed in the work. In comparison with other widespread approaches, the conceptual model of the RWC constructed in the HS formal basis contains connected models of RWC subsystems, their processes, the RWC structure, its dynamic presentation as the unit in its environment, and the RWC coordinator. The design and control system of RWC is presented in the form of an HS coordinator. For the detailed design of the selected RWC, the Visual Components system was applied in the work. First, the conceptual model of the RWC is presented in the paper. The application of the Visual Components program system for the detailed design of the RWC is described after that. Third, the laboratory experiment with the KUKA KR16-2 F robot is briefly considered. The originality of the proposed work lies in the application of the novel HS technology in the creation of the conceptual model and design of the selected RWC. The model developed at the conceptual design phase is coordinated with the model created at the detailed design phase within the framework of the Visual Components system. The effectiveness of the proposed HS approach in comparison with other known design, AI, and mathematical methods lies in the possibility of solving RWC synthesis and analysis design problems within the framework of one common formal HS model using an HS coordinator that connects the structure of the system being designed with its function, predicting, in this way, the system’s dynamics in its environment, and performing RWC control. The reliability of the model proposed was verified while performing the design and control tasks of the presented RWC and various other mechatronic objects. The results and conclusive remarks are finally presented in the paper. Full article

(This article belongs to the Special Issue New Challenges in Conceptual Design of Robotic and Mechatronic Systems: 2nd Edition)

14 pages, 1416 KiB

Open AccessReview

Focused Ultrasounds in the Rehabilitation Setting: A Narrative Review

by Carmelo Pirri, Nicola Manocchio, Daniele Polisano, Andrea Sorbino and Calogero Foti

Appl. Sci. 2025, 15(9), 4743; https://doi.org/10.3390/app15094743 - 24 Apr 2025

Abstract

Focused ultrasound (FUS) is an emerging noninvasive technology with significant therapeutic potential across various clinical domains. FUS enables precise targeting of tissues using mechanisms like thermoablation, mechanical disruption, and neuromodulation, minimizing damage to surrounding areas. In movement disorders such as essential tremor and [...] Read more.

Focused ultrasound (FUS) is an emerging noninvasive technology with significant therapeutic potential across various clinical domains. FUS enables precise targeting of tissues using mechanisms like thermoablation, mechanical disruption, and neuromodulation, minimizing damage to surrounding areas. In movement disorders such as essential tremor and Parkinson’s disease, MR-guided FUS thalamotomy has demonstrated substantial tremor reduction and improved quality of life. Psychiatric applications include anterior capsulotomy for treatment-resistant obsessive-compulsive disorder and major depressive disorder, with promising symptom relief and minimal cognitive side effects. FUS also facilitates blood-brain barrier opening for drug delivery in neurological conditions like Alzheimer’s disease. Musculoskeletal applications highlight its efficacy in managing chronic pain from knee osteoarthritis and lumbar facet joint syndrome through precise thermal ablation. Additionally, FUS has shown potential in neuropathic pain management and peripheral nerve stimulation, offering innovative approaches for amputees and cancer survivors. Cognitive and neuromodulatory research underscores its ability to enhance motor function and interhemispheric cortical balance, benefiting stroke and traumatic brain injury rehabilitation. Despite these conditions frequently leading to various kinds of disabilities, no direct exploration of the possible FUS application in rehabilitation is yet available in the literature. All this considered, this review aims to discuss how FUS could be applied in rehabilitation, exploring the current status of knowledge and highlighting future directions. Full article

(This article belongs to the Special Issue Innovative Approaches and Tools for Healthcare and Medical Applications)

31 pages, 1975 KiB

Open AccessArticle

Research on a Bone Stick Fragment Stitching Method Based on Improved Corner Detection

by Jiahuan Liu, Huiqin Wang, Rui Liu, Ke Wang, Zhan Wang and Ting Wang

Appl. Sci. 2025, 15(9), 4742; https://doi.org/10.3390/app15094742 - 24 Apr 2025

Abstract

The stitching of bone stick fragments is of great significance for the inheritance of and research into the outstanding traditional culture of the Western Han Dynasty. Focused on the problem that the existing methods have a low bone stick fragment stitching success rate [...] Read more.

The stitching of bone stick fragments is of great significance for the inheritance of and research into the outstanding traditional culture of the Western Han Dynasty. Focused on the problem that the existing methods have a low bone stick fragment stitching success rate due to their complex edges, this paper proposes a bone stick fragment stitching method based on improved corner detection, which strengthens the features of broken edges and improves the success rate of stitching. First, the maximum outer contour of the bone stick fragment is obtained using connectivity analysis. Then, the broken edge features are enhanced by combining multi-scale and multi-stage corner detection, as well as a double screening mechanism of local template and corner density analysis. On this basis, the maximum outer contour is segmented using a region segmentation method based on corner features. Then, a priority matching strategy is used to perform multi-dimensional sequential priority matching of corner features for the densest segments and to match other contour segments in the order of density. Finally, based on the matching results, the bone stick fragment is stitched exactly and restored. Experimental results show that compared with other algorithms, the average proportion of broken corners when using the method in this paper is increased by about 44.89%, and the average comprehensive weighted similarity is increased by about 32.42%, which meets the needs of bone stick fragment stitching. Full article

20 pages, 2527 KiB

Open AccessArticle

Post-Occupancy Evaluation in High-Rise Apartment Buildings in Vietnam

by Yuanchen Wang, Anh Tuan Tran, Thi Hai Ha Pham, Thi Hoa Nguyen, Konstantinos Stergiaropoulos and Dirk Schwede

Appl. Sci. 2025, 15(9), 4741; https://doi.org/10.3390/app15094741 - 24 Apr 2025

Abstract

As part of the CAMaRSEC research project, long-term indoor environmental measurements with accompanying occupant surveys were conducted over one year in 49 households in 15 high-rise residential apartment buildings in Hanoi, Vietnam. A comprehensive analysis of the collected data revealed differences in the [...] Read more.

As part of the CAMaRSEC research project, long-term indoor environmental measurements with accompanying occupant surveys were conducted over one year in 49 households in 15 high-rise residential apartment buildings in Hanoi, Vietnam. A comprehensive analysis of the collected data revealed differences in the indoor environment and energy consumption patterns during the operational phase of the buildings, as well as their correlation with diverse occupant behaviors. In addition, by comparing subjective thermal evaluations based on occupant surveys with predictions based on comfort models, the limitations of existing models in predicting the thermal sensations of local people were identified. Furthermore, the findings indicated that the apartment building design standard in Vietnam underestimates the thermal adaptation of occupants, which may lead to significant building performance gaps. Larger scale surveys and measurements are required to provide sufficient databases to refine local building design standards, especially for mixed-mode buildings. Full article

(This article belongs to the Special Issue Advances in the Energy Efficiency and Thermal Comfort of Buildings)

18 pages, 2611 KiB

Open AccessArticle

A Few-Shot Learning Framework for Depth Completion Based on Self-Training with Noise and Pixel-Wise Knowledge Distillation

by Shijie Zhang, Shengjie Zhao, Jin Zeng and Hao Deng

Appl. Sci. 2025, 15(9), 4740; https://doi.org/10.3390/app15094740 - 24 Apr 2025

Abstract

Depth completion generates a comprehensive depth map by utilizing sparse depth data inputs, supplemented by guidance provided by an RGB image. Deep neural network models depend on annotated datasets for optimal training. However, when the quantity of training data is limited, the generalization [...] Read more.

Depth completion generates a comprehensive depth map by utilizing sparse depth data inputs, supplemented by guidance provided by an RGB image. Deep neural network models depend on annotated datasets for optimal training. However, when the quantity of training data is limited, the generalization capability of deep neural network (DNN)-based methods diminishes considerably. Moreover, acquiring a large dataset of depth maps is challenging and resource intensive. To address these challenges, we introduce a novel few-shot learning approach for depth completion. Our approach integrates noisy-student training with knowledge distillation (KD) techniques to enhance model performance and generalization. We incorporate both the noisy-student training and KD modules into a basic deep regression network using a non-local spatial propagation network (NLSPN) for depth completion. The noisy-student training framework enhances the model’s performance and generalization capabilities by introducing controlled noise and self-learning mechanisms. Within our few-shot learning framework for depth completion, the KD mechanism transfers advanced capabilities from the teacher model to the student model. Experimental evaluations demonstrate that our approach effectively addresses the challenges associated with depth completion tasks, particularly in scenarios with limited training data and a constrained number of available samples. Full article

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25 pages, 3357 KiB

Open AccessArticle

Optimal Design and Seismic Performance of Base-Isolated Structures with Varying Heights Equipped with Tuned Inerter Dampers Subjected to Far-Fault and Near-Fault Ground Motions

by Yingjie Kang, Zewen Zhang, Zeyu Zhang, Xinyu Zhang and Qingkuan Liu

Appl. Sci. 2025, 15(9), 4739; https://doi.org/10.3390/app15094739 - 24 Apr 2025

Abstract

This paper investigates the optimal design of base-isolated structures equipped with tuned inerter dampers (TIDs) subjected to various ground motions. The Clough–Penzien model is employed to simulate the power spectrum of three types of ground motions: far-fault, near-fault without pulse subset, and near-fault [...] Read more.

This paper investigates the optimal design of base-isolated structures equipped with tuned inerter dampers (TIDs) subjected to various ground motions. The Clough–Penzien model is employed to simulate the power spectrum of three types of ground motions: far-fault, near-fault without pulse subset, and near-fault with pulse subset, with the relevant parameters identified based on actual ground motions. The optimal parameters of the TID for base-isolated structures are determined using the H² optimization criterion to reduce the structural displacement response. The impact of relevant design properties about the optimal parameters is analyzed. The seismic control effectiveness of the TID for 5-storey, 10-storey, and 15-storey base-isolated structures with varying heights is then evaluated through time history analysis, considering far-fault, near-fault without pulse subset, and near-fault with pulse subset ground motions. The main conclusions of this study are as follows: the ground motion type, the natural vibration period of the isolated structure, the damping ratio of the isolated structure and the mass ratio of the TID all affect the optimal parameters and should be analyzed based on specific circumstances. The control effectiveness of the TID on displacement and acceleration response is more pronounced under far-fault ground motion than under near-fault ground motion. The TID equipped in the isolation storey exhibits considerable effectiveness in controlling the seismic response of 5-storey and 10-storey base isolated structures, while it exhibits weaker control over the seismic response of the 15-storey structure. Additionally, while the TID primarily targets displacement response control, it also exhibits substantial control over the absolute acceleration response of the structure. Full article

21 pages, 25885 KiB

Open AccessArticle

Analysis of Different Guide Elements’ Designs in Hydraulic Cylinders

by Jan Pustavrh, Ana Trajkovski, Vito Tič, Marko Polajnar, Uroš Bohinc and Franc Majdič

Appl. Sci. 2025, 15(9), 4738; https://doi.org/10.3390/app15094738 - 24 Apr 2025

Abstract

In this study, the frictional behaviours of three different guide elements—guide rings, labyrinth seals, and hydrostatic bearings—in hydraulic cylinders is investigated experimentally. A modular, double-acting hydraulic cylinder was designed to compare these three different design elements under different pressures (0 bar, 120 bar, [...] Read more.

In this study, the frictional behaviours of three different guide elements—guide rings, labyrinth seals, and hydrostatic bearings—in hydraulic cylinders is investigated experimentally. A modular, double-acting hydraulic cylinder was designed to compare these three different design elements under different pressures (0 bar, 120 bar, and 240 bar), velocities, and radial loads. The results show that the guide rings exhibit the highest friction, especially at high pressures. Labyrinth seals exhibit significantly lower friction and extend the service life of the components. Hydrostatic bearings allow low friction but require precise control of the fluid, which limits their use. The results provide practical guidelines for selecting guide elements and optimising the friction performance, durability, and efficiency of hydraulic systems. We found that the best solution from the points of view of design, friction, and economics is to use labyrinth seals as guiding elements for the fast reciprocal moving rods of hydraulic cylinders. Full article

(This article belongs to the Section Mechanical Engineering)

19 pages, 1249 KiB

Open AccessArticle

The Effect of Cut-Off Frequency on Signal Features When Filtering Equine sEMG Signal from Selected Extensor Muscles

by Małgorzata Domino, Marta Borowska, Elżbieta Stefanik, Natalia Domańska-Kruppa and Bernard Turek

Appl. Sci. 2025, 15(9), 4737; https://doi.org/10.3390/app15094737 (registering DOI) - 24 Apr 2025

Abstract

The use of surface electromyography (sEMG) in equine locomotion research has increased significantly due to the essential role of balanced, symmetrical, and efficient movement in riding. However, variations in sEMG signal processing for forelimb extensor muscles across studies have made cross-study comparisons challenging. [...] Read more.

The use of surface electromyography (sEMG) in equine locomotion research has increased significantly due to the essential role of balanced, symmetrical, and efficient movement in riding. However, variations in sEMG signal processing for forelimb extensor muscles across studies have made cross-study comparisons challenging. This study aims to compare the sEMG signal characteristics from carpal extensor muscles under different filtering methods: raw signal, low-pass filtering (10 Hz cut-off), and bandpass filtering (40–450 Hz cut-off and 7–200 Hz cut-off). sEMG signals were collected from four muscles of three horses during walking and trotting. The raw signals were normalized and filtered separately using a 4th-order Butterworth filter: low-pass 10 Hz, bandpass 40–450 Hz, or bandpass 7–200 Hz. For each filtered signal variant, eight activity bursts were annotated, and amplitude, root mean square (RMS), median frequency (MF), and signal-to-noise ratio (SNR) were extracted. Signal loss and residual signal were calculated to assess noise reduction and data retention. For m. extensor digitorum lateralis and m. extensor carpi ulnaris, bandpass filtering at 40–450 Hz resulted in the lowest signal loss and the highest amplitude, RMS, MF, and SNR after filtering. However, variations were observed for the other two carpal extensors. These findings support the hypotheses that the characteristics of myoelectric activity in equine carpal extensors vary depending on the filtering method applied and differ among individual muscles, thereby guiding future research on sEMG signal processing and, consequently, equine biomechanics. Since both noise and its reduction alter raw sEMG signals, potentially affecting data analysis, this study provides valuable insights for improving the reliability and reproducibility of equine biomechanics research across different sEMG studies. Full article

(This article belongs to the Special Issue Current Updates in Clinical Biomedical Signal Processing)

10 pages, 337 KiB

Open AccessArticle

Evaluation of Disassembling Process Inference Based on Positional Relations Matrix

by Kazuyuki Hanahara and Kaori Yamada

Appl. Sci. 2025, 15(9), 4736; https://doi.org/10.3390/app15094736 - 24 Apr 2025

Abstract

Disassembling is an important process in the maintenance, reparation, and disposal of mechanical as well as structural systems. More often than not, however, disassembling processes are not prepared in advance; we need to organize the disassembling process based on the obtained arrangement information [...] Read more.

Disassembling is an important process in the maintenance, reparation, and disposal of mechanical as well as structural systems. More often than not, however, disassembling processes are not prepared in advance; we need to organize the disassembling process based on the obtained arrangement information of the constituent parts of the system. In this study, we deal with a disassembling process inference based on the positional relations matrix. On the basis of the positional relations matrix, the geometrical constraints among the parts can be expressed in a general form. The developed disassembling process inference based on the matrix is considered to be practical. We have evaluated the practicality of the proposed disassembling process inference based on a number of disassembling problems which were generated by means of a problem-generation system based on random number generator. The obtained evaluation demonstrated that the proposed approach does not always result in the optimal disassembling process but provides a fairly appropriate disassembling process in general, and the required computational cost is considerably small. We concluded that the proposed disassembling process inference is practical enough. Full article

(This article belongs to the Special Issue ICEBA2024: Engineering, Physics, MEMS-Biosensors and Applications)

17 pages, 3239 KiB

Open AccessArticle

MSF-SLAM: Enhancing Dynamic Visual SLAM with Multi-Scale Feature Integration and Dynamic Object Filtering

by Yongjia Duan, Jing Luo and Xiong Zhou

Appl. Sci. 2025, 15(9), 4735; https://doi.org/10.3390/app15094735 - 24 Apr 2025

Abstract

Conventional visual SLAM systems often struggle with degraded pose estimation accuracy in dynamic environments due to the interference of moving objects and unstable feature tracking. To address this critical challenge, we present a groundbreaking enhancement to visual SLAM by introducing an innovative architecture [...] Read more.

Conventional visual SLAM systems often struggle with degraded pose estimation accuracy in dynamic environments due to the interference of moving objects and unstable feature tracking. To address this critical challenge, we present a groundbreaking enhancement to visual SLAM by introducing an innovative architecture that integrates advanced feature extraction and dynamic object filtering mechanisms. At the core of our approach lies a novel Multi-Scale Feature Consolidation (MSFConv) module, which we have developed to significantly boost the feature extraction capabilities of the YOLOv8 network. This module enables superior multi-scale feature representation, leading to significant improvements in object detection accuracy and robustness. Furthermore, we have developed a Dynamic Object Filtering Framework (DOFF) that seamlessly integrates with the ORB-SLAM3 architecture. By leveraging the Lucas-Kanade (LK) optical flow method, DOFF effectively distinguishes and removes dynamic feature points while preserving the integrity of static features. This ensures high-precision pose estimation in highly dynamic environments. Comprehensive experiments on the TUM RGB-D dataset validate the exceptional performance of our proposed method, demonstrating 93.34% and 94.43% improvements in pose estimation accuracy over the baseline ORB-SLAM3 in challenging dynamic sequences. These substantial improvements are achieved through the synergistic combination of enhanced feature extraction and precise dynamic object filtering. Our work represents a significant leap forward in visual SLAM technology, offering a robust solution to the long-standing problem of dynamic environment handling. The proposed innovations not only advance the state-of-the-art in SLAM research but also pave the way for more reliable real-world applications in robotics and autonomous systems. Full article

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23 pages, 15421 KiB

Open AccessArticle

Evaluation of a Microporous Acoustic Liner Using Advanced Noise Control Fan Engine

by Bharath Kenchappa and Kunigal Shivakumar

Appl. Sci. 2025, 15(9), 4734; https://doi.org/10.3390/app15094734 - 24 Apr 2025

Abstract

A novel microstructurally controlled graded micro-porous material was developed and experimentally validated for noise reduction through a normal incidence impedance test. Extensive parametric studies were conducted to understand the influence of test specimen size, particle size, porosity, pore size, and its distribution on [...] Read more.

A novel microstructurally controlled graded micro-porous material was developed and experimentally validated for noise reduction through a normal incidence impedance test. Extensive parametric studies were conducted to understand the influence of test specimen size, particle size, porosity, pore size, and its distribution on acoustic absorption and transmission loss. Based on previous research, this study evaluates the application of graded microporous material as an acoustic liner technology for aircraft turbomachine engines. The liner was fabricated in eight 45° segments, assembled in an aluminum test rig, and tested on NASA Glenn Research Center’s Advanced Noise Control Fan (ANCF) low-speed test bed for tonal and broadband noise. The study demonstrates that microstructurally controlled graded microporous material is very effective in dissipating sound energy with reductions in tonal sound pressure level (SPL) of 2 to 13 dB at blade passing frequencies and reductions in broadband SPL of about 2 to 3 dB for the shaft order greater than 40. While the proposed two-layer graded liner model successfully validated the concept, additional design optimization is needed to enhance performance further. This work highlights the potential of graded microporous material as next-generation acoustic liners, offering lightweight, efficient, and scalable aircraft engine noise reduction solutions. Full article

(This article belongs to the Special Issue New Advances in Acoustic Materials: Design and Application)

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20 pages, 1916 KiB

Open AccessReview

Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete

by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu and Zhenhua Wei

Appl. Sci. 2025, 15(9), 4733; https://doi.org/10.3390/app15094733 - 24 Apr 2025

Abstract

Nano-modified concrete has attracted wide attention due to its improved mechanical properties. Among them, compressive strength is the most critical indicator. However, testing nano-concrete is costly and complex because it requires control over many factors, such as nanoparticle content and dispersion. Machine learning [...] Read more.

Nano-modified concrete has attracted wide attention due to its improved mechanical properties. Among them, compressive strength is the most critical indicator. However, testing nano-concrete is costly and complex because it requires control over many factors, such as nanoparticle content and dispersion. Machine learning offers a data-driven way to predict compressive strength more efficiently. It reduces trial-and-error efforts and supports mix design optimization. Currently, machine learning is more adept at handling complicated datasets than experimental and traditional statistical models. In this article, the development of machine learning research in predicting the strength of concrete enhanced by nanoparticles is reviewed. First, we systematically outline a three-phase ML framework encompassing data curation, model development, and validation protocols; next, popular algorithms and their uses in predicting the strength of nano-modified concrete are evaluated, such as Artificial Neural Networks, K-Nearest Neighbor, Random Forest, etc. Ultimately, the article offers a forward-looking perspective on how future machine learning advancements can foster and accelerate the development of nano-modified concrete. Full article

(This article belongs to the Special Issue Research on Properties of Novel Building Materials)

10 pages, 2833 KiB

Open AccessCommunication

Crust and Upper Mantle Structure of Mars Determined from Surface Wave Analysis

by Víctor Corchete

Appl. Sci. 2025, 15(9), 4732; https://doi.org/10.3390/app15094732 - 24 Apr 2025

Abstract

The crust and upper mantle structure of Mars is determined in the depth range of 0 to 100 km, by means of dispersion analysis and its inversion, which is performed for the surface waves present in the traces of the seismic event: S1094b. [...] Read more.

The crust and upper mantle structure of Mars is determined in the depth range of 0 to 100 km, by means of dispersion analysis and its inversion, which is performed for the surface waves present in the traces of the seismic event: S1094b. From these traces, Love and Rayleigh waves are measured in the period range of 4 to 40 s. This dispersion was calculated with a combination of digital filtering techniques, and later was inverted to obtain both models: isotropic (from 0 to 100 km depth) and anisotropic (from 0 to 15 km depth), which were calculated considering the hypothesis of the surface wave propagation in slightly anisotropic media. The seismic anisotropy determined from 0 to 5 km depth (7% of S-velocity variation and ξ ~ 1.1) could be associated with the presence of sediments or lava-flow layering, and wide damage zones surrounding the long-term fault networks. For greater depths, the observed anisotropy (17% of S-velocity variation and ξ ~ 1.4) could be due to the possible presence of volcanic materials and/or the layering of lava flows. Another cause for this anisotropy could be the presence of layered intrusions due to a single or multiple impacts, which could cause internal layering within the crust. Finally, the Moho depth is determined at 50 km as a gradual transition from crust to mantle S-velocities, through an intermediate value (3.90 km/s) determined from 50 to 60 km-depth. Full article

(This article belongs to the Special Issue Advances in Structural Geology)

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15 pages, 620 KiB

Open AccessArticle

XClinic Sensors: Validating Accuracy in Measuring Range of Motion Across Trauma Conditions

by Ilaria Ruotolo, Giovanni Sellitto, Giovanni Galeoto, Donatella Valente, Emanuele Amadio, Anna Berardi, Francescaroberta Panuccio, Raffaele La Russa, Umberto Guidoni, Gianpietro Volonnino and Paola Frati

Appl. Sci. 2025, 15(9), 4731; https://doi.org/10.3390/app15094731 - 24 Apr 2025

Abstract

Background: Accidents and injuries are major causes of chronic disability, leading to a loss of healthy years. Accurate assessment is essential for planning personalized rehabilitation programs. In recent years, wearable sensors have been introduced into research for motion analysis. This study aimed to [...] Read more.

Background: Accidents and injuries are major causes of chronic disability, leading to a loss of healthy years. Accurate assessment is essential for planning personalized rehabilitation programs. In recent years, wearable sensors have been introduced into research for motion analysis. This study aimed to validate the Xclinic wearable sensors for ROM assessment in patients with trauma. Methods: Participants were recruited from the Sapienza University of Rome (September 2023–November 2024) after road accident trauma. The active ROM of the hip, knee, and ankle was assessed bilaterally based on the injury. The SF-36 and other specific tools were also administered. Construct validity was tested using Pearson’s correlation coefficient. Results: A total of 44 participants (mean age 42.7 ± 17.3 years, 69% male) were included. Item-by-item analysis revealed significant correlations, with notable findings related to other outcome measures. Conclusions: The correlation between joint restrictions, functional impairment, and psychosocial factors highlights the need to integrate physical and psychological care into rehabilitation. Further research is needed to refine assessment tools to improve patients’ quality of life. Full article

(This article belongs to the Special Issue Digital Innovations in Healthcare)

21 pages, 14298 KiB

Open AccessArticle

Research on Overburdened Rock Structures and Support Resistance of Shallow Buried Large Mining Heights Based on Sheet Gangs

by Pei Zhang, Yang Chen, Yibo Wei, Zhuo Li and Liqiang Dong

Appl. Sci. 2025, 15(9), 4730; https://doi.org/10.3390/app15094730 - 24 Apr 2025

Abstract

In the mining of shallow coal seams, the increase in mining height will lead to a sharp increase in the probability and degree of coal wall spalling. Rib spalling will affect the normal production of coal mines and may also threaten the safety [...] Read more.

In the mining of shallow coal seams, the increase in mining height will lead to a sharp increase in the probability and degree of coal wall spalling. Rib spalling will affect the normal production of coal mines and may also threaten the safety of miners. Under the state of coal wall ganging in large mining height working faces, determining the working face’s support resistance is a key engineering problem that involves many factors, such as bracket design, the mechanical behavior of the roof rock layer, coal wall stability, and so on. In this paper, (1) the relationship between coal wall pressure and working face support resistance is analyzed by constructing a mechanical model of roof control in the large height mining field, (2) and four roof structure models are established based on the single and double key layer structures of step rock beams in shallow buried coal beds. (3) The calculation methods of working face support resistance after coal wall sheet ganging under the four structural models are deduced. Determining the working face’s support resistance is the key to solving the problem of coal wall ganging in large height working faces, which has a significant impact on the design of bracing, the mechanical behavior of the roof rock layer, and coal wall stability. Full article

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24 pages, 775 KiB

Open AccessArticle

Artificial Intelligence and Employment: A Delicate Balance Between Progress and Quality in China

by Sonia Chien-I Chen, Chuanming Zhang and Chung-Ming Own

Appl. Sci. 2025, 15(9), 4729; https://doi.org/10.3390/app15094729 - 24 Apr 2025

Abstract

The quality of employment is significantly impacted by the transformation of global labor markets resulting from artificial intelligence (AI). This study investigates the impact of AI on employment quality in China, with an emphasis on regional disparities between prefecture-level cities. Using panel data [...] Read more.

The quality of employment is significantly impacted by the transformation of global labor markets resulting from artificial intelligence (AI). This study investigates the impact of AI on employment quality in China, with an emphasis on regional disparities between prefecture-level cities. Using panel data and a two-way fixed-effects model, we investigate how AI adoption affects employment outcomes, taking into account industrial structure and economic development. The findings show that while AI adoption increases productivity, it has varying implications on employment quality due to geographical differences. Relevant government rules and focused policies are critical for reducing negative impacts and encouraging long-term employment. This research makes concrete recommendations for policymakers and contributes to the worldwide conversation about AI and labor market developments. Full article

25 pages, 7540 KiB

Open AccessArticle

A Novel Temperature Reconstruction Method for Acoustic Pyrometry Under Strong Temperature Gradients and Limited Measurement Points

by Jingkao Tan, Lehang Chen, Na Li, Qulan Zhou, Zhongquan Gao and Jie Zhou

Appl. Sci. 2025, 15(9), 4728; https://doi.org/10.3390/app15094728 - 24 Apr 2025

Abstract

Acoustic pyrometry (AP) is a promising methodology for high-quality temperature field reconstruction, which is widely used in the monitoring of atmosphere, room, and furnace. However, most of the existing acoustic reconstruction algorithms are developed and utilized in relatively uniform temperature distributions. Furthermore, their [...] Read more.

Acoustic pyrometry (AP) is a promising methodology for high-quality temperature field reconstruction, which is widely used in the monitoring of atmosphere, room, and furnace. However, most of the existing acoustic reconstruction algorithms are developed and utilized in relatively uniform temperature distributions. Furthermore, their ability of tracking hotspots are rarely discussed. This paper first proposed the coefficient of heating effect (C_HE) to quantitatively assess the intrinsic characteristics of the reconstructed temperature field. Aiming to accurately reconstruct the temperature fields under strong gradients and limited measurement points, this paper presents a novel temperature reconstruction method based on the adaptive hybrid kernel (AHK) and the adaptive grid evolution strategy (AGES). The proposed AGES-AHK method implements adaptive hybrid kernel adjustments on AGES-optimized nonuniform grids, achieving significant improvements in both reconstruction fidelity and hotspot characterization. The reconstruction results show that at C_HE levels below 15, the AGES-AHK method achieved the normalized root mean square error (NRMSE) of less than 3.7%, the hotspot position deviation D_h of less than 2.3% and the hotspot temperature error E_h of less than 15%, improving reconstruction accuracy by more than 33% compared to the basis method. Qualitative and quantitative analyses demonstrate the AGES-AHK method’s superior performance in challenging conditions. Full article

19 pages, 964 KiB

Open AccessArticle

High-Pressure Processing of Reduced Salt Pangasius Catfish (Pangasianodon hypophthalmus) Minced Muscle: The Effects on Selected Quality Properties of Its Gels

by Binh Q. Truong, Roman Buckow, Kha N. H. Nguyen, Linh T. Nguyen, Tuan N. A. Huynh and Van Chuyen Hoang

Appl. Sci. 2025, 15(9), 4727; https://doi.org/10.3390/app15094727 - 24 Apr 2025

Abstract

This study investigated the effects of high-pressure processing (HPP) on selected physicochemical properties of pangasius gels at reduced salt concentrations. Minced pangasius muscle was treated at different HPP conditions (300–500 MPa/10 °C/10 min) with 1% or 2% added salt, then cooking (90 °C/30 [...] Read more.

This study investigated the effects of high-pressure processing (HPP) on selected physicochemical properties of pangasius gels at reduced salt concentrations. Minced pangasius muscle was treated at different HPP conditions (300–500 MPa/10 °C/10 min) with 1% or 2% added salt, then cooking (90 °C/30 min) and compared to heat-induced gels (HIGs) with 2% added salt and cooking (90 °C/30 min). The results showed that HPP significantly improved the texture, whiteness, and water-holding capacity of gels added salt 2% as compared to HIGs. At a reduced salt concentration of 1%, the gel texture, whiteness, and water-holding capacity of pangasius gels are similar to HIGs. SDS-PAGE showed a reduction in myosin band intensity of both SDS-soluble and sarcoplasmic proteins with pressure treatment. Sarcoplasmic actin protein was undetectable in all treatments. Fourier transform infrared spectroscopy (FTIR) analysis revealed higher α-helix content in HPP-treated samples, while SEM images confirmed the formation of a denser, more uniform gel network, particularly at 2% salt. These findings suggested that HPP improved the quality of gel with 2% salt added, while producing gels with similar quality compared to HIGs at reduced salt concentration. Full article

(This article belongs to the Special Issue Innovative Technologies for Food Preservation and Processing)

16 pages, 4787 KiB

Open AccessArticle

Enhancement Processing of High-Resolution Spaceborne SAR Wake Based on Equivalent Multi-Channel Technology

by Lei Yu, Yuting Liu, Xiaofei Xi and Pengbo Wang

Appl. Sci. 2025, 15(9), 4726; https://doi.org/10.3390/app15094726 - 24 Apr 2025

Abstract

Ship wake detection plays a crucial role in compensating for target detection failures caused by defocusing or displacement in SAR images due to vessel motion. This study addresses the challenge of enhancing wake features in high-resolution spaceborne SAR by exploiting the distinct linear [...] Read more.

Ship wake detection plays a crucial role in compensating for target detection failures caused by defocusing or displacement in SAR images due to vessel motion. This study addresses the challenge of enhancing wake features in high-resolution spaceborne SAR by exploiting the distinct linear characteristics of wake echoes and the random motion of ocean background clutter. We propose a novel method based on sub-aperture image sequences, which integrates equivalent multi-channel technology to fuse wake and wave information. This approach significantly improves the quality of raw wake images by enhancing linear features and suppressing background noise. The Radon transform is then applied to evaluate the enhanced wake images. Through a combination of principle analysis, enhancement processing, and both subjective and objective evaluations, we conducted experiments using real data from the AS01 SAR satellite and compared our method with traditional wake enhancement techniques. The results demonstrate that our method achieves significant wake enhancement and improves the recognition of detail wake features. Full article

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19 pages, 5522 KiB

Open AccessArticle

Performance of Fine-Tuning Techniques for Multilabel Classification of Surface Defects in Reinforced Concrete Bridges

by Benyamin Pooraskarparast, Son N. Dang, Vikram Pakrashi and José C. Matos

Appl. Sci. 2025, 15(9), 4725; https://doi.org/10.3390/app15094725 - 24 Apr 2025

Abstract

Machine learning models often face challenges in bridge inspections, especially in handling complex surface features and overlapping defects that make accurate classification difficult. These challenges are common for image-based monitoring, which has become increasingly popular for inspecting and assessing the structural condition of [...] Read more.

Machine learning models often face challenges in bridge inspections, especially in handling complex surface features and overlapping defects that make accurate classification difficult. These challenges are common for image-based monitoring, which has become increasingly popular for inspecting and assessing the structural condition of reinforced concrete bridges with automated possibilities. Despite advances in defect detection using convolutional neural networks (CNNs), although challenges such as overlapping defects, complex surface textures, and data imbalance remain difficult, full fine-tuning of deep learning models helps them better adapt to these conditions by updating all the layers for domain-specific learning. The aim of this study is to demonstrate how effective the fine-tuning of several deep learning architectures for bridge damage classification allows for robust performance and the best utilization value of the methods. Six CNN architectures, ResNet-18, ResNet-50, ResNet-101, ResNeXt-50, ResNeXt-101 and EfficientNet-B3, were fine-tuned using the CODEBRIM dataset. Their performance was evaluated using Precision, Recall, F1 Score, Balanced Accuracy and AUC-ROC metrics to ensure a robust evaluation framework. This indicates that the EfficientNet-B3 and ResNeXt-101 models outperformed the other models and achieved the highest classification accuracy in all the error categories. EfficientNet-B3 showed the best-balanced Precision (0.935) and perfect Recall (1.000) in background classification, indicating its ability to distinguish defect-free areas from structural damage. These results highlight the potential of these models to improve automated bridge inspection systems and thus increase accuracy and efficiency in real-world applications, as well as provide guidance for the selection of methods based on whether accuracy or overall consistency is more important for a specific application. Full article

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24 pages, 4382 KiB

Open AccessArticle

Research on Pedestrian Avoidance Behavior for School Section Based on Improved BP Neural Network and XGboost Algorithm

by Guiliang Lu and Mingwei Liu

Appl. Sci. 2025, 15(9), 4724; https://doi.org/10.3390/app15094724 - 24 Apr 2025

Abstract

As society evolves and technology advances, increasing transportation demands have heightened safety risks near schools and on mixed-traffic roads. While traditional studies on pedestrian evasive behavior have mainly focused on general traffic environments and used image-based features to predict trajectories, few have specifically [...] Read more.

As society evolves and technology advances, increasing transportation demands have heightened safety risks near schools and on mixed-traffic roads. While traditional studies on pedestrian evasive behavior have mainly focused on general traffic environments and used image-based features to predict trajectories, few have specifically addressed the behavior of pedestrians in school zones. This study fills that gap by analyzing pedestrian evasive actions near school zones in Pudong New Area, Shanghai, using real-time video data. In contrast to previous approaches, our research leverages key traffic variables—such as vehicle speed, pedestrian proximity, and traffic density—to predict whether pedestrians will engage in evasive behavior. We independently apply three predictive models: the traditional BP (Backpropagation) neural network, an improved GA-BP(genetic algorithm–backpropagation) neural network, and the XGBoost (Extreme Gradient Boosting) ensemble learning method. Our findings show that the improved GA-BP model outperforms the others, achieving an accuracy of over 79%. Furthermore, this study identifies crucial traffic factors influencing pedestrian behavior, offering valuable insights for road safety decision-making in school zones. This research demonstrates the potential of advanced predictive models for forecasting pedestrian evasive behavior. It enhances safety in school zones by highlighting the key traffic variables affecting pedestrians. Full article

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28 pages, 3332 KiB

Open AccessArticle

Classifying and Characterizing Fandom Activities: A Focus on Superfans’ Posting and Commenting Behaviors in a Digital Fandom Community

by Yeoreum Lee and Sangkeun Park

Appl. Sci. 2025, 15(9), 4723; https://doi.org/10.3390/app15094723 - 24 Apr 2025

Abstract

As digital fandom communities expand and diversify, user engagement patterns increasingly shape the social and emotional fabric of online platforms. In the era of Industry 4.0, data-driven approaches are transforming how online communities understand and optimize user engagement. In this study, we examine [...] Read more.

As digital fandom communities expand and diversify, user engagement patterns increasingly shape the social and emotional fabric of online platforms. In the era of Industry 4.0, data-driven approaches are transforming how online communities understand and optimize user engagement. In this study, we examine how different forms of activity, specifically posting and commenting, characterize fandom engagement on Weverse, a global fan community platform. By applying a clustering approach to large-scale user data, we identify distinct subsets of heavy users, separating those who focus on creating posts (post-heavy users) from those who concentrate on leaving comments (comment-heavy users). A subsequent linguistic analysis using the Linguistic Inquiry and Word Count (LIWC) tool revealed that post-heavy users typically employ a structured, goal-oriented style with collective pronouns and formal tones, whereas comment-heavy users exhibit more spontaneous, emotionally rich expressions enhanced by personalized fandom-specific slang and extensive emoji use. Building on these findings, we propose design implications such as pinning community-driven content, offering contextual translations for fandom-specific slang, and introducing reaction matrices that address the unique needs of each group. Taken together, our results underscore the value of distinguishing multiple dimensions of engagement in digital fandoms, providing a foundation for more nuanced platform features that can enhance positive user experience, social cohesion, and sustained community growth. Full article

(This article belongs to the Special Issue Human-Computer Interaction in Smart Factory and Industry 4.0)

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33 pages, 2273 KiB

Open AccessArticle

Research on the Acoustic Attenuation Performance and Optimization of Split-Stream Rushing Exhaust Mufflers in the Presence of Acoustic–Structure Coupling Effects

by Peiyan Huang, Pei Wu, He Su, Jing Xue, Haijun Zhang, Yongan Zhang and Yuchen Guo

Appl. Sci. 2025, 15(9), 4722; https://doi.org/10.3390/app15094722 - 24 Apr 2025

Abstract

The split-stream rushing exhaust muffler is a design that improves acoustic attenuation performance and reduces exhaust resistance by lowering the internal airflow velocity. In the past, researchers often applied a rigid treatment to the muffler wall when studying this new muffler and neglected [...] Read more.

The split-stream rushing exhaust muffler is a design that improves acoustic attenuation performance and reduces exhaust resistance by lowering the internal airflow velocity. In the past, researchers often applied a rigid treatment to the muffler wall when studying this new muffler and neglected the acoustic–structure coupling effect. As a result, differences existed between the calculated results and practical situations. This research employed COMSOL 6.2 software to perform finite element calculations on the acoustic performance of this muffler under acoustic–structural coupling. It analyzed the causes of transmission loss discrepancies with and without the acoustic–structural coupling effect, and the findings were validated experimentally. Building upon this foundation, further optimization and refinement of the muffler’s structural parameters were conducted. The results demonstrated that the transmission loss curve under the acoustic–structure coupling effect followed a similar trend to that observed without the acoustic–structure coupling effect. However, the transmission loss curve changed owing to the influence of the acoustic–structure coupling effect on sound pressure, which resulted in a 6.24% decrease in the average transmission loss. The transmission loss curve accounting for the acoustic–structure coupling effect aligned more closely with the test results than the curve that did not account for the coupling effect. Furthermore, this study delved into the influences of the wall thickness, inner tube diameter, and inner tube length on the muffler’s acoustic performance under acoustic–structural coupling. Subsequently, the muffler was optimized based on the findings. Full article

26 pages, 2336 KiB

Open AccessArticle

Normalized Residual Displacements for Single-Degree-of-Freedom Systems Subjected to Mainshock–Aftershock Sequences

by Zhibin Feng, Jiying Wang, Hua Huang and Jinxin Gong

Appl. Sci. 2025, 15(9), 4721; https://doi.org/10.3390/app15094721 - 24 Apr 2025

Abstract

Post-earthquake structural rehabilitation faces critical challenges from aftershock-induced cumulative damage, particularly through residual displacement accumulation that compromises structural realignment feasibility. While residual displacements serve as pivotal indicators for repair-or-replace decisions, the amplification effects of aftershocks on such displacements remain systematically underexplored. This study [...] Read more.

Post-earthquake structural rehabilitation faces critical challenges from aftershock-induced cumulative damage, particularly through residual displacement accumulation that compromises structural realignment feasibility. While residual displacements serve as pivotal indicators for repair-or-replace decisions, the amplification effects of aftershocks on such displacements remain systematically underexplored. This study investigates residual displacement demands of bilinear single-degree-of-freedom (SDOF) systems subjected to mainshock–aftershock sequences. A novel metric is proposed, defined as the maximum residual displacement considering both isolated mainshock and full sequence scenarios, normalized against peak inelastic displacements (termed residual displacement ratio) for predictive analysis. The influence of sequence characteristics (duration, frequency content, aftershock intensity) and structural properties (post-yield stiffness ratio, displacement ductility, natural period) on residual displacement ratios is evaluated. Statistical analysis reveals that aftershocks amplify mainshock-induced residual displacements in the statistical mean sense, with an observed maximum increase reaching up to 72%. The mainshock with stronger aftershocks tends to result in larger residual displacement ratios. A constant-ductility residual displacement ratio response spectrum is finally developed for the repairability assessment of structures against mainshock–aftershock sequences in terms of residual displacements. Full article

21 pages, 3991 KiB

Open AccessArticle

Synergistic Evolution and Spatial-Temporal Differences in Green Technological Innovation and Carbon Emission Reduction in the Construction Industry from the Perspective of New Productive Forces

by Zihao Niu and Qingjie Xie

Appl. Sci. 2025, 15(9), 4720; https://doi.org/10.3390/app15094720 - 24 Apr 2025

Abstract

Green technological innovation, as a critical emerging resource element, is instrumental in advancing sustainable and high-quality development of the construction sector. However, despite extensive research, the synergistic mechanism linking regional green technology innovation (RGTI) and carbon reduction in the construction industry (CRCI) remains [...] Read more.

Green technological innovation, as a critical emerging resource element, is instrumental in advancing sustainable and high-quality development of the construction sector. However, despite extensive research, the synergistic mechanism linking regional green technology innovation (RGTI) and carbon reduction in the construction industry (CRCI) remains theoretically underexplored, especially through the lens of new quality productivity (NQP). Based on dynamic panel data from 30 Chinese provinces spanning 2013–2021, this study employed multiple analytical approaches, including econometric models, coupling coordination models, kernel density estimation, and Dagum Gini coefficient decomposition, to systematically examine their interactive relationships and spatiotemporal evolution characteristics. The findings reveal that RGTI directly reduces the carbon emissions intensity of the construction industry and yields a “dual-driving effect” through the mediating role of NQP. Significant coupling coordination effects were identified among RGTI, NQP, and CRCI. Further investigation showed that their synergistic evolution manifests distinct “regional lock-in effects” and “polarization effects”, with eastern regions achieving positive interactions, while central and western regions remain constrained by developmental limitations. Although overall disparities narrowed during the study period, inter-regional differences persisted as the dominant factor. This study extends the research perspective on construction industry carbon reduction, contributing to new quality productivity formation and inter-regional emission reduction coordination. Full article

(This article belongs to the Section Civil Engineering)

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15 pages, 1298 KiB

Open AccessReview

Medical Applications of Picosecond Lasers for Removal of Non-Tattoo Skin Lesions—A Comprehensive Review

by Anna Kroma-Szal, Mariola Pawlaczyk, Maria Urbańska, Julia Cieślawska, Daria Sobkowska, Iwona Pordąb and Justyna Gornowicz-Porowska

Appl. Sci. 2025, 15(9), 4719; https://doi.org/10.3390/app15094719 - 24 Apr 2025

Abstract

Picosecond lasers are gaining increasing popularity in dermatology and aesthetic medicine due to their favorable safety profile and a wide range of therapeutic applications. While originally employed primarily for tattoo removal, their versatility has extended their use to the treatment of various aesthetic [...] Read more.

Picosecond lasers are gaining increasing popularity in dermatology and aesthetic medicine due to their favorable safety profile and a wide range of therapeutic applications. While originally employed primarily for tattoo removal, their versatility has extended their use to the treatment of various aesthetic skin conditions, including hyperpigmentation, acne scars, stretch marks, and signs of photoaging. Owing to their ultra-short pulse duration, picosecond lasers effectively target pigment particles and stimulate dermal remodeling, offering patients a safe and effective solution to improve the appearance of their skin. The introduction of the picosecond laser into clinical dermatology practice marks a notable advancement in addressing a broad spectrum of skin problems. Full article

(This article belongs to the Special Issue Cosmetics and Advanced Equipment Applied in Cosmetology and Aesthetic Medicine)

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Appl. Sci., Volume 15, Issue 9 (May-1 2025) – 154 articles

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