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25 pages, 2357 KB  
Article
Gradient-Based Calibration of a Precipitation Hardening Model for 6xxx Series Aluminium Alloys
by Amir Alizadeh, Maaouia Souissi, Mian Zhou and Hamid Assadi
Metals 2025, 15(9), 1035; https://doi.org/10.3390/met15091035 (registering DOI) - 19 Sep 2025
Abstract
Precipitation hardening is the primary mechanism for strengthening 6xxx series aluminium alloys. The characteristics of the precipitates play a crucial role in determining the mechanical properties. In particular, predicting yield strength (YS) based on microstructure is experimentally complex and costly because its key [...] Read more.
Precipitation hardening is the primary mechanism for strengthening 6xxx series aluminium alloys. The characteristics of the precipitates play a crucial role in determining the mechanical properties. In particular, predicting yield strength (YS) based on microstructure is experimentally complex and costly because its key variables, such as precipitate radius, spacing, and volume fraction (VF), are difficult to measure. Physics-based models have emerged to tackle these complications utilising advancements in simulation environments. Nevertheless, pure physics-based models require numerous free parameters and ongoing debates over governing equations. Conversely, purely data-driven models struggle with insufficient datasets and physical interpretability. Moreover, the complex dynamics between internal model variables has led both approaches to adopt heuristic optimisation methods, such as the Powell or Nelder–Mead methods, which fail to exploit valuable gradient information. To overcome these issues, we propose a gradient-based optimisation for the Kampmann–Wagner Numerical (KWN) model, incorporating CALPHAD (CALculation of PHAse Diagrams) and a strength model. Our modifications include facilitating differentiability via smoothed approximations of conditional logic, optimising non-linear combinations of free parameters, and reducing computational complexity through a single size-class assumption. Model calibration is guided by a mean squared error (MSE) loss function that aligns the YS predictions with interpolated experimental data using L2 regularisation for penalising deviations from a purely physics-based modelling structure. A comparison shows that the gradient-based adaptive moment estimation (ADAM) outperforms the gradient-free Powell and Nelder–Mead methods by converging faster, requiring fewer evaluations, and yielding more physically plausible parameters, highlighting the importance of calibration techniques in the modelling of 6xxx series precipitation hardening. Full article
(This article belongs to the Special Issue Modeling Thermodynamic Systems and Optimizing Metallurgical Processes)
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11 pages, 248 KB  
Article
Cutibacterium acnes Phylotyping and Antibiotic Resistance to Six Antibiotics: A Bulgarian Study
by Lyudmila Boyanova, Georgi Dimitrov, Vessela Raykova, Kircho Patrikov, Raina Gergova and Rumyana Markovska
Microorganisms 2025, 13(9), 2185; https://doi.org/10.3390/microorganisms13092185 (registering DOI) - 19 Sep 2025
Abstract
Cutibacterium acnes subspecies/phylotypes can cause infections requiring antibiotic therapy. Phylotyping of 73 (55 acneic and 18 non-acneic) C. acnes strains was performed, and antibiotic susceptibility was tested by E tests, breakpoint susceptibility test, or disk diffusion method. The dominant phylotype in both acneic [...] Read more.
Cutibacterium acnes subspecies/phylotypes can cause infections requiring antibiotic therapy. Phylotyping of 73 (55 acneic and 18 non-acneic) C. acnes strains was performed, and antibiotic susceptibility was tested by E tests, breakpoint susceptibility test, or disk diffusion method. The dominant phylotype in both acneic and non-acneic strains was IA1 (56.2%). Phylotype II was >3-fold more frequent in non-acneic than acneic isolates. Resistance in acneic strains was >41% for clindamycin, 36.4% for tetracycline and 15.9% for levofloxacin, and that in non-acneic strains was >38% for clindamycin, 22.2% for tetracycline and 5.6% for levofloxacin. No strain was piperacillin/tazobactam or vancomycin resistant. Amoxicillin resistance was found in both acneic (5.4%) and non-acneic strains (11.1%), and was rare (1.8%) in phylotype I but higher (23.5%) in other strains. Double resistance was found in 32.6% of acneic and 22.2% of the non-acneic strains, and 9.3% of acneic strains displayed multidrug resistance. In conclusion, IA1 phylotype was dominant in both acneic and non-acneic strains, and type II was more frequent in non-acneic isolates. The detection (at >6%) of amoxicillin resistance represents a rare yet important finding. The presence of double/multidrug resistance strongly implies the need of susceptibility-guided therapy of the associated infections. Full article
(This article belongs to the Special Issue Healthcare-Associated Infections and Antimicrobial Therapy—2nd Edition)
13 pages, 1711 KB  
Article
Pilot Study of Genetic Diversity and Structure in Elite Germplasm of Hibiscus syriacus
by Yan Gao, Wei Yan and Chunying Zhang
Plants 2025, 14(18), 2909; https://doi.org/10.3390/plants14182909 (registering DOI) - 19 Sep 2025
Abstract
Rose of Sharon (Hibiscus syriacus L.) is an important perennial deciduous ornamental plant, featured by the daily flowering habit and a prolonged flowering period. However, the genetic relationships of the elite germplasmare largely unclear, which hampers the breeding programs of H. syriacus [...] Read more.
Rose of Sharon (Hibiscus syriacus L.) is an important perennial deciduous ornamental plant, featured by the daily flowering habit and a prolonged flowering period. However, the genetic relationships of the elite germplasmare largely unclear, which hampers the breeding programs of H. syriacus. Here, we analyzed the genetic diversity andstructure of 46 cultivars by employing a combination of 10 simple sequence repeat (SSR) and 5 inter-simple sequence repeat (ISSR) polymorphicmarkers. On average, 1.251 effective alleles per locus were detected for the SSR markers, in contrast to 1.321 for ISSR. Consistently, these elite accessions were grouped into five clades when using either marker or a combination of both, albeit with some differences. In the combined topology, clade II contains three relatively less multiple-petaled accessions, “Notwoodone” and its branch mutant “Bricutts”, as well as H. syriacus var. Shigyoku. By contrast, “Duc de Brabant” and “Mindour1” are both pink multiple-petaled accessions in clade III, in addition to a solo single-petaled “Oiseau Bleu” in clade I. Clade V was the largest group of 34 accessions, which account for 73.9% of the evaluated Hibiscus varieties and cluster into six subclasses. Overall, these varieties have some morphological variances in both patterns and colors of flowers. They show similarities in subclass scale, as exemplified by “Lady Stanley” and its branch mutant, “America Irene Scott”. The distantly related varieties, like in clade I and clade V, would benefit for breeding new varieties of high-hybrid vigor. Together, we updated a pilot study of the genetic diversity andstructure in elite varieties of H. syriacus, which could provide new insights into marker-assisted selection and genetic breeding of new varieties. Full article
(This article belongs to the Section Plant Systematics, Taxonomy, Nomenclature and Classification)
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12 pages, 393 KB  
Article
Evolution of Perioperative Outcomes in Robot-Assisted Radical Cystectomy over 20 Years of Experience in a High-Volume Tertiary Robotic Center
by Simone Morra, Stefano Resca, Nicola Frego, Sara Tamburini, Marco Ticonosco, Alessandro Pissavini, Andrea Noya Mourullo, Francesco Barletta, Mario de Angelis, Edward Lambert, Frederiek D’Hondt, Ruben De Groote, Geert De Naeyer and Alexandre Mottrie
Cancers 2025, 17(18), 3060; https://doi.org/10.3390/cancers17183060 (registering DOI) - 19 Sep 2025
Abstract
Background/Objectives: Robot-assisted radical cystectomy (RARC) has demonstrated improved perioperative outcomes and recovery in bladder cancer (BCa) patients. This study compares patient and tumor characteristics, operative time (OT), length of stay (LOS), and complication rates between a historical (2003–2016) and a contemporary cohort (2017–2024) [...] Read more.
Background/Objectives: Robot-assisted radical cystectomy (RARC) has demonstrated improved perioperative outcomes and recovery in bladder cancer (BCa) patients. This study compares patient and tumor characteristics, operative time (OT), length of stay (LOS), and complication rates between a historical (2003–2016) and a contemporary cohort (2017–2024) treated at a high-volume robotic center. Methods: Data from 274 BCa patients who underwent RARC at AZORG Hospital, Aalst, Belgium, were analyzed. Perioperative outcomes were compared between cohorts. Multivariable Poisson regression models identified predictors of longer OT and LOS, while multivariable logistic regression models (MLRMs) assessed predictors of higher complication rates. Results: Overall, 274 BCa patients who underwent RARC were identified (38% historical cohort vs. 62% contemporary cohort). The contemporary cohort had a significantly shorter median OT (345 vs. 360 min; p = 0.048) and LOS (8 vs. 12 days; p < 0.001) compared to the historical cohort. Postoperative complications were lower in the contemporary group, with more cases experiencing no complications (60% vs. 41%) and fewer grade 3–4 complications (10% vs. 27%; p < 0.001). In multivariable Poisson regression, the contemporary cohort was an independent predictor of shorter OT (Incidence Rate Ratio [IRR]: 0.94, 95% [Confidence Interval] CI: 0.93–0.96; p = 0.04) and shorter LOS (IRR: 0.65, 95% CI: 0.60–0.69; p < 0.001). In MLRMs predicting complications, the contemporary cohort was associated with lower risk (Odds Ratio: 0.42, 95% CI: 0.23–0.76; p = 0.005). Conclusions: RARC outcomes improved significantly over time, with reduced OT, LOS, and complication rates in the contemporary cohort, highlighting advancements in surgical techniques, perioperative care, and patient safety. These findings reinforce the role of RARC in optimizing BCa treatment. Full article
(This article belongs to the Special Issue Clinical Outcomes in Urologic Cancers)
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9 pages, 248 KB  
Article
Fixed-Point Theorem with a Novel Contraction Approach in Banach Algebras
by Hamza El Bazi, Younes Lahraoui, Cheng-Chi Lee, Loubna Omri and Abdellatif Sadrati
Mathematics 2025, 13(18), 3024; https://doi.org/10.3390/math13183024 (registering DOI) - 19 Sep 2025
Abstract
In this paper, we establish a fixed-point theorem for mixed monotone operators in ordered Banach algebras by introducing a novel contraction condition formulated in terms of the product law, which represents a significant departure from the traditional additive approach. By exploiting the underlying [...] Read more.
In this paper, we establish a fixed-point theorem for mixed monotone operators in ordered Banach algebras by introducing a novel contraction condition formulated in terms of the product law, which represents a significant departure from the traditional additive approach. By exploiting the underlying algebraic structure, our method ensures both the existence and uniqueness of fixed points under broader conditions. To illustrate the effectiveness of the proposed theorem, we also provide a concrete example that demonstrates its applicability. Full article
26 pages, 8999 KB  
Article
Experimental Study on Overlay Tester of Asphalt Mixture Based on Discrete Element Method
by Jianhui Wei, Xiangyang Fan and Tao Fu
Coatings 2025, 15(9), 1097; https://doi.org/10.3390/coatings15091097 (registering DOI) - 19 Sep 2025
Abstract
To evaluate the feasibility of a virtual overlay tester (OT), a modeling approach was proposed based on the discrete element method (DEM). Simulations were conducted on three types of asphalt mixtures across three different thickness conditions. Through the analysis of the load/displacement curves, [...] Read more.
To evaluate the feasibility of a virtual overlay tester (OT), a modeling approach was proposed based on the discrete element method (DEM). Simulations were conducted on three types of asphalt mixtures across three different thickness conditions. Through the analysis of the load/displacement curves, crack propagation paths, force chains, and contact force characteristics, it was observed that the peak loads decrease with increasing thicknesses, indicating a notable size effect. The complexity of the crack path was positively correlated with the particle size along the path and the fractal dimension. Coarse aggregates can inhibit crack propagation to some extent. Prior to reaching the peak load, compressive force chains in asphalt concrete-13 (AC13) and large stone porous asphalt mixture-30 (LSPM30) exhibited a symmetrical and divergent distribution along the crack, while tensile force chains formed an arch-like pattern. After the peak load, compressive force chains were symmetrically distributed in an arch shape along the crack. In stone mastic asphalt-13 (SMA13), compressive forces were transmitted along coarse aggregates, forming several continuous vertical paths. The proportion of strong compressive force chains to total compressive force chains across the three gradations ranged from 0.74 to 0.83, while the corresponding proportion for tensile force chains ranged from 0.72 to 0.78. Full article
(This article belongs to the Special Issue Novel Cleaner Materials for Pavements)
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11 pages, 3412 KB  
Article
Friction Coefficient Tests for Designs of Belt Conveyor Drive Systems
by Dariusz Woźniak
Appl. Sci. 2025, 15(18), 10204; https://doi.org/10.3390/app151810204 (registering DOI) - 19 Sep 2025
Abstract
In conveyor belt drive pulleys and intermediate belt drives, the power transferred from the drive system to the belt increases together with the increasing friction coefficient between the belt surface and the pulley surface, or between the surface of the main (carrying) belt [...] Read more.
In conveyor belt drive pulleys and intermediate belt drives, the power transferred from the drive system to the belt increases together with the increasing friction coefficient between the belt surface and the pulley surface, or between the surface of the main (carrying) belt and the surface of the intermediate (drive) belt. Belt conveyors used in the mining industry are typically exposed to dust and moisture. This paper presents the method and results of laboratory tests on the friction coefficient between a conveyor belt and rubber plates with grooved and flat surfaces. The tests were performed for different mine-typical contamination conditions of these surfaces. The results demonstrate that in the case of dry friction (regardless of the presence of dust), the grooving of the surface does not significantly affect the friction coefficient of the rubber–rubber friction pair. However, grooving has a significantly positive impact in the case of wet friction. In cases where the surface is grooved in a “diamond” pattern, the measured friction coefficient values are similar for both wet and dry surfaces. The lowest friction coefficient values were obtained for surfaces contaminated with solid rock dust. Full article
(This article belongs to the Section Mechanical Engineering)
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14 pages, 4057 KB  
Article
Sustainable Valorization of Kenaf Fiber Waste in Polymer Composites for Drone Arm Structure: A Finite Element Analysis Approach
by Navaneetha Krishna Chandran, Mohamed Thariq Hameed Sultan, Farah Syazwani Shahar and Andrzej Łukaszewicz
J. Compos. Sci. 2025, 9(9), 505; https://doi.org/10.3390/jcs9090505 (registering DOI) - 19 Sep 2025
Abstract
This study investigates the feasibility of kenaf fiber, which is a natural fiber, used as a polymer composite for use in quadcopter arm structures through finite element analysis. The research emphasizes the mechanical performance of various fiber orientations and cross-sectional configurations of the [...] Read more.
This study investigates the feasibility of kenaf fiber, which is a natural fiber, used as a polymer composite for use in quadcopter arm structures through finite element analysis. The research emphasizes the mechanical performance of various fiber orientations and cross-sectional configurations of the quadcopter arm, focusing on optimizing stress resistance, displacement, and strain characteristics. By relating the relationship between deflection and area moment of inertia of the quadcopter arm, a comparative analysis was conducted for circular hollow tubes, hollow rectangular tubes, and solid rectangular tubes, with the circular hollow tube configuration demonstrating the highest stiffness and minimal deflection. The result from the theoretical calculation and the simulation result of deflection are compared. The study also evaluates the influence of kenaf fiber orientations on the mechanical properties of the composite. Among the seven tested orientations, the sequence 0°, 30°, 45°, 30°, 0° yielded the highest maximum stress (0.3427 MPa), indicating optimal load distribution. Conversely, the 0°, 45°, 0°, 45°, 0° orientation provided the least displacement, making it ideal for high rigidity applications. These findings confirm the potential of kenaf fiber-reinforced polymer as an eco-friendly, lightweight alternative to synthetic fibers for UAV applications, offering a balance of strength, flexibility, and structural stability, and promoting sustainable value in the field of aerospace, as it proves the utilization of waste product into a high-value product. Full article
(This article belongs to the Special Issue Sustainable Polymer Composites: Waste Reutilization and Valorization)
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28 pages, 775 KB  
Article
Leveraging FMMEA for Digital Twin Development: A Case Study on Intelligent Completion in Oil and Gas
by Nelson Victor Costa da Silva, Flavia Albuquerque Pontes, Mariana Santos da Silva, Breno Cagide Fialho, Jamile Eleutério Delesposte, Dalton Garcia Borges de Souza, Luiz Antônio de Oliveira Chaves and Rodolfo Cardoso
Sensors 2025, 25(18), 5846; https://doi.org/10.3390/s25185846 (registering DOI) - 19 Sep 2025
Abstract
The implementation of Digital Twins (DTs) represents a significant advancement for the Oil and Gas (O&G) industry. A DT virtually replicates a physical asset, enabling the monitoring, diagnosis, prediction, and optimization of its outcomes. Since failures are undesirable outcomes, investigations into potential failure [...] Read more.
The implementation of Digital Twins (DTs) represents a significant advancement for the Oil and Gas (O&G) industry. A DT virtually replicates a physical asset, enabling the monitoring, diagnosis, prediction, and optimization of its outcomes. Since failures are undesirable outcomes, investigations into potential failure modes are often integrated into the development. Traditional methods, such as Failure Modes and Effects Analysis (FMEA) and Failure Mode, Effects, and Criticality Analysis (FMECA), are widely used to identify, assess, and mitigate risks. However, there is still a lack of specific guidelines for studying potential failures in complex systems. This article introduces a framework for Failure Modes, Mechanisms, and Effects Analysis (FMMEA) as a tool for identifying and assessing failures in early DT development. Exploring failure mechanisms is highlighted as essential for effective prediction and management We also propose adjustments to FMMEA for complex, predictable systems, such as using a DPR (Detectable Priority Risk) instead of RPN (Risk Priority Number) for prioritizing risks. A comprehensive case illustrates the framework’s application in developing a DT for an intelligent completion system in a major O&G company. The approach enables mechanism-oriented failure analysis and more detailed prognostic health management, providing greater transparency in the failure identification process. Full article
(This article belongs to the Section Intelligent Sensors)
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9 pages, 1385 KB  
Article
Prevalence and Genetic Diversity of Torque teno felis virus (FcTTV) in Domestic Cats from Kazakhstan
by Gulzhan Yessembekova, Bolat Abdigulov, Alexandr Shevtsov, Asylulan Amirgazin, Sarsenbay Abdrakhmanov, Elena Shevtsova, Symbat Bolysbekkyzy, Salima Baduanova and Alexandr Shustov
Viruses 2025, 17(9), 1265; https://doi.org/10.3390/v17091265 (registering DOI) - 19 Sep 2025
Abstract
Anelloviruses have a broad mammalian host range, including Torque teno felis virus (FcTTV), a felid-associated member that remains undercharacterized. This is the first comprehensive study of FcTTV in domestic cats in Central Asia. We analyzed blood samples from 206 domestic cats from the [...] Read more.
Anelloviruses have a broad mammalian host range, including Torque teno felis virus (FcTTV), a felid-associated member that remains undercharacterized. This is the first comprehensive study of FcTTV in domestic cats in Central Asia. We analyzed blood samples from 206 domestic cats from the large city of Astana, Kazakhstan, collected in 2023–2024. Using nested PCR we identified 63 FcTTV-positive samples (30.6% prevalence), and the sequences were compared to global reference strains. Potential demographic associations (sex and age) were assessed. The study revealed an overall FcTTV prevalence of 30.6%. Infection rates showed no significant sex-related differences: ages varied 4–168 months. ORF1 sequencing revealed multiple FcTTV variants in 27% of samples, with no demographic links. Phylogenetic analysis revealed distinct patterns at both nucleotide and amino acid levels: 3 groups of nucleotide sequences (max divergence 21.68%; intra-cluster 5.15–6.8%), and 3 clusters of amino acid sequences (max divergence 16.81%; intra-cluster 2.82–6.68%). Deletions were found in ORF1 in some variants. Global phylogeny aligned clusters with Asian/European strains (90–98% identity), confirming FcTTV1 affiliation and inter-regional transmission. Our study of FcTTV in Kazakhstan reveals moderate virus prevalence with considerable genetic diversity across viral strains and frequent co-infections with multiple variants. Full article
(This article belongs to the Section Animal Viruses)
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17 pages, 241 KB  
Article
Theoretical Foundations for Governing AI-Based Learning Outcome Assessment in High-Risk Educational Contexts
by Flavio Manganello, Alberto Nico and Giannangelo Boccuzzi
Information 2025, 16(9), 814; https://doi.org/10.3390/info16090814 (registering DOI) - 19 Sep 2025
Abstract
The governance of artificial intelligence (AI) in education requires theoretical grounding that extends beyond system compliance toward outcome-focused accountability. The EU AI Act classifies AI-based learning outcome assessment (AIB-LOA) as a high-risk application (Annex III, point 3b), underscoring the importance of algorithmic decision-making [...] Read more.
The governance of artificial intelligence (AI) in education requires theoretical grounding that extends beyond system compliance toward outcome-focused accountability. The EU AI Act classifies AI-based learning outcome assessment (AIB-LOA) as a high-risk application (Annex III, point 3b), underscoring the importance of algorithmic decision-making in student evaluation. Current regulatory frameworks such as GDPR and ALTAI focus primarily on ex-ante and system-focused approaches. ALTAI applications in education concentrate on compliance and vulnerability analysis while often failing to integrate governance principles with established educational evaluation practices. While explainable AI research demonstrates methodological sophistication (e.g., LIME, SHAP), it often fails to deliver pedagogically meaningful transparency. This study develops the XAI-ED Consequential Assessment Framework (XAI-ED CAF) as a sector-specific, outcome-focused governance model for AIB-LOA. The framework reinterprets ALTAI’s seven requirements (human agency, robustness, privacy, transparency, fairness, societal well-being, and accountability) through three evaluation theories: Messick’s consequential validity, Kirkpatrick’s four-level model, and Stufflebeam’s CIPP framework. Through this theoretical integration, the study identifies indicators and potential evidence types for institutional self-assessment. The analysis indicates that trustworthy AI in education extends beyond technical transparency or legal compliance. Governance must address student autonomy, pedagogical validity, interpretability, fairness, institutional culture, and accountability. The XAI-ED CAF reconfigures ALTAI as a pedagogically grounded accountability model, establishing structured evaluative criteria that align with both regulatory and educational standards. The framework contributes to AI governance in education by connecting regulatory obligations with pedagogical evaluation theory. It supports policymakers, institutions, and researchers in developing outcome-focused self-assessment practices. Future research should test and refine the framework through Delphi studies and institutional applications across various contexts. Full article
(This article belongs to the Special Issue Advances in Explainable Artificial Intelligence, 2nd Edition)
21 pages, 3518 KB  
Article
New Insights in blaKPC Gene Mobilization in Pseudomonas aeruginosa: Acquisition of blaKPC-3 and Identification of a New Tn2-like NTE Mobilizing blaKPC-2
by Deisy Abril, Juan Bravo-Ojeda, Julio-Cesar Garcia, Aura Lucia Leal-Castro, Carlos Humberto Saavedra-Trujillo, Johana Madroñero, Rosa-Helena Bustos, Ricaurte Alejandro Marquez-Ortiz, Zayda Lorena Corredor Rozo, Natasha Vanegas Gómez and Javier Escobar-Pérez
Antibiotics 2025, 14(9), 947; https://doi.org/10.3390/antibiotics14090947 (registering DOI) - 19 Sep 2025
Abstract
Carbapenem-resistant Pseudomonas aeruginosa is a major cause of healthcare associated infections in hospitalized patients and what is more warring with reduced therapeutic options. The KPC is a powerful enzyme capable of hydrolyzing the carbapenems, described first in Klebsiella pneumoniae and it already has [...] Read more.
Carbapenem-resistant Pseudomonas aeruginosa is a major cause of healthcare associated infections in hospitalized patients and what is more warring with reduced therapeutic options. The KPC is a powerful enzyme capable of hydrolyzing the carbapenems, described first in Klebsiella pneumoniae and it already has found in P. aeruginosa.Objective: To perform a comparative genomic analysis of two new genetic platforms mobilizing the blaKPC-2 and blaKPC-3 in two ST111 and ST235 pandemic clones of P. aeruginosa in Colombia, South America. Methods: Sixty-six blaKPC-harboring P. aeruginosa isolates were identified and characterized during a prospective study conducted in six high complex hospitals in Colombia. Genetic platforms mobilizing the blaKPC were analyzed. Results: The blaKPC-2 and blaKPC-3 were identified in 24 and 42 isolates, respectively. The blaKPC-2-harboring isolates belonged to ST235 and blaKPC-3 to ST111. The whole genome sequencing indicated that the blaKPC-3 gene was mobilized by the Tn4401b within a 55-kb-size environmental origin plasmid, which, in other isolates, was inserted into the chromosome through a transposition event of ISPa38. Regarding the blaKPC-2 gene, this was mobilized by a new Non-Tn4401 Element (NTE) derived from transposon Tn2 (proposed as variant IIg), which has been transposed into a 43-Kb-size little-studied plasmid related to Klebsiella spp. Conclusions: Our results reveal a new acquisition event of blaKPC in P. aeruginosa, in this case blaKPC-3. Likewise, the pandemic high-risk clones ST111 and ST235 of P. aeruginosa continues to spread blaKPC gene through different mobile genetic elements, jumping of conventional Tn4401b and acquiring new Tn2-derived NTE, which were inserted in diverse plasmids. Full article
(This article belongs to the Section Mechanism and Evolution of Antibiotic Resistance)
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21 pages, 3742 KB  
Article
Research on Monitoring and Intelligent Identification of Typical Defects in Small and Medium-Sized Bridges Based on Ultra-Weak FBG Sensing Array
by Xinyan Lin, Yichan Zhang, Yinglong Kang, Sheng Li, Qiuming Nan, Lina Yue, Yan Yang and Min Zhou
Optics 2025, 6(3), 43; https://doi.org/10.3390/opt6030043 (registering DOI) - 19 Sep 2025
Abstract
To address the challenge of efficiently identifying and providing early warnings for typical structural damages in small and medium-sized bridges during long-term service, this paper proposes an intelligent monitoring and recognition method based on ultra-weak fiber Bragg grating (UWFBG) array sensing. By deploying [...] Read more.
To address the challenge of efficiently identifying and providing early warnings for typical structural damages in small and medium-sized bridges during long-term service, this paper proposes an intelligent monitoring and recognition method based on ultra-weak fiber Bragg grating (UWFBG) array sensing. By deploying UWFBG strain-sensing cables across the bridge, the system enables continuous acquisition and spatial analysis of multi-point strain data. Based on this, a series of experimental scenarios simulating typical structural damages—such as single-slab loading, eccentric loading, and bearing detachment—are designed to systematically analyze strain evolution patterns before and after damage occurrence. While strain distribution maps allow for visual identification of some typical damages, the approach remains limited by reliance on manual interpretation, low recognition efficiency, and weak detection capability for atypical damages. To overcome these limitations, machine learning algorithms are further introduced to extract features from strain data and perform pattern recognition, enabling the construction of an automated damage identification model. This approach enhances both the accuracy and robustness of damage recognition, achieving rapid classification and intelligent diagnosis of structural conditions. The results demonstrate that the integration of the monitoring system with intelligent recognition algorithms effectively distinguishes different types of damage and shows promising potential for engineering applications. Full article
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36 pages, 505 KB  
Review
Dietary Modulation of Metabolic Health: From Bioactive Compounds to Personalized Nutrition
by Aleksandra Leziak, Julia Lipina, Magdalena Reclik and Piotr Kocelak
Metabolites 2025, 15(9), 624; https://doi.org/10.3390/metabo15090624 (registering DOI) - 19 Sep 2025
Abstract
Metabolic health is a dynamic equilibrium influenced by diet and lifestyle. This review synthesizes evidence on how specific dietary patterns and bioactive nutrients modulate metabolic disorders. Diets like the Mediterranean and DASH plans consistently improve cardiometabolic markers: a Mediterranean diet can halve metabolic [...] Read more.
Metabolic health is a dynamic equilibrium influenced by diet and lifestyle. This review synthesizes evidence on how specific dietary patterns and bioactive nutrients modulate metabolic disorders. Diets like the Mediterranean and DASH plans consistently improve cardiometabolic markers: a Mediterranean diet can halve metabolic syndrome prevalence (~52% reduction) in as little as 6 months, while the DASH diet typically lowers systolic blood pressure by ~5–7 mmHg and modestly improves lipid profiles (LDL-C by ~3–5 mg/dL). Plant-based diets (vegetarian/vegan) are associated with lower BMI, improved insulin sensitivity, and reduced inflammation. Ketogenic diets induce rapid weight loss (~12% body weight vs. 4% on control diets) and improve glycemic control (reducing HbA1c and triglycerides), though long-term effects (elevated LDL) warrant caution. Bioactive compounds present in these diets play critical roles: polyphenols improve insulin signaling and reduce oxidative stress (resveratrol supplementation reduced HOMA-IR by ~0.5 units and fasting glucose by ~0.3 mmol/L); omega-3 fatty acids (fish oil) reduce triglycerides by ~25–30% and inflammation; and probiotic interventions modestly enhance glycemic control (lowering HOMA-IR and HbA1c) and gut health. Personalized nutrition approaches, which account for genetic and microbiome differences, are emerging to maximize these benefits. In conclusion, evidence-based dietary strategies rich in fiber, unsaturated fats, and phytochemicals can substantially improve metabolic health outcomes, underscoring the potential of tailored nutrition in preventing and managing obesity-related metabolic disorders. Full article
(This article belongs to the Special Issue Effects of Diet on Metabolic Health of Obese People)
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16 pages, 518 KB  
Article
High-Intensity Interval Training (HIIT): Impact of Duration on Body Composition, Cardiometabolic Health, and Aerobic Capacity in Adolescent Women
by Mima Stankovic, Ilma Čaprić, Luka Pezelj, Emir Biševac, Raid Mekić, Armin Zećirović, Zerina Salihagić, Aldina Ajdinović and Igor Jelaska
Metabolites 2025, 15(9), 623; https://doi.org/10.3390/metabo15090623 (registering DOI) - 19 Sep 2025
Abstract
Background: High-intensity interval training (HIIT) is a time-efficient approach that has been recognized to enhance cardiometabolic health and aerobic capacity in adolescents. The purpose of this study was to investigate the effects of various HIIT durations on cardiometabolic health and aerobic ability in [...] Read more.
Background: High-intensity interval training (HIIT) is a time-efficient approach that has been recognized to enhance cardiometabolic health and aerobic capacity in adolescents. The purpose of this study was to investigate the effects of various HIIT durations on cardiometabolic health and aerobic ability in adolescent women aged 17 to 19 years. Methods: Participants were separated into two intervention groups: HIIT 1 (6 weeks) and HIIT 2 (8 weeks), along with a control group. Both HIIT regimens included two weekly sessions: warm-up (jogging, accelerated running, and dynamic stretching), major sets (2 × 6–9 bouts of 30 s training at 90–95% HRmax with active recovery), and cooldown. Pre- and post-intervention measurements included body mass, BMI, body fat percentage, lipid profile, blood pressure, fasting glucose, and VO2max. Results: Both HIIT programs resulted in significant reductions in body weight, BMI, and body fat percentage (all p < 0.001), as well as improvements in total cholesterol, triglycerides, LDL cholesterol, and systolic and diastolic blood pressure (all p < 0.001), compared to the control group. The changes in glycemia (p = 0.078) and HDL cholesterol (p = 0.825) were not statistically significant. Both HIIT groups showed significantly higher VO2max (p < 0.001). Conclusions: Adolescent women’s cardiometabolic health and aerobic capacity increased considerably following 6- and 8-week HIIT training. These findings emphasize HIIT as a practical and time-saving strategy for this population, highlighting its effectiveness in improving key health parameters within a relatively short period. Full article
(This article belongs to the Special Issue Effects of Various Exercise Methods on Metabolic Health)
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16 pages, 685 KB  
Article
Long-Term Outcomes Following Reconstruction of Diaphyseal Defects of the Upper and Lower Extremities Using Diaphyseal Implants: A Retrospective Study with Focus on Fixation Technique
by Tymoteusz Budny, Anna Maria Rachbauer, Georg Gosheger, Felix Lückel, Marieke De Vaal, Sebastian Klingebiel, Jan Christoph Theil and Niklas Deventer
Cancers 2025, 17(18), 3059; https://doi.org/10.3390/cancers17183059 (registering DOI) - 19 Sep 2025
Abstract
Background: The reconstruction of diaphyseal bone defects following tumor resection offers various biological and endoprosthetic treatment options. The present study analyzes the impact of the fixation method (cemented; uncemented; with locking screw; without locking screw) of the diaphyseal implant on clinical outcomes. Factors [...] Read more.
Background: The reconstruction of diaphyseal bone defects following tumor resection offers various biological and endoprosthetic treatment options. The present study analyzes the impact of the fixation method (cemented; uncemented; with locking screw; without locking screw) of the diaphyseal implant on clinical outcomes. Factors such as patient age and weight as well as tumor type and location are also considered. Methods: This study included 39 patients who underwent intercalary endoprosthetic reconstruction of the humerus (n = 4); femur (n = 29); and tibia (n = 6) between 1998 and 2020. Prosthetic complications, fixation methods and the MSTS score for functional outcome were statistically analyzed using SPSS and R. Results: The event-free probability in the competing risk model was 61% (95% CI 43–74%) after one year and 11% (95% CI 3–28%) after five years. The complication rate in the patient cohort was 54%. Cementless prosthesis fixation was associated with a statistically significant better functional outcome. Additionally, higher body weight and older patient age were associated with lower MSTS scores. Conclusions: Patients requiring rapid remobilization or adjuvant radiation therapy may benefit more from diaphyseal implants compared to biological reconstructions. However, the complication and revision rates of diaphyseal implants are elevated. The chosen fixation method shows a statistically significant influence on functional outcome. Full article
(This article belongs to the Special Issue Advances in Soft Tissue and Bone Sarcoma (2nd Edition))
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23 pages, 11963 KB  
Article
CIRS: A Multi-Agent Machine Learning Framework for Real-Time Accident Detection and Emergency Response
by Sadaf Ayesha, Aqsa Aslam, Muhammad Hassan Zaheer and Muhammad Burhan Khan
Sensors 2025, 25(18), 5845; https://doi.org/10.3390/s25185845 (registering DOI) - 19 Sep 2025
Abstract
Road traffic accidents remain a leading cause of fatalities worldwide, and the consequences are considerably worsened by delayed detection and emergency response. Although several machine learning-based approaches have been proposed, accident detection systems are not widely deployed, and most existing solutions fail to [...] Read more.
Road traffic accidents remain a leading cause of fatalities worldwide, and the consequences are considerably worsened by delayed detection and emergency response. Although several machine learning-based approaches have been proposed, accident detection systems are not widely deployed, and most existing solutions fail to handle the growing complexity of modern traffic environments. This study introduces Collaborative Intelligence for Road Safety (CIRS), a novel, multi-agent, machine-learning-based framework designed for real-time accident detection, semantic scene understanding, and coordinated emergency response. Each agent in CIRS is designed for a distinct role perception, classification, description, localization, and decision-making, working collaboratively to enhance situational awareness and response efficiency. These agents integrate advanced models: YOLOv11 for high-accuracy accident detection and VideoLLaMA3 for contextual-rich scene description. CIRS bridges the gap between low-level visual analysis and high-level situational awareness. Extensive evaluation on a custom dataset comprising (5200 accident, 4800 nonaccident) frames demonstrates the effectiveness of the proposed approach. YOLOv11 achieves a top-1 accuracy of 86.5% and a perfect top-5 accuracy of 100%, ensuring reliable real-time detection. VideoLLaMA3 outperforms other vision-language models with superior factual accuracy and fewer hallucinations, generating strong results in the metrics of BLEU (0.0755), METEOR (0.2258), and ROUGE-L (0.3625). The decentralized multi-agent architecture of CIRS enables scalability, reduced latency, and the timely dispatch of emergency services while minimizing false positives. Full article
(This article belongs to the Section Intelligent Sensors)
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10 pages, 1598 KB  
Article
Legume as Vegetal Nitrogen Source with Olive Mill Wastewater for Methane Production Through Two-Stage Anaerobic Co-Digestion Process
by Ana I. Parralejo, Jerónimo González, Luis Royano and Juan F. González
Energies 2025, 18(18), 4973; https://doi.org/10.3390/en18184973 (registering DOI) - 19 Sep 2025
Abstract
Energy security fosters the development of biogas, particularly in the context of the rapid energy transition. Substrates suitable for anaerobic digestion serve as feedstocks to produce biogas. Determining the optimal feedstock ratio is a key factor for achieving viable anaerobic digestion (AD) processes [...] Read more.
Energy security fosters the development of biogas, particularly in the context of the rapid energy transition. Substrates suitable for anaerobic digestion serve as feedstocks to produce biogas. Determining the optimal feedstock ratio is a key factor for achieving viable anaerobic digestion (AD) processes with high methane yields. This study evaluated different two-stage AD assays using biomass from a leguminous crop (Lupinus Albus, lupin) and olive mill wastewater (OMW). The highest methane yields were obtained in assays with higher proportions of lupin in the feed mixture (532 L kg VS−1 and 522 L kg VS−1) and at a higher Organic Load Rate (OLR) evaluated (510 L kg VS−1). Moreover, the presence of OMW in the feedstock significantly increased the Volatile Fatty Acid (VFA) concentration, as observed in the assay. Full article
(This article belongs to the Section A4: Bio-Energy)
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17 pages, 1267 KB  
Article
Characterization of Quesillo Caquetá with Protected Designation of Origin (PDO): Mineral Composition and Carbohydrate, Fatty Acid, and Peptide Profiles
by Andrés Grajales-Zuleta, Sandra Estrada, Andrea Hermosa, Isidra Recio, Beatriz Miralles and Mar Villamiel
Dairy 2025, 6(5), 52; https://doi.org/10.3390/dairy6050052 (registering DOI) - 19 Sep 2025
Abstract
Cheese products worldwide have gained protected designation of origin status in many instances, yet this food group also has the highest reported fraud rates. Quesillo Caquetá is the first Colombian cheese to acquire a protected designation of origin, but still there is a [...] Read more.
Cheese products worldwide have gained protected designation of origin status in many instances, yet this food group also has the highest reported fraud rates. Quesillo Caquetá is the first Colombian cheese to acquire a protected designation of origin, but still there is a lack of information regarding its composition. In this study, a compositional analysis was performed to establish a set of characteristic parameters to aid the identification of the authenticity of Quesillo Caquetá. Physicochemical analysis, mineral composition determination, carbohydrate, fatty acid, and peptide profiles were conducted on 29 samples of Quesillo Caquetá made with milk from the northern, southern, and central regions of the province of Caquetá. The results revealed 7 minerals, 3 carbohydrates, 19 fatty acids, and 45 peptides (21 peptides from bovine αs1-casein and 24 peptides from bovine β-casein). This suggests that Quesillo Caquetá is a significant source of sodium, calcium, phosphorus, and monounsaturated fatty acids such as oleic acid, omega-3, and omega-6, as well as some peptides that match sequences with antihypertensive, immunomodulatory, antioxidant, and antimicrobial activity reported in the literature. The specificity of the fatty acid and peptide profiles can become a valuable tool for identifying the authenticity of Quesillo Caquetá against possible imitations in the market. Full article
(This article belongs to the Section Metabolomics and Foodomics)
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18 pages, 3666 KB  
Article
Effect of Behavioral Change Communication and Livestock Feed Intervention on Dietary Practices in a Kenyan Pastoral Community: A Randomized Controlled Trial
by Nyamai Mutono, Josphat Muema, Zipporah Bukania, Irene Kimani, Erin Boyd, Immaculate Mutua, George Gacharamu, Francis Wambua, Anita Makori, Joseph Njuguna, Christine Jost, Abdal Monium Osman, Darana Souza, Guy H. Palmer, Jonathan Yoder and S. M. Thumbi
Nutrients 2025, 17(18), 2997; https://doi.org/10.3390/nu17182997 (registering DOI) - 19 Sep 2025
Abstract
Low dietary diversity is a key driver of undernutrition and remains a significant public health challenge in low- and middle-income countries. This study evaluated the effect of nutritional counselling and the provision of livestock feed, aimed at sustaining milk production during dry periods, [...] Read more.
Low dietary diversity is a key driver of undernutrition and remains a significant public health challenge in low- and middle-income countries. This study evaluated the effect of nutritional counselling and the provision of livestock feed, aimed at sustaining milk production during dry periods, on the dietary diversity of women and children in a pastoralist setting. Methods: A cluster randomized controlled trial was conducted among households in Laisamis subcounty, north-eastern Kenya, which were assigned to one of three arms: (1) an intervention arm providing livestock feed during critically dry periods, (2) an intervention arm providing livestock feed plus enhanced nutritional counselling (provided once a week, covering topics including hygiene and sanitation, breastfeeding, maternal nutrition, immunization and complementary feeding) or (3) a control arm. The dietary diversity of mothers and children was assessed every six weeks over two years. Panel difference-in-difference regression models were used to estimate intervention effects on dietary outcomes including child minimum dietary diversity (MDD), minimum acceptable diet (MAD), women’s dietary diversity (MDD-W) and food security. Results: A total of 1734 households participated (639 in arm 1, 585 in arm 2, and 510 in the control arm). The provision of livestock feed alone had significant gains in child MAD (OR 1.20; 95% CI 1.08–1.34), child MDD (OR 1.15; 1.11–1.20), and MDD-W (OR 1.10; 1.01–1.19) whereas combined livestock feed with counselling, reduced child food poverty (OR 0.89; 95% CI 0.81–0.99), increased child MAD (OR 1.39; 1.22–1.52), and improved MDD-W (OR 1.21; 1.16–1.28) relative to control. Neither intervention increased child minimum meal frequency relative to control. Purchasing livestock was associated with higher odds of meeting dietary-diversity indicators but a lower meal frequency (OR 0.80; 0.80–0.90); in contrast, cash-transfer receipt was linked to reduced odds of achieving child MDD (OR 0.90; 0.87–0.94), child MAD (OR 0.95; 0.85–0.97), and women’s MDD (OR 0.73; 0.54–0.89). Conclusions: Livestock feed provision sustains milk consumption and improves dietary diversity in pastoralist populations. When combined with nutritional counselling, these interventions strengthen the link between animal and human health, with important implications for food security. Full article
(This article belongs to the Section Nutritional Epidemiology)
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13 pages, 463 KB  
Article
Enhancing Food Security in an Asian Regional Organization: The Case of the Economic Cooperation Organization
by Alexandra Zamfirache and Ileana Tache
Economies 2025, 13(9), 274; https://doi.org/10.3390/economies13090274 (registering DOI) - 19 Sep 2025
Abstract
This study investigates the agri-food sector, food trade, and food availability (as a component of food security) within the Economic Cooperation Organization (ECO), emphasizing the critical importance of agriculture across its member states. This significance is particularly pronounced in less industrialized countries such [...] Read more.
This study investigates the agri-food sector, food trade, and food availability (as a component of food security) within the Economic Cooperation Organization (ECO), emphasizing the critical importance of agriculture across its member states. This significance is particularly pronounced in less industrialized countries such as Tajikistan, Kyrgyzstan, and Afghanistan. The rationale behind this research stems from the observation that food trade and food security issues in the ECO region remain insufficiently addressed in the academic literature. Given the strategic geographical position of ECO countries—at the intersection of Europe, Asia, and the Middle East—these states possess considerable potential to function as vital trade hubs. The present study addresses this research gap by offering conceptual insights and empirical data relevant to the region’s policymakers, traders, and other stakeholders. Methodologically, the research integrates both qualitative and quantitative approaches. On the qualitative side, it includes historical and documentary analysis concerning ECO’s evolution and its agri-food sector’s development. Quantitatively, the study employs a regression model to examine the moderating effect of food imports on the relationship between food exports and food availability across member states. The results indicate a significant interaction effect: food imports moderate the negative association between exports and domestic food availability. Drawing on these findings, the paper formulates a set of policy recommendations to enhance agricultural trade strategies and strengthen food security in ECO countries. Full article
(This article belongs to the Special Issue The Agri-Food Sector and the Development of Local Markets)
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16 pages, 2981 KB  
Article
CNN-Based Road Event Detection Using Multiaxial Vibration and Acceleration Signals
by Abiel Aguilar-González and Alejandro Medina Santiago
Appl. Sci. 2025, 15(18), 10203; https://doi.org/10.3390/app151810203 (registering DOI) - 19 Sep 2025
Abstract
Road event detection plays a key role in tasks such as monitoring, anomaly identification, and urban traffic optimization. Conventional methods often rely on feature extraction and classification or classical machine learning models, which may struggle when processing high-frequency signals in real time. In [...] Read more.
Road event detection plays a key role in tasks such as monitoring, anomaly identification, and urban traffic optimization. Conventional methods often rely on feature extraction and classification or classical machine learning models, which may struggle when processing high-frequency signals in real time. In this work, we propose a CNN-based classification approach designed to handle multi-axial acceleration and vibration signals captured from road scenarios. Instead of relying on static feature sets, our method leverages a convolutional neural network architecture capable of automatically learning discriminative patterns from raw sensor data. We structure the time-series input into temporal windows and use it to train models that can identify different event categories, including “Speed Bumps”, “Potholes”, and “Sudden Braking” events. The experimental results show that our approach achieves an accuracy of 93.51%, with a precision of 93.56% and a recall of 93.51%. Further, the average AUC score of 0.9855 confirms the strong discriminative power of our proposal. In contrast to rule-based methods, which require frequent tuning to adapt to new datasets, our approach generalizes better across different road conditions and offers a practical alternative for real-time deployment in dynamic environments, outperforming rule-based approaches by over 10% in F1-score, while preserving deployment efficiency on embedded hardware. Full article
(This article belongs to the Special Issue Advanced Convolutional Neural Network (CNN) Technology in Object Detection and Data Processing)
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21 pages, 4651 KB  
Article
Phosphogypsum and Borogypsum as Additives for Sustainable and High-Performance 3D-Printable Concrete
by Yeşim Tarhan and Berrin Atalay
Polymers 2025, 17(18), 2530; https://doi.org/10.3390/polym17182530 (registering DOI) - 19 Sep 2025
Abstract
3D-printable concretes often require high binder content. This study evaluates the use of industrial gypsum by-products, phosphogypsum (PG) and borogypsum (BG), as partial cement replacements to enhance sustainability without compromising printability. PG and BG were incorporated at 2.5–10 wt% to replace the gypsum [...] Read more.
3D-printable concretes often require high binder content. This study evaluates the use of industrial gypsum by-products, phosphogypsum (PG) and borogypsum (BG), as partial cement replacements to enhance sustainability without compromising printability. PG and BG were incorporated at 2.5–10 wt% to replace the gypsum fraction in cement-based mortars containing fly ash (FA) or ground granulated blast-furnace slag (GGBS), with and without fibers. The fresh properties (spread flow diameter, open time, air content, density, and pH) and compressive strength were measured. At 28 days, the highest strength was achieved with a 7.5% PG addition to the GGBS system (~51 MPa), which exceeded the strength of the GGBS control C1 (~47.6 MPa). In the FA system, 2.5% PG reached 42.5 MPa, comparable to the FA control C2 (41.2 MPa). BG caused pronounced strength penalties at ≥7.5% across both binder systems, indicating a practical BG ceiling of ≤5%. Open time increased from ~0.75 h in the controls to ~2–2.5 h in BG-FA mixes with fibers, whereas PG mixes generally maintained a stable, printable window close to control levels. Overall, adding 5–7.5% PG, particularly in the presence of GGBS, improved mechanical performance without compromising workability. However, BG should be limited to ≤5% unless extended open time is the primary objective. These findings provide quantitative guidance on selecting PG/BG dosages and FA/GGBS systems to balance strength and printability in cement-based, 3D-printable concretes. Full article
(This article belongs to the Special Issue Application of Polymers in Cementitious Materials)
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28 pages, 5663 KB  
Article
Quasi-Infinite Horizon Nonlinear Model Predictive Control for Cooperative Formation Tracking of Underactuated USVs with Four Degrees of Freedom
by Meng Yang, Ruonan Li, Hao Wang, Wangsheng Liu and Zaopeng Dong
J. Mar. Sci. Eng. 2025, 13(9), 1812; https://doi.org/10.3390/jmse13091812 (registering DOI) - 19 Sep 2025
Abstract
To address the issues of external unknown disturbances and roll motion in the tracking control of underactuated unmanned surface vehicle (USV) formation, a cooperative formation control method based on nonlinear model predictive control (NMPC) algorithm and finite-time disturbance observer is proposed. Initially, a [...] Read more.
To address the issues of external unknown disturbances and roll motion in the tracking control of underactuated unmanned surface vehicle (USV) formation, a cooperative formation control method based on nonlinear model predictive control (NMPC) algorithm and finite-time disturbance observer is proposed. Initially, a tracking error model for the USV formation is established within a leader–follower framework, utilizing a four-degree-of-freedom (4-DOF) dynamic model to simultaneously account for roll motion and trajectory tracking. This error model is then approximately linearized and discretized. To mitigate the initial non-smoothness in the desired trajectories of the follower USVs, a tracking differentiator is designed to smooth the heading angle of the leader USV. Thereafter, a quasi-infinite horizon NMPC algorithm is developed, in which a terminal penalty function is constructed based on quasi-infinite horizon theory. Furthermore, a finite-time disturbance observer is developed to facilitate real-time estimation and compensation for unknown marine disturbances. The proposed method’s effectiveness is validated both mathematically and in simulation. Mathematically, closed-loop stability is rigorously guaranteed via a Lyapunov-based proof of the quasi-infinite horizon NMPC design. In simulations, the algorithm demonstrates superior performance, reducing steady-state tracking errors by over 80% and shortening convergence times by up to 75% compared to a conventional PID controller. These results confirm the method’s robustness and high performance for complex USV formation tasks. Full article
(This article belongs to the Special Issue Autonomous Marine Vehicle Operations—3rd Edition)
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16 pages, 3480 KB  
Article
Reinforcement Learning for Robot Assisted Live Ultrasound Examination
by Chenyang Li, Tao Zhang, Ziqi Zhou, Baoliang Zhao, Peng Zhang and Xiaozhi Qi
Electronics 2025, 14(18), 3709; https://doi.org/10.3390/electronics14183709 (registering DOI) - 19 Sep 2025
Abstract
Due to its portability, non-invasiveness, and real-time capabilities, ultrasound imaging has been widely adopted for liver disease detection. However, conventional ultrasound examinations heavily rely on operator expertise, leading to high workload and inconsistent imaging quality. To address these challenges, we propose a Robotic [...] Read more.
Due to its portability, non-invasiveness, and real-time capabilities, ultrasound imaging has been widely adopted for liver disease detection. However, conventional ultrasound examinations heavily rely on operator expertise, leading to high workload and inconsistent imaging quality. To address these challenges, we propose a Robotic Ultrasound Scanning System (RUSS) based on reinforcement learning to automate the localization of standard liver planes. It can help reduce physician burden while improving scanning efficiency and accuracy. The reinforcement learning agent employs a Deep Q-Network (DQN) integrated with LSTM to control probe movements within a discrete action space, utilizing the cross-sectional area of the abdominal aorta region as the criterion for standard plane determination. System performance was comprehensively evaluated against a target standard plane, achieving an average Peak Signal-to-Noise Ratio (PSNR) of 24.51 dB and a Structural Similarity Index (SSIM) of 0.70, indicating high fidelity in the acquired images. Furthermore, a mean Dice coefficient of 0.80 for the abdominal aorta segmentation confirmed high anatomical localization accuracy. These preliminary results demonstrate the potential of our method for achieving consistent and autonomous ultrasound scanning. Full article
(This article belongs to the Topic Robot Manipulation Learning and Interaction Control)
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21 pages, 4203 KB  
Article
Hierarchical Prediction of Subway-Induced Ground Settlement Based on Waveform Characteristics and Machine Learning with Applications to Building Safety
by Xin Meng, Yongjun Qin, Liangfu Xie, Peng He and Liling Zhu
Buildings 2025, 15(18), 3390; https://doi.org/10.3390/buildings15183390 (registering DOI) - 19 Sep 2025
Abstract
Ground settlement caused by urban subway construction can significantly impact surrounding buildings and underground infrastructure, posing risks to structural safety and long-term performance. Accurate prediction of settlement trends is therefore essential for ensuring building integrity and supporting informed decision-making during construction. This study [...] Read more.
Ground settlement caused by urban subway construction can significantly impact surrounding buildings and underground infrastructure, posing risks to structural safety and long-term performance. Accurate prediction of settlement trends is therefore essential for ensuring building integrity and supporting informed decision-making during construction. This study proposes a hierarchical prediction framework that incorporates waveform-based curve classification and machine learning to forecast ground settlement patterns. Monitoring data from the Urumqi Metro construction project are analyzed, and settlement curve types are identified using Fréchet distance, categorized into five distinct forms: inverse cotangent, exponential, multi-step, one-shaped, and oscillating. Each type is then matched with the most suitable predictive model, including the Autoregressive Integrated Moving Average (ARIMA), Attention Mechanism-enhanced Long Short-Term Memory (AM-LSTM), Genetic Algorithm-optimized Support Vector Regression (GA-SVR), and Particle Swarm Optimization-based Backpropagation neural network (PSO-BP). Results show that AM-LSTM achieves the best performance for inverse cotangent and large-sample exponential curves; ARIMA excels for small-sample exponential curves; PSO-BP is most effective for multi-step curves; and GA-SVR offers superior accuracy for one-shaped and oscillating curves. Validation on a newly excavated section of Urumqi Metro Line 2 confirms the model’s potential in enhancing the safety management of buildings and infrastructure in subway construction zones. Full article
(This article belongs to the Topic Resilient Civil Infrastructure, 2nd Edition)
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