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Defect detection in the hot rolling process is closely linked to the quality of the final product. Among these defects, slab camber during the intermediate rolling stage is one of the primary manifestations of asymmetry, which significantly impairs both the quality of the finished strip and the stability of subsequent rolling processes. Conventional image-based edge detection methods for slab camber are prone to detection deviations in complex industrial environments, mainly due to their weak noise robustness. To address the scientific challenge of low accuracy and poor robustness in feature extraction for hot-rolled intermediate slab camber detection, which is induced by environmental interference in complex industrial settings, we break through the technical bottlenecks of traditional edge detection methods and existing deep learning models in terms of channel–spatial feature collaborative optimization and anti-interference fusion of multi-scale features. We establish a dense perception network model integrated with a channel–spatial attention mechanism, realize robust feature recognition of slab edges under complex working conditions, and provide theoretical and technical support for the real-time quantitative detection of slab shape defects in the hot rolling process. The proposed model significantly improves detection accuracy and robustness through multi-scale feature enhancement and noise suppression, effectively meeting the requirements for real-time quantitative detection of slab camber in the roughing rolling stage. Field experiments verify that the method increases detection accuracy by 36.55% and achieves favorable performance on evaluation metrics, including ODS and OIS. Full article

(This article belongs to the Special Issue Advances in Rolling Process of Metallic Materials: Measurement, Modeling, Optimization and Applications)

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25 pages, 714 KB

Open AccessArticle

A Risk-Informed Sustainability Index for Infrastructure Drainage Projects: A Fuzzy Decision-Making Framework

by Murat Gunduz, Khalid Kamal Naji and Ahmed Eltagy

Sustainability 2026, 18(7), 3311; https://doi.org/10.3390/su18073311 (registering DOI) - 28 Mar 2026

Abstract

Infrastructure drainage projects play a critical role in urban development but are increasingly exposed to environmental, operational, and climate-related risks that challenge their long-term sustainability. Despite this, decision-makers continue to lack risk-informed, structured methods to assess sustainability performance in an uncertain environment. In order to facilitate evidence-based decision-making and sustainable risk management, this study suggests a risk-informed sustainability index for infrastructure drainage projects. The study first points out a weakness in the methods currently used for sustainability assessments, specifically the lack of risk-sensitive, standardized frameworks designed for drainage infrastructure systems. Altogether, 28 sustainability indicators are identified, with 22 indicators retained after the application of fuzzy set theory criteria. The sustainability index is developed by normalizing, weighting, and combining these indicators using a multi-criteria decision analysis (MCDA) method. To show the usefulness and practicality of the suggested approach in assessing sustainability performance and pinpointing risk-critical improvement areas, it is used for a long-term infrastructure drainage project. In order to improve infrastructure resilience, the findings emphasize the significance of early integration of sustainability and risk considerations, stakeholder engagement, and ongoing performance monitoring. The suggested approach offers a flexible and transferable framework for risk-informed decision-making, assisting engineers, project managers, and policymakers in enhancing the resilience and sustainability of infrastructure drainage systems. Full article

(This article belongs to the Special Issue Engineering Safety Prevention and Sustainable Risk Management: 2nd Edition)

27 pages, 4695 KB

Open AccessArticle

A Novel Weighted Ensemble Framework of Transformer and Deep Q-Network for ATP-Binding Site Prediction Using Protein Language Model Features

by Jiazhi Song, Jingqing Jiang, Chenrui Zhang and Shuni Guo

Int. J. Mol. Sci. 2026, 27(7), 3097; https://doi.org/10.3390/ijms27073097 (registering DOI) - 28 Mar 2026

Abstract

Adenosine triphosphate (ATP) serves as a central energy currency and signaling molecule in cellular processes, with ATP-binding sites in proteins playing critical roles in enzymatic catalysis, signal transduction, and gene regulation. The accurate identification of ATP-binding sites is essential for understanding protein function mechanisms and facilitating drug discovery, enzyme engineering, and disease pathway analysis. In this study, we present a novel hybrid deep learning framework that synergizes heterogeneous learning paradigms based on protein sequence information for accurate ATP-binding site prediction. Our approach integrates two complementary base classifiers. One is a Transformer-based model, which leverages high-level contextual embeddings generated by Evolutionary Scale Modeling 2 (ESM-2), a state-of-the-art protein language model, combined with a local–global dual-attention mechanism that enables the model to simultaneously characterize short-segment and long-range contextual dependencies across the entire protein sequence. The other is a deep Q-network (DQN)-inspired classifier that achieves residue-level prediction as a sequential decision-making process. The final predictions are generated using a weighted ensemble strategy, where optimal weights are determined via cross-validations to leverage the strengths of both models. The prediction results on benchmark independent testing sets indicate that our method achieves satisfactory performance on key metrics. Beyond predictive efficacy, this work uncovers the intrinsic biological mechanisms underlying protein–ATP interactions, including the synergistic roles of local structural motifs and global conformational constraints, as well as family-specific binding patterns, endowing the research with substantial biological significance. The research in this work offers a deeper understanding of the protein–ligand recognition mechanisms and supportive efforts on large-scale functional annotations that are critical for system biology and drug target discovery. Full article

(This article belongs to the Section Molecular Informatics)

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17 pages, 847 KB

Open AccessArticle

Low-Dose CT Image Denoising Based on a Progressive Fusion Distillation Network with Pixel Attention

by Xinyi Wang and Bao Pang

Appl. Sci. 2026, 16(7), 3292; https://doi.org/10.3390/app16073292 (registering DOI) - 28 Mar 2026

Abstract

Low-dose computed tomography (LDCT) can effectively reduce ionizing radiation; however, the associated image noise and artifacts can severely compromise the accuracy of clinical diagnosis. To address the challenge of balancing noise suppression and detail preservation in LDCT images, this study proposes a deep learning (DL)-based image denoising method termed Progressive Fusion Distillation Network (PFDN). Building upon the Information Multi-distillation Network (IMDN), the proposed method incorporates a pixel attention (PA) mechanism and a progressive fusion strategy, and further designs a Pixel Parallel Extraction Block (PPEB) together with a Progressive Fusion Distillation Block (PFDB) to fully exploit multi-scale and multi-channel features, thereby optimizing the image denoising network through efficient feature separation and re-fusion. In addition, by explicitly leveraging the noise characteristics specific to LDCT images, the method establishes an end-to-end training framework suitable for medical imaging. Experimental results demonstrate that PFDN not only effectively reduces image noise and artifacts, but also enhances overall image quality while preserving diagnostically relevant image structures under the adopted evaluation setting. Full article

22 pages, 3794 KB

Open AccessArticle

Retarding Effect and Hydration Mechanism of Sodium Polyacrylate on Magnesium Potassium Phosphate Cement

by Yunpeng Cui, Runqing Liu, Yuanquan Yang, Bo Pang and Yihe Wang

Materials 2026, 19(7), 1349; https://doi.org/10.3390/ma19071349 (registering DOI) - 28 Mar 2026

Abstract

Magnesium phosphate cement (MPC) is a type of rapid-hardening inorganic cementitious material, which has important application value in rapid road repair, solidification of hazardous and radioactive waste, and other fields. However, it suffers from excessively fast setting and hardening and a short working time retention, which severely restrict its engineering application. Therefore, the development of high-efficiency set retarders is of great significance for optimizing MPC performance, enhancing its construction workability, and expanding its application scope. In this study, the effect of sodium polyacrylate (PAAS) on the setting and hardening of magnesium potassium phosphate cement (MKPC) was investigated by testing the setting time and fluidity at a low water-to-solid ratio (W/S = 0.18). Through pH and electrical conductivity measurements, combined with XRD, TG/DTG, and FTIR characterizations, we elucidated the retarding mechanism of PAAS on MKPC using a high water-to-solid ratio (W/S = 10). The results indicate that the setting time of MKPC is positively correlated with the PAAS dosage, whereas the fluidity and compressive strength exhibited a negative correlation with the PAAS dosage. Additionally, PAAS reduces the total heat release and the heat release rate of MKPC. The addition of PAAS increased the pH of the suspension, thereby reducing the solubility of MgO, but did not inhibit the dissolution of KH₂PO₄ The carboxylate groups in PAAS chemically reacted with Mg²⁺ on the surface of MgO to form magnesium carboxylate complexes (Mg-PAA), which remained as precipitates in the MKPC suspension system, thus reducing the amount of available Mg²⁺ participating in the hydration reaction. Furthermore, PAAS had no effect on the final precipitate composition at the end of hydration, which was composed of MgKPO₄·6H₂O and Mg₃(PO₄)₂·22H₂O in all cases. Full article

(This article belongs to the Special Issue Advances in Hydration, Microstructure, and Properties of Modern Cement and Concrete Composites)

34 pages, 393 KB

Open AccessArticle

Symmetry-Aware Dual-Encoder Architecture for Context-Aware Grammatical Error Correction in Chinese Learner English: Toward a Spaced-Repetition Instructional Structure Sensitive to Individual Differences

by Jun Tian

Symmetry 2026, 18(4), 579; https://doi.org/10.3390/sym18040579 (registering DOI) - 28 Mar 2026

Abstract

Grammatical error correction (GEC) for Chinese learner English is still dominated by sentence-level modeling, which limits discourse-level consistency and weakens adaptation to learner-specific error profiles. From an instructional perspective, these limitations also reduce the value of automated feedback as a basis for spaced-repetition instructional structures sensitive to individual differences. This study proposes a symmetry-aware dual-encoder architecture for context-aware GEC in Chinese learner English. A context encoder captures preceding-sentence information, while a source encoder integrates BERT-based semantic representations with Bi-GRU-based syntactic features for the current sentence. A gated decoder performs asymmetric fusion of local and contextual evidence. To better reflect corpus-level tendencies in Chinese learner English, a CLEC-informed augmentation strategy generates synthetic errors using empirical category frequencies as a coarse sampling prior. Experiments on CoNLL-2014, JFLEG, and CLEC show consistent improvements over strong neural baselines in F_0.5 and GLEU under the current desktop-oriented implementation setting. Nevertheless, the integration of BERT, dual encoders, and gated decoding introduces non-negligible computational overhead, and the present system is therefore better suited to desktop writing-support scenarios than to strict real-time or large-scale online deployment. The proposed framework thus provides a practical technical basis for personalized grammar feedback and for future spaced-repetition instructional designs in ESL writing support. Full article

(This article belongs to the Special Issue Symmetry and Asymmetry in Natural Language Processing)

32 pages, 19480 KB

Open AccessArticle

Influence of Punch Shape on Joint Strength in Forge Joining of Al-Si-Coated 22MnB5 Steel During Hot Stamping and Application to Hat Bending

by Jarupong Charoensuk, Takuma Iwai, Surasak Suranuntchai and Tomoyoshi Maeno

Metals 2026, 16(4), 376; https://doi.org/10.3390/met16040376 (registering DOI) - 28 Mar 2026

Abstract

Ultra-high-strength steel sheets were joined by forge joining during hot stamping. This study investigated the influence of punch cross-sectional shape and punch tip inclination shape on joint strength through experiments and finite element simulation, with applications in hat bending. The experiments systematically evaluated various punch geometries by varying the punch’s cross-sectional shape and the aspect ratio of rectangular punches. A second set of experiments focused on the influence of punch tip inclination shape. These experiments examined a rectangular punch with a slope. Joint strength is primarily assessed by measuring the tensile shear load. Finite element simulation was used to analyze joining mechanisms, investigating contact pressure and surface expansion rate distribution. The results from the experiments consistently indicated that, for a constant cross-sectional area, punch shapes with a larger punch perimeter on the upper sheet yielded a higher tensile shear load, though the changing inclination shape of the rectangular punch tip did not lead to an observed improvement in joint strength. Finite element simulation analysis revealed that punch shapes promoting a uniform distribution of contact pressure and surface expansion rate across the joint area tended to exhibit higher joint strength compared with the same punch cross-sectional area but less uniform distribution, a tendency that was more pronounced for the distribution of contact pressure than for the surface expansion rate. Full article

(This article belongs to the Special Issue Advances in Welding Processes of Metallic Materials—2nd Edition)

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19 pages, 2448 KB

Open AccessArticle

Advancing Guidelines for the Design of Tooth-Supported Surgical Guides with Free-End Configurations: A Simulation Study of the Influence of Surgeon’s Hand Force

by Nikola Šimunić, Vladimir Tudić, Josip Hoster and Zvonimir Kralj

Appl. Sci. 2026, 16(7), 3287; https://doi.org/10.3390/app16073287 (registering DOI) - 28 Mar 2026

Abstract

Numerous studies have demonstrated that tooth-supported dental guides improve the accuracy of implant placement. However, current manufacturing procedures and available materials are not yet optimal and may still lead to deviations from the planned implant position. The influence of the surgeon’s manual force on the deformation of dental guides during implant placement has not yet been sufficiently investigated. Therefore, this study evaluates the mechanical behavior of dental guides using finite element analysis (FEA) in order to assess the influence of the surgeon’s hand force during clinical application. Finite element simulations of deformation and stress were performed for four types of tooth-supported dental guides, including cantilever dental guides with free ends and beam-type guides with a large span between the supporting teeth. The manual force applied by the surgeon was arbitrarily set to 30 N. Simulations were conducted for five commonly used biocompatible polymer materials: Stratasys MED610, VeroGlaze MED620, EOS PA2200, Formlabs FLSGAM01, and Stratasys ULTEM 1010. The numerical results quantified the deformation of dental guides caused by the applied manual force during surgical manipulation. For all analyzed guide designs, the deflection was primarily influenced by the arm length, i.e., the distance between the support and the point of force application. Based on the obtained results, design diagrams were developed to provide guidelines for the design of beam-type (A and A1) and cantilever-type (B and B1) tooth-supported dental guides. Full article

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

14 pages, 432 KB

Open AccessArticle

Minimal Blocking Sets Arising from Joining Some of the Smallest Singer Orbits

by Stefano Innamorati

Mathematics 2026, 14(7), 1137; https://doi.org/10.3390/math14071137 (registering DOI) - 28 Mar 2026

Abstract

A blocking set in a finite projective plane is defined as a set of points which meets every line. Since lines are the smallest blocking sets, a blocking set containing a line is called trivial. A blocking set is minimal when no proper subset of it is a blocking set. In the literature, there are plenty of constructions for minimal blocking sets by considering suitable Singer orbits of points. The most studied minimal blocking sets are those consisting of a single Singer orbit and not much seems to be known about the general case of those consisting of unions of several small orbits. The question arises whether a generalization would be possible when the size of Singer orbits is the smallest. In this paper, we propose a different method for constructing minimal blocking sets using the smallest Singer orbits, and we provide minimal blocking sets by joining some of them. Full article

(This article belongs to the Section B: Geometry and Topology)

38 pages, 2279 KB

Open AccessArticle

Universal Comparison Methodology for Hough Transform Approaches

by Danil Kazimirov, Vitalii Gulevskii, Alexey Kroshnin, Ekaterina Rybakova, Arseniy Terekhin, Elena Limonova and Dmitry Nikolaev

Mathematics 2026, 14(7), 1136; https://doi.org/10.3390/math14071136 (registering DOI) - 28 Mar 2026

Abstract

The Hough transform (HT) is widely used in computer vision, tomography, and neural networks. Numerous algorithms for HT computation have been proposed, making their systematic comparison essential. However, existing comparative methodologies are either non-universal and limited to certain HT formulations or task-oriented, relying on application-specific criteria that do not fully capture algorithmic properties. This paper introduces a novel unified methodology for the systematic comparison of HT algorithms. It evaluates key characteristics, including computational complexity, accuracy, and auxiliary space complexity, while explicitly accounting for the property of self-adjointness. The methodology integrates both implementation-level and theoretical considerations related to the interpretation of HT as a discrete approximation of the Radon transform. A set of mathematically justified evaluation functions, not previously described in the literature, is proposed to support our methodology. Importantly, the methodology is universal, applicable across diverse HT paradigms, encompasses pattern-based and Fourier-based fast HT (FHT) algorithms, and offers a comprehensive alternative to existing task-specific methodologies. Its application to several state-of-the-art FHT algorithms (

F H T 2 D T

F H T 2 S P

A S D 2

K H M

, and Fast Slant Stack) yields new experimentally confirmed theoretical insights, identifies

A S D 2

as the most balanced algorithm, and provides practical guidelines for algorithm selection. In particular, the methodology reveals that for image sizes up to 3000, the maximum normalized computational complexity increases as follows:

F H T 2 D T

(1.1),

A S D 2

(15.3), and

K H M

(30.6), while the remaining algorithms exhibit at least 1.1 times higher values. The maximum orthotropic approximation error equals 0.5 for

A S D 2

K H M

, and Fast Slant Stack; lies between 0.5 and 1.5 for

F H T 2 S P

; and reaches 2.1 for

F H T 2 D T

. In terms of worst-case normalized auxiliary space complexity, the lowest values are achieved by

F H T 2 D T

(2.0), Fast Slant Stack (4.0, lower bound), and

A S D 2

(6.8), with all other algorithms requiring at least 8.2 times more memory. Full article

(This article belongs to the Special Issue Applications of Mathematical Models in Image Processing and Algorithm Theory)

22 pages, 352 KB

Open AccessFeature PaperArticle

Nursing Practice Environments and Professional and Care-Related Outcomes in Portuguese Emergency Services: A Descriptive Study of 2018 and 2022

by Ângela Pragosa, Sofia Roque, Beatriz Araújo and Élvio Jesus

Nurs. Rep. 2026, 16(4), 111; https://doi.org/10.3390/nursrep16040111 (registering DOI) - 28 Mar 2026

Abstract

Background/Objectives: Emergency Services (ESs) are highly demanding clinical settings where Nursing Practice Environments (NPEs) play a critical role in shaping professional- and care-related outcomes. International evidence suggests that unfavorable NPEs are associated with reduced job satisfaction, compromised care quality, and increased safety risks. This study aimed to describe NPEs and selected professional and care-related outcomes among ESs nurses in Portugal in 2018 and 2022. Methods: A descriptive, cross-sectional study was conducted using data from two national surveys of ESs nurses collected in 2018 (n = 390) and 2022 (n = 434). Data were collected through an online questionnaire including the Practice Environment Scale of the Nursing Work Index (PES-NWI), measures of job satisfaction, intention to leave, perceived quality and safety of care, safety culture, incident occurrence, and missed nursing care. Descriptive statistics were used to summarize results across both samples. Results: NPEs were predominantly classified as unfavorable in both samples, with around 70% of nurses working in unfavorable environments. The most compromised dimensions were staffing and resource adequacy, nurses’ participation in hospital affairs, and nurse manager ability, leadership, and support of nurses. Job satisfaction was low in both samples, and a high proportion of nurses reported an intention to leave the organization. Differences were observed between samples in perceived quality and safety of care, incident occurrence, and missed nursing care, particularly in relational and autonomous interventions. Collegial nurse–physician relations emerged as the only favorable dimension in both samples. Conclusions: The findings indicate that NPEs in Portuguese ESs were predominantly unfavorable in both study periods, reflecting structural and organizational challenges. These findings may be associated with nurses’ professional outcomes and perceived care quality and safety, highlighting the importance of targeted organizational interventions to improve practice environments. Full article

(This article belongs to the Special Issue Nursing Leadership: Contemporary Challenges)

21 pages, 5258 KB

Open AccessArticle

Exploring the Potential of Multispectral Imaging for Automatic Clustering of Archeological Wall Painting Fragments

by Piercarlo Dondi, Lucia Cascone, Chiara Delledonne, Michela Albano, Elena Mariani, Marina Volonté, Marco Malagodi and Giacomo Fiocco

Sensors 2026, 26(7), 2111; https://doi.org/10.3390/s26072111 (registering DOI) - 28 Mar 2026

Abstract

The digital reconstruction of damaged archeological wall paintings is a challenging task due to severe material degradation, high fragmentation, and the lack of reference images. A crucial preliminary step is the separation and grouping of fragments originating from different wall paintings, which are often found mixed together at archeological sites. To address this issue, we explored the potential of multispectral imaging (MSI) for unsupervised fragment clustering, aiming to assess whether integrating multiple spectral bands can enhance fragment discrimination compared to using the visible band alone. As a test set, we examined five groups of wall painting fragments from a Roman domus (1st c. BC–1st c. AD) provided by the Archaeological Museum of Cremona (Italy). Images were acquired using the Hypercolorimetric Multispectral Imaging (HMI) system developed by Profilocolore^® Srl (Rome, Italy). Specifically, we considered visible reflectance (VIS), infrared reflectance (IR), infrared false color (IRFC), and Ultraviolet-induced Fluorescence (UVF) images. Through a systematic benchmarking study, we compared several state-of-the-art feature extraction and clustering methods across single- and multi-band configurations. Results show that combining MSI data can substantially enhance the system’s ability to correctly separate and group fragments, indicating a promising direction for future research. Full article

(This article belongs to the Special Issue Advances in Multispectral Sensing, Imaging Techniques and Computational Applications in Cultural Heritage)

29 pages, 3576 KB

Open AccessArticle

A Neighbor Feature Aggregation-Based Multi-Agent Reinforcement Learning Method for Fast Solution of Distributed Real-Time Power Dispatch Problem

by Baisen Chen, Chenghuang Li, Qingfen Liao, Wenyi Wang, Lingteng Ma and Xiaowei Wang

Electronics 2026, 15(7), 1415; https://doi.org/10.3390/electronics15071415 (registering DOI) - 28 Mar 2026

Abstract

To address the challenges posed by the strong uncertainty of high-proportion renewable energy sources (RES) to the secure and stable operation of distributed real-time power dispatch (D-RTPD) in new-type power systems, this paper proposes an integrated solution combining a neighborhood feature aggregation-based graph attention network (NFA-GAT) and multi-agent deep deterministic policy gradient (MADDPG). First, the D-RTPD problem is modeled as a decentralized partially observable Markov decision process (Dec-POMDP), which effectively captures the stochastic game characteristics of multi-regional agents and the partial observability of grid states. Second, the NFA-GAT is designed to enhance agents’ perception of grid operating states: by introducing a spatial discount factor, it realizes rational aggregation of multi-order neighborhood information while modeling the attenuation of electrical quantity influence with topological distance. Third, a prior-guided mechanism is integrated into the MADDPG framework to eliminate constraint-violating actions by setting their actor logits to negative infinity, improving training efficiency and strategy reliability. Simulation validations on the IEEE 118-bus test system (75.2% RES installed capacity ratio) show that the proposed method achieves efficient training convergence. Compared with the multi-layer perceptron (MLP) structure, it attains higher cumulative reward values and scenario win rates. When compared with traditional model-driven (ADMM) and data-driven (Q-MIX) methods, the proposed method balances solution efficiency, operational safety (98.7% maximum line load rate, zero power flow violation rate), and economic performance ($12,845 daily dispatch cost), providing a reliable technical support for D-RTPD under high-proportion RES integration. Full article

(This article belongs to the Special Issue AI-Enhanced Strategies for Power Grid Operation and Resilience: Integration of Emerging Resources and Technologies)

10 pages, 1309 KB

Open AccessArticle

The Effects of Speed with Dynamic Stretching on Musculotendinous Stiffness

by Naoto Kyotani, Kensuke Oba, Tomoya Ishida, Yuta Koshino, Miho Komatsuzaki, Minori Tanaka, Satoshi Kasahara, Harukazu Tohyama and Mina Samukawa

Appl. Sci. 2026, 16(7), 3278; https://doi.org/10.3390/app16073278 (registering DOI) - 28 Mar 2026

Abstract

Dynamic stretching (DS) comprises repetitive movements throughout the joint range of motion, and DS speed is known to affect athletic performance. However, it is unclear how DS speed affects musculotendinous stiffness (MTS). This study aimed to compare the DS effects at three different speeds on the maximum ankle dorsiflexion angle, maximum passive torque, and MTS. Based on sample size calculation (f = 0.25, α = 0.05, power = 0.80), 12 participants were needed, and 12 healthy university male athletes enrolled. DS to ankle plantar flexors was performed under the following conditions: low-speed (30 reps/min), moderate-speed (60 reps/min), high-speed (120 reps/min), and control (no DS). DS was performed for 15 reps × four sets with a 30 s rest. To assess musculotendinous extensibility, the maximum ankle dorsiflexion angle, maximum passive torque, and MTS were measured before and after DS. The maximum ankle dorsiflexion angle significantly increased after all DS (p = 0.001–0.006, d_z = 0.98–1.38) and was significantly larger in the high-speed DS than in the control condition (p = 0.039). MTS significantly increased after high-speed DS (p = 0.038, d = 0.68) but significantly decreased after moderate-speed DS (p = 0.025, d_z = −0.75) compared to baseline values. Maximal passive torque significantly increased after low-, moderate-, and high-speed DS (p < 0.001 to p = 0.011, d_z = 0.89–1.89) and was significantly higher after high-speed DS than after control (p = 0.004, d = 0.58). These results indicate that DS increases the ankle dorsiflexion angle regardless of speed and is effective in decreasing MTS at moderate speed. Full article

(This article belongs to the Special Issue Biomechanical Analysis for Sport Performance)

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22 pages, 8563 KB

Open AccessArticle

Computer Simulation-Guided Rational Design of Sulfadiazine-Imprinted Polymers for High-Efficiency Adsorption of Antibiotics in Complex Aquatic Matrices

by Mengfan Xu, Yanhong Wang, Mingfen Niu, Qiang Zhou and Wang Yang

Membranes 2026, 16(4), 118; https://doi.org/10.3390/membranes16040118 (registering DOI) - 28 Mar 2026

Abstract

To address the limited selectivity of conventional membrane materials toward sulfonamide antibiotics, this study employed a DFT calculation approach to optimize the design of a molecularly imprinted system for sulfadiazine (SDZ). A hierarchical set of template molecules—aniline (ANL), sulfanilamide (SNM), and SDZ—was introduced to systematically elucidate structure-dependent template–monomer matching mechanisms in sulfonamide imprinting systems. Through rational screening, trifluoroethyl methacrylate (TFEMAA) was identified as the optimal functional monomer, with an optimal imprinting molar ratio of 1:4 (SDZ to TFEMAA). Guided by the simulation results, SDZ molecularly imprinted polymers (MIPs) were synthesized via precipitation polymerization and systematically characterized for their morphology and recognition properties. The MIPs exhibited a well-defined spherical morphology with abundant imprinted cavities, achieving adsorption equilibrium within 1.5 h. The adsorption kinetics followed a pseudo-second-order model, indicating a chemisorption-dominated process. Scatchard analysis revealed the presence of both high- and low-affinity binding sites in the MIPs. Selectivity experiments, quantified by distribution coefficients (K_d) and selectivity coefficients (k), demonstrated a significantly higher adsorption capacity for SDZ than for structural analogs and non-analogs. In real water samples, the MIPs outperformed conventional HLB sorbents and showed strong anti-interference capability (RSD < 3%). This work provides a material foundation for developing highly selective SDZ-imprinted membranes and advances the application of molecular imprinting technology in membrane separation systems. Full article

(This article belongs to the Special Issue Advances in Reverse Osmosis Membrane Research Through Computer Simulation)

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