Applied Sciences

38 pages, 3696 KB

Open AccessReview

Research Advances in the Distribution, Migration, Transformation, and Removal of Antibiotics in Aquatic Ecosystems

by Rensheng Lv, Sheng Li, Xiao Wang, Yinggang Jia, Yanyan Ge, Man Xia, Xing Gao, Jiahao Ma, Bengang Liu, Lingyun Zhang, Tianwei Qi, Junfeng Meng, Bowen Zhao, Feilong Jie and Fengjuan Chen

Appl. Sci. 2025, 15(23), 12777; https://doi.org/10.3390/app152312777 (registering DOI) - 2 Dec 2025

Abstract

Antibiotics are widely used in medicine, livestock and other fields, leading to increasingly prominent enrichment, transformation and potential ecological risks in the global water environment. This poses a serious threat to ecological balance and public health, making the development of efficient and economical [...] Read more.

Antibiotics are widely used in medicine, livestock and other fields, leading to increasingly prominent enrichment, transformation and potential ecological risks in the global water environment. This poses a serious threat to ecological balance and public health, making the development of efficient and economical treatment technologies a research hotspot for addressing water antibiotic pollution. This paper systematically analyzes the current status of global water antibiotic pollution, migration and transformation characteristics, and research progress in removal technologies. We summarize the main types of antibiotics in water and their spatial distribution across different global water bodies, explore their primary entry pathways into the water environment, and elaborate on transformation behaviors such as migration, adsorption and degradation, as well as residual risks to aquatic ecosystems and human health. We also focus on existing artificial removal technologies, including physical methods like adsorption and membrane separation, chemical methods centered on advanced oxidation, and biological methods utilizing microbial metabolism. And we discuss emerging technologies such as microbial fuel cells and biocatalyst remediation, along with hybrid processes, regarding their development status and application potential. Finally, we outline key challenges in practical application of current technologies, provide an outlook on future research directions and engineering applications, aiming to offer references for water antibiotic pollution control. Full article

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34 pages, 23757 KB

Open AccessArticle

Fuzzy-Partitioned Multi-Agent TD3 for Photovoltaic Maximum Power Point Tracking under Partial Shading

by Diana Ortiz-Muñoz, David Luviano-Cruz, Luis Asunción Pérez-Domínguez, Alma Guadalupe Rodríguez-Ramírez and Francesco García-Luna

Appl. Sci. 2025, 15(23), 12776; https://doi.org/10.3390/app152312776 - 2 Dec 2025

Abstract

Maximum power point tracking (MPPT) under partial shading is a nonconvex, rapidly varying control problem that challenges multi-agent policies deployed on photovoltaic modules. We present Fuzzy–MAT3D, a fuzzy-augmented multi-agent TD3 (Twin-Delayed Deep Deterministic Policy Gradient) controller trained under centralized training/decentralized execution (CTDE). On [...] Read more.

Maximum power point tracking (MPPT) under partial shading is a nonconvex, rapidly varying control problem that challenges multi-agent policies deployed on photovoltaic modules. We present Fuzzy–MAT3D, a fuzzy-augmented multi-agent TD3 (Twin-Delayed Deep Deterministic Policy Gradient) controller trained under centralized training/decentralized execution (CTDE). On the theory side, we prove that differentiable fuzzy partitions of unity endow the actor–critic maps with global Lipschitz regularity, reduce temporal-difference target variance, enlarge the input-to-state stability (ISS) margin, and yield a global

L_{\infty}

γ

-contraction of fixed-policy evaluation (hence, non-expansive with

κ = γ < 1

). We further state a two-time-scale convergence theorem for CTDE-TD3 with fuzzy features; a PL/last-layer-linear corollary implies point convergence and uniqueness of critics. We bound the projected Bellman residual with the correct contraction factor (for

L^{\infty}

and

L^{2} (ρ)

under measure invariance) and quantified the negative bias induced by

min {Q_{1}, Q_{2}}

; an N-agent extension is provided. Empirically, a balanced common-random-numbers design across seven scenarios and 20 seeds, analyzed by ANOVA and CRN-paired tests, shows that Fuzzy–MAT3D attains the highest mean MPPT efficiency (

92.0

±

4.0

), outperforming MAT3D and Multi-Agent Deep Deterministic Policy Gradient controller (MADDPG). Overall, fuzzy regularization yields higher efficiency, suppresses steady-state oscillations, and stabilizes learning dynamics, supporting the use of structured, physics-compatible features in multi-agent MPPT controllers. At the level of PV plants, such gains under partial shading translate into higher effective capacity factors and smoother renewable generation without additional hardware. Full article

(This article belongs to the Special Issue Advances in Control and Optimization of Renewable Energy in Industrial Systems)

24 pages, 636 KB

Open AccessReview

Biomass of Microalgae and Other Phototrophic Microorganisms: Current Trends in Regulation of Its Accumulation and Application of Immobilized Forms

by Elena Efremenko, Olga Senko, Kamella Teplova and Aysel Aslanli

Appl. Sci. 2025, 15(23), 12775; https://doi.org/10.3390/app152312775 (registering DOI) - 2 Dec 2025

Abstract

The current interest in microalgal biomass does not subside but continues to intensify due to the emergence of new trends in the use of this bioresource in various biotechnological and environmental processes. The rather slow growth rate of phototrophs compared to other microorganisms [...] Read more.

The current interest in microalgal biomass does not subside but continues to intensify due to the emergence of new trends in the use of this bioresource in various biotechnological and environmental processes. The rather slow growth rate of phototrophs compared to other microorganisms limits more active application of the biomass for various purposes. Stimulation of the Quorum Sensing formation in the cells due to the appearance of their own quorum molecules or those produced by other co-cultured microorganisms in the medium is one of the efficient approaches for overcoming this limitation. This review discusses the immobilization or co-immobilization of phototrophic cells with other microorganisms as an effective way to maintain accumulation of the target biomass for long-term period at improved rates. The 40% increase in the use of co-immobilized phototrophs for biomass obtaining and its use in wastewater treatment has been observed over the past five years. The level of investigations of co-immobilized microalgae cells is four times higher than that of the immobilized single cultures. Among the main trends in the new investigations of immobilized forms of microalgae, the predominant application of Chlorella genus cells in immobilized samples of individual cultures and the involvement of diatom microalgae and cyanobacteria, in addition to Chlorella cells, in co-immobilization with other microorganisms, was ascertained. The most significant increase in the rate of microalgal biomass accumulation uncovered in cases of co-immobilization of microalgae with bacteria. In several cases, in the presence of bacteria, co-immobilization has led to the emergence of new characteristics in microalgal cells (increased synthesis of pigments, polysaccharides, biofilm formation, etc.), which opens new directions for their further practical use as biopesticides, components of packaging and building materials, etc. Full article

(This article belongs to the Special Issue Advances in Microbial Biotechnology)

17 pages, 3414 KB

Open AccessArticle

Research on Low-Frequency Sound Absorption Based on the Combined Array of Hybrid Digital–Analog Shunt Loudspeakers

by Jiachen Liu, Yubing Xu, Chaonan Cong and Jiawei Wu

Appl. Sci. 2025, 15(23), 12774; https://doi.org/10.3390/app152312774 (registering DOI) - 2 Dec 2025

Abstract

Low-frequency noise, the most critical noise frequency band affecting human physical and mental health, poses a significant challenge for effective control in spatially constrained building environments. The shunt loudspeaker offers a novel solution to control low-frequency noise. Unlike traditional methods, it does not [...] Read more.

Low-frequency noise, the most critical noise frequency band affecting human physical and mental health, poses a significant challenge for effective control in spatially constrained building environments. The shunt loudspeaker offers a novel solution to control low-frequency noise. Unlike traditional methods, it does not rely on large cavity depth but only requires the adjustment of parameters or structure of the shunt circuit. However, most shunt loudspeakers utilize analog shunt technology, which leads to instability and inaccuracy owing to the negative impedance converter circuit and parasitic impedance in analog electronic components. The paper proposes a tunable low-frequency sound absorber utilizing a combined array of hybrid digital–analog shunt loudspeakers. The theoretical model was established based on the electro-mechanical–acoustic analogy method and parallel impedance method. Numerical simulations and experimental studies were performed to verify the proposed model. The results demonstrate that the proposed absorber can achieve excellent low-frequency sound absorption capability by designing only a few digital filter parameters, while simultaneously enhancing the stability and accuracy of the system. This study presents a promising innovative method for low-frequency noise control at sub-wavelength scales, providing a space-efficient solution. Full article

(This article belongs to the Special Issue Novel Advances in Noise and Vibration Control)

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25 pages, 22285 KB

Open AccessArticle

Effect of Multilayer Cr/CrN Coatings Deposited by Magnetron Sputtering on the Thermal Stability and High-Temperature Steam Oxidation Resistance of Zirconium Alloy E110

by Nazerke Muktanova, Madina Kamet and Bauyrzhan Rakhadilov

Appl. Sci. 2025, 15(23), 12773; https://doi.org/10.3390/app152312773 - 2 Dec 2025

Abstract

The effect of the multilayer structure of Cr/CrN coatings deposited by reactive magnetron sputtering on zirconium alloy E110 (Zr–1Nb) on their thermal stability and resistance to steam oxidation at 1100 °C was studied. Coatings with different numbers of alternating Cr and CrN sublayers [...] Read more.

The effect of the multilayer structure of Cr/CrN coatings deposited by reactive magnetron sputtering on zirconium alloy E110 (Zr–1Nb) on their thermal stability and resistance to steam oxidation at 1100 °C was studied. Coatings with different numbers of alternating Cr and CrN sublayers (1, 2, 4, and 6) were fabricated using experimental methods of X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive analysis (SEM/EDS). It was shown that an increase in the number of alternating Cr and CrN sublayers leads to the preservation of the cubic phase of CrN, the formation of a dense structure, and a decrease in Cr–Zr interdiffusion. After testing, multilayer coatings retaining the internal structure and a sufficiently structurally dense Cr₂O₃ layer effectively ensured air penetration. The best thermal stability was demonstrated by a six-layer coating, ensuring minimal oxidation and preservation of the E110 substrate. Full article

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

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26 pages, 18496 KB

Open AccessArticle

Turbulence and Windshear Study for Typhoon Wipha in 2025

by Ka Wai Lo, Ming Chun Lam, Kai Kwong Lai, Man Lok Chong, Pak Wai Chan, Yu Cheng Xue and E Deng

Appl. Sci. 2025, 15(23), 12772; https://doi.org/10.3390/app152312772 - 2 Dec 2025

Abstract

This paper reports on the study of turbulence at various locations in Hong Kong during Typhoon Wipha in July 2025, including turbulence intensity based on Doppler Light Detection and Ranging (LIDAR) systems and radiosondes, observations by microclimate stations, and low-level windshear and turbulence [...] Read more.

This paper reports on the study of turbulence at various locations in Hong Kong during Typhoon Wipha in July 2025, including turbulence intensity based on Doppler Light Detection and Ranging (LIDAR) systems and radiosondes, observations by microclimate stations, and low-level windshear and turbulence at the Hong Kong International Airport (HKIA) by LIDAR, flight data, and pilot reports. Although the observation period was primarily limited to 20 July 2025, passage of a typhoon over a densely instrumented urban area is uncommon; these observations on turbulent flow associated with typhoons therefore can serve as valuable benchmarks for similar studies on turbulent flow associated with typhoons in other coastal areas, particularly for operational alerts in aviation. To assess the predictability of turbulence, the eddy dissipation rate (EDR) was derived from a high-resolution numerical weather prediction (NWP) model using diagnostic and reconstruction approaches. Compared with radiosonde data, both approaches performed similarly in the shear-dominated low-level atmosphere, while the diagnostic approach outperformed when buoyancy became important. This result highlights the importance of incorporating buoyancy effects in the reconstruction approach if the EDR diagnostic is not available. The high-resolution NWP was also used to provide time-varying boundary conditions for computational fluid dynamics simulations in urban areas, and its limitations were discussed. This study also demonstrated the difficulty of capturing low-level windshear encountered by departing aircraft in an operational environment and demonstrated that a trajectory-aware method for deriving headwind could align more closely with onboard measurements than the standard fixed-path product. Full article

(This article belongs to the Special Issue Transportation and Infrastructures Under Extreme Weather Conditions)

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25 pages, 3455 KB

Open AccessArticle

High-Frame-Rate Camera-Based Vibration Analysis for Health Monitoring of Industrial Robots Across Multiple Postures

by Tuniyazi Abudoureheman, Hayato Otsubo, Feiyue Wang, Kohei Shimasaki and Idaku Ishii

Appl. Sci. 2025, 15(23), 12771; https://doi.org/10.3390/app152312771 - 2 Dec 2025

Abstract

Accurate vibration measurement is crucial for maintaining the performance, reliability, and safety of automated manufacturing environments. Abnormal vibrations caused by faults in gears or bearings can degrade positional accuracy, reduce productivity, and, over time, significantly impair production efficiency and product quality. Such vibrations [...] Read more.

Accurate vibration measurement is crucial for maintaining the performance, reliability, and safety of automated manufacturing environments. Abnormal vibrations caused by faults in gears or bearings can degrade positional accuracy, reduce productivity, and, over time, significantly impair production efficiency and product quality. Such vibrations may also disrupt supply chains, cause financial losses, and pose safety risks to workers through collisions, falling objects, or other operational hazards. Conventional vibration measurement techniques, such as wired accelerometers and strain gauges, are typically limited to a few discrete measurement points. Achieving multi-point measurements requires numerous sensors, which increases installation complexity, wiring constraints, and setup time, making the process both time-consuming and costly. The integration of high-frame-rate (HFR) cameras with Digital Image Correlation (DIC) enables non-contact, multi-point, full-field vibration measurement of robot manipulators, effectively addressing these limitations. In this study, HFR cameras were employed to perform non-contact, full-field vibration measurements of industrial robots. The HFR camera recorded the robot’s vibrations at 1000 frames per second (fps), and the resulting video was decomposed into individual frames according to the frame rate. Each frame, with a resolution of 1920 × 1080 pixels, was divided into 128 × 128 pixel blocks with a 64-pixel stride, yielding 435 sub-images. This setup effectively simulates the operation of 435 virtual vibration sensors. By applying mask processing to these sub-images, nine key points representing critical robot components were selected for multi-point DIC displacement measurements, enabling effective assessment of vibration distribution and real-time vibration visualization across the entire manipulator. This approach allows simultaneous capture of displacements across all robot components without the need for physical sensors. The transfer function is defined in the frequency domain as the ratio between the output displacement of each robot component and the input excitation applied by the shaker mounted on the end-effector. The frequency–domain transfer functions were computed for multiple robot components, enabling accurate and full-field vibration analysis during operation. Full article

(This article belongs to the Special Issue Innovative Approaches to Non-Destructive Evaluation)

21 pages, 1064 KB

Open AccessArticle

The Problem of Resolving Train Movement Conflicts in a Traffic Management System

by Janusz Szkopiński, Maciej Śmieszek and Andrzej Kochan

Appl. Sci. 2025, 15(23), 12770; https://doi.org/10.3390/app152312770 - 2 Dec 2025

Abstract

This article addresses selected aspects of designing a Traffic Management System (TMS) for the railway component of Poland’s Central Communication Port (CPK) project. The primary objective was to determine train headway times while considering automated traffic conflict resolution and speed profile optimization in [...] Read more.

This article addresses selected aspects of designing a Traffic Management System (TMS) for the railway component of Poland’s Central Communication Port (CPK) project. The primary objective was to determine train headway times while considering automated traffic conflict resolution and speed profile optimization in relation to traction energy consumption. The study utilized simulations in the MATLAB/Simulink (Version number: R2024a Update 3) environment, modeling the movement of an ETR610 (ED250) train on a line equipped with the European Train Control System (ETCS). The simulation results provided insights into the impact of the adopted assumptions on TMS operational efficiency under failure conditions and its capability to optimize train movements. The conclusions underscore the critical importance of time reserves in effective conflict resolution, the interplay between buffer allocation and speed restrictions, and the impact of minimizing train stops on energy consumption. They also highlight the necessity of adapting operational strategies to infrastructure characteristics and the influence of simulation time on the effectiveness of conflict resolution methods. Furthermore, the study emphasizes the need to broaden operational scenarios to include failures of traction vehicles and train control systems, along with appropriate planning for time reserves. Full article

(This article belongs to the Special Issue Technical Advances in Railway Systems: Condition Monitoring, Smart Control and Optimization)

19 pages, 7109 KB

Open AccessArticle

Development of a Coastal Erosion Monitoring Plan Using In Situ Measurements and Satellite Images

by Víctor Castro-Quintero, Moisés Lima-Delgado and Gisselle Guerra-Chanis

Appl. Sci. 2025, 15(23), 12769; https://doi.org/10.3390/app152312769 - 2 Dec 2025

Abstract

Coastal erosion affects nearly 70% of global beaches, threatening ecosystems and socio-economic development. This study proposes a monitoring framework integrating Differential GNSS RTK, RPA photogrammetry with PPK, and high-resolution satellite imagery to evaluate shoreline change and beach profiles along Panama’s Pacific coast. Short-term [...] Read more.

Coastal erosion affects nearly 70% of global beaches, threatening ecosystems and socio-economic development. This study proposes a monitoring framework integrating Differential GNSS RTK, RPA photogrammetry with PPK, and high-resolution satellite imagery to evaluate shoreline change and beach profiles along Panama’s Pacific coast. Short-term (3–5 months) and long-term (13 years) analyses were conducted using DSAS metrics—End Point Rate (EPR) and Net Shoreline Movement (NSM)—to quantify erosion trends. Results show Differential GNSS provides superior accuracy for sandy beach profiling, while RPA photogrammetry is effective in complex terrains such as rocky-bottom beaches. Combining RPA and satellite imagery enhances long-term shoreline monitoring. The proposed plan offers a scalable, cost-effective approach for coastal management, supporting evidence-based policy, land-use planning, and disaster risk reduction, while serving as a methodological reference for future research. Full article

(This article belongs to the Topic Coastal Engineering: Past, Present and Future)

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20 pages, 1036 KB

Open AccessArticle

Auxiliary Down-Slope Effects of Anti-Rollback Mechanisms in Manual Wheelchair Systems

by Bartosz Wieczorek, Łukasz Warguła and Marcin Giedrowicz

Appl. Sci. 2025, 15(23), 12768; https://doi.org/10.3390/app152312768 - 2 Dec 2025

Abstract

The aim of this study was to experimentally assess the effect of increased rolling resistance, generated by the Anti-Rollback System, on the muscular load of a manual wheelchair user during downhill movement. Three descent conditions were compared: without the module (NAR), with a [...] Read more.

The aim of this study was to experimentally assess the effect of increased rolling resistance, generated by the Anti-Rollback System, on the muscular load of a manual wheelchair user during downhill movement. Three descent conditions were compared: without the module (NAR), with a flexible roller (EAR), and with a rigid roller (SAR). The experiment was conducted on a 6.3 m ramp inclined at 5°, involving eight adult male participants. Muscle effort was evaluated using three indicators: normalized cumulative muscle load per second (CML/s), normalized muscle activity (EMG_norm), and the peak-to-mean ratio of the EMG signal (PMR). Statistical analysis revealed significant differences between configurations (p < 0.05). Use of the module significantly reduced muscular load compared with the reference condition: CML/s decreased by 29.41% in both EAR and SAR, while EMG_norm was reduced by 44.44% in EAR and 50.00% in SAR. PMR reached its lowest value in EAR (4.78), suggesting smoother muscle activation and lower local peak tension. The results indicate that the resistive torque generated by the frictional coupling between the wheelchair tire and the anti-rollback roller, although disadvantageous during propulsion, contributes to improved control and stability during downhill descent, highlighting the system’s dual functional potential. Full article

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23 pages, 2384 KB

Open AccessArticle

DyGAS: Dynamic Graph-Augmented Sequence Modeling for Knowledge Tracing

by Xiuyun Li, Zihao Yan, Yongchun Gu, Siwei Zhou and Shasha Yang

Appl. Sci. 2025, 15(23), 12767; https://doi.org/10.3390/app152312767 - 2 Dec 2025

Abstract

Online learning environments generate vast amounts of student interaction data. While these records capture observable behaviors, they do not directly reveal students’ underlying knowledge states, which are essential for tracking learning progress. Knowledge tracing (KT) addresses this gap by predicting students’ future performance [...] Read more.

Online learning environments generate vast amounts of student interaction data. While these records capture observable behaviors, they do not directly reveal students’ underlying knowledge states, which are essential for tracking learning progress. Knowledge tracing (KT) addresses this gap by predicting students’ future performance on exercises related to specific concepts, thereby enabling personalized learning and intelligent tutoring. Existing deep learning-based KT methods achieve promising results, but they often overemphasize either the sequential evolution of knowledge or the static structural relationships, which does not reflect the dynamic evolution of student learning. Moreover, they fail to model students’ knowledge state accurately under sparse interactions. To overcome these limitations, we propose DyGAS, a dynamic graph-augmented sequence modeling framework for knowledge tracing. The sequential module captures the dynamics pattern of knowledge acquisition and forgetting, while the structural module employs graph convolutional networks (GCN) to model inter-concept dependencies and knowledge transfer. Additionally, we propose that static knowledge modeling provides semantic priors to stabilize the representation of sparse concepts. Empirical results on three benchmark datasets demonstrate that DyGAS achieves superior performance compared to state-of-the-art methods, offering accurate and robust knowledge tracing across diverse learning scenarios. Full article

(This article belongs to the Special Issue Generative AI for Intelligent Knowledge Systems and Adaptive Learning)

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19 pages, 2362 KB

Open AccessArticle

Experimental and Simulation Analysis of Die Gating System Design for AlSi₉Cu₃ Alloy Castings

by Juraj Ružbarský and Jozef Žarnovský

Appl. Sci. 2025, 15(23), 12766; https://doi.org/10.3390/app152312766 - 2 Dec 2025

Abstract

This study investigates the melt-flow behavior of the AlSi₉Cu₃ alloy during high-pressure die casting using a combined experimental and numerical approach. A transparent die and a high-speed camera were used to capture the transient motion of the melt front, while [...] Read more.

This study investigates the melt-flow behavior of the AlSi₉Cu₃ alloy during high-pressure die casting using a combined experimental and numerical approach. A transparent die and a high-speed camera were used to capture the transient motion of the melt front, while a validated computational model reproduced the filling dynamics under identical boundary conditions. The influence of the gating-system geometry—particularly the gate thickness, flow-path length, and inlet cross-section—was analyzed with respect to filling velocity, filling time, and flow stability. To quantify hydraulic losses that arise in practical die-casting conditions, an empirical correction coefficient k₂ was introduced. Its value was obtained by regression analysis based on ten repeated measurements of filling time for each configuration. The deviation between the simulated and experimental velocities did not exceed 5%, demonstrating the reliability of the numerical model within the tested parameter range. The results show that the optimized gating design reduces flow instability, suppresses air entrapment zones, and yields a more uniform velocity distribution across the cavity. The empirical relations derived involving k₂ provide a practical tool for preliminary design of gating systems, enabling faster optimization without extensive trial-and-error procedures. The methodology presented in this work offers a validated basis for improving gating-system performance in high-pressure die casting of aluminum alloys. Full article

(This article belongs to the Section Mechanical Engineering)

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21 pages, 2876 KB

Open AccessArticle

Coupled Water–Nitrogen Transport and Multivariate Prediction Models for Muddy Water Film Hole Irrigation

by Feilong Jie and Youliang Peng

Appl. Sci. 2025, 15(23), 12765; https://doi.org/10.3390/app152312765 - 2 Dec 2025

Abstract

Against the backdrop of global water scarcity, utilizing sediment-laden river water for agricultural irrigation is a critical strategy for ensuring food security. However, the associated water and nitrogen transport processes are influenced by the coupled effects of multiple factors, and the governing mechanisms [...] Read more.

Against the backdrop of global water scarcity, utilizing sediment-laden river water for agricultural irrigation is a critical strategy for ensuring food security. However, the associated water and nitrogen transport processes are influenced by the coupled effects of multiple factors, and the governing mechanisms are not yet fully understood. To investigate the coupled effects of muddy water sediment concentration (ρ), physical clay content (d_0.01), applied nitrogen concentration (N), and pressure head (H) on infiltration characteristics during film hole irrigation, this study conducted an indoor soil-box experiment using an orthogonal design to analyze soil water and nitrogen transport dynamics. Results indicated that sediment properties were the dominant factors governing infiltration, with their relative influence on cumulative infiltration following the order ρ > d_0.01 > H > N. ρ and d_0.01 strongly inhibited infiltration; for instance, an increase in ρ from 3% to 9% reduced the initial infiltration rate by as much as 49.3%. Conversely, H and N exhibited a slight promoting effect. High muddy water sediment concentration and physical clay content significantly restricted water and nitrogen transport, causing substantial amounts of ammonium nitrogen (NH₄⁺-N) to be retained within the surface soil layer adjacent to the irrigation hole. Paradoxically, the same factors that reduced infiltration (ρ and d_0.01) led to a significant increase in the average change in volumetric water content (Δθ) within the wetted soil volume. Based on these findings, multivariate power function models were developed to predict key parameters. The models demonstrated high predictive accuracy, with coefficients of determination (R²) of 0.9715 for cumulative infiltration, 0.94 for wetting front migration, and 0.9758 for Δθ, and validation errors were within acceptable limits. In conclusion, the film hole irrigation process is predominantly governed by physical clogging from sediment particles, a mechanism that decisively controls the spatial distribution of water and nitrogen. Furthermore, the slight enhancement of infiltration by nitrogen fertilizer suggests a potential physicochemical mechanism, possibly involving ion-induced flocculation of clay particles. The models developed in this study provide a quantitative basis for precision fertigation management in China’s Yellow River irrigation district and other regions with similar conditions. Full article

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21 pages, 695 KB

Open AccessArticle

Packet Traceability in the OpenStack Cloud Environment

by Dalibor Kafka, Pavel Segec, Marek Moravcik and Martin Kontsek

Appl. Sci. 2025, 15(23), 12764; https://doi.org/10.3390/app152312764 - 2 Dec 2025

Abstract

OpenStack is a popular open-source cloud platform that orchestrates virtualized compute, storage, and networking resources. In such virtualized environments, packet traceability refers to the ability to track the path and transformations of network packets as they traverse virtual switches, routers, and interfaces. This [...] Read more.

OpenStack is a popular open-source cloud platform that orchestrates virtualized compute, storage, and networking resources. In such virtualized environments, packet traceability refers to the ability to track the path and transformations of network packets as they traverse virtual switches, routers, and interfaces. This paper presents a comprehensive overview of packet traceability in OpenStack cloud environments. We provide an introduction to the OpenStack architecture with a focus on the Networking component (Neutron) and discuss how packets flow through virtual networking elements. We examine the routing and interface mechanisms that enable communication within and across nodes, and compare single-node versus multi-node OpenStack deployments from a packet tracing perspective. Furthermore, we survey tools and techniques for packet tracing (such as monitoring interfaces, using tcpdump, and Open vSwitch tracing), and highlight the challenges faced (multi-tenancy, overlay networks, etc.) in tracing packets. We offer recommendations for improving traceability, including leveraging built-in OpenStack features and advanced kernel-level tracing technologies. Our goal is to aid cloud administrators and researchers in understanding and improving network packet observability in OpenStack clouds, thereby enhancing troubleshooting and security analysis capabilities. Full article

(This article belongs to the Special Issue Cloud Computing: New Network Technology and Information Security)

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13 pages, 4200 KB

Open AccessArticle

Intelligent Identification of Embankment Termite Nest Hidden Danger by Electrical Resistivity Tomography

by Fuyu Jiang, Yao Lei, Peixuan Qiao, Likun Gao, Jiong Ni, Xiaoyu Xu and Sheng Zhang

Appl. Sci. 2025, 15(23), 12763; https://doi.org/10.3390/app152312763 - 2 Dec 2025

Abstract

Traditional electrical resistivity tomography (ERT) technology confronts bottlenecks such as the volume effect in the detection of termite nests in levees, while the ERT based on deep learning has insufficient interpretation accuracy due to small sample data. This study proposes an intelligent ERT [...] Read more.

Traditional electrical resistivity tomography (ERT) technology confronts bottlenecks such as the volume effect in the detection of termite nests in levees, while the ERT based on deep learning has insufficient interpretation accuracy due to small sample data. This study proposes an intelligent ERT diagnosis framework that integrates generative adversarial networks (GANs) with semantic segmentation models. The GAN-enhanced networks (GFU-Net and GFL-Net) are developed, incorporating a Squeeze-and-Excitation (SE) attention mechanism to suppress false anomalies. Additionally, a comprehensive loss function combining binary cross-entropy (BCE) and the Focal loss function is used to address the issue of sample imbalance. Using forward modeling based on the finite difference method (FDM), a termite nest hidden danger ERT dataset, which includes seven types of high-resistance anomaly configurations, is generated. Numerical simulations demonstrate that GFL-Net achieves a mean intersection-over-union (mIoU) of 97.68% and a spatial positioning error of less than 0.04 m. In field validation on a red clay embankment in Jiangxi Province, this method significantly improves the positioning accuracy of hidden termite nests compared to traditional least squares (LS) inversion. Excavation verification results show that the maximum error in the horizontal center and top burial depth of the termite nest identified by GFL-Net is less than 7% and 16%, respectively. The research findings provide reliable technical support for the accurate identification of termite nest hidden dangers in embankments. Full article

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15 pages, 1210 KB

Open AccessArticle

AI-Driven Anomaly Detection in Cloud-Native Microservices: The Night’s Watch Algorithm

by Ghaith Dkmak, Baris Can, Orkun Sevinc, Cenk Burak Egeli, Fatih Baday and Bekir Cetintav

Appl. Sci. 2025, 15(23), 12762; https://doi.org/10.3390/app152312762 - 2 Dec 2025

Abstract

As organizations shift to microservice architectures, the need for effective anomaly detection becomes more critical. Classic approaches rely heavily on predefined thresholds or labeled data, both of which scale poorly in distributed and dynamic environments. This paper introduces the Night’s Watch algorithm, a [...] Read more.

As organizations shift to microservice architectures, the need for effective anomaly detection becomes more critical. Classic approaches rely heavily on predefined thresholds or labeled data, both of which scale poorly in distributed and dynamic environments. This paper introduces the Night’s Watch algorithm, a novel unsupervised method for detecting anomalies in microservices. By integrating multi-source data and temporal features, the algorithm addresses key limitations of existing approaches. Our experiments demonstrate that the Night’s Watch algorithm significantly improves precision (up to 92%) and recall (up to 39%) depending on the training set size. These results indicate that the algorithm can reduce false positives and enhance real-time anomaly detection in microservice environments. These findings contribute to the development of more robust AI-driven monitoring systems, advancing the state of anomaly detection in cloud-native architectures. Full article

17 pages, 1201 KB

Open AccessReview

Application of Plastic Waste as a Sustainable Bitumen Mixture—A Review

by Nuha S. Mashaan and Thakur Chamlagai

Appl. Sci. 2025, 15(23), 12761; https://doi.org/10.3390/app152312761 - 2 Dec 2025

Abstract

Plastic waste is growing rapidly, while asphalt binders remain heavily reliant on petroleum bitumen. Incorporating recycled plastics into bitumen can divert waste and enhance pavement performance. This review compiles 251 experimental records from 56 studies to evaluate how plastic type, dosage, and processing [...] Read more.

Plastic waste is growing rapidly, while asphalt binders remain heavily reliant on petroleum bitumen. Incorporating recycled plastics into bitumen can divert waste and enhance pavement performance. This review compiles 251 experimental records from 56 studies to evaluate how plastic type, dosage, and processing conditions affect softening point, penetration, and viscosity. Across studies, plastics (PET, LDPE/HDPE/LLDPE, PP, and hybrids) consistently stiffen binders, reducing penetration and increasing softening point and viscosity, thereby improving rutting resistance while potentially raising mixing/compaction demands. Using grouped cross-validated machine-learning models (median baseline, ridge, random forest, XGBoost), we quantify the predictability of binder properties and show that nonlinear methods outperform linear baselines for softening point. Prediction of penetration and viscosity shows larger scatter, reflecting study-to-study variability and incomplete reporting of key processing variables. We identify research needs in standardized testing, compatibility/dispersion characterization, and life-cycle assessment. The curated dataset and modeling workflow provide a data-driven foundation for designing durable, higher-performance plastic-modified binders. Full article

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21 pages, 577 KB

Open AccessReview

The Present and Future of Sarcopenia Diagnosis and Exercise Interventions: A Narrative Review

by Hongje Jang, Jeonghyeok Song, Jeonghun Kim, Hyeongmin Lee, Hyemin Lee, Hye-yeon Park, Huijin Shin, Yeah-eun Kwon, Yeji Kim and JongEun Yim

Appl. Sci. 2025, 15(23), 12760; https://doi.org/10.3390/app152312760 - 2 Dec 2025

Abstract

The aim of this review was to harmonize major consensus statements (European Working Group on Sarcopenia in Older People 2; Asian Working Group for Sarcopenia 2019; Foundation for the National Institutes of Health Sarcopenia Project operational criteria) into a stage- and setting-stratified algorithm. [...] Read more.

The aim of this review was to harmonize major consensus statements (European Working Group on Sarcopenia in Older People 2; Asian Working Group for Sarcopenia 2019; Foundation for the National Institutes of Health Sarcopenia Project operational criteria) into a stage- and setting-stratified algorithm. It maps diagnostic strata to dose-defined resistance and combined training, integrates multimodal and technology-enabled options (whole-body electrical muscle stimulation, whole-body vibration, virtual reality, AI-assisted telerehabilitation) with safety cues, and embeds nutrition (≥1.2 g/kg/day protein, vitamin D, key micronutrients) and education to sustain adherence. Sarcopenia is a consequential geriatric syndrome linked to falls, loss of independence, hospitalization, mortality, and psychosocial burden, yet translation to practice is hindered by heterogeneous definitions, diagnostics, and treatment guidance. Literature searches via PubMed/MEDLINE, EBSCO, SciELO, and Google Scholar (January 2000 to August 2025) yielded 354 records; after screening and deduplication, 132 peer-reviewed studies were included. We summarize tools for screening, strength, muscle mass, and function (e.g., Sarcopenia Five-Item Questionnaire, grip strength, dual-energy X-ray absorptiometry, gait speed) and identify resistance exercise as the cornerstone, with aerobic, balance, and flexibility training adding functional and metabolic benefits. Clinic-ready tables and figures operationalize a stepwise program across primary to severe sarcopenia and across acute or iatrogenic to community settings. Early screening plus structured, exercise-centered care, augmented by targeted nutrition and education, offers pragmatic, scalable benefits. Full article

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20 pages, 31487 KB

Open AccessArticle

Design and Implementation of a Companion Robot with LLM-Based Hierarchical Emotion Motion Generation

by Yoongu Lim, Jaeuk Cho, Duk-Yeon Lee, Dongwoon Choi and Dong-Wook Lee

Appl. Sci. 2025, 15(23), 12759; https://doi.org/10.3390/app152312759 - 2 Dec 2025

Abstract

Recently, human–robot interaction (HRI) with social robots has attracted significant attention. Among them, companion robots, which exhibit pet-like behaviors and interact with people primarily through non-verbal means, particularly require the generation of appropriate gestures. This paper presents the design and implementation of a [...] Read more.

Recently, human–robot interaction (HRI) with social robots has attracted significant attention. Among them, companion robots, which exhibit pet-like behaviors and interact with people primarily through non-verbal means, particularly require the generation of appropriate gestures. This paper presents the design and implementation of a companion cat robot, named PEPE, with a large language model (LLM)-based hierarchical emotional motion generation method. To design the cat-like companion robot, an analysis of feline emotional behaviors was conducted to identify the body parts and motions essential for effective emotional expression. Based on this analysis, the required degrees of freedom (DoFs) and structural configuration for PEPE were derived. To generate expressive gestures efficiently and reliably, a hierarchical LLM-based emotional motion generation method was proposed. The process defines the robot’s structural features, establishes a gesture generation code format, and incorporates emotion-based guidelines grounded in feline behavioral analysis to mitigate LLM hallucination and ensure physical feasibility. The proposed method was implemented on the physical robot, and eight emotional gestures were generated—Happy, Angry, Sad, Fearful, Joyful, Excited, Positive Feedback, and Negative Feedback. A user study with 15 participants was conducted to validate the system. The high-arousal gestures—Angry, Joyful, and Excited—were rated significantly above the neutral clarity threshold (p < 0.05), demonstrating clear user recognition. Meanwhile, low-arousal gestures exhibited neutral-level perceptions consistent with their subtle motion profiles. These results confirm that the proposed LLM-based framework effectively generates expressive, physically executable gestures for a companion robot. Full article

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Applied Sciences

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