Applied Sciences

19 pages, 4676 KB

Open AccessArticle

A Dual-Frame SLAM Framework for Simulation-Based Pre-Adjustment of Ballastless Track Geometry

by Bin Cui, Ran An, Zhao Tan, Chunyu Qi, Debin Shi and Qian Zhao

Appl. Sci. 2026, 16(2), 1148; https://doi.org/10.3390/app16021148 (registering DOI) - 22 Jan 2026

The geometric precision of ballastless tracks critically determines the performance and safety of high-speed railways. Traditional manual fine adjustment methods remain labor-intensive, iterative, and sensitive to human expertise, making it difficult to achieve sub-millimeter accuracy and global consistency. To address these challenges, this [...] Read more.

The geometric precision of ballastless tracks critically determines the performance and safety of high-speed railways. Traditional manual fine adjustment methods remain labor-intensive, iterative, and sensitive to human expertise, making it difficult to achieve sub-millimeter accuracy and global consistency. To address these challenges, this paper proposes a virtual-model–enabled pre-adjustment framework for high-speed ballastless track construction. The framework integrates a dual-frame SLAM-based and multi-sensor measurement system based on RC-SLAM principles and a local attitude compensation model, enabling accurate 3D mapping and reconstruction of long-track segments under extended-range and GNSS-denied conditions typical of linear infrastructure scenarios. A constraint-based global optimization algorithm is further developed to transform empirical fine adjustment into a computable geometric control problem, generating executable adjustment configurations with engineering feasibility. Field validation on a 1 km railway section demonstrates that the proposed method achieves sub-millimeter measurement accuracy, improves adjustment efficiency by over eight times compared with manual operations, and reduces material waste by $2800–$7000 per kilometer. This paper demonstrates a previously unexplored execution-level workflow for long-rail fine adjustment, establishing a closed-loop paradigm from measurement to predictive optimization and paving the way for SLAM-driven, simulation-based, and multi-sensor–integrated precision control in next-generation railway construction. Full article

(This article belongs to the Special Issue SLAM and Multi-Sensor Fusion for Robotics, Low-Altitude Remote Sensing, and 3D Applications)

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23 pages, 924 KB

Open AccessArticle

Test–Retest Reliability and Agreement of Postural Control Variables Within and Between Single-Leg Squat Variations

by Vasileios Chatziilias, Ioannis Kafetzakis and Dimitris Mandalidis

Appl. Sci. 2026, 16(2), 1147; https://doi.org/10.3390/app16021147 (registering DOI) - 22 Jan 2026

Abstract

Single-leg squats are commonly used to assess lower-limb strength and alignment; however, their application for evaluating postural control remains underexplored. This study assessed the reliability and agreement of postural control measures within and between unipedal squat variations. Twenty-eight physically active adults performed a [...] Read more.

Single-leg squats are commonly used to assess lower-limb strength and alignment; however, their application for evaluating postural control remains underexplored. This study assessed the reliability and agreement of postural control measures within and between unipedal squat variations. Twenty-eight physically active adults performed a conventional single-leg squat (CSLSQ), the anterior excursion of the Y-Balance Test (ANYBT), and a forward step-down (FRSTD) with both limbs on two occasions, 5–7 days apart. The mean values of five trials were analyzed for center-of-pressure (COP) 95% confidence ellipse area (95%CEA), path length (PL), velocity (VL), and mediolateral and anteroposterior variability (RMS-X and RMS-Y). Most COP variables demonstrated good-to-excellent reliability (ICC = 0.780–0.948), whereas RMS-X showed lower reliability (ICC = 0.367–0.803) and higher measurement error across limbs. The FRSTD demonstrated high ICCs (0.780–0.948) and low measurement error, comparable to the CSLSQ (0.794–0.940) and generally higher than the ANYBT (0.790–0.895), regardless of limb. Overall, the dominant limb exhibited higher ICCs and lower measurement error than the non-dominant limb. Inter-task agreement was greatest between the CSLSQ and FRSTD, primarily on the dominant limb, indicating greater potential interchangeability for selected COP metrics (95% CEA, VL, and RMS-Y). These findings may assist clinicians and sports scientists in selecting appropriate single-leg squat tasks and COP measures for assessment. Full article

(This article belongs to the Special Issue Recent Advances in the Prevention and Rehabilitation of ACL Injuries—2nd Edition)

28 pages, 9471 KB

Open AccessArticle

Shaking Table Test-Based Verification of PDEM for Random Seismic Response of Anchored Rock Slopes

by Xuegang Pan, Jinqing Jia and Lihua Zhang

Appl. Sci. 2026, 16(2), 1146; https://doi.org/10.3390/app16021146 (registering DOI) - 22 Jan 2026

Abstract

This study systematically verified the applicability and accuracy of the Probability Density Evolution Method (PDEM) in the probabilistic modeling of the dynamic response of anchored rock slopes under random seismic action through large-scale shaking table model tests. Across 144 sets of non-stationary random [...] Read more.

This study systematically verified the applicability and accuracy of the Probability Density Evolution Method (PDEM) in the probabilistic modeling of the dynamic response of anchored rock slopes under random seismic action through large-scale shaking table model tests. Across 144 sets of non-stationary random ground motions and 7 sets of white noise excitations, key response data such as acceleration, displacement, and changes in anchor axial force were collected. The PDEM was used to model the instantaneous probability density function (PDF) and cumulative distribution function (CDF), which were then compared with the results of normal distribution, Gumbel distribution, and direct sample statistics from multiple dimensions. The results show that the PDEM does not require a preset distribution form and can accurately reproduce the non-Gaussian, multi-modal, and time evolution characteristics of the response; in the reliability assessment of peak responses, its prediction deviation is much smaller than that of traditional parametric models; the three-dimensional probability density evolution cloud map further reveals the law governing the entire process of the response PDF from “narrow and high” in the early stage of the earthquake, “wide and flat” in the main shock stage, to “re-convergence” after the earthquake. The study confirms that the PDEM has significant advantages and engineering application value in the analysis of random seismic responses and the dynamic reliability assessment of anchored slopes. Full article

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12 pages, 2195 KB

Open AccessArticle

Field-Controlled Magnetisation Patterns in Three-Arm Star-Shaped Nanoparticles as Prototypes of Reconfigurable Routing and Vortex State Memory Devices

by Dominika Kuźma, Piotr Zegan, Yaroslav Parkhomenko and Piotr Zieliński

Appl. Sci. 2026, 16(2), 1145; https://doi.org/10.3390/app16021145 (registering DOI) - 22 Jan 2026

Abstract

A model of nanoparticles has been designed to partially resemble self-similar ferroelastic star-like domain textures. Numerical computations have been used to find the equilibrium configurations of magnetisation in such systems. As expected from the symmetry, the self-similar initial states give room to other [...] Read more.

A model of nanoparticles has been designed to partially resemble self-similar ferroelastic star-like domain textures. Numerical computations have been used to find the equilibrium configurations of magnetisation in such systems. As expected from the symmetry, the self-similar initial states give room to other types of domain structure as a function of the star parameters. When relaxed without an external field, the self-similar pattern mostly turns into a massive vortex in the centre with radially oriented domains in the star’s peripheral arms. In contrast, a random initial state ends up in a configuration of a triple valve with one input and two outputs, or vice versa, analogous to logical gates. A treatment with an in-plane magnetic field always leads to the valve configuration. The triple-valve states turn out stable, whereas the vortex ones are metastable. The results may be in the design of magnetic-based logic devices. Full article

(This article belongs to the Special Issue Application of Magnetic Nanoparticles)

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19 pages, 1323 KB

Open AccessArticle

Modernisation Potential of Civil Defence Shelters: Compliance Assessment and Risk-Based Retrofit Strategy in Poland

by Marlena Anna Jurczak and Maria Tunkiewicz

Appl. Sci. 2026, 16(2), 1144; https://doi.org/10.3390/app16021144 (registering DOI) - 22 Jan 2026

Abstract

Civil defence shelters constitute an essential component of safety systems in emergency situations. The aim of this article is to assess the modernization potential of existing civil defence shelters in Poland, using a representative facility located in Olsztyn (Poland) as a case study. [...] Read more.

Civil defence shelters constitute an essential component of safety systems in emergency situations. The aim of this article is to assess the modernization potential of existing civil defence shelters in Poland, using a representative facility located in Olsztyn (Poland) as a case study. The analysis is based on a review of the current legal framework and identification of legislative gaps that affect the implementation of effective protective solutions. Within the case study, a detailed technical assessment of the protective structure was carried out, focusing on construction, protection against radiation and contamination, fire safety, and user ergonomics. Based on this assessment, a comparative analysis was performed between the surveyed facility and current as well as proposed technical requirements. The results revealed partial compliance with regulations while identifying significant deficiencies. To address these issues, measures such as replacing ventilation units with modern systems featuring automatic control, installing EI120-certified doors, improving emergency exit dimensions, and adding emergency lighting were proposed. Subsequently, risks associated with modernization were identified in accordance with ISO 31000. The findings highlight the need for systematic modernization of existing protective structures, clarification of legal regulations, and increased investment, which are key conditions for improving civilian safety. Full article

(This article belongs to the Section Civil Engineering)

26 pages, 3037 KB

Open AccessArticle

Proactive Path Planning Using Centralized UAV-UGV Coordination in Semi-Structured Agricultural Environments

by Dimitris Katikaridis, Lefteris Benos, Dimitrios Kateris, Elpiniki Papageorgiou, George Karras, Ioannis Menexes, Remigio Berruto, Claus Grøn Sørensen and Dionysis Bochtis

Appl. Sci. 2026, 16(2), 1143; https://doi.org/10.3390/app16021143 (registering DOI) - 22 Jan 2026

Abstract

Unmanned ground vehicles (UGVs) in agriculture face challenges in navigating complex environments due to the presence of dynamic obstacles. This causes several practical problems including mission delays, higher energy consumption, and potential safety risks. This study addresses the challenge by shifting path planning [...] Read more.

Unmanned ground vehicles (UGVs) in agriculture face challenges in navigating complex environments due to the presence of dynamic obstacles. This causes several practical problems including mission delays, higher energy consumption, and potential safety risks. This study addresses the challenge by shifting path planning from reactive local avoidance to proactive global optimization. To that end, it integrates aerial imagery from an unmanned aerial vehicle (UAV) to identify dynamic obstacles using a low-latency YOLOv8 detection pipeline. These are translated into georeferenced exclusion zones for the UGV. The UGV follows the optimized path while relying on a LiDAR-based reactive protocol to autonomously detect and respond to any missed obstacles. A farm management information system is used as the central coordinator. The system was tested in 30 real-field trials in a walnut orchard for two distinct scenarios with varying worker and vehicle loads. The system achieved high mission success, with the UGV completing all tasks safely, with four partial successes caused by worker detection failures under afternoon shadows. UAV energy consumption remained stable, while UGV energy and mission time increased during reactive maneuvers. Communication latency was low and consistent. This enabled timely execution of both proactive and reactive navigation protocols. In conclusion, the present UAV–UGV system ensured efficient and safe navigation, demonstrating practical applicability in real orchard conditions. Full article

(This article belongs to the Special Issue The Use of Evolutionary Algorithms in Robotics)

19 pages, 1928 KB

Open AccessFeature PaperArticle

Effects of Voltage on the Microstructure and Properties of Micro-Arc Oxidation Coatings of Zirconium Alloy

by Yao Mu, Xinya Feng, Xingwei Liu, Shuo Li and Jinxu Liu

Appl. Sci. 2026, 16(2), 1142; https://doi.org/10.3390/app16021142 (registering DOI) - 22 Jan 2026

Abstract

To enhance the wear and corrosion resistance of Zr alloy components in marine engineering, this study investigated the influence of the applied voltage (ranging from 470 to 620 V) on the morphology, structure, and properties of ceramic coatings formed on a Zr alloy [...] Read more.

To enhance the wear and corrosion resistance of Zr alloy components in marine engineering, this study investigated the influence of the applied voltage (ranging from 470 to 620 V) on the morphology, structure, and properties of ceramic coatings formed on a Zr alloy substrate by Micro-arc Oxidation (MAO) in a silicate–phosphate composite electrolyte. The results showed that with increasing voltage, the coating thickness increased (from 15.12 to 52.80 μm) and the surface roughness increased (from 1.12 to 4.89 μm), while both the surface and cross-sectional porosity first increased and then reached their minimum values at 620 V (1.61% and 5.75%, respectively). Phase analyses indicated that the coatings consisted mainly of monoclinic ZrO₂ (m-ZrO₂), along with minor amounts of SiO₂, ZrSiO₄, and Zr₃(PO₄)₄. The coating prepared at 620 V exhibited optimal performance: its hardness was 1.98 times that of the substrate, the wear volume decreased by approximately 87%, the self-corrosion potential shifted positively by 539 mV, the corrosion current density decreased by nearly two orders of magnitude, and the polarization resistance increased by approximately two orders of magnitude. These results demonstrate a substantial improvement in the service performance of Zr alloys for marine applications. Full article

(This article belongs to the Special Issue Characterization and Mechanical Properties of Alloys)

30 pages, 6189 KB

Open AccessArticle

Shear Properties and User Material Modelling of Sandwich Panel Cores for Marine Structures

by Davor Bolf, Albert Zamarin, Marino Brčić and Domagoj Vrtovšnik

Appl. Sci. 2026, 16(2), 1141; https://doi.org/10.3390/app16021141 (registering DOI) - 22 Jan 2026

Abstract

In the design of marine structures, structural design remains a critical activity, heavily guided by classification society rules that define dimensions of the structural elements. With the development of increasingly complex structures and the increasing use of composite materials in ship structural design, [...] Read more.

In the design of marine structures, structural design remains a critical activity, heavily guided by classification society rules that define dimensions of the structural elements. With the development of increasingly complex structures and the increasing use of composite materials in ship structural design, accurate knowledge of material properties, particularly those of sandwich panel cores, is essential for direct calculations. This article presents experimental data and numerical analysis results for the PVC core of sandwich panels, the selection of appropriate material models from the LS-DYNA standard material database, and the development of a user-defined material model to accurately capture the physical behaviour of foam cores in sandwich constructions. The comprehensive dataset obtained from polymer foam tests is made publicly available to support future structural calculations. Full article

(This article belongs to the Special Issue State-of-the-Art in Computational Analysis of Machines, Mechanisms, Structures and Materials)

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23 pages, 15578 KB

Open AccessArticle

Cascaded Linear–Nonlinear Active Disturbance Rejection Control and Parameter Tuning of Magnetic Levitation Ball System

by Yubo Wang, Zhixian Zhong, Peng Liu and Meng Wang

Appl. Sci. 2026, 16(2), 1140; https://doi.org/10.3390/app16021140 (registering DOI) - 22 Jan 2026

Abstract

Due to the significant nonlinear characteristics of the magnetic bearing, it is difficult to establish an accurate mathematical model, and it is susceptible to external disturbances. Traditional control methods struggle to meet the control requirements. Active disturbance rejection control (ADRC) does not rely [...] Read more.

Due to the significant nonlinear characteristics of the magnetic bearing, it is difficult to establish an accurate mathematical model, and it is susceptible to external disturbances. Traditional control methods struggle to meet the control requirements. Active disturbance rejection control (ADRC) does not rely on accurate models and has outstanding anti-interference ability. In order to improve the anti-disturbance ability and control stability of the system, a cascaded linear–nonlinear active disturbance rejection control method (CL-NLADRC) based on the improved artificial jellyfish algorithm is proposed and applied to the magnetic levitation ball system. Firstly, the mathematical model of the magnetic levitation ball system is established, and based on this model, a cascaded linear–nonlinear extended state observer is constructed to estimate and compensate for the system state, thereby enhancing the dynamic response capability of the system. Subsequently, the tangent spiral motion and the lens reversal learning strategy are introduced to improve the artificial jellyfish algorithm to further improve the global optimization performance of the algorithm. Finally, the improved artificial jellyfish algorithm is used to optimize the CL-NLADRC controller parameters. The simulation and experimental results show that compared with the traditional LADRC and PID controllers, the proposed CL-NLADRC has a significant improvement in the steady-state error, response speed, and anti-disturbance performance of the system. Among them, the root mean square error decreased by 14% and 47%, respectively, which verified the effectiveness and stability of the method in the magnetic levitation ball system. Full article

15 pages, 2333 KB

Open AccessArticle

Prediction of Fatigue Damage Evolution in 3D-Printed CFRP Based on Ultrasonic Testing and LSTM

by Erzhuo Li, Sha Xu, Hongqing Wan, Hao Chen, Yali Yang and Yongfang Li

Appl. Sci. 2026, 16(2), 1139; https://doi.org/10.3390/app16021139 (registering DOI) - 22 Jan 2026

Abstract

To address the prediction of fatigue damage for 3D-printed Carbon Fiber Reinforced Polymer (CFRP), this study used 3D-printing technology to fabricate CFRP specimens. Through multi-stage fatigue testing, samples with varying porosity levels were obtained. Based on porosity test results and ultrasonic attenuation coefficient [...] Read more.

To address the prediction of fatigue damage for 3D-printed Carbon Fiber Reinforced Polymer (CFRP), this study used 3D-printing technology to fabricate CFRP specimens. Through multi-stage fatigue testing, samples with varying porosity levels were obtained. Based on porosity test results and ultrasonic attenuation coefficient measurements of specimens under different fatigue cycle counts, a quantitative relationship model was established between the porosity and ultrasonic attenuation coefficient of 3D-printed CFRP. According to the porosity and fatigue-loading cycles obtained from tests, the Time-series Generative Adversarial Network (TimeGAN) algorithm was employed for data augmentation to meet the requirements for neural-network training. Subsequently, the Long Short-Term Memory (LSTM) neural network was utilized to predict the fatigue damage evolution of 3D-printed CFRP specimens. Research findings indicate that by integrating the established relationship between porosity and ultrasonic attenuation coefficient, non-destructive testing of material fatigue damage evolution based on ultrasonic attenuation coefficient can be achieved. Full article

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14 pages, 281 KB

Open AccessArticle

Comparative Cephalometric Norms for Skeletal Class I Adults: A Study of Yemeni and Turkish Cypriot Populations

by Amr Mustafa Al Muhaya, Orhan Özdiler and Lale Taner

Appl. Sci. 2026, 16(2), 1138; https://doi.org/10.3390/app16021138 (registering DOI) - 22 Jan 2026

Abstract

Background: The shift toward precision orthodontics necessitates population-specific cephalometric databases. Reliance on Eurocentric norms for ethnically diverse populations—particularly underrepresented Middle Eastern groups—represents a significant evidence gap. This study establishes initial normative cephalometric data for Yemeni and Northern Turkish Cypriot (NTC) adults. Methods: This [...] Read more.

Background: The shift toward precision orthodontics necessitates population-specific cephalometric databases. Reliance on Eurocentric norms for ethnically diverse populations—particularly underrepresented Middle Eastern groups—represents a significant evidence gap. This study establishes initial normative cephalometric data for Yemeni and Northern Turkish Cypriot (NTC) adults. Methods: This retrospective comparative study analyzed 400 lateral cephalograms from skeletal Class I adults (200 Yemeni and 200 NTC; age 18–40; gender-balanced). Twenty standardized parameters were assessed using VistaDent OC™ software (version 4.2.61, GAC Orthodontic Software solutions, Birmingham, AL, USA). Analyses included *t*-tests, MANOVA, effect size computations (Cohen’s *d*), and variance partitioning. The False Discovery Rate method controlled multiple comparisons. Results: Yemeni adults exhibited a more vertical facial growth pattern (indicated by a lower Jarabak ratio: 60.18 ± 4.50% vs. 65.79 ± 5.20%; *d* = 1.15) and pronounced soft-tissue convexity (N-A-Pog: 5.76 ± 1.20 mm vs. 3.82 ± 1.10 mm; *d* =1.69). NTC adults showed a mild skeletal Class II tendency (ANB: 4.51 ± 1.70° vs. 3.35 ± 1.50°; *d* = 0.72). Ethnicity accounted for 21.3% of craniofacial variance (partial η² = 0.213). Conclusions: This study provides foundational cephalometric reference data for two underrepresented populations. The significant morphological distinctions quantified here underscore the necessity of developing population-specific norms. These data should be considered as one component within comprehensive, individualized diagnostic frameworks in orthodontics, rather than standalone diagnostic criteria. Full article

(This article belongs to the Section Applied Dentistry and Oral Sciences)

23 pages, 3977 KB

Open AccessArticle

Study on Waveform Superposition and Ultrasonic Gain During Nonlinear Propagation of Ultrasound in Fibrin Clots

by Linlin Zhang, Xiaomin Zhang, Fan Mo and Zhipeng Zhao

Appl. Sci. 2026, 16(2), 1137; https://doi.org/10.3390/app16021137 (registering DOI) - 22 Jan 2026

Abstract

Fibrin clots with strain-hardening characteristics exhibit pronounced material nonlinearity and acoustic dispersion under ultrasound, leading to waveform distortion and shock formation during finite-amplitude wave propagation. However, peak-shock stress is limited by viscoelastic dissipation and dispersion, constraining the efficiency of ultrasound in applications such [...] Read more.

Fibrin clots with strain-hardening characteristics exhibit pronounced material nonlinearity and acoustic dispersion under ultrasound, leading to waveform distortion and shock formation during finite-amplitude wave propagation. However, peak-shock stress is limited by viscoelastic dissipation and dispersion, constraining the efficiency of ultrasound in applications such as thrombus ablation. To overcome this limitation, a shock wave amplification method using designed multi-wave-packet sequences is proposed. Based on a power-law model from quasi-static compression tests, shock generation under a single sinusoidal pulse was first simulated. The dual-wave-packet chasing strategy was then developed, in which the amplitude, frequency, and time delay of the second packet were tuned to achieve effective superposition with the precursor. The waveform superposition factor (WSF) was introduced for quantitative evaluation. Numerical results demonstrate that this strategy can significantly increase the peak-shock-wave stress, with a maximum gain of 22.7%. Parametric analysis further identified amplitude as the dominant factor influencing wavefront steepness and amplification effectiveness. This study provides a novel method and theoretical support for developing efficient and controllable ultrasonic sequences for thrombolysis. Full article

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12 pages, 681 KB

Open AccessArticle

Second-Harmonic Generation in Optical Fibers Under an External Electric Field

by Lanlan Liu, Chongqing Wu, Zihe Huang, Linkai Xia and Kaihong Wang

Appl. Sci. 2026, 16(2), 1136; https://doi.org/10.3390/app16021136 (registering DOI) - 22 Jan 2026

Abstract

A method for the second-harmonic generation (SHG) in optical fibers by exploiting the third-order nonlinearity under an external electric field is proposed. The analysis begins with the electric polarization vector of the SHG, and the analytical solution for the SHG is presented. When [...] Read more.

A method for the second-harmonic generation (SHG) in optical fibers by exploiting the third-order nonlinearity under an external electric field is proposed. The analysis begins with the electric polarization vector of the SHG, and the analytical solution for the SHG is presented. When fiber birefringence is neglected, a mode-field matching condition is introduced. The nonlinearity-induced shift in propagation constant is provided based on Gaussian approximation. For a specific case, the power of SHG is calculated. The results show that the SHG power scales quadratically with the nonlinear coefficient. Reducing the effective area of the fiber and increasing the nonlinear coefficient can enhance the SHG power by 1–2 orders of magnitude. Since phase matching strongly affects the SHG process, optimizing the fiber design is crucial. Additionally, the polarization state of SHG is shown to have the same as the equivalent optical field of the injected fundamental wave. This work demonstrates potential for distributed sensing of electric fields and lightning events in high-voltage power grids using optical fibers. Full article

(This article belongs to the Special Issue Applications of Nonlinear Optical Devices and Materials)

26 pages, 2500 KB

Open AccessArticle

Improving the Efficiency of Collaboration Between Humans and Embodied AI Agents in 3D Virtual Environments

by Seowon Han and Kang Hoon Lee

Appl. Sci. 2026, 16(2), 1135; https://doi.org/10.3390/app16021135 (registering DOI) - 22 Jan 2026

Abstract

This study proposes a human-in-the-loop dynamic graph-based planning framework designed to elevate LLM-based Embodied Agents from simple tools to trustworthy collaborative partners. To achieve this, we address the trade-off between the structural rigidity of plan-centric approaches and the instability of reactive methods. The [...] Read more.

This study proposes a human-in-the-loop dynamic graph-based planning framework designed to elevate LLM-based Embodied Agents from simple tools to trustworthy collaborative partners. To achieve this, we address the trade-off between the structural rigidity of plan-centric approaches and the instability of reactive methods. The framework utilizes a Directed Acyclic Graph (DAG) with AND/OR nodes to ensure robustness while maintaining flexibility. Critically, the agent features an Automated Recovery Mechanism for self-correction and a Dynamic Modification Mechanism that employs Relevance Analysis to effectively translate human interventions (Switch, Add, Delete) into graph updates. Comparative experiments in Minecraft with 30 participants validated the method’s effectiveness. The proposed agent (Agent B) outperformed the reactive baseline (Agent A), reducing mission completion time by 9.3%. Notably, the agent demonstrated high instruction compliance and reduced user frustration by approximately 20%, leading to statistically higher satisfaction scores (PSSUQ). These results confirm that by ensuring planning robustness and responsiveness, the proposed framework successfully enables agents to function as trustworthy partners in complex environments. Full article

(This article belongs to the Special Issue Augmented and Virtual Reality for Smart Applications)

19 pages, 813 KB

Open AccessSystematic Review

Neural Network Architectures in Video Capsule Endoscopy: A Systematic Review and Meta-Analysis on Accuracy and Reading Time Performances

by Daniele Salvi, Chiara Zani, Cristiano Spada, Stefania Piccirelli, Lorenzo Zileri Dal Verme, Giulia Tripodi, Loredana Gualtieri, Paola Cesaro and Clarissa Ferrari

Appl. Sci. 2026, 16(2), 1134; https://doi.org/10.3390/app16021134 (registering DOI) - 22 Jan 2026

Abstract

Artificial intelligence (AI) has revolutionized medical image analysis. Several neural network (NN) architectures were developed and applied across the last decade, becoming essential for automated diagnosis and clinical applications. AI based on NNs has become increasingly integrated into gastroenterology, offering new opportunities for [...] Read more.

Artificial intelligence (AI) has revolutionized medical image analysis. Several neural network (NN) architectures were developed and applied across the last decade, becoming essential for automated diagnosis and clinical applications. AI based on NNs has become increasingly integrated into gastroenterology, offering new opportunities for automated lesion detection and workflow optimization. Small-bowel capsule endoscopy (SBCE) has benefited substantially from these advances, addressing long-standing challenges such as time-consuming video review and variability among readers. This systematic review and meta-analysis evaluated neural network-based models for lesion detection in SBCE, assessing pooled diagnostic accuracy and the impact of AI on reading time. A total of 44 primary studies were included: 36 validation studies for accuracy and 9 clinical studies for reading time. All NN architectures demonstrated high diagnostic performance, with a pooled accuracy of 95.3% (95% CI: 94.1–96.5%). More recent architectures, including transformer-based and capsule networks, outperformed classical convolutional neural networks (CNNs). AI assistance significantly reduced SBCE reading time, with a pooled mean reduction of 84% compared to standard review. These findings highlight the strong potential of AI to enhance SBCE efficiency and diagnostic reliability. Full article

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

16 pages, 442 KB

Open AccessArticle

Valorization of Chestnut Outer Shell, a Waste Biomass from the Chestnut Supply Chain: Source of Phenols or Additive for Breadmaking

by Agnese Spadi, Giulia Angeloni, Alessio Cappelli, Ferdinando Corti, Alessandro Parenti and Piernicola Masella

Appl. Sci. 2026, 16(2), 1133; https://doi.org/10.3390/app16021133 (registering DOI) - 22 Jan 2026

Abstract

Global chestnut production has grown significantly in recent years, driven by its health benefits and growing interest in sustainable agriculture. Chestnut processing produces a solid residue consisting primarily of the fruit’s outer shell (pericarp), which is generally disposed of by on-farm combustion. However, [...] Read more.

Global chestnut production has grown significantly in recent years, driven by its health benefits and growing interest in sustainable agriculture. Chestnut processing produces a solid residue consisting primarily of the fruit’s outer shell (pericarp), which is generally disposed of by on-farm combustion. However, this waste biomass shows a high potential for valorization due to its nutritional composition, particularly as a source of dietary fiber and polyphenols. In this study, the valorization potential of chestnut outer shells was evaluated through two approaches, demonstrating possible applicability at an industrial level: (1) the recovery of polyphenols using a simple and environmentally friendly extraction method, easily applicable on-farm, based on hot water as a solvent under different time–temperature combinations according to Response Surface Methodology (Central Composite Design); (2) the addition of chestnut outer shell flour during breadmaking as a source of fiber supplementation. Optimization of the extraction process using Response Surface Methodology combined with the desirability function identified optimal conditions at 102 min and 115 °C, yielding a maximum of approximately 172.30 mg of polyphenols per gram of dry outer shell. The incorporation of chestnut outer shell flour into bread formulations resulted in reduced dough workability, increased crust hardness (13.00 ± 0.87; 36.00 ± 1.00), and a darker bread color (1278.33 ± 39.27; 584.33 ± 25.90 RGB), particularly in the crumb. Full article

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

21 pages, 8730 KB

Open AccessArticle

Characteristics of Stratum Disturbance During the Construction of Dual-Line Shield Tunnels with Consideration of Soil Spatial Variability

by Yuan Lyu, Yong Liu, Chaoqun Huang, Zehang Wang, Dong Huang, Jing Peng and Xuedong Luo

Appl. Sci. 2026, 16(2), 1132; https://doi.org/10.3390/app16021132 (registering DOI) - 22 Jan 2026

Abstract

Soil spatial variability is an inherent feature of natural strata, and random field theory provides an effective framework for quantifying it, aiding accurate deformation prediction. This study focuses on the tunnel section between Kepugongyuan and Gangduhuayuan Stations on Wuhan Metro Line 12. Its [...] Read more.

Soil spatial variability is an inherent feature of natural strata, and random field theory provides an effective framework for quantifying it, aiding accurate deformation prediction. This study focuses on the tunnel section between Kepugongyuan and Gangduhuayuan Stations on Wuhan Metro Line 12. Its novelty focuses on analyzing dual-line shield-induced ground response with explicit consideration of multi-layer soil spatial variability. It examines the effects of the coefficient of variation and the horizontal/vertical spatial correlation distances of cohesion, internal friction angle, and elastic modulus—considering multilayer soil variability—on ground disturbance induced by twin-tunnel shield construction. The main findings include the following: (1) In cross-section, the settlement trough transitions from a “W”-shaped double trough to a “V”-shaped single trough as excavation advances, with the settlement center moving toward the midpoint between the tunnels. Longitudinally, soil heaves ahead of the shield and settles behind. (2) Ignoring spatial variability results in underestimated deformations; nearly 80% of stochastic simulations produced larger maximum surface settlements compared to deterministic analysis. (3) Ground loss and shield thrust disturbance are categorized into four zones based on tunnel diameter (D): Disturbance Zone, Secondary Zone, Transition Zone, and Undisturbed Zone. These findings provide practical guidance for predicting ground deformation and managing settlement-related risks in urban dual-line shield projects. Full article

(This article belongs to the Special Issue Application and Development of New Materials and Intelligent Technologies in Civil Engineering Construction)

22 pages, 392 KB

Open AccessArticle

PROMETHEE-Based Ranking of EU Countries Across Key Agricultural and Environmental Indicators

by Stefanos Tsiaras and Spyridon Mantzoukas

Appl. Sci. 2026, 16(2), 1131; https://doi.org/10.3390/app16021131 (registering DOI) - 22 Jan 2026

Abstract

This study evaluates the agri-environmental performance of the EU-27 Member States using the PROMETHEE multiple-criteria decision analysis method, based on three Eurostat indicators linked to the sustainability pillars: Harmonized Risk Indicator 1 (HRI1, social pillar), pesticide sales intensity (kg/ha UAA, environmental pillar), and [...] Read more.

This study evaluates the agri-environmental performance of the EU-27 Member States using the PROMETHEE multiple-criteria decision analysis method, based on three Eurostat indicators linked to the sustainability pillars: Harmonized Risk Indicator 1 (HRI1, social pillar), pesticide sales intensity (kg/ha UAA, environmental pillar), and environmental protection investments (% GDP, economic pillar). The analysis uses the most recent available Eurostat data (primarily from 2023) and examines three weighting scenarios: (i) equal weights, (ii) higher emphasis on the economic pillar, and (iii) higher emphasis on the environmental and social pillars. Across all scenarios, Slovenia ranked first (net flow, φ = 0.4173 to 0.4734), followed by Czechia (φ = 0.2796 to 0.3260) and France (φ = 0.1886 to 0.2240), while Malta (φ = −0.3356 to −0.3691), Cyprus (φ = −0.2916 to −0.3027), and Estonia (φ = −0.2641 to −0.2903) consistently occupied the lowest positions. The stability of rankings across alternative weighting schemes indicates robust performance patterns, with minimal shifts for most Member States. Overall, the results highlight persistent cross-country differences in agri-environmental performance despite common EU regulatory frameworks, underlining the relevance of national implementation capacity and investment strategies. The proposed PROMETHEE-based ranking provides a transparent and policy-aligned benchmarking tool that can support monitoring and prioritization of interventions related to pesticide risk reduction and environmental investment across EU Member States. Full article

(This article belongs to the Section Applied Biosciences and Bioengineering)

18 pages, 3170 KB

Open AccessArticle

Grey Wolf Optimization-Optimized Ensemble Models for Predicting the Uniaxial Compressive Strength of Rocks

by Xigui Zheng, Arzoo Batool, Santosh Kumar and Niaz Muhammad Shahani

Appl. Sci. 2026, 16(2), 1130; https://doi.org/10.3390/app16021130 (registering DOI) - 22 Jan 2026

Abstract

Reliable models for predicting the uniaxial compressive strength (UCS) of rocks are crucial for mining operations and rock engineering design. Empirical methods, including statistical methods, are often faced with many limitations when generalizing in a wide range of lithological types. To address this [...] Read more.

Reliable models for predicting the uniaxial compressive strength (UCS) of rocks are crucial for mining operations and rock engineering design. Empirical methods, including statistical methods, are often faced with many limitations when generalizing in a wide range of lithological types. To address this limitation, this study investigates the capability of grey wolf optimization (GWO)-optimized ensemble machine learning models, including decision tree (DT), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost) for predicting UCS using a small dataset of easily measurable and non-destructive rock index properties. The study’s objective is to evaluate whether metaheuristic-based hyperparameter optimization can enhance model robustness and generalization performance under small-sample conditions. A unified experimental framework incorporating GWO-based optimization, three-fold cross-validation, sensitivity analysis, and multiple statistical performance indicators was implemented. The findings of this study confirm that although the GWO-XGBoost model achieves the highest training accuracy, it exhibits signs of mild overfitting. In contrast, the GWO-AdaBoost model outpaced with significant improvement in terms of coefficient of determination (R²) = 0.993, root mean square error (RMSE) = 2.2830, mean absolute error (MAE) = 1.6853, and mean absolute percentage error (MAPE) = 4.6974. Therefore, the GWO-AdaBoost has proven to be the most effective in terms of its prediction potential of UCS, with significant potential for adaptation due to its effectively learned parameters. From a theoretical perspective, this study highlights the non-equivalence between training accuracy and predictive reliability in UCS modeling. Practically, the findings support the use of GWO-AdaBoost as a reliable decision-support tool for preliminary rock strength assessment in mining and geotechnical engineering, particularly when comprehensive laboratory testing is not feasible. Full article

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