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24 pages, 7153 KB

Open AccessArticle

Wireless 22 kW Charging at Scale: An N-Box Architecture for Light-Duty EV Fleet Charging Infrastructure

by Tobias D. Götz, Thomas Caruyer, Maximilian Arnold, Axel Hoppe, Jannes Langemann and Nejila Parspour

Energies 2026, 19(19), 4541; https://doi.org/10.3390/en19194541 (registering DOI) - 24 Sep 2026

Abstract

Automated bidirectional charging of electric vehicle fleets offers massive energy system benefits that have barely been leveraged so far. Inductive charging, due to its contactless power transfer, represents a particularly robust solution for automation and avoids the mechanical wear and robotic-handling requirements inherent [...] Read more.

Automated bidirectional charging of electric vehicle fleets offers massive energy system benefits that have barely been leveraged so far. Inductive charging, due to its contactless power transfer, represents a particularly robust solution for automation and avoids the mechanical wear and robotic-handling requirements inherent to conductive systems with high plug-in cycles. This article investigates scalable topologies for inductive charging infrastructure with per-point power levels up to 22 kW. For this purpose, an N-box design architecture is introduced to systematically map power electronics sub-components into functional boxes between the grid interface and charging pads. The proposed framework thus enables a comparative cost assessment of supply schemes, i.e., DC link, 50 Hz AC, and 85 kHz high-frequency power distribution. The results show that using an optimized N-box architecture with grouping of four to seven charging points reduces the total CAPEX costs of an infrastructure from two to 50 parking lots by up to 32% on average compared to scaling state-of-the-art designs from private inductive home charging. Architectural grouping is therefore identified to be more important than the choice of power electronic topology. Further conclusions are listed at the end of the article. Full article

(This article belongs to the Special Issue Smart Grids and Electric Vehicle Integration: Challenges and Opportunities)

28 pages, 16107 KB

Open AccessArticle

The Partial Collapse of the South Road Axis Viaduct in Brasilia—A Forensic Investigation

by Yuri Bessa Cesarino, José Melo, Humberto Varum and Carlos Feijão

Buildings 2026, 16(19), 3806; https://doi.org/10.3390/buildings16193806 (registering DOI) - 24 Sep 2026

Abstract

The partial collapse of the South Road Axis Viaduct in 2018 generated widespread concern about the safety of similar critical bridges and viaducts built during the same historical period in Brasilia. Since many of these structures were designed with analogous structural systems, a [...] Read more.

The partial collapse of the South Road Axis Viaduct in 2018 generated widespread concern about the safety of similar critical bridges and viaducts built during the same historical period in Brasilia. Since many of these structures were designed with analogous structural systems, a thorough post-incident investigation was conducted to understand the failure mechanisms involved. The viaduct collapse remains insufficiently examined in the available technical literature. The present work offers a detailed forensic investigation of the partial collapse of the asset, clarifying the key structural elements and governing mechanics that triggered the sudden failure. This study combined the collection of historical documentation, in situ debris investigation, geometrical and mechanical characterization, manual and numerical calculations, and the determination of structural performance. The results revealed that the viaduct had hidden vulnerabilities (such as a lack of structural redundancy and insufficient reinforcing steel) and significant material degradation and that it was operating under unpredicted high cyclic shear demands. Lastly, the repairs and strengthening techniques employed in the viaduct’s recovery are also presented. Full article

(This article belongs to the Special Issue Selected Papers from the XXII International Conference on Building Pathology and Construction Repair (CINPAR 2026))

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29 pages, 8127 KB

Open AccessArticle

Geographical and Climatic Effects on the Quality Attributes of Chinese Mango Fruit

by Lihong Xie, Xuemei He, Youxia Shan, Ping Yi, Chuanyan Rao, Jinfeng Sheng, Ying Yang, Min Huang, Ting Gan, Dongqing Ye, Ming Xin, Xuefeng Wang, Zhichun Li, Li Li and Jian Sun

Foods 2026, 15(19), 3425; https://doi.org/10.3390/foods15193425 (registering DOI) - 24 Sep 2026

Abstract

Mango (Mangifera indica L.) is a commercially important fruit crop whose quality attributes are shaped by genetic background and cultivation environment, yet the relative contributions of geographic origin, climatic factors, and cultivar remain poorly resolved across China’s diverse production regions. Forty mango [...] Read more.

Mango (Mangifera indica L.) is a commercially important fruit crop whose quality attributes are shaped by genetic background and cultivation environment, yet the relative contributions of geographic origin, climatic factors, and cultivar remain poorly resolved across China’s diverse production regions. Forty mango groups representing six major cultivars (Tainong No. 1, Jinhuang, Guifei, Guire 82, Keitt, and Eagle-mouth) were collected from four principal production provinces (Guangxi, Hainan, Sichuan, and Yunnan), spanning latitudes from 19° N to 27° N and elevations from 6 to 1668 masl. Twelve quality traits were quantified alongside nine environmental variables. PCA captured 41.2% of total variance but revealed substantial interprovincial overlap, indicating limited discriminatory power of geographic origin alone. OPLS-DA showed that mean relative humidity (VIP = 1.48) and extreme maximum temperature (VIP = 1.15) emerged as the primary environmental discriminators among the variables examined. Hierarchical clustering revealed that samples from the same province were frequently dispersed across multiple clusters, further highlighting the apparent role of cultivar-specific genetic factors. Pooled Pearson correlation analysis showed that fruit-quality variation was associated mainly with cultivar: cultivar correlated significantly with total soluble solids (r = 0.598), carotene (r = 0.535), and pectin (r = 0.525), whereas environment–quality associations were weak and exploratory, with only two nominally significant correlations (extreme maximum temperature with carotene, r = −0.332, and with moisture, r = 0.327). These findings suggest that mango fruit quality is governed predominantly by cultivar, with local microclimate and geographic provenance serving as modulating factors. Such insights offer preliminary evidence-based guidance for regional cultivar deployment and quality-oriented orchard management, particularly in cultivar selection for targeted fresh-market and processing applications. Full article

(This article belongs to the Special Issue Processing, Comprehensive Utilization and In-Depth Development of Climate-Resilient Subtropical Crops)

12 pages, 519 KB

Open AccessArticle

Hospital-Based COVID-19 Surveillance in the Context of National and Global Pandemic Trends: A Retrospective Study of Demographic and Temporal Patterns

by Yasemin Ardicoglu Akisin, Rohat Sakar, Ebrar Gultekin, Parisa Sharafi and Julide Sedef Gocmen

COVID 2026, 6(10), 170; https://doi.org/10.3390/covid6100170 (registering DOI) - 24 Sep 2026

Abstract

Background: Institutional COVID-19 testing patterns may differ from population-level trends owing to differences in testing practices, case ascertainment, and demographic composition. Retrospective evaluation of these patterns may provide insights into future surveillance of infectious diseases. This study aimed to characterise the demographic and [...] Read more.

Background: Institutional COVID-19 testing patterns may differ from population-level trends owing to differences in testing practices, case ascertainment, and demographic composition. Retrospective evaluation of these patterns may provide insights into future surveillance of infectious diseases. This study aimed to characterise the demographic and temporal patterns of COVID-19 at TOBB University of Economics and Technology Faculty of Medicine Hospital and to contextualise these patterns within contemporaneous surveillance data from Turkey, the WHO European Region, and globally. Methods: In this retrospective descriptive study, SARS-CoV-2 reverse transcription polymerase chain reaction records from the hospital and aggregate World Health Organization surveillance data were evaluated from September 2020 to November 2022. Hospital data were evaluated according to age, sex, test positivity, and calendar month. Test positivity rates with 95% confidence intervals (CIs) were calculated, and sex-specific positivity rates were compared using Pearson’s chi-square test. Monthly hospital values were compared with the corresponding monthly national values for Turkey using Spearman’s rank correlation. Results: Among 49,318 SARS-CoV-2 reverse transcription polymerase chain reaction test results taken from the hospital data, 4810 were positive (9.75%; 95% CI: 9.49–10.01%). Test positivity did not differ between females and males (9.86% vs. 9.65%, p = 0.43). Adults aged 30–39 years represented the largest proportion of reported cases in the hospital (27.03%), Turkey (20.28%), the WHO European Region (16.48%), and globally (18.11%), whereas hospital testing was concentrated among adults aged 20–59 years. Hospital case counts peaked in November 2020 and February 2022, with the latter coinciding with the major COVID-19 surge in early 2022 in broader surveillance data. Monthly hospital case counts were positively correlated with monthly national case counts for Turkey (Spearman rho = 0.55, p = 0.003). Conclusions: Hospital-based surveillance identified major demographic and temporal features of the pandemic. However, differences in testing populations, case ascertainment, and reporting practices limit direct comparisons. Integrating institutional- and population-level data may strengthen surveillance frameworks for future respiratory infectious disease outbreaks. Full article

(This article belongs to the Special Issue Past, Present and Future of COVID-19: Advances and Lessons Learned)

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22 pages, 764 KB

Open AccessReview

Autonomous Obstacle Avoidance and Navigation Technologies for Unmanned Aerial Vehicles Based on LiDAR: A Review

by Svitlana Pavlova, Valerii Chepizhenko, Fuzhong Li and Fupeng Li

Appl. Sci. 2026, 16(19), 9523; https://doi.org/10.3390/app16199523 (registering DOI) - 24 Sep 2026

Abstract

Light Detection and Ranging (LiDAR) has become a benchmark sensing modality for autonomous unmanned aerial vehicle (UAV) navigation in GPS-denied and obstacle-dense environments such as forests, urban canyons, and indoor structures. This paper presents a structured review of the LiDAR-based UAV autonomy pipeline, [...] Read more.

Light Detection and Ranging (LiDAR) has become a benchmark sensing modality for autonomous unmanned aerial vehicle (UAV) navigation in GPS-denied and obstacle-dense environments such as forests, urban canyons, and indoor structures. This paper presents a structured review of the LiDAR-based UAV autonomy pipeline, spanning raw point-cloud processing, three-dimensional environment representation and mapping, simultaneous localization and mapping (SLAM), multi-sensor fusion, and real-time obstacle avoidance and trajectory planning. Reactive geometric methods, volumetric and distance-field mapping frameworks, tightly coupled LiDAR–inertial and LiDAR–inertial–visual odometry systems, gradient- and sampling-based trajectory optimizers, and learning-based end-to-end policies are compared with respect to computational cost, robustness, and applicability to resource-constrained micro-UAV platforms. The review further synthesizes current technical bottlenecks, including onboard computational limits, LiDAR performance degradation under adverse atmospheric conditions, and the difficulty of tracking fast-moving dynamic obstacles, as well as emerging research directions such as solid-state LiDAR integration, kinodynamic trajectory optimization, multi-sensor fusion (including radar- and event-camera-assisted schemes), learning-based exploration and foundation-model-based control, multi-UAV collaborative mapping, and simulation-to-reality transfer. The synthesis indicates that LiDAR remains a strong perceptual backbone for UAV autonomy, but that state-of-the-art systems increasingly combine it with inertial, visual, radar, and learning-based components rather than relying on LiDAR in isolation. Full article

(This article belongs to the Special Issue Applications of Robot Navigation in Autonomous Systems)

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52 pages, 4640 KB

Open AccessReview

Waste-Derived Natural Polymer Biosorbents for Toxic Metal Ions: Structure–Sorption Relationships, Modification Strategies, and Prospects for Solid-Phase Sensing

by Aisha Nurlybayeva, Zulaykho Smanova, Zhanna Tazhiyeva, Zulfiya Unerbayeva, Raikhan Rakhmetullayeva, Gulsim Matniyazova, Ainur Seitkhan, Raushan Taubayeva, Bekzat Saurbayeva, Aitkul Aidarova and Ergali Rustem

Polymers 2026, 18(19), 2336; https://doi.org/10.3390/polym18192336 (registering DOI) - 24 Sep 2026

Abstract

Waste-derived natural polymers offer a route to low-cost sorbents for toxic metal ions, but reported performance is difficult to compare because precursor composition, polymer processing, modification, and experimental conditions vary widely. This critical review examines silk fibroin, banana peel, orange peel, and pectin [...] Read more.

Waste-derived natural polymers offer a route to low-cost sorbents for toxic metal ions, but reported performance is difficult to compare because precursor composition, polymer processing, modification, and experimental conditions vary widely. This critical review examines silk fibroin, banana peel, orange peel, and pectin as structurally distinct platforms and evaluates how macromolecular chemistry, esterification, ionic crosslinking, morphology, and regeneration influence metal uptake. Particular attention is given to the distinction between untreated biomass, isolated biopolymers, and chemically engineered materials; to mechanistic evidence from spectroscopy, elemental analysis, ion exchange, and controlled structural modification; and to the limitations of interpreting Langmuir or pseudo-second order fitting as direct proof of adsorption mechanism. The literature supports strong roles for pectic carboxyl groups and Ca²⁺-mediated exchange in several cation-binding systems, while silk fibroin provides a reusable protein-based matrix with different donor-site chemistry. Across the four platforms, high q_max values are not transferable material constants and do not by themselves establish selectivity, practical treatment performance, or analytical sensitivity. Major gaps include precursor standardization, matched comparison of raw and modified sorbents, multicomponent and real-water testing, nonlinear model evaluation, continuous-flow studies, regeneration stability, metal recovery, and end-of-life management. Diffuse-reflectance sensing is considered as a downstream value-added function once a reproducible biosorbent has been established. An evidence-based roadmap is proposed for converting polymer-rich wastes into controlled, regenerable, and application-oriented biosorbents. Full article

(This article belongs to the Special Issue Advances in the Sustainability of Natural Polymer Composites)

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20 pages, 10537 KB

Open AccessArticle

Development and Metrological Evaluation of a Low-Cost Stepper Motor Positioning System with Magnetic Feedback: Analysis of Deterministic Error Mechanisms

by Alan Kondrusik, Agnieszka Choroszucho, Tomasz Szczegielniak and Dariusz Kusiak

Energies 2026, 19(19), 4542; https://doi.org/10.3390/en19194542 (registering DOI) - 24 Sep 2026

Abstract

Modern industrial automation systems and intelligent electric drives require precise and reliable methods for position measurement and actuator operational parameter diagnostics. Cost-effective systems that enable real-time monitoring of drive operation and analysis of errors affecting positioning accuracy are particularly crucial in this domain. [...] Read more.

Modern industrial automation systems and intelligent electric drives require precise and reliable methods for position measurement and actuator operational parameter diagnostics. Cost-effective systems that enable real-time monitoring of drive operation and analysis of errors affecting positioning accuracy are particularly crucial in this domain. This article presents the design and validation of a custom measurement and control platform for precise positioning of a stepper motor shaft using an AS5600 absolute magnetic encoder as a feedback element. The proposed architecture integrates the sensing hardware, controller based on the ESP32 microcontroller and dedicated software enabling the acquisition, analysis, and diagnostics of drive operating parameters. A comprehensive metrological evaluation of the sensor system was conducted, assessing measurement resolution, position accuracy, repeatability and the effect of the mechanical assembly tolerances on error generation. Experimental tests revealed the occurrence of systematic deviations resulting primarily from misalignment of mechanical components and non-ideal positioning of the magnet relative to the sensor. The results demonstrate that these systematic errors can be effectively compensated for using look-up tables (LUTs) or Fourier-series harmonic modeling. The developed platform offers a blueprint for implementing advanced, low-cost measurement, and control units in high-precision drives. Furthermore, the findings show that detailed sensor characterization and error source identification enable significant control quality improvements using budget-friendly components. Overall, this approach highlights the vital role of integrating data acquisition, analysis, and digital error correction to enhance accuracy in modern electric drives. Full article

(This article belongs to the Special Issue Efficient Energy Management: Modelling and Robust Control for Electric Drives and Mechatronic Systems)

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20 pages, 1867 KB

Open AccessArticle

Clinicopathological and Perioperative Factors Associated with Overall Survival and 90-Day Mortality Following Esophagectomy for Esophageal Cancer

by Hüseyin Esin and Murat Güner

J. Clin. Med. 2026, 15(19), 7453; https://doi.org/10.3390/jcm15197453 (registering DOI) - 24 Sep 2026

Abstract

Background/Objectives: Esophageal cancer (EC) is an aggressive malignancy, and outcomes following esophagectomy are influenced by both oncological and perioperative factors. This study aimed to identify clinicopathological and perioperative factors associated with overall survival (OS) after esophagectomy for EC and, secondarily, to evaluate factors [...] Read more.

Background/Objectives: Esophageal cancer (EC) is an aggressive malignancy, and outcomes following esophagectomy are influenced by both oncological and perioperative factors. This study aimed to identify clinicopathological and perioperative factors associated with overall survival (OS) after esophagectomy for EC and, secondarily, to evaluate factors associated with 90-day mortality. Methods: A total of 101 patients who underwent radical esophagectomy with two-field lymphadenectomy between April 2016 and April 2023 were retrospectively evaluated. The primary outcome was OS, defined as the time from esophagectomy to death from any cause or the date of last follow-up. The secondary outcome was 90-day postoperative mortality. OS was evaluated using Kaplan–Meier and Cox proportional hazards analyses, whereas 90-day mortality was assessed using Firth penalized-likelihood logistic regression because of the limited number of events. Results: During follow-up, 74 patients (73.3%) died, including 11 deaths within 90 days after esophagectomy. The estimated 1-, 3-, and 5-year OS rates were 80.1%, 44.8%, and 38.0%, respectively. In the whole-cohort multivariable Cox model, stratified by surgical approach, lymph node positivity was associated with poorer OS (HR 10.57, 95% CI 4.78–23.38; p < 0.001). Among patients receiving neoadjuvant chemotherapy (n = 76), lymph node positivity (HR 6.34, 95% CI 2.60–15.45; p < 0.001) and pathological non-response (HR 2.96, 95% CI 1.13–7.73; p = 0.027) were associated with poorer OS. In exploratory Firth regression analysis, lymph node positivity (OR 103.11, 95% CI 7.40 –> 1000; p < 0.001) and intraoperative complications (OR 75.58, 95% CI 7.42 –> 1000; p < 0.001) were strongly associated with 90-day mortality. Conclusions: Lymph node positivity was consistently associated with poorer OS both in the entire cohort and among patients receiving neoadjuvant chemotherapy. Pathological non-response was additionally associated with poorer OS in the neoadjuvant chemotherapy subgroup, while lymph node positivity and intraoperative complications were strongly associated with 90-day mortality. Full article

(This article belongs to the Special Issue Esophageal and Upper Gastrointestinal Surgery: Clinical Advances and Practical Updates)

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29 pages, 623 KB

Open AccessArticle

Online Deinterleaving of Frequency-Agile Radar Emitters via Jump-Set Representation and Adaptive Scoring

by Yunwei Pu, Yalin He, Chunjing Tian and Huijie Zhao

Electronics 2026, 15(19), 4409; https://doi.org/10.3390/electronics15194409 (registering DOI) - 24 Sep 2026

Abstract

Passive electronic intelligence (ELINT) and electronic warfare receivers must deinterleave pulse descriptor word (PDW) streams in real time: each pulse is labelled on arrival, unsupervised and irrevocably, at bounded cost. Frequency- and PRI-agile emitters defeat the single-Gaussian models of mainstream online sorters: an [...] Read more.

Passive electronic intelligence (ELINT) and electronic warfare receivers must deinterleave pulse descriptor word (PDW) streams in real time: each pulse is labelled on arrival, unsupervised and irrevocably, at bounded cost. Frequency- and PRI-agile emitters defeat the single-Gaussian models of mainstream online sorters: an agile emitter hops across (RF, PRI) cells, so, under a discrete-grid mixture model, its mean and covariance are not sufficient for membership, and moment-matched covariances of distinct emitters overlap. We cast sorting as membership inference under a mixture of probability mass functions (PMFs) on this grid, represent each emitter by its jump sets and joint PMF, and score each pulse by an approximate log-posterior at

O (\hat{K})

cost with support-bounded storage. On the Turing Synthetic Radar Dataset, against HDBSCAN, leader clustering, Gaussian-mixture stream clustering and Bayesian merging, the strictly online configuration averages a V-measure of

0.833

over eight scenarios,

+ 0.211

above the strongest baseline, and reaches

0.827

under pure agility, the only online method above

0.5

; a guarded post hoc merge raises the average to

0.927

, and a windowed optimal-transport sorter reaches

0.670

on agile scenarios. Given a correct partition and each emitter’s PRI, a shared-RF ablation credits

0.235

–

0.472

gains to the joint distribution term; no compared method separates such emitters from a blind cold start. Full article

25 pages, 971 KB

Open AccessArticle

Design of a 3D Aggregation Backbone Network-on-Chip Architecture for High-Speed Data Acquisition Systems

by Yunhui Deng, Chuanpei Xu, Wei Mo and Chunting Wan

Micromachines 2026, 17(10), 1119; https://doi.org/10.3390/mi17101119 (registering DOI) - 24 Sep 2026

Abstract

Time-interleaved high-speed data acquisition (HS-DAQ) systems based on three-dimensional network-on-chip (3D NoC) architectures require efficient transmission of multi-channel sampled data. However, existing general-purpose NoC architectures are not well suited for the deterministic multi-source aggregation communication pattern of HS-DAQ systems, which may result in [...] Read more.

Time-interleaved high-speed data acquisition (HS-DAQ) systems based on three-dimensional network-on-chip (3D NoC) architectures require efficient transmission of multi-channel sampled data. However, existing general-purpose NoC architectures are not well suited for the deterministic multi-source aggregation communication pattern of HS-DAQ systems, which may result in increased long-distance transmission overhead and localized traffic congestion. To address these issues, this paper proposes a 3D aggregation backbone network-on-chip architecture (3D AB-NoC) for HS-DAQ systems. This architecture is based on a 3D Mesh structure and enables the rapid transmission of long-distance aggregated data by establishing coarse-grained aggregation backbone subnets between defined aggregation routing nodes. Furthermore, a Backbone-Boosted XYZ (BB-XYZ) routing algorithm is proposed, which selects the next hop based on the remaining transmission distance of both the basic mesh path and the backbone path, thereby achieving coordinated routing for both local transmission and long-distance aggregation. Simulation results based on the Access Noxim platform demonstrate that the 3D AB-NoC maintains stable basic communication performance under general communication scenarios. In HS-DAQ communication scenarios, the proposed architecture reduces average latency by up to approximately 44%, improves throughput by approximately 29.3%, and significantly suppresses the growth of maximum latency under high-load conditions. Full article

29 pages, 5592 KB

Open AccessArticle

Investigating the Interacting Mechanisms of Precast Intersecting Cracks in Concrete: Insights from the Simulations Based on Discrete Element Method

by Yuexing Yu, Wenxin Li, Zhiwei Sun, Liang Liu, Zhiyong Zhang, Runlin Luo, Xianzheng Zhu and Shuyang Yu

Materials 2026, 19(19), 4097; https://doi.org/10.3390/ma19194097 (registering DOI) - 24 Sep 2026

Abstract

Underground mines often use shotcrete and reinforced concrete as support. Excavation disturbance, in situ stress, and blasting cause initial fractures to propagate. Intersecting fractures are common. This paper studies how intersecting fracture geometry affects fracture propagation under uniaxial compression. DEM and Particle Flow [...] Read more.

Underground mines often use shotcrete and reinforced concrete as support. Excavation disturbance, in situ stress, and blasting cause initial fractures to propagate. Intersecting fractures are common. This paper studies how intersecting fracture geometry affects fracture propagation under uniaxial compression. DEM and Particle Flow Code (PFC2D, Particle Flow Code) are used to build mesoscopic models with single-intersecting fractures (30–150°) and double-intersecting fractures with five offset levels: Zero, Minor, Moderate, Substantial, and Maximum. For single-intersecting fractures, smaller angles cause stronger shear slip and more multi-source cracking. Peak stress, ultimate strain, and final crack number (defined as the sum of tensile and shear micro-cracks from parallel-bond failure) increase. Larger angles lead to brittle failure and weaker properties. For double-intersecting fractures, bearing capacity first increases then stabilizes with offset. Zero and Minor offset have lower strength; Moderate, Substantial, and Maximum offset have higher capacity. Crack number increases with offset. Maximum offset has the most cracks but the smallest ultimate strain, while Substantial offset has the largest, with deformation from shear slip and higher brittle failure risk. Double-intersecting fracture specimens have fewer cracks but more concentrated damage and weaker properties than single-fracture specimens. This indicates damage distribution, not crack number, governs degradation. This study reveals how fracture configuration controls concrete response, providing mechanistic references for understanding failure behaviors related to safety-analysis and reinforcement-oriented research. Full article

(This article belongs to the Special Issue Advanced Experimental Technology, Theory and Numerical Methods in Concrete Materials)

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30 pages, 9754 KB

Open AccessArticle

Calculation Method for Jacking Force of Straight Steel Pipe Jacking Considering Circumferential Deformation Effect

by Shichong Yang, Tianshuo Xu, Peng Zhang, Jingran Guo, Kaiqi Li and Shukang Ying

Buildings 2026, 16(19), 3808; https://doi.org/10.3390/buildings16193808 (registering DOI) - 24 Sep 2026

Abstract

Flexible steel jacking pipes undergo circumferential deformation under external loads, causing soil pressure redistribution and additional frictional resistance. To accurately predict jacking forces, 2D numerical simulations were utilized to reveal a “quasi-elliptical” soil pressure redistribution evolving with burial depth, soil friction angle, and [...] Read more.

Flexible steel jacking pipes undergo circumferential deformation under external loads, causing soil pressure redistribution and additional frictional resistance. To accurately predict jacking forces, 2D numerical simulations were utilized to reveal a “quasi-elliptical” soil pressure redistribution evolving with burial depth, soil friction angle, and radius-to-thickness ratio. Based on Spangler’s theory and a full pipe–soil contact model, a novel analytical model incorporating soil arching is proposed. The elastic center method is employed to solve for bidirectional deformations. Crucially, an iterative fitting algorithm is introduced to quantify the non-linear coupling between bidirectional pipe deformation and soil pressure redistribution under various burial depths. Accounting for annular slurry lubrication, a comprehensive jacking force calculation framework is established and validated through an engineering case study. Results indicate: (1) Significant circumferential deformation renders traditional rigid pipe earth pressure assumptions inapplicable. (2) Case study horizontal deformation reaches 8‰ of the pipe diameter, inducing a maximum additional horizontal soil pressure of 125.26 kN/m², far exceeding traditional active earth pressure. (3) Measured jacking forces successfully fall within the model’s prediction envelope, with the lower limit yielding a −19.3% average error, significantly outperforming current specifications. These findings optimize the design and construction control of large-diameter flexible steel jacking pipes. Full article

(This article belongs to the Section Building Structures)

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32 pages, 1096 KB

Open AccessReview

Transcatheter Aortic Valve Implantation in Complex Anatomy: An Anatomy-Driven Framework for Bicuspid Stenosis, Pure Aortic Regurgitation, and the Small Annulus in the Era of Lifetime Management

by Daniel Miron Brie, Cristian Mornoș, Roxana Popescu and Alina Diduța Brie

J. Clin. Med. 2026, 15(19), 7452; https://doi.org/10.3390/jcm15197452 (registering DOI) - 24 Sep 2026

Abstract

Background: Transcatheter aortic valve implantation is established for severe calcific tricuspid aortic stenosis, but its application in bicuspid aortic valve (BAV) stenosis, pure native aortic regurgitation (AR), and small aortic annulus anatomy remains limited by heterogeneous morphology, device-specific constraints, and uncertain long-term [...] Read more.

Background: Transcatheter aortic valve implantation is established for severe calcific tricuspid aortic stenosis, but its application in bicuspid aortic valve (BAV) stenosis, pure native aortic regurgitation (AR), and small aortic annulus anatomy remains limited by heterogeneous morphology, device-specific constraints, and uncertain long-term outcomes. These settings require decisions that extend beyond immediate procedural success to encompass coronary access, reintervention, valve durability, and associated aortopathy. This review synthesizes current evidence and proposes an anatomy-driven framework integrating imaging, device selection, procedural planning, and lifetime management. Methods: A structured narrative review was conducted in accordance with the Scale for the Assessment of Narrative Review Articles (SANRA) criteria. PubMed/MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials were searched from 1 January 2010 to 31 March 2026 for studies addressing TAVI in BAV stenosis, pure native AR, and small aortic annulus anatomy. Randomized trials, meta-analyses, multicenter registries, pivotal device studies, and guideline or consensus documents were prioritized. After screening 2663 records and assessing 330 full-text reports, 101 records were retained for qualitative synthesis. Evidence was appraised by anatomical substrate, imaging phenotype, device strategy, procedural hazards, and implications for lifetime management. Results: In BAV stenosis, contemporary registry and prospective cohort data support high device success and acceptable early and mid-term outcomes in carefully selected patients; however, calcified raphe, bulky asymmetric leaflet or left ventricular outflow tract calcification, annular eccentricity, and concomitant aortopathy identify higher-risk phenotypes that often favor surgery. Randomized evidence in younger low-risk BAV patients remains limited and exploratory, with the NOTION-2 trial showing a numerically higher 3-year composite event rate after TAVI than surgical aortic valve replacement (20.4% vs. 7.8%; hazard ratio 2.9, 95% confidence interval 0.9–9.0) in the small bicuspid subgroup. In pure native AR, lack of annular calcification and frequent root dilatation impair anchoring of conventional transcatheter heart valves, increasing risks of migration, embolization, residual AR, and second-valve implantation. Dedicated leaflet-anchoring devices have improved outcomes: in ALIGN-AR, the JenaValve Trilogy system achieved procedural success above 95% in high-surgical-risk patients, although evidence remains single-arm and nonrandomized. In small annuli, the strongest comparative evidence comes from the SMART trial, in which supra-annular self-expanding valves were non-inferior to balloon-expandable valves for the 12-month clinical composite and reduced moderate/severe prosthesis–patient mismatch at 30 days (11.2% vs. 35.3%). Across all three phenotypes, electrocardiography-gated computed tomography is fundamental for defining anchoring, sizing, calcium distribution, root and coronary anatomy, anticipated coronary re-access, and the feasibility of redo-TAVI. Surgery remains particularly relevant when aortic repair, annular/root enlargement, or a more durable lifetime strategy is required. Conclusions: TAVI is feasible in selected patients with BAV stenosis, pure native AR, and small aortic annuli, but the evidentiary strength and optimal procedural strategy differ substantially across these anatomies. Treatment should be guided by an anatomy-driven, computed-tomography-based Heart Team assessment that integrates immediate procedural feasibility with age, surgical candidacy, aortopathy, prosthesis–patient mismatch risk, coronary access, durability, and future reintervention options. Surgery remains the more established strategy for many younger, operable patients with unfavorable BAV morphology or aortopathy, AR with root dilatation, or very small annuli amenable to enlargement. Dedicated randomized trials, standardized imaging criteria, and long-term durability data are needed to refine lifetime management in complex aortic valve anatomy. Full article

(This article belongs to the Special Issue Novel Perspectives in Transcatheter Aortic Valve Implantation)

13 pages, 3428 KB

Open AccessArticle

Benchmarking Gemini 1.5 Pro in Pediatric Emergency Radiology: Sensitivity Gap and Physiological Bias in the Immature Skeleton

by Cristiano Benelli, Luca Labianca, Vito Caiolo, Gabriele Altavilla and Nicola Maffulli

Diagnostics 2026, 16(19), 3112; https://doi.org/10.3390/diagnostics16193112 (registering DOI) - 24 Sep 2026

Abstract

Background/Objectives: To assess the diagnostic performance of Gemini 1.5 Pro, a general-purpose Large Multimodal Model (LMM), as a zero-shot, smartphone-based decision support tool to distinguish pediatric fractures from healthy controls. Methods: A retrospective diagnostic accuracy study was conducted on 182 pediatric radiographs (112 [...] Read more.

Background/Objectives: To assess the diagnostic performance of Gemini 1.5 Pro, a general-purpose Large Multimodal Model (LMM), as a zero-shot, smartphone-based decision support tool to distinguish pediatric fractures from healthy controls. Methods: A retrospective diagnostic accuracy study was conducted on 182 pediatric radiographs (112 confirmed fractures, 70 healthy controls) using the Gemini 1.5 Pro mobile interface with a 4-question prompt protocol (Detection, Characterization, Skeletal Maturity, Management). Diagnostic metrics were calculated with 95% Confidence Intervals (95% CI). Ground truth was established by a senior musculoskeletal radiologist. Results: The model showed an overall sensitivity of 90.2% (95% CI: 83.1–95.0%) and specificity of 87.1% (95% CI: 77.0–93.9%). A significant sensitivity gap occurred between displaced (100.0%; 95% CI: 91.4–100.0%) and non-displaced fractures (84.5%; 95% CI: 74.0–92.0%; p = 0.007). Qualitative taxonomy revealed a primary physiological bias leading to a 12.8% false-positive rate due to growth plate misinterpretation, alongside minor characterization and localization errors (3.6% of correctly identified fractures). When fractures were correctly identified, proposed management strategies aligned with international standards in 95.0% of cases. Inter-observer reliability was excellent (weighted k = 0.96). Conclusions: Gemini 1.5 Pro displays robust clinical reasoning for obvious trauma. However, its zero-shot performance is limited by subtle morphological disruptions and developmental anatomical nuances such as open growth plates. It shows promise as a mobile clinical decision support system for non-specialists, but expert human supervision remains necessary to ensure safety in the complex radiographic landscape of the immature skeleton. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

25 pages, 7193 KB

Open AccessArticle

Research on Semi-Active Suspension Attitude Control for Commercial Vehicle Cab Under Braking and Steering Conditions

by Yang Jin, Zhanyun An, Liang Li, Jun Liu, Yiyang Liu and Changcheng Yin

Vehicles 2026, 8(10), 230; https://doi.org/10.3390/vehicles8100230 (registering DOI) - 24 Sep 2026

Abstract

During transient maneuvers such as emergency braking and steering, the cab attitude of a commercial vehicle may change abruptly, thereby posing a potential risk to driving safety. To address this issue, this study investigates a cab attitude control method for a specific commercial [...] Read more.

During transient maneuvers such as emergency braking and steering, the cab attitude of a commercial vehicle may change abruptly, thereby posing a potential risk to driving safety. To address this issue, this study investigates a cab attitude control method for a specific commercial vehicle under braking and steering conditions based on a semi-active suspension system. First, full-vehicle road tests were conducted under emergency braking and steering conditions. The measured signals at the lower mounting points of the cab suspension were collected, preprocessed, and used as disturbance inputs to the system. Subsequently, performance tests were carried out on a continuous damping control (CDC) damper, and forward and inverse interpolation-based lookup table models of the damper, together with a three-degree-of-freedom predictive model of the cab, were established. In addition, a model predictive control (MPC) controller for the semi-active suspension was designed based on the predictive model, with different performance indices formulated for the braking and steering conditions. Finally, the control effectiveness of the MPC method on the cab attitude responses under braking and steering conditions was evaluated using the MATLAB/Simulink platform. The results show that the proposed control method can effectively improve the dynamic responses of the cab in terms of vertical acceleration, pitch angular acceleration, and roll angular acceleration, thereby mitigating braking- and steering-induced cab attitude deviations. Full article

21 pages, 883 KB

Open AccessArticle

SGIS-RC: Bio-Inspired Identifiability-Aware Single-Anchor Scalar-Range Compensation

by Xiang Zhang, Huaixiang Zhang, Ertao Li and Zhirong Wang

Biomimetics 2026, 11(10), 692; https://doi.org/10.3390/biomimetics11100692 (registering DOI) - 24 Sep 2026

Abstract

Biological control often combines selective sensing, complementary response scales, and attenuation under weak evidence. Guided by these principles, this paper presents Spectrum-Guided Identifiable Single-Anchor Range Compensation (SGIS-RC), a deterministic physics–data framework for single-anchor scalar-range compensation. SGIS-RC removes the local anchor–bias nuisance tangent from [...] Read more.

Biological control often combines selective sensing, complementary response scales, and attenuation under weak evidence. Guided by these principles, this paper presents Spectrum-Guided Identifiable Single-Anchor Range Compensation (SGIS-RC), a deterministic physics–data framework for single-anchor scalar-range compensation. SGIS-RC removes the local anchor–bias nuisance tangent from the kinematic sensitivity, retains a numerically conditioned physical subspace, and models the remaining discrepancy through a Chebyshev–Matérn global–local residual field. The learned correction is further regulated by leverage, configuration-space support, and bounded amplitude control. On two public workbooks, ABB IRB120 and HSR-C JR680, a pre-specified outer-partition evaluation performed after the model specification was frozen yielded configuration-group MAEs of

0.2306 \pm 0.0148

mm and

0.0493 \pm 0.0021

mm, respectively, while the matched conventional hybrid yielded slightly lower mean errors of

0.2244 \pm 0.0151

mm and

0.0478 \pm 0.0015

mm. Same-fit analyses show that support placement can alter the balance between global and local residual correction, and the block protocols indicate that support-shift behavior remains dataset dependent. Overall, SGIS-RC provides a structured and auditable framework that integrates identifiability-aware physical adaptation, global–local residual modeling, and support-aware deployment control for single-anchor scalar-range compensation. Full article

(This article belongs to the Special Issue Bio-Inspired Data-Driven Methods and Their Applications in Engineering Control, Optimization and AI)

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41 pages, 37205 KB

Open AccessArticle

Influenza A Virus RNA Polymerase Is Enriched on the Chromatin of Innate Immune Response Genes

by Jia Yi, Jessica Morel, Mickaël Costallat, Nathalie Lejal, Bernard Delmas, Christian Muchardt and Eric Batsché

Viruses 2026, 18(10), 1063; https://doi.org/10.3390/v18101063 (registering DOI) - 24 Sep 2026

Abstract

The influenza A virus hijacks host cell machinery by “snatching” molecular caps from cellular RNAs to prime its own transcription. While this process is typically associated with the beginning of genes, this study reveals that the viral RNA polymerase exerts a far-reaching influence [...] Read more.

The influenza A virus hijacks host cell machinery by “snatching” molecular caps from cellular RNAs to prime its own transcription. While this process is typically associated with the beginning of genes, this study reveals that the viral RNA polymerase exerts a far-reaching influence on host gene expression. Using genome-wide mapping and comparative pathway analyses, we show that viral polymerase (FluPol) recruitment is decoupled from general host transcriptional activity; instead, FluPol is markedly enriched at a distinct subset of promoters and enhancers associated with defense-related pathways. Beyond the initiation site, FluPol remains associated with host transcripts throughout elongation, extending into downstream-of-gene (DoG) regions. It further accumulates at gene ends, potentially contributing to widespread defects in transcription termination. By remaining linked to host transcripts across the entire gene body, FluPol could extend its opportunity for cap-snatching and impair the recycling of cellular transcription machinery. Together, these findings demonstrate how FluPol accumulation across key cellular defense loci spans from initiation through to termination, driving host transcriptional attenuation. Full article

(This article belongs to the Section Human Virology and Viral Diseases)

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19 pages, 6487 KB

Open AccessArticle

Optimized Synthesis and Properties of Dumbbell-Shaped NaYF₄:Yb,Tm@NaGdF₄:Eu@NH₂-MIL-53(Fe) Core–Shell Nanocomposite

by Xinyao Su, Wen Guo, Qunming Zhou, Tingting Xie, Lingyan Wu, Shangyang Wang, You Fu, Shurong Li, Wei Peng, Yun Qi, Lingyan Zhang and Peijun Meng

Molecules 2026, 31(19), 3412; https://doi.org/10.3390/molecules31193412 (registering DOI) - 24 Sep 2026

Abstract

Cancer theranostics urgently demands multifunctional nanomaterials capable of simultaneously enabling high-sensitivity imaging and multimodal synergistic therapy. In this study, a three-layer core–shell nanocomposite, NaYF₄:Yb,Tm@NaGdF₄:Eu@NH₂-MIL-53(Fe), was designed and synthesized. The NaYF₄:Yb,Tm nanoparticle core provides upconversion luminescence [...] Read more.

Cancer theranostics urgently demands multifunctional nanomaterials capable of simultaneously enabling high-sensitivity imaging and multimodal synergistic therapy. In this study, a three-layer core–shell nanocomposite, NaYF₄:Yb,Tm@NaGdF₄:Eu@NH₂-MIL-53(Fe), was designed and synthesized. The NaYF₄:Yb,Tm nanoparticle core provides upconversion luminescence upon near-infrared (NIR) excitation and can serve as an excitation source for photodynamic therapy. An epitaxially grown NaGdF₄:Eu intermediate shell was introduced to enhance luminescence and provide T₁-weighted magnetic resonance imaging (MRI) capability. The outermost NH₂-MIL-53(Fe) metal–organic framework shell was subsequently coated to provide potential chemodynamic therapy (CDT) capability. The effects of the Eu³⁺ doping concentration, reaction temperature, reaction time, and oleic acid (OA)/1-octadecene (ODE) ratio on the anisotropic growth into a dumbbell-like morphology were examined to determine the optimal conditions. Under the optimal conditions (10 mol% Eu³⁺, 300 °C, 60 min, OA/ODE = 4:16), core–shell nanocrystals with regular morphology, uniform size, and the strongest upconversion luminescence were obtained. Polyvinylpyrrolidone (PVP)-mediated surface functionalization successfully induced the in situ growth of the NH₂-MIL-53(Fe) outer shell, thereby constructing a three-layer core–shell nanocomposite as a potential theranostic platform. Various characterizations confirmed that the resulting composite integrates upconversion luminescence, paramagnetism, and hydroxyl radical generation capability, suggesting potential for NIR-driven dual-modal imaging-guided synergistic therapy. Full article

(This article belongs to the Section Materials Chemistry)

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22 pages, 7133 KB

Open AccessArticle

Comparative Analysis of Microbial Community and Metabonomics in Traditional Sour Meat from Different Regions of China

by Qing Guo, Shijie Liu, Qian Ding, Miaoyun Li, Dong Liang, Lijun Zhao and Yanxia Liu

Foods 2026, 15(19), 3424; https://doi.org/10.3390/foods15193424 (registering DOI) - 24 Sep 2026

Abstract

To characterize the microbial communities and metabolomic profiles of traditional sour meat from different regions of China, sour meat samples collected from Guangxi, Hunan, Guizhou, and Yunnan, together with laboratory-prepared sour meat (LSM), were analyzed using 16S rRNA gene amplicon sequencing and untargeted [...] Read more.

To characterize the microbial communities and metabolomic profiles of traditional sour meat from different regions of China, sour meat samples collected from Guangxi, Hunan, Guizhou, and Yunnan, together with laboratory-prepared sour meat (LSM), were analyzed using 16S rRNA gene amplicon sequencing and untargeted metabolomics. Significant regional differences were observed in both microbial community composition and metabolite profiles. Firmicutes were the predominant bacterial phylum in most samples, whereas Proteobacteria showed relatively higher abundances in Guizhou sour meat (GZSM) and Yunnan sour meat (YNSM). At the genus level, Lactobacillus predominated in Guangxi sour meat (GXSM) and Hunan sour meat (HNSM), while GZSM and YNSM exhibited distinct bacterial community characteristics with enrichment of specific genera. Metabolomic analysis identified substantial differences in metabolite composition among regions, and the differential metabolites were mainly associated with amino acid, carbohydrate, and lipid metabolic pathways. Overall, traditional sour meat from different geographical origins exhibited pronounced regional differentiation in microbial and metabolomic characteristics. These findings provide new insights into the regional characteristics of traditional Chinese sour meat and support future studies on microbial resources, quality evaluation, and product standardization. Full article

(This article belongs to the Section Foodomics)

21 pages, 1116 KB

Open AccessArticle

Measuring End-of-Life Care: Development of a National Questionnaire for Bereaved Family Members

by Alexandra Pereira, Amélia Ferreira and Sara Pinto

Healthcare 2026, 14(19), 3178; https://doi.org/10.3390/healthcare14193178 (registering DOI) - 24 Sep 2026

Abstract

Background: Evaluating end-of-life care quality remains a central challenge in health systems facing population ageing and complex chronic disease trajectories. Given the clinical challenges of direct data collection at the end-of-life, bereaved family members act as critical proxies, providing data on the care [...] Read more.

Background: Evaluating end-of-life care quality remains a central challenge in health systems facing population ageing and complex chronic disease trajectories. Given the clinical challenges of direct data collection at the end-of-life, bereaved family members act as critical proxies, providing data on the care delivered in the final months of life. However, most available instruments lack the contextual sensitivity required for national-level epidemiological surveillance. Objectives: This study aims to develop and establish the face validity of a national questionnaire to evaluate the healthcare trajectory of adults with advanced chronic disease from the proxy perspective. Methods: A four-stage developmental protocol was implemented: (1) conceptual framework definition; (2) item generation through a review of national regulations, a scoping review of seven international instruments, and a focus group with clinical experts; (3) item reduction and refinement through expert panel review; and (4) face validity and feasibility testing through cognitive interviews and a pilot study. Results: The consensus process and pilot testing resulted in a final instrument comprising 84 items, structured into 7 sections and 17 thematic clusters. The questionnaire covers core care trajectories, the last 48 h of life, and bereavement support, while integrating specific national settings like integrated continuous care, alongside items on spiritual care and communication. The pilot study yielded a mean completion time of 14.6 min, while cognitive interview and pilot testing supported participant acceptability and feasibility for both telephone-assisted and self-administration modes. Conclusions: This questionnaire provides a face-validated, evidence-informed tool for post-death proxy reporting at the end-of-life. By aligning international quality indicators with country-specific healthcare structures, the instrument is ready for further testing of its reliability and validity and may support future comparative research, clinical auditing and health policy development. Full article

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30 pages, 3820 KB

Open AccessArticle

A ResNet with Coordinate Attention for Intelligent Prediction of the Strouhal Number of 2D Bluff Body Sections at Reynolds 20,000

by Qiuhan Kong, Li Ming, Ke Li, Bowen Yan, Shaopeng Li and Yu Qin

Aerospace 2026, 13(10), 864; https://doi.org/10.3390/aerospace13100864 (registering DOI) - 24 Sep 2026

Abstract

Accurate evaluation of the Strouhal number is important for wind-resistant design, but traditional aerodynamic assessments are computationally expensive. To support rapid schematic design, this paper proposes a deep learning framework to predict the Strouhal number for 2D bluff bodies. Arbitrary irregular sections are [...] Read more.

Accurate evaluation of the Strouhal number is important for wind-resistant design, but traditional aerodynamic assessments are computationally expensive. To support rapid schematic design, this paper proposes a deep learning framework to predict the Strouhal number for 2D bluff bodies. Arbitrary irregular sections are represented using a unified three-channel geometric tensor that combines distance and spatial coordinate fields. A Residual Network integrated with Coordinate Attention, termed ResCA-Net, is developed to focus on vortex-shedding determinants, particularly leading-edge separation points. The model was trained on 1000 randomly generated convex sections, with target St values obtained from 2D URANS simulations at Re = 2 × 10⁴. On an independent test set, ResCA-Net achieves an R² of 0.9129, an MAE of 0.0316, and a median absolute percentage error of 6.56%. Systematic benchmarking shows that the embedded Coordinate Attention outperforms SE, CBAM, and the baseline ResNet. A single inference takes only 43.56 milliseconds, which is over 160,000 times faster than transient CFD simulations. This end-to-end method provides an efficient and accurate surrogate model for rapid iterative screening of aerodynamic shapes. Full article

(This article belongs to the Special Issue Machine Learning for Aerodynamic Analysis and Optimization)

15 pages, 742 KB

Open AccessArticle

Association of Structured Preclinical Phantom Training and OSCE/OSPE-Based Assessment with Endodontic Procedural Complications Among Dental Students: A Retrospective Cohort Study

by Esma Dinger, Özlem Sivas Yılmaz, Melis Oya Ateş, Münevver Ayşegül Görgülü Pınar, Ayşe Nur Atay Altunkaya and Gül Sena Eser

Diagnostics 2026, 16(19), 3113; https://doi.org/10.3390/diagnostics16193113 (registering DOI) - 24 Sep 2026

Abstract

Background/Objectives: The aim of this retrospective cohort study was to evaluate the association between structured phantom laboratory training and Objective Structured Clinical Examination (OSCE)/Objective Structured Practical Examination (OSPE)-based assessment and procedural complications observed during root canal treatments performed by undergraduate dental students in [...] Read more.

Background/Objectives: The aim of this retrospective cohort study was to evaluate the association between structured phantom laboratory training and Objective Structured Clinical Examination (OSCE)/Objective Structured Practical Examination (OSPE)-based assessment and procedural complications observed during root canal treatments performed by undergraduate dental students in the clinical setting. Methods: Periapical radiographs obtained from 1204 completed root canal treatments performed at the Department of Endodontics, Faculty of Dentistry, Bolu Abant İzzet Baysal University, were evaluated. The teeth that underwent root canal treatment in the clinic by students who had not received structured phantom laboratory training and OSCE/OSPE-based assessment and by those who had received this training were divided into two groups, comprising 722 teeth and 482 teeth, respectively. The association between training status and overall procedural complications was analyzed using generalized linear mixed models (GLMMs), taking into account the clustering of treatments within students. Results: The prevalence of at least one procedural complication was 42.9% in the non-training group and 37.8% in the training group. In the primary GLMM analysis adjusted for the number of treated teeth per student, training status was not significantly associated with the overall occurrence of procedural complications (odds ratio (OR) = 0.58, 95% confidence interval (CI): 0.29–1.16, p = 0.069). In the secondary/exploratory analyses, lower odds of canal transportation (OR = 0.12, 95% CI: 0.02–0.94, p = 0.044) and overfilling (OR = 0.56, 95% CI: 0.38–0.82, p = 0.003) were observed in the training group, whereas the odds of missed canals were higher (OR = 6.23, 95% CI: 2.08–18.65, p = 0.001). The likelihood of procedural complications was higher in molar teeth than in anterior teeth (OR = 5.84, 95% CI: 3.66–9.46, p < 0.001). Conclusions: Although structured phantom laboratory training and OSCE/OSPE-based assessment were not significantly associated with the overall occurrence of procedural complications, exposure to the revised educational program was associated with lower odds of certain technical errors. Full article

(This article belongs to the Section Clinical Diagnosis and Prognosis)

34 pages, 1710 KB

Open AccessArticle

Explainable Cross-Dataset Violence Detection for Public Safety Using a Two-Stream I3D Network

by Kubilay Muhammed Sunnetci, Ufuk Bal and Ahmet Çağdaş Seçkin

Appl. Sci. 2026, 16(19), 9524; https://doi.org/10.3390/app16199524 (registering DOI) - 24 Sep 2026

Abstract

Camera networks now cover almost every public space, but the footage they generate has long outpaced what any human team can watch in real time. That gap is exactly where automated violence detection earns its place. The hard part is ambiguity—a hug or [...] Read more.

Camera networks now cover almost every public space, but the footage they generate has long outpaced what any human team can watch in real time. That gap is exactly where automated violence detection earns its place. The hard part is ambiguity—a hug or a bit of play-fighting can look a lot like a real attack, and systems that get this wrong flood operators with false alarms. Since violence lives in motion as much as in appearance, we build GoogLeNet-based Inflated 3D (I3D) two-stream classifiers that read space and time together. Three variants are trained and validated on the Real Life Violence Situations (RLVS) dataset (2000 videos, 80/20 split), each differing in temporal depth and resolution. The strongest, I3D Network 3, reaches 98.75% in-domain validation accuracy, with an F1 score of 98.74% and a Matthews Correlation Coefficient of 97.51%, values that should be read as upper bounds because of the file-level split and the validation-based checkpoint selection. Numbers on the home dataset only tell part of the story, so we push every model onto the independent RWF-2000 set, untouched during training. Even under this strict zero-shot transfer, I3D Network 3 holds 79.75% accuracy, although it is seen that this single value hides a strongly asymmetric error profile. The recall of the violence class decreases to 65.70%, in other words 343 of 1000 violent clips are missed, while the recall of the peaceful class remains at 93.80%, and McNemar and paired t-tests confirm the gaps between networks are real, rather than noise. For this reason, this result is evaluated as partial generalization. The only published values obtained under the same RLVS to RWF-2000 zero-shot protocol are 68.76% and 74.68%, so the margin is real but narrow. To open the black box, 3D Grad-CAM produces separate spatial and motion explanations that show where and when the model sees violence. Finally, the best model is embedded in ViolenceNet, a lightweight interface that keeps a human in the loop. Considering the missed-incident rate measured under domain shift, ViolenceNet is positioned as an assisted-review and triage tool, rather than as an autonomous alarm system. Full article

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

40 pages, 5724 KB

Open AccessReview

Symmetry Design of Metal–Organic Frameworks for High-Performance Piezocatalysis: Fundamental Mechanisms and Multi-Scale Structural Regulation

by Kailai Zhang, Ao Feng, Aoan Chen, Hang Chen, Shurui Xu, Guoyu Zhong and Baizeng Fang

Catalysts 2026, 16(10), 867; https://doi.org/10.3390/catal16100867 (registering DOI) - 24 Sep 2026

Abstract

Driven by the pursuit of carbon-neutral and distributed energy systems, extensive efforts have been devoted to harvesting ubiquitous low-grade ambient mechanical energy. Piezocatalysis offers a unique light-independent and electricity-free pathway that converts mechanical vibration into reactive radical species. Conventional inorganic ferroelectrics and piezoelectric [...] Read more.

Driven by the pursuit of carbon-neutral and distributed energy systems, extensive efforts have been devoted to harvesting ubiquitous low-grade ambient mechanical energy. Piezocatalysis offers a unique light-independent and electricity-free pathway that converts mechanical vibration into reactive radical species. Conventional inorganic ferroelectrics and piezoelectric polymers face severe limitations originating from rigid lattice configurations, insufficient surface active sites, and unmodulable electronic band structures. Benefiting from reticular chemistry, metal-organic frameworks (MOFs) emerge as versatile piezoactive candidates. Crystallographic inversion symmetry, which acts as the core determinant of intrinsic lattice dipoles and strain-activated charge screening behavior, can be precisely regulated at the molecular level. Most existing reviews classify MOFs piezocatalysts primarily by metal-node types. However, a systematic analytical framework centered on symmetry breaking to clarify structure-activity relationships is still lacking. This review establishes a multi-scale symmetry modulation paradigm focusing on crystal inversion-symmetry engineering. It comprehensively demonstrates three fundamentally piezocatalytic mechanisms and systematically highlights the unique piezoelectric structural superiority of tunable MOFs over traditional piezoelectric materials. This work elaborates a three-tier symmetry engineering strategy covering intrinsic lattice regulation, metal-mediated dipole amplification, and multicomponent heterostructure construction. It summarizes full-scale bottlenecks involving fundamental mechanisms, material design, and device integration. This review delivers symmetry-oriented structural principles and theoretical support for the efficient utilization of low-grade mechanical energy. Finally, it discusses the prospects of artificial intelligence-assisted high-throughput screening to advance the rational exploration of high-performance, symmetry-compliant piezocatalytic MOFs. Full article

(This article belongs to the Section Catalytic Reaction Engineering)

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14 pages, 2269 KB

Open AccessArticle

A Harmonic-Energy Regional-Control Jamming Method Based on a Radiating Space–Time-Modulated Digital Metasurface

by Yuehang Sun, Yu Xia, Yuhua Chen, Tianshuo Gao, Xudong Bai, Jingfeng Chen and Ronghong Jin

Photonics 2026, 13(10), 908; https://doi.org/10.3390/photonics13100908 (registering DOI) - 24 Sep 2026

Abstract

Complex electromagnetic warfare poses increasingly stringent requirements on the spatial selectivity of jamming systems. Existing jamming methods mainly focus on false-target generation, while research on regional coverage of harmonic energy remains limited. In this paper, a harmonic-energy regional-control jamming method based on a [...] Read more.

Complex electromagnetic warfare poses increasingly stringent requirements on the spatial selectivity of jamming systems. Existing jamming methods mainly focus on false-target generation, while research on regional coverage of harmonic energy remains limited. In this paper, a harmonic-energy regional-control jamming method based on a radiating space–time-modulated digital metasurface is proposed. By optimizing the turn-on instants and duty cycles of 1-bit programmable elements, the amplitude, phase, and far-field superposition of the target harmonic are controlled, thereby constructing a predefined jamming region as a reconfigurable angular-domain energy window. The energy ratio inside the designated region, the in-region fluctuation, and the out-of-region leakage are incorporated into a unified optimization objective, enabling different jamming modes such as narrow-angle highly concentrated coverage and wide-angle uniform coverage. Both simulations and experiments verify the controllability of the harmonic radiation patterns and regional energy distributions under different coverage angles. The proposed method provides a quantitatively designable implementation approach for intelligent jamming systems with spatially reconfigurable harmonic energy. Full article

(This article belongs to the Special Issue Metasurface-Based Photonic Devices and Their Applications)

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21 pages, 902 KB

Open AccessArticle

Enhancing FT-MIR Prediction of Short-Chain Free Fatty Acids in Milk Through High-Lipolysis Field Samples, Reference Method Evaluation and Machine Learning Approaches

by Octave S. Christophe, Didier Veselko, Julie Leblois, Frédéric Dehareng and Hélène Soyeurt

Foods 2026, 15(19), 3423; https://doi.org/10.3390/foods15193423 (registering DOI) - 24 Sep 2026

Abstract

Lipolysis is a longstanding and appealing topic within the dairy industry. Having been extensively researched throughout the twentieth century, lipolysis is often prematurely dismissed as a settled or outdated field of study. In recent years, the advent of robotic milking systems and increased [...] Read more.

Lipolysis is a longstanding and appealing topic within the dairy industry. Having been extensively researched throughout the twentieth century, lipolysis is often prematurely dismissed as a settled or outdated field of study. In recent years, the advent of robotic milking systems and increased milking frequencies have led to a rise in lipolysis levels, sparking renewed interest in the monitoring of milk quality. Predicting lipolysis more effectively relies on the analysis of free fatty acid (FFA) concentrations. Recent research has demonstrated the feasibility of quantifying individual FFA in raw milk. In particular, Fourier-transform mid-infrared (FT-MIR) spectroscopy has shown considerable potential for predicting these compounds. However, that study presented several limitations, including the use of non-standardized reference methods and the reliance on artificially lipolyzed samples to enhance variability within the calibration dataset. To overcome these limitations, FT-MIR FFA models have been used as a preliminary screening tool in order to select samples (n = 248) with high lipolysis, and the selected samples were analyzed using the ISO reference method. A total of 248 samples were selected, of which 208 were obtained through the Walloon DHI in Belgium and 40 were sampled at the CRA-W experimental farm. A comparison between the two reference methods was performed and highlighted the need to harmonize reference analysis as the two reference methods are only comparable for short-chain free fatty acids (SCFFA). A mixed model for SCFFA combining both references was built using different algorithms such as Partial Least Squares (PLS), Kernel Ridge Regression (KRR), Support Vector Machine Regression (SVR), Random Forest Regression (RFR) and Gaussian Process Regression (GPR). The model developed for SCFFA showed predictive performances comparable to those reported in the literature with an R²val of 0.80 and an RMSEval of 32.08 mg/L. Qualitative models for SCFFA were created with a threshold highlighted in the literature using the same algorithms as the quantitative model and gave an accuracy of correct classification of 85% applied on the test dataset. This work has highlighted the necessity to correctly select the reference method in order to build the calibration dataset. Non-linear algorithms provided analyte-dependent improvements over PLS, particularly for C6, C8 and SCFFA prediction. Full article

(This article belongs to the Special Issue Spectroscopy and Intelligent Data Processing for Food Quality, Safety and Authenticity)

31 pages, 4431 KB

Open AccessArticle

A Socio-Technical Fuzzy Decision-Support Framework for Sustainable Smart Waste Management

by Fazeelat Aziz and Abroon Qazi

Sustainability 2026, 18(19), 9812; https://doi.org/10.3390/su18199812 (registering DOI) - 24 Sep 2026

Abstract

The adoption of smart waste management systems (SWMSs) is increasingly important for textile organizations seeking to improve sustainability while addressing interconnected technological, managerial, organizational, and environmental constraints. A persistent gap is that prior SWMS studies often examine digital technologies or individual barriers in [...] Read more.

The adoption of smart waste management systems (SWMSs) is increasingly important for textile organizations seeking to improve sustainability while addressing interconnected technological, managerial, organizational, and environmental constraints. A persistent gap is that prior SWMS studies often examine digital technologies or individual barriers in isolation, offering limited support for jointly structuring socio-technical constraints and selecting implementation strategies under uncertainty in expert judgment. This study develops an integrated socio-technical fuzzy multi-criteria decision-support framework in which technical infrastructure and data capabilities are evaluated alongside managerial decisions, organizational capabilities, workforce factors, and the broader environmental and policy context. Barriers and implementation alternatives were identified from the literature and refined through purposive consultation with three experienced textile-industry professionals in Pakistan, with 7–14 years of experience across environment, health and safety, technical, and procurement functions. Spherical fuzzy Analytic Hierarchy Process (SF-AHP) converts linguistic pairwise judgements into criteria and sub-criteria weights while accounting for varying degrees of agreement, disagreement, and uncertainty in expert assessments. These weights are then transferred to triangular fuzzy VIKOR (TF-VIKOR) to evaluate four implementation strategies against the identified barriers. Organizational constraints receive the highest weight (0.284), followed by managerial (0.254), environmental (0.233), and technological (0.230) constraints. Employee empowerment and training (A₃) emerges as the preferred strategy (Q = 0.0000), followed by investment in R&D and innovation (A₁; Q = 0.7702), policy advocacy and government support (A₄; Q = 0.8996), and cross-sector collaboration and partnerships (A₂; Q = 0.9795). The first-place ranking of A3 remains unchanged when the VIKOR decision parameter varies from 0.1 to 0.9, although the ordering of A₂ and A₄ changes at higher values of the parameter. The findings are specific to this expert-based case in Pakistan’s textile industry and should not be interpreted as statistically representative of the national industry. The framework supports managers and policymakers in prioritizing capability building, collaboration, technology investment, and policy support while considering environmental, economic, and social sustainability outcomes. In practical terms, the ranking can guide the sequencing of SWMS investments by emphasizing workforce readiness before sequencing technology investment, policy support, and cross-sector collaboration for capabilities such as waste tracking, automation, recycling technologies, and data analytics. Full article

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