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Zirconium-Containing Metal–Organic Frameworks (MOFs) as Catalysts for Biomass Conversion
Implementing Deep Neural Networks on ARM-Based Microcontrollers: Application for Ventricular Fibrillation Detection
Impact of Cross-Linking-Monomer Characteristics on Pore-Filling-Membrane Performance and Durability in Anion-Exchange Water Electrolysis
Innovative Antibacterial Polymer Coatings
Exploring Adsorption Performance of Functionalized Mesoporous Silicas with a Different Pore Structure as Strong Cation-Exchange Sorbents for Solid-Phase Extraction of Atropine and Scopolamine

Journal Description

Applied Sciences

Applied Sciences is an international, peer-reviewed, open access journal on all aspects of applied natural sciences published semimonthly online by MDPI.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, Inspec, CAPlus / SciFinder, and other databases.
Journal Rank: JCR - Q1 (Engineering, Multidisciplinary) / CiteScore - Q1 (General Engineering )
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18.4 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the second half of 2024).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Testimonials: See what our authors say about Applied Sciences.
Companion journals for Applied Sciences include: Applied Nano, AppliedChem, Applied Biosciences, Virtual Worlds, Spectroscopy Journal, JETA and AI in Medicine.

Impact Factor: 2.5 (2023); 5-Year Impact Factor: 2.7 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2076-3417

Latest Articles

16 pages, 3162 KiB

Open AccessArticle

A Study of the Influence of Sodium Alginate Molecular Weight and Its Crosslinking on the Properties of Potato Peel Waste-Based Films

by Mohsen Sadeghi-Shapourabadi, Mathieu Robert and Said Elkoun

Appl. Sci. 2025, 15(12), 6385; https://doi.org/10.3390/app15126385 (registering DOI) - 6 Jun 2025

This study develops a sustainable biopolymer film derived from potato peel waste (PW), enhanced with low- and high-viscosity sodium alginate (SA) through a solution casting method. The effect of calcium chloride crosslinking on the PW/SA composites was also evaluated. Scanning electron microscopy (SEM) [...] Read more.

This study develops a sustainable biopolymer film derived from potato peel waste (PW), enhanced with low- and high-viscosity sodium alginate (SA) through a solution casting method. The effect of calcium chloride crosslinking on the PW/SA composites was also evaluated. Scanning electron microscopy (SEM) analysis revealed that SA incorporation improved the film’s cohesion and uniformity, with both low- and high-viscosity SA showing nearly similar effects. Both the addition of SA and crosslinking led to enhanced tensile strength, as well as improved moisture barrier properties, by lowering the water vapor permeability (WVP) factor. The inclusion of high-viscosity SA (hvSA) resulted in superior mechanical and moisture barrier properties compared to the low-viscosity SA (lvSA), achieving a tensile strength of 5.34 MPa, with a 68% improvement compared to the pure PW film. The WVP analysis showed that hvSA had a superior impact, leading to a 32% reduction in WVP compared to the pure film. Crosslinking further boosted the tensile strength and moisture barrier properties. The crosslinked hvSA/PW composite shows the highest tensile strength among all samples, measuring 6.47 MPa, which accounts for a 104% enhancement compared to the pure film. It also led to a 34% reduction in WVP, reaching a value of 1.58 × 10⁻¹² g/(Pa·cm·s). The findings demonstrate that PW/SA composites, especially the crosslinked hvSA/PW, offer the highest mechanical and barrier properties, making them suitable for biodegradable packaging and biomedical applications. Full article

(This article belongs to the Special Issue Design, Characterization, and Applications of Biodegradable Polymers)

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13 pages, 2253 KiB

Open AccessArticle

Organic Acid-Assisted Hydrothermal Leaching of Silver from End-of-Life Photovoltaic Panels

by Eleni Kastanaki, Rafaela Athanasiadou, Anastasia Katsifou and Apostolos Giannis

Appl. Sci. 2025, 15(12), 6383; https://doi.org/10.3390/app15126383 (registering DOI) - 6 Jun 2025

The aim of this study was the hydrothermal leaching of silver from waste monocrystalline silicon (m-Si) and polycrystalline silicon (p-Si) photovoltaic panel (PV) cells using organic acids, namely oxalic acid (OA) and citric acid (CA). Before leaching, two different pretreatment procedures were applied. [...] Read more.

The aim of this study was the hydrothermal leaching of silver from waste monocrystalline silicon (m-Si) and polycrystalline silicon (p-Si) photovoltaic panel (PV) cells using organic acids, namely oxalic acid (OA) and citric acid (CA). Before leaching, two different pretreatment procedures were applied. First, the fluoropolymer backsheet was manually removed from the panel pieces and, then, the samples were subjected to high-temperature heating for the thermal degradation of the ethylene vinyl acetate (EVA) polymer. When removal by hand was not feasible, the second pretreatment procedure was followed by toluene immersion to remove the EVA and backsheet and separate the cells, glass, and films. After pretreatment, 4 M HCl leaching was applied to remove the aluminum layer from the cells. The remaining cells were subjected to hydrothermal leaching with organic acids to extract the silver. Several hydrothermal parameters were investigated, such as acid concentration (1-1.5-2 M), processing time (60-105-150 min), and temperature (150-180-210 °C), while the liquid-to-solid (L/S) ratio was fixed at 30 mL: 1 g, based on preliminary tests. Response surface methodology (RSM) was applied to optimize the hydrothermal leaching parameters. The optimized parameters were 210 °C, 95 min, 2 M CA or 210 °C, 60 min, 1 M OA. OA was more effective in Ag leaching than CA. The results were compared to HNO₃ leaching. The green leaching of silver from end-of-life PV panels with organic acids is an environmentally beneficial route. Full article

(This article belongs to the Special Issue Remanufacturing, Reuse and Recycling Pathways for E-Waste and Used Batteries)

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20 pages, 2853 KiB

Open AccessArticle

Three-Dimensional Pedalling Kinematics Analysis Through the Development of a New Marker Protocol Specific to Cycling

by Ezequiel Martín-Sosa, Elena Soler-Vizán, Juana Mayo and Joaquín Ojeda

Appl. Sci. 2025, 15(12), 6382; https://doi.org/10.3390/app15126382 - 6 Jun 2025

This study aims to develop and evaluate a cycling-specific marker protocol that minimises the number of markers while accounting for the unique biomechanics of cycling. Although movements in the frontal and transverse planes during cycling are limited, they are clinically relevant due to [...] Read more.

This study aims to develop and evaluate a cycling-specific marker protocol that minimises the number of markers while accounting for the unique biomechanics of cycling. Although movements in the frontal and transverse planes during cycling are limited, they are clinically relevant due to their association with overuse injuries. Existing gait-based marker protocols often fail to consider cycling-specific factors such as posture, range of motion, marker occlusion, and muscle-induced artifacts. The proposed protocol (PP) uses 15 physical and 8 virtual markers. In the absence of a gold standard for 3D pedalling kinematics, the PP was evaluated by comparing it with established gait analysis protocols. The protocol demonstrated high correlation in gait (CCC > 0.98 for hip and knee in the sagittal plane), low intra-subject variability (CV < 15% for hip, knee, and ankle), and high repeatability. During pedalling, position, velocity, and acceleration were measured in all three spatial directions. Notably, angular velocity and linear acceleration showed significant components outside the sagittal plane, particularly for angular velocity. These findings highlight the importance of considering 3D motion when estimating forces, joint moments, and joint-specific powers in cycling biomechanics. Full article

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13 pages, 532 KiB

Open AccessArticle

Effects of Algae-Based Supplementation on Metabolic, Oxidative, and Inflammatory Markers in Physically Active Adults: A Pilot Randomized Controlled Trial

by Maria Martínez-Olcina, Manuel Vicente-Martínez, Belén Leyva-Vela, Lucia Gonzálvez-Alvarado, Nuria Asencio-Mas, Izan Rodríguez-López, Yolanda Nadal-Nicolás, Bernardo José Cuestas-Calero, Marcelo Peñaranda-Moraga, Guillermo Cortés-Roco, Rodrigo Yáñez-Sepúlveda and Alejandro Martínez Rodríguez

Appl. Sci. 2025, 15(12), 6381; https://doi.org/10.3390/app15126381 - 6 Jun 2025

Algae-based supplements are gaining attention for their potential metabolic, antioxidant, and anti-inflammatory properties in sports nutrition. Methods: A 30-day pilot randomized controlled trial was conducted in 70 healthy male athletes (mean age 25.4 ± 4.9 years) from competitive soccer and handball teams. Participants [...] Read more.

Algae-based supplements are gaining attention for their potential metabolic, antioxidant, and anti-inflammatory properties in sports nutrition. Methods: A 30-day pilot randomized controlled trial was conducted in 70 healthy male athletes (mean age 25.4 ± 4.9 years) from competitive soccer and handball teams. Participants were randomly assigned to a supplementation group (6 g/day of Ulva-derived algae powder) or a control group. Both groups followed identical training routines and adhered to standardized nutritional recommendations, including macronutrient distribution and permitted supplements (e.g., isotonic drinks, protein shakes). Biochemical markers analyzed at baseline and post-intervention included HbA1c, lipid profile, malondialdehyde (MDA), catalase, myeloperoxidase (MPO), erythrocyte sedimentation rate (ESR), and cortisol. Genetic polymorphisms related to metabolic traits were also assessed. Results: Significant group × time interactions (p < 0.001) were observed for HbA1c, LDL, triglycerides, MDA, MPO, ESR, and cortisol, all of which improved in the algae-supplemented group. Correlation analysis revealed associations between HbA1c and LDL/TG as well as between cortisol and MPO. No significant genetic modulation of responses was detected, although a trend was noted for cortisol variation and insulin resistance risk. Conclusions: Algae-based supplementation led to favorable metabolic, oxidative, and inflammatory changes. These findings suggest its potential utility as a nutritional strategy to support recovery in athletes during periods of high training load or competition. Full article

(This article belongs to the Special Issue Functional Foods and Their Impact on Human Health: From Mechanisms to Applications)

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20 pages, 4853 KiB

Open AccessArticle

A Comparative Study on the Accuracy and Resolution of DAS and DORT-MUSIC Damage Imaging Method Based on Ultrasonic Guided Waves

by Chenguang Xu, Ying Luo, Guidong Xu, Sai Zhang and Baiqiang Xu

Appl. Sci. 2025, 15(12), 6380; https://doi.org/10.3390/app15126380 - 6 Jun 2025

The ultrasonic guided wave-based damage imaging methods are often limited in detection accuracy and resolution due to the dispersive characteristics of guided waves. Finding ways to extract more information from the guided wave field to improve imaging resolution has always been a hot [...] Read more.

The ultrasonic guided wave-based damage imaging methods are often limited in detection accuracy and resolution due to the dispersive characteristics of guided waves. Finding ways to extract more information from the guided wave field to improve imaging resolution has always been a hot topic in ultrasonic imaging. Based on the same set of guided wave field data obtained by numerical simulation and experiments, this paper compares the detection accuracy and resolution of the time-domain delay-and-sum (DAS) method, the frequency-domain DAS method, and the DORT-MUSIC method, which integrates time-reversal operator decomposition with multiple signal classification. The results show that, compared to the traditional time-domain imaging method, the frequency-domain method that incorporates dispersion relations exhibits significantly higher imaging accuracy. Additionally, the DORT-MUSIC method demonstrates a remarkable advantage in resolution, which can approach the diffraction limit. Related work in this paper provides a research basis for improving the imaging accuracy and resolution for ultrasonic guided waves in the practical application of structure damage detection. Full article

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29 pages, 7990 KiB

Open AccessArticle

Dynamic Low-Latency Load Balancing Model to Improve Quality of Experience in a Hybrid Fog and Edge Architecture for Massively Multiplayer Online (MMO) Games

by Ernesto José García Fernández de Castro, Ernesto José García Puche and Daladier Jabba Molinares

Appl. Sci. 2025, 15(12), 6379; https://doi.org/10.3390/app15126379 - 6 Jun 2025

In the evolving landscape of online gaming, ensuring a high quality of experience (QoE) for players is paramount. This study introduces a dynamic, low-latency load balancing model designed to enhance QoE in massively multiplayer online (MMO) games through a hybrid fog and edge [...] Read more.

In the evolving landscape of online gaming, ensuring a high quality of experience (QoE) for players is paramount. This study introduces a dynamic, low-latency load balancing model designed to enhance QoE in massively multiplayer online (MMO) games through a hybrid fog and edge computing architecture. The model addresses the challenges of latency and load distribution by leveraging fog and edge resources to optimize player engagement and response times. The experiments conducted in this study were simulations, providing a controlled environment to evaluate the proposed model’s performance. Key findings demonstrate a significant 67.5% reduction in average latency, a 60.3% reduction in peak latency, and a 65.8% reduction in latency variability, ensuring a more consistent and immersive gaming experience. Additionally, the proposed model was benchmarked against a base model, based on the article titled “A Cloud Gaming Architecture Leveraging Fog for Dynamic Load Balancing in Cluster-Based MMOs”, highlighting its superior performance in load distribution and latency reduction. This research provides a framework for future developments in cloud-based gaming infrastructure, emphasizing the importance of innovative load balancing techniques in maintaining seamless gameplay and scalable systems. Full article

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22 pages, 517 KiB

Open AccessArticle

Modeling Heat Consumption of an Office Building During COVID-19 Restrictions

by Stanislav Chicherin

Appl. Sci. 2025, 15(12), 6378; https://doi.org/10.3390/app15126378 - 6 Jun 2025

COVID-19 restricted the number of employees. Operational data showed that traditional methods of modeling heat consumption are not correct anymore. The aim is to model the energy demand of an office building during COVID-19 limitations and showcase improvements after a new controller or [...] Read more.

COVID-19 restricted the number of employees. Operational data showed that traditional methods of modeling heat consumption are not correct anymore. The aim is to model the energy demand of an office building during COVID-19 limitations and showcase improvements after a new controller or suggested alternatives are applied. After an actual heat consumption profile was simulated, energy conservation scenarios were considered: the usage of thermostatic radiator valves (TRVs); accounting impacts of solar radiation and wind; changing mass flow rates based on the indoor temperature; adopting an additional control, changing the temperature setpoint; introducing night and day setbacks. After implementing new design and operational methods, the overheating of indoor spaces was alleviated, and the average indoor temperature was reduced from 23.5 °C to 20.4 °C. The annual specific heat consumption decreased to 174 kWh/m² (20.2% lower). The methodology ensured thermal comfort and high energy-saving potential. If operating parameters were adjusted, the total saving effect in energy demand was 119.8 MWh, with an energy-saving rate of 19.8%. Employing TRV-related savings and considering thermal inertia provided more stable indoor temperatures and higher energy performance. The minimum saving effect corresponded to the optimal operation and ensuring the indoor environment by considering wind and the maximum one-to-night setbacks. The fluctuations in indoor temperature became smoother. Full article

(This article belongs to the Special Issue Energy Implications of Thermal Comfort in Buildings considering Climate Change, Second Edition)

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20 pages, 3894 KiB

Open AccessArticle

Designing Social Robots with LLMs for Engaging Human Interaction

by Maria Pinto-Bernal, Matthijs Biondina and Tony Belpaeme

Appl. Sci. 2025, 15(11), 6377; https://doi.org/10.3390/app15116377 - 5 Jun 2025

Large Language Models (LLMs), particularly those enhanced through Reinforcement Learning from Human Feedback, such as ChatGPT, have opened up new possibilities for natural and open-ended spoken interaction in social robotics. However, these models are not inherently designed for embodied, multimodal contexts. This paper [...] Read more.

Large Language Models (LLMs), particularly those enhanced through Reinforcement Learning from Human Feedback, such as ChatGPT, have opened up new possibilities for natural and open-ended spoken interaction in social robotics. However, these models are not inherently designed for embodied, multimodal contexts. This paper presents a user-centred approach to integrating an LLM into a humanoid robot, designed to engage in fluid, context-aware conversation with socially isolated older adults. We describe our system architecture, which combines real-time speech processing, layered memory summarisation, persona conditioning, and multilingual voice adaptation to support personalised, socially appropriate interactions. Through iterative development and evaluation, including in-home exploratory trials with older adults (n = 7) and a preliminary study with young adults (n = 43), we investigated the technical and experiential challenges of deploying LLMs in real-world human–robot dialogue. Our findings show that memory continuity, adaptive turn-taking, and culturally attuned voice design enhance user perceptions of trust, naturalness, and social presence. We also identify persistent limitations related to response latency, hallucinations, and expectation management. This work contributes design insights and architectural strategies for future LLM-integrated robots that aim to support meaningful, emotionally resonant companionship in socially assistive settings. Full article

23 pages, 4110 KiB

Open AccessArticle

Exploring CeO₂-Doped Co/SBA-15 Catalysts for Acetic Acid Oxidative Steam Reforming

by Carlos A. Chirinos, Álvaro Moreno de la Calle, Pedro J. Megía, Arturo J. Vizcaíno, José A. Calles and Alicia Carrero

Appl. Sci. 2025, 15(11), 6376; https://doi.org/10.3390/app15116376 - 5 Jun 2025

This work explores the effect of the incorporation of CeO₂ into Co/SBA-15 catalysts in hydrogen production through acetic acid oxidative steam reforming as a bio-oil aqueous phase model compound. CeO₂ was incorporated (5–30 wt.%) to improve the physicochemical properties of the [...] Read more.

This work explores the effect of the incorporation of CeO₂ into Co/SBA-15 catalysts in hydrogen production through acetic acid oxidative steam reforming as a bio-oil aqueous phase model compound. CeO₂ was incorporated (5–30 wt.%) to improve the physicochemical properties of the catalyst. XRD analysis confirmed that the addition of CeO₂ resulted in smaller Co⁰ mean crystallite sizes, while H₂-TPR showed enhanced reducibility properties. The catalytic performance was evaluated in the 400–700 °C range, S/C molar ratio = 2, O₂/C molar ratio = 0.0375, WHSV = 30.2 h⁻¹, and P = 1 atm. Catalysts containing 10 and 20 wt.% of CeO₂ exhibited the best catalytic performance, achieving nearly complete conversions and H₂ yield values, approaching thermodynamic equilibrium at 550 °C. Both samples maintained an acetic acid conversion above 90% after 30 h of time-on-stream, with H₂ yields above 55% along the steam reforming tests. This agrees with their lower coke formation rates (7.2 and 12.0 mg_coke·g_cat⁻¹·h⁻¹ for Co/10CeO₂-SBA15 and Co/20CeO₂-SBA15, respectively). Full article

(This article belongs to the Special Issue Advances in New Sources of Energy and Fuels)

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25 pages, 1220 KiB

Open AccessReview

Shedding Light on FIRE Syndrome: An Overview of a Novel Condition in Eosinophilic Esophagitis

by Selda Ali, Maria Cătălina Cernat, Mihaela Ruxandra Vintilă, Elena Camelia Berghea and Roxana Silvia Bumbăcea

Appl. Sci. 2025, 15(11), 6375; https://doi.org/10.3390/app15116375 - 5 Jun 2025

Food-Induced Immediate Response of the Esophagus (FIRE) is a newly described syndrome observed in eosinophilic esophagitis (EoE) patients. It is defined by an immediate hypersensitivity reaction of the esophagus that occurs when specific foods and beverages interface with esophageal mucosa. The available data [...] Read more.

Food-Induced Immediate Response of the Esophagus (FIRE) is a newly described syndrome observed in eosinophilic esophagitis (EoE) patients. It is defined by an immediate hypersensitivity reaction of the esophagus that occurs when specific foods and beverages interface with esophageal mucosa. The available data regarding this topic is scarce. Therefore, we aimed to review relevant publications in order to better characterize the main aspects of this syndrome and hypothesize about potential mechanisms underlying FIRE syndrome and possible future therapeutic approaches. We searched PubMed, Embase, and Web of Science databases for relevant articles published before February 1st, 2025. The results were narrowed down to four articles describing a total of 105 cases of FIRE syndrome. These patients had a distinct clinical presentation, characterized by retrosternal discomfort or pain, differentiating it from solid food dysphagia or pollen-food allergy syndrome (PFAS). Currently, diagnosis is based on clinical presentation, with no diagnostic tests or biomarkers available. Emerging evidence suggests that IgE-mediated hypersensitivity, mast cells, and neuroimmune interactions may play a central role in the pathogenesis of FIRE syndrome. The therapeutic approaches remain speculative, with trigger avoidance being the main option. This article brings to the forefront the need for continued research to address current knowledge gaps regarding FIRE syndrome, which is important for optimizing patient management. Full article

(This article belongs to the Special Issue New Diagnostic and Therapeutic Approaches in Food Allergy)

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41 pages, 6794 KiB

Open AccessArticle

Effectiveness of Electrode Design Methodologies for Fast EDM Slotting of Thick Silicon Wafers

by Mahmud Anjir Karim and Muhammad Pervej Jahan

Appl. Sci. 2025, 15(11), 6374; https://doi.org/10.3390/app15116374 - 5 Jun 2025

Silicon is the most commonly used material in the electronic industries due to its unique properties, which also make it very difficult to machine using conventional machining. Electrical discharge machining (EDM) is a non-traditional process that is gaining popularity for machining silicon, although [...] Read more.

Silicon is the most commonly used material in the electronic industries due to its unique properties, which also make it very difficult to machine using conventional machining. Electrical discharge machining (EDM) is a non-traditional process that is gaining popularity for machining silicon, although a slower machining rate is one of its limitations. This study investigates two electrode design strategies to enhance the efficiency of EDM by improving the material removal rates, reducing tool wear, and refining the quality of machined features. The first approach involves using graphite electrodes in various array configurations (1 × 4 to 6 × 4) and leg heights (0.2″ and 0.3″). The second approach employs hollow electrodes with differing wall thicknesses (0.04″, 0.08″, and 0.12″). The effects of these variables on performance were evaluated by maintaining constant EDM parameters. The results indicate that increasing the number of electrode legs improves the flushing conditions, resulting in shorter machining times. Meanwhile, the shorter electrode height outperforms the taller electrode, providing a higher machining speed. The thinnest wall thickness for hollow electrodes yielded the best performance due to the increased energy distribution. Both electrode design methodologies can be used for the mass fabrication of features with targeted profiles on silicon using the die-sinking EDM process. Full article

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23 pages, 1101 KiB

Open AccessArticle

QELPS Algorithm: A Novel Dynamic Optimization Technology for Quantum Circuits Scheduling Engineering Problems

by Zuoqiang Du, Xingjie Li and Hui Li

Appl. Sci. 2025, 15(11), 6373; https://doi.org/10.3390/app15116373 - 5 Jun 2025

In the noisy medium-scale quantum era, quantum computers are constrained by a limited number of qubits, restricted physical topological structures, and interference from environmental noise, making efficient and stable circuit scheduling a significant challenge. To improve the feasibility of quantum computing, it is [...] Read more.

In the noisy medium-scale quantum era, quantum computers are constrained by a limited number of qubits, restricted physical topological structures, and interference from environmental noise, making efficient and stable circuit scheduling a significant challenge. To improve the feasibility of quantum computing, it is essential to optimize the scheduling of quantum gates and the insertion of SWAP gates, reducing running time and enhancing computational efficiency. We propose a collaborative optimization framework that integrates the Quantum Exchange Lock Parallel Scheduler (QELPS) with the Full-level Joint Optimization SWAP Algorithm (FJOSA). In QELPS, SWAP conflict characteristics are used to adjust the layout of quantum gates across different levels while considering physical constraints and dynamically adapting to the circuit’s execution state. Quantum lock parallel technology enables the selective postponement of certain quantum gates, minimizing circuit depth and mitigating inefficiencies caused by excessive SWAP gate insertions. Meanwhile, FJOSA employs a cross-layer optimization strategy that combines heuristic algorithms with cost functions to improve gate scheduling at a global level. This approach effectively reduces quantum gate conflicts found in traditional methods and optimizes execution order, leading to better computational efficiency and circuit performance. Experimental results show that, compared to the traditional 2QAN algorithm, QELPS and FJOSA reduce additional gate insertions by 85.59% and 89.38%, respectively, while decreasing running time by 56.32% and 66.47%. These improvements confirm that the proposed method significantly enhances circuit scheduling efficiency and reduces resource consumption, making it a promising approach for optimizing quantum computation. Full article

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21 pages, 512 KiB

Open AccessArticle

Enhancing Sign Language Recognition Performance Through Coverage-Based Dynamic Clip Generation

by Taewan Kim and Bongjae Kim

Appl. Sci. 2025, 15(11), 6372; https://doi.org/10.3390/app15116372 - 5 Jun 2025

Sign Language Recognition (SLR) has made substantial progress through advances in deep learning and video-based action recognition. Conventional SLR systems typically segment input videos into a fixed number of clips (e.g., five clips per video), regardless of the video’s actual length, to meet [...] Read more.

Sign Language Recognition (SLR) has made substantial progress through advances in deep learning and video-based action recognition. Conventional SLR systems typically segment input videos into a fixed number of clips (e.g., five clips per video), regardless of the video’s actual length, to meet the fixed-length input requirements of deep learning models. While this approach simplifies model design and training, it fails to account for temporal variations inherent in sign language videos. Specifically, applying a fixed number of clips to videos of varying lengths can lead to significant information loss: longer videos suffer from excessive frame skipping, causing the model to miss critical gestural cues, whereas shorter videos require frame duplication, introducing temporal redundancy that distorts motion dynamics. To address these limitations, we propose a dynamic clip generation method that adaptively adjusts the number of clips during inference based on a novel coverage metric. This metric quantifies how effectively a clip selection captures the temporal information in a given video, enabling the system to maintain both temporal fidelity and computational efficiency. Experimental results on benchmark SLR datasets using multiple models-including 3D CNNs, R(2+1)D, Video Swin Transformer, and Multiscale Vision Transformers demonstrate that our method consistently outperforms fixed clip generation methods. Notably, our approach achieves 98.67% accuracy with the Video Swin Transformer while reducing inference time by 28.57%. These findings highlight the effectiveness of coverage-based dynamic clip generation in improving both accuracy and efficiency, particularly for videos with high temporal variability. Full article

(This article belongs to the Topic Applied Computing and Machine Intelligence (ACMI))

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17 pages, 2006 KiB

Open AccessArticle

Mitigating Long-Term Forecasting Bias in Time-Series Neural Networks via Ensemble of Short-Term Dependencies

by Jiahui Wang, Wenqian Zhou, Fangshu Chen, Liming Wang, Ruijun Pan and Chengcheng Yu

Appl. Sci. 2025, 15(11), 6371; https://doi.org/10.3390/app15116371 - 5 Jun 2025

Time-series forecasting is essential for predicting future trends based on historical data, with significant applications in meteorology, transportation, and finance. However, existing models often exhibit unsatisfactory performance in long-term forecasting scenarios. To address this limitation, we propose the Time-Series Neural Networks via Ensemble [...] Read more.

Time-series forecasting is essential for predicting future trends based on historical data, with significant applications in meteorology, transportation, and finance. However, existing models often exhibit unsatisfactory performance in long-term forecasting scenarios. To address this limitation, we propose the Time-Series Neural Networks via Ensemble of Short-Term Dependencies (TSNN-ESTD). This model leverages iTransformer as the base predictor to simultaneously train short-term and long-term forecasting models. The vanilla iTransformer’s linear decoding layer is optimized by replacing it with an LSTM layer, and an additional long-term model is introduced to enhance stability. The ensemble strategy employs short-term predictions to correct the bias in long-term forecasts. Our extensive experiments demonstrate that TSNN-ESTD reduces the MSE and MAE by 9.17% and 2.3% on five benchmark datasets. Full article

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14 pages, 1003 KiB

Open AccessArticle

A Linear Fitting Algorithm Based on Modified Random Sample Consensus

by Yujin Min, Yun Tang, Hao Chen and Faquan Zhang

Appl. Sci. 2025, 15(11), 6370; https://doi.org/10.3390/app15116370 - 5 Jun 2025

When performing linear fitting on datasets containing outliers, common algorithms may face problems like inadequate fitting accuracy. We propose a linear fitting algorithm based on Locality-Sensitive Hashing (LSH) and Random Sample Consensus (RANSAC). Our algorithm combines the efficient similarity search capabilities of the [...] Read more.

When performing linear fitting on datasets containing outliers, common algorithms may face problems like inadequate fitting accuracy. We propose a linear fitting algorithm based on Locality-Sensitive Hashing (LSH) and Random Sample Consensus (RANSAC). Our algorithm combines the efficient similarity search capabilities of the LSH algorithm with the robust fitting mechanism of RANSAC. With proper hash functions designed, similar data points are mapped to the same hash bucket, thereby enabling the efficient identification and removal of outliers. RANSAC is then used to fit the model parameters of the processed dataset. The optimal parameters for the linear model are obtained after multiple iterative processes. This algorithm significantly reduces the influence of outliers on the dataset, resulting in improved fitting accuracy and enhanced robustness. Experimental results demonstrate that the proposed improved RANSAC linear fitting algorithm outperforms the Weighted Least Squares, traditional RANSAC, and Maximum Likelihood Estimation methods, achieving a reduction in the sum of squared residuals by 29%, 16%, and 8%, respectively. Full article

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18 pages, 3095 KiB

Open AccessArticle

Study on the Evolution Law of Overlying Rock Collapse Induced by Mining Based on BOTDR

by Chenrui Huang, Chaomin Mu, Hui Zhou and Quanmin Xie

Appl. Sci. 2025, 15(11), 6369; https://doi.org/10.3390/app15116369 - 5 Jun 2025

Based on Brillouin optical time-domain reflectometry (BOTDR) technology, this study integrates laboratory tensile tests and similarity simulation experiments to systematically investigate the relationship between overlying strata collapse and fiber strain during coal seam mining. An analytical expression was established to describe the correlation [...] Read more.

Based on Brillouin optical time-domain reflectometry (BOTDR) technology, this study integrates laboratory tensile tests and similarity simulation experiments to systematically investigate the relationship between overlying strata collapse and fiber strain during coal seam mining. An analytical expression was established to describe the correlation between overlying strata displacement and fiber strain. The horizontal fiber monitoring results indicate that fiber strain accurately captures the evolution of overlying strata collapse and exhibits strong agreement with actual displacement height. When the working face advanced to 115 m and 155 m, the rock strata primarily underwent stress adjustment with minimal failure. At 195 m, the collapse zone expanded significantly, resulting in a notable increase in fiber strain. By 240 m, severe roof failure occurred, forming a complete caving zone in the goaf. The fiber strain curve exhibited a characteristic “double convex peak” pattern, with peak positions closely corresponding to rock fracture locations, further validating the feasibility of fiber monitoring in coal seam mining. Vertical fiber monitoring clearly delineated the evolution of the “three-zone” structure (caving zone, fracture zone, and bending subsidence zone) in the overlying strata. The fiber strain underwent a staged transformation from compressive strain to tensile strain, followed by stable compaction. The “stepped” characteristics of the strain curve effectively represented the heights of the three zones, highlighting the progressive and synchronized nature of rock failure. These findings demonstrate that fiber strain effectively characterizes the collapse height and evolution of overlying strata, enabling precise identification of rock fracture locations. This research provides scientific insights and technical support for roof stability assessment and mine safety management in coal seam mining. Full article

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19 pages, 5578 KiB

Open AccessArticle

Array Design and Transmitter Coils Selection for Underwater Wireless Power Transfer System

by Hanxi Xu, Wenhua Li, Zhongjiu Zheng and Yunhe Wang

Appl. Sci. 2025, 15(11), 6368; https://doi.org/10.3390/app15116368 - 5 Jun 2025

This paper proposes a method for array design and optimal transmitting coil selection of underwater wireless power transfer systems. This method is divided into three steps. Firstly, by analyzing the influence of different ratio side lengths of the transmitting coil and receiving coil [...] Read more.

This paper proposes a method for array design and optimal transmitting coil selection of underwater wireless power transfer systems. This method is divided into three steps. Firstly, by analyzing the influence of different ratio side lengths of the transmitting coil and receiving coil on mutual inductance, the optimal ratio side length coil is selected. Secondly, by analyzing the relative size of the reflection impedance of the power supply coil and its surrounding coils, the optimal coil activation criterion is derived. Finally, by estimating the position of the receiving coil without communication, the switching of the power supply coil is realized. According to the proposed method, it was verified on the experimental platform. Under a rated power of 300 W with a load resistance of 20 Ω, the system maintains efficiency ≥ 80% even under horizontal offsets up to 150 mm (75% of the transmitting coil side length) and two-dimensional offsets up to 200 mm (100% of the transmitting coil side length). Full article

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14 pages, 1894 KiB

Open AccessArticle

Peri-Implantitis Causal Therapy with and Without Doxycycline: Retrospective Cohort Clinical Study

by Bianca D’Orto and Elisabetta Polizzi

Appl. Sci. 2025, 15(11), 6367; https://doi.org/10.3390/app15116367 - 5 Jun 2025

Background: Topical application within peri-implant pockets ensures high drug concentrations at the infection site while minimizing systemic exposure. However, the comparative effectiveness of non-surgical causal therapy alone versus its combination with doxycycline remains unclear. This retrospective observational clinical study aimed to evaluate the [...] Read more.

Background: Topical application within peri-implant pockets ensures high drug concentrations at the infection site while minimizing systemic exposure. However, the comparative effectiveness of non-surgical causal therapy alone versus its combination with doxycycline remains unclear. This retrospective observational clinical study aimed to evaluate the impact of adjunctive doxycycline on peri-implant parameters, considering smoking, systemic conditions, and implant–prosthetic rehabilitation (single implant, implant-supported bridge, or full-arch). Methods: Patients were retrospectively assigned to a control group (CG), receiving non-surgical causal therapy alone, or a test group (TG), which is also treated with topical doxycycline. Peri-implant parameters, including Peri-implant Probing Depht (PPD), Bleeding on Probing (BoP), Plaque Index (PI), and suppuration, were assessed at baseline (T0) and follow-up (T1). Multivariate logistic regression and stratified subgroup analyses were conducted to adjust for confounders such as smoking, systemic conditions, and implant–prosthetic rehabilitation types. Results: Two hundred nine patients were included in the study, of whom 97 were in the CG and 112 were in the TG. At T1, the TG exhibited a statistically significant reduction in PPD, BoP, PI, and suppuration compared to the CG (p < 0.05). Conclusions: The adjunctive use of topical doxycycline significantly enhances clinical outcomes in non-surgical peri-implantitis treatment. Further longitudinal studies are needed to confirm these findings and assess long-term stability. Full article

(This article belongs to the Special Issue Dental Implants: Latest Advances and Prospects)

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21 pages, 967 KiB

Open AccessArticle

A Heuristic Algorithm for Locating Line-to-Line Faults in Photovoltaic Systems

by Jia-Zhang Jhan, Bo-Hong Li, Hsun-Tsung Chiu, Hong-Chan Chang and Cheng-Chien Kuo

Appl. Sci. 2025, 15(11), 6366; https://doi.org/10.3390/app15116366 - 5 Jun 2025

Photovoltaic (PV) systems have experienced rapid global deployment. However, line-to-line short-circuit faults pose serious safety risks and can lead to significant power losses or fire hazards. While existing fault detection methods can identify fault types, they cannot precisely locate fault positions, resulting in [...] Read more.

Photovoltaic (PV) systems have experienced rapid global deployment. However, line-to-line short-circuit faults pose serious safety risks and can lead to significant power losses or fire hazards. While existing fault detection methods can identify fault types, they cannot precisely locate fault positions, resulting in time-consuming and costly maintenance. This paper proposes a heuristic algorithm for accurately locating such faults in PV arrays based on module group voltage measurements. The algorithm employs a two-phase approach: fault candidate marking and fault location determination, capable of handling both intra-string and cross-string faults. Simulation tests on a 21 × 2 PV array configuration demonstrate a 97.56% fault location success rate, reducing the troubleshooting scope to within a single-module group. The proposed method offers a simple, fast, and cost-effective solution for PV system maintenance, potentially saving significant labor costs and reducing system downtime. Full article

30 pages, 10731 KiB

Open AccessArticle

Real-Time 3D Vision-Based Robotic Path Planning for Automated Adhesive Spraying on Lasted Uppers in Footwear Manufacturing

by Ya-Yung Huang, Jun-Ting Lai and Hsien-Huang Wu

Appl. Sci. 2025, 15(11), 6365; https://doi.org/10.3390/app15116365 - 5 Jun 2025

The automation of adhesive application in footwear manufacturing is challenging due to complex surface geometries and model variability. This study presents an integrated 3D vision-based robotic system for adhesive spraying on lasted uppers. A triangulation-based scanning setup reconstructs each upper into a high-resolution [...] Read more.

The automation of adhesive application in footwear manufacturing is challenging due to complex surface geometries and model variability. This study presents an integrated 3D vision-based robotic system for adhesive spraying on lasted uppers. A triangulation-based scanning setup reconstructs each upper into a high-resolution point cloud, enabling customized spraying path planning. A six-axis robotic arm executes the path using an adaptive transformation matrix that aligns with surface normals. UV fluorescent dye and inspection are used to verify adhesive coverage. Experimental results confirm high repeatability and precision, with most deviations within the industry-accepted ±1 mm range. While localized glue-deficient areas were observed around high-curvature regions such as the toe cap, these remain limited and serve as a basis for further system enhancement. The system significantly reduces labor dependency and material waste, as observed through the replacement of four manual operators and the elimination of adhesive over-application in the tested production line. It has been successfully installed and validated on a production line in Hanoi, Vietnam, meeting real-world industrial requirements. This research contributes to advancing intelligent footwear manufacturing by integrating 3D vision, robotic motion control, and automation technologies. Full article

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