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Search Results (2,314)

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22 pages, 15270 KiB  
Article
Fake News Detection Based on Contrastive Learning and Cross-Modal Interaction
by Zhenxiang He, Hanbin Wang and Le Li
Symmetry 2025, 17(8), 1260; https://doi.org/10.3390/sym17081260 - 7 Aug 2025
Abstract
In recent years, the proliferation of fake news and misinformation has grown exponentially, far surpassing that of genuine news and posing a serious threat to social stability. Existing research in fake news detection primarily applies contrastive learning methods with a single-hot labeling strategy. [...] Read more.
In recent years, the proliferation of fake news and misinformation has grown exponentially, far surpassing that of genuine news and posing a serious threat to social stability. Existing research in fake news detection primarily applies contrastive learning methods with a single-hot labeling strategy. The issue does not lie with contrastive learning as a technique but with its current application in fake news detection systems. Specifically, these systems penalize all negative samples equally due to the use of single-hot labeling, thus overlooking the underlying semantic relationships among negative samples. As a result, contrastive learning models tend to learn from simple samples while neglecting highly deceptive samples located at the boundary between true and false, as well as the heterogeneity of text-image features, which complicates cross-modal fusion. To mitigate these known limitations in current applications, this paper proposes a fake news detection method based on contrastive learning and cross-modal interaction. First, a consistency-aware soft-label contrastive learning mechanism based on semantic similarity is designed to provide more granular supervision signals for contrastive learning. Secondly, a difficult negative sample mining strategy based on a similarity matrix is designed to optimize the symmetry alignment of image and text features, which effectively improves the model’s ability to discriminate boundary samples. To further optimize the feature fusion process, a cross-modal interaction module is designed to learn the symmetric interaction relationship between image and text features. Finally, an attention mechanism is designed to adaptively adjust the contributions of text-image features and interaction features, forming the final multimodal feature representation. Experiments are conducted on two major social media platform datasets, and compared with existing methods, the proposed method effectively improves the detection capability of fake news. Full article
(This article belongs to the Section Computer)
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16 pages, 6256 KiB  
Article
Influence of Alpha/Gamma-Stabilizing Elements on the Hot Deformation Behaviour of Ferritic Stainless Steel
by Andrés Núñez, Irene Collado, Marta Muratori, Andrés Ruiz, Juan F. Almagro and David L. Sales
J. Manuf. Mater. Process. 2025, 9(8), 265; https://doi.org/10.3390/jmmp9080265 - 6 Aug 2025
Abstract
This study investigates the hot deformation behaviour and microstructural evolution of two AISI 430 ferritic stainless steel variants: 0A (basic) and 1C (modified). These variants primarily differ in chemical composition, with 0A containing higher austenite-stabilizing elements (C, N) compared to 1C, which features [...] Read more.
This study investigates the hot deformation behaviour and microstructural evolution of two AISI 430 ferritic stainless steel variants: 0A (basic) and 1C (modified). These variants primarily differ in chemical composition, with 0A containing higher austenite-stabilizing elements (C, N) compared to 1C, which features lower interstitial content and slightly higher Si and Cr. This research aimed to optimize hot rolling conditions for enhanced forming properties. Uniaxial hot compression tests were conducted using a Gleeble thermo-mechanical system between 850 and 990 C at a strain rate of 3.3 s1, simulating industrial finishing mill conditions. Analysis of flow curves, coupled with detailed microstructural characterization using electron backscatter diffraction, revealed distinct dynamic restoration mechanisms influencing each material’s response. Thermodynamic simulations confirmed significant austenite formation in both materials within the tested temperature range, notably affecting their deformation behaviour despite their initial ferritic state. Material 0A consistently exhibited a strong tendency towards dynamic recrystallization (DRX) across a wider temperature range, particularly at 850 C. DRX led to a microstructure with a high concentration of low-angle grain boundaries and sharp deformation textures, actively reorienting grains towards energetically favourable configurations. However, under this condition, DRX did not fully complete the recrystallization process. In contrast, material 1C showed greater activity of both dynamic recovery and DRX, leading to a much more advanced state of grain refinement and recrystallization compared to 0A. This indicates that the composition of 1C helps mitigate the strong influence of the deformation temperature on the crystallographic texture, leading to a weaker texture overall than 0A. Full article
14 pages, 2180 KiB  
Article
Study on Preparation of Nano-CeO2 Modified Aluminized Coating by Low Temperature Pack Aluminizing on γ-TiAl Intermetallic Compound
by Jiahui Song, Yunmei Long, Yifan He, Yichen Li, Dianqi Huang, Yan Gu, Xingyao Wang, Jinlong Wang and Minghui Chen
Coatings 2025, 15(8), 914; https://doi.org/10.3390/coatings15080914 (registering DOI) - 5 Aug 2025
Viewed by 40
Abstract
TiAl alloy offers advantages including low density, high specific strength and stiffness, and excellent high-temperature creep resistance. It is widely used in the aerospace, automotive, and chemical sectors, as well as in other fields. However, at temperatures of 800 °C and above, it [...] Read more.
TiAl alloy offers advantages including low density, high specific strength and stiffness, and excellent high-temperature creep resistance. It is widely used in the aerospace, automotive, and chemical sectors, as well as in other fields. However, at temperatures of 800 °C and above, it forms a porous oxide film predominantly composed of TiO2, which fails to provide adequate protection. Applying high-temperature protective coatings is therefore essential. Oxides demonstrating protective efficacy at elevated temperatures include Al2O3, Cr2O3, and SiO2. The Pilling–Bedworth Ratio (PBR)—defined as the ratio of the volume of the oxide formed to the volume of the metal consumed—serves as a critical criterion for assessing oxide film integrity. A PBR value greater than 1 but less than 2 indicates superior film integrity and enhanced oxidation resistance. Among common oxides, Al2O3 exhibits a PBR value within this optimal range (1−2), rendering aluminum-based compound coatings the most extensively utilized. Aluminum coatings can be applied via methods such as pack cementation, thermal spraying, and hot-dip aluminizing. Pack cementation, being the simplest to operate, is widely employed. In this study, a powder mixture with the composition Al:Al2O3:NH4Cl:CeO2 = 30:66:3:1 was used to aluminize γ-TiAl intermetallic compound specimens via pack cementation at 600 °C for 5 h. Subsequent isothermal oxidation at 900 °C for 20 h yielded an oxidation kinetic curve adhering to the parabolic rate law. This treatment significantly enhanced the high-temperature oxidation resistance of the γ-TiAl intermetallic compound, thereby broadening its potential application scenarios. Full article
(This article belongs to the Special Issue High-Temperature Protective Coatings)
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28 pages, 3272 KiB  
Review
Research Advancements in High-Temperature Constitutive Models of Metallic Materials
by Fengjuan Ding, Tengjiao Hong, Fulong Dong and Dong Huang
Crystals 2025, 15(8), 699; https://doi.org/10.3390/cryst15080699 - 31 Jul 2025
Viewed by 1046
Abstract
The constitutive model is widely employed to characterize the rheological properties of metallic materials under high-temperature conditions. It is typically derived from a series of high-temperature tests conducted at varying deformation temperatures, strain rates, and strains, including hot stretching, hot compression, separated Hopkinson [...] Read more.
The constitutive model is widely employed to characterize the rheological properties of metallic materials under high-temperature conditions. It is typically derived from a series of high-temperature tests conducted at varying deformation temperatures, strain rates, and strains, including hot stretching, hot compression, separated Hopkinson pressure bar testing, and hot torsion. The original experimental data used for establishing the constitutive model serves as the foundation for developing phenomenological models such as Arrhenius and Johnson–Cook models, as well as physical-based models like Zerilli–Armstrong or machine learning-based constitutive models. The resulting constitutive equations are integrated into finite element analysis software such as Abaqus, Ansys, and Deform to create custom programs that predict the distributions of stress, strain rate, and temperature in materials during processes such as cutting, stamping, forging, and others. By adhering to these methodologies, we can optimize parameters related to metal processing technology; this helps to prevent forming defects while minimizing the waste of consumables and reducing costs. This study provides a comprehensive overview of commonly utilized experimental equipment and methods for developing constitutive models. It discusses various types of constitutive models along with their modifications and applications. Additionally, it reviews recent research advancements in this field while anticipating future trends concerning the development of constitutive models for high-temperature deformation processes involving metallic materials. Full article
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17 pages, 666 KiB  
Review
Three Major Deficiency Diseases Harming Mankind (Protein, Retinoid, Iron) Operate Under Tryptophan Dependency
by Yves Ingenbleek
Nutrients 2025, 17(15), 2505; https://doi.org/10.3390/nu17152505 - 30 Jul 2025
Viewed by 213
Abstract
This story began half a century ago with the discovery of an unusually high presence of tryptophan (Trp, W) in transthyretin (TTR), one of the three carrier proteins of thyroid hormones. With the Trp-rich retinol-binding protein (RBP), TTR forms a plasma complex implicated [...] Read more.
This story began half a century ago with the discovery of an unusually high presence of tryptophan (Trp, W) in transthyretin (TTR), one of the three carrier proteins of thyroid hormones. With the Trp-rich retinol-binding protein (RBP), TTR forms a plasma complex implicated in the delivery of retinoid compounds to body tissues. W has the lowest concentration among all AAs involved in the sequencing of human body proteins. The present review proposes molecular maps focusing on the ratio of W/AA residues found in the sequence of proteins involved in immune events, allowing us to ascribe the guidance of inflammatory processes as fully under the influence of W. Under the control of cytokine stimulation, plasma biomarkers of protein nutritional status work in concert with major acute-phase reactants (APRs) and with carrier proteins to release, in a free and active form, their W and hormonal ligands, interacting to generate hot spots affecting the course of acute stress disorders. The prognostic inflammatory and nutritional index (PINI) scoring formula contributes to identifying the respective roles played by each of the components prevailing during the progression of the disease. Glucagon demonstrates ambivalent properties, remaining passive under steady-state conditions while displaying stronger effects after cytokine activation. In developing countries, inappropriate weaning periods lead to toddlers eating W-deficient cereals as a staple, causing a dramatic reduction in the levels of W-rich biomarkers in plasma, constituting a novel nutritional deficiency at the global scale. Appropriate counseling should be set up using W implementations to cover the weaning period and extended until school age. In adult and elderly subjects, the helpful immune protections provided by W may be hindered by the surge in harmful catabolites with the occurrence of chronic complications, which can have a significant public health impact but lack the uncontrolled surges in PINI observed in young infants and teenagers. Biomarkers of neurodegenerative and neoplastic disorders measured in elderly patients indicate the slow-moving elevation of APRs due to rampant degradation processes. Full article
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19 pages, 4287 KiB  
Article
Tailoring Microstructure via Rolling to Achieve Concurrent High Strength and Thermal Conductivity in Mg-Zn-Nd-Zr Alloys
by Hailong Shi, Xiaohuan Zhang, Xin Li, Yining Zhang, Siqi Li, You Wang, Xiaojun Wang, Xiaoshi Hu, Xuejian Li, Chao Xu, Weimin Gan and Chao Ding
Materials 2025, 18(15), 3578; https://doi.org/10.3390/ma18153578 - 30 Jul 2025
Viewed by 170
Abstract
This study examined the comprehensive properties of Mg-Zn-Nd-Zr alloys in order to achieve both high strength and thermal conductivity simultaneously. The impact of rolling on the microstructure, mechanical properties, and thermal conductivity was analyzed for Mg-5Zn-xNd-0.4Zr alloys (x = 1, 2). The results [...] Read more.
This study examined the comprehensive properties of Mg-Zn-Nd-Zr alloys in order to achieve both high strength and thermal conductivity simultaneously. The impact of rolling on the microstructure, mechanical properties, and thermal conductivity was analyzed for Mg-5Zn-xNd-0.4Zr alloys (x = 1, 2). The results indicate that the addition of Nd promotes the formation of the W phase (Mg3Zn3RE2), which contributes to grain boundary strengthening and enhances the overall strength. Moreover, dynamic precipitation during the rolling process leads to the formation of nanoscale MgZn2 and Zn2Zr phases, significantly improving both the strength and thermal conductivity. After rolling, both the Mg-5Zn-1Nd-0.4Zr (ZNK510) and Mg-5Zn-2Nd-0.4Zr (ZNK520) alloys exhibited a notable enhancement in thermal conductivity, with ZNK520 demonstrating superior properties due to its higher Nd content. This study highlights that optimizing alloy composition and phase evolution through rolling can markedly enhance both the mechanical and thermal properties, offering a promising strategy for the development of high-performance magnesium alloys. Full article
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14 pages, 7356 KiB  
Article
Study on Incremental Sheet Forming Performance of AA2024 Aluminum Alloy Based on Adaptive Fuzzy PID Temperature Control
by Zhengfang Li, Zhengyuan Gao, Kaiguo Qian, Lijia Liu, Jiangpeng Song, Shuang Wu, Li Liu and Xinhao Zhai
Metals 2025, 15(8), 852; https://doi.org/10.3390/met15080852 - 30 Jul 2025
Viewed by 288
Abstract
The development of technology has driven a rising need for high-accuracy and high-efficiency manufacturing of low-volume products. Incremental forming technology, characterized by die-free flexibility and low production costs, can effectively replace stamping processes for manufacturing customized small-batch products. However, high-performance aluminum alloys generally [...] Read more.
The development of technology has driven a rising need for high-accuracy and high-efficiency manufacturing of low-volume products. Incremental forming technology, characterized by die-free flexibility and low production costs, can effectively replace stamping processes for manufacturing customized small-batch products. However, high-performance aluminum alloys generally exhibit poor room-temperature plasticity but excellent high-temperature plasticity, necessitating the integration of thermal-assisted methods for manufacturing such products. However, the temperature of the forming region will excessively rise without temperature control, which will affect the forming performance of the material in hot incremental sheet forming of AA2024-T4 aluminum alloy. This study focuses on AA2024-T4 aluminum alloy and proposes a uniform temperature control method for the electric hot tube-assisted incremental sheet forming process, incorporating an adaptive fuzzy PID algorithm. The temperature difference of the forming region is lower than 6% under the various temperatures. On this basis, the forming limit angle and the microstructure state of the material are analyzed, and the grain feature of the material exhibits significantly refined grains and the uniform fine grain distribution under 180 °C with the temperature control of the adaptive fuzzy PID algorithm. Full article
(This article belongs to the Special Issue Advances in the Forming and Processing of Metallic Materials)
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19 pages, 2633 KiB  
Article
Influence of Mullite and Halloysite Reinforcement on the Ablation Properties of an Epoxy Composite
by Robert Szczepaniak, Michał Piątkiewicz, Dominik Gryc, Paweł Przybyłek, Grzegorz Woroniak and Joanna Piotrowska-Woroniak
Materials 2025, 18(15), 3530; https://doi.org/10.3390/ma18153530 - 28 Jul 2025
Viewed by 280
Abstract
This paper explores the impact of applying a powder additive in the form of halloysite and mullite on the thermal protection properties of a composite. The authors used CES R70 epoxy resin with CES H72 hardener, modified by varying the amount of powder [...] Read more.
This paper explores the impact of applying a powder additive in the form of halloysite and mullite on the thermal protection properties of a composite. The authors used CES R70 epoxy resin with CES H72 hardener, modified by varying the amount of powder additive. The composite samples were exposed to a mixture of combustible gases at a temperature of approximately 1000 °C. The primary parameters analyzed during this study were the temperature on the rear surface of the sample and the ablative mass loss of the tested material. The temperature increase on the rear surface of the sample, which was exposed to the hot stream of flammable gases, was measured for 120 s. Another key parameter considered in the data analysis was the ablative mass loss. The charred layer of the sample played a crucial role in this process, as it helped block oxygen diffusion from the boundary layer of the original material. This charred layer absorbed thermal energy until it reached a temperature at which it either oxidized or was mechanically removed due to the erosive effects of the heating factor. The incorporation of mullite reduced the rear surface temperature from 58.9 °C to 49.2 °C, and for halloysite, it was reduced the rear surface temperature to 49.8 °C. The ablative weight loss dropped from 57% to 18.9% for mullite and to 39.9% for halloysite. The speed of mass ablation was reduced from 77.9 mg/s to 25.2 mg/s (mullite) and 52.4 mg/s (halloysite), while the layer thickness loss decreased from 7.4 mm to 2.8 mm (mullite) and 4.4 mm (halloysite). This research is innovative in its use of halloysite and mullite as functional additives to enhance the ablative resistance of polymer composites under extreme thermal conditions. This novel approach not only contributes to a deeper understanding of composite behavior at high temperatures but also opens up new avenues for the development of advanced thermal protection systems. Potential applications of these materials include aerospace structures, fire-resistant components, and protective coatings in environments exposed to intense heat and flame. Full article
(This article belongs to the Section Advanced Composites)
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12 pages, 941 KiB  
Article
Data Center Temperature Control Method Based on Multi-Parameter Model-Free Adaptive Control Strategy
by Di Jiang, Shangxuan Zhang and Kaiyan Pan
Processes 2025, 13(8), 2360; https://doi.org/10.3390/pr13082360 - 24 Jul 2025
Viewed by 274
Abstract
With the continuous expansion of data center scales worldwide, the problem of energy consumption has become increasingly prominent. To address the multi-parameter control challenge in environmental temperature regulation for large data center computer rooms, achieve precise control of hot-aisle temperatures in data centers, [...] Read more.
With the continuous expansion of data center scales worldwide, the problem of energy consumption has become increasingly prominent. To address the multi-parameter control challenge in environmental temperature regulation for large data center computer rooms, achieve precise control of hot-aisle temperatures in data centers, and reduce energy waste, this paper designs a multi-parameter model-free adaptive control (MMFAC) algorithm suitable for computer room environmental temperatures. The algorithm integrates the model-free adaptive control (MFAC) algorithm with a weight matrix to perform scaling transformations. Considering the large parameter space of the MFAC controller and the dynamic complexity of data center temperature control systems, compact-form dynamic linearization (CFDL) technology and optimization mathematical methods are used to simplify the parameter identification of the pseudo-Jacobian matrices and the calculation of control quantities for the regulation devices. Simulation experiments based on measured data from a data center show that the proposed algorithm can calculate control quantities for equipment such as air conditioners according to real-time environmental parameter measurements and drive each device based on these control quantities. Meanwhile, the algorithm can reduce errors in key parameters by adjusting the weight matrix. Comparative tests with other control algorithms show that the algorithm has faster response in temperature control and smaller control errors, verifying the effectiveness and application prospects of the algorithm in data center temperature control. Full article
(This article belongs to the Section Process Control and Monitoring)
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21 pages, 1905 KiB  
Article
Wax-Based Sustained-Release Felodipine Oral Dosage Forms Manufactured Using Hot-Melt Extrusion and Their Resistance to Alcohol-Induced Dose Dumping
by Gerard Sweeney, Dijia Liu, Taher Hatahet, David S. Jones, Shu Li and Gavin P. Andrews
Pharmaceutics 2025, 17(8), 955; https://doi.org/10.3390/pharmaceutics17080955 - 24 Jul 2025
Viewed by 397
Abstract
Background/Objectives: Hot-melt extrusion (HME) has gained prominence for the manufacture of sustained-release oral dosage forms, yet the application of wax-based matrices and their resilience to alcohol-induced dose dumping (AIDD) remains underexplored. This study aimed to develop and characterise wax-based sustained-release felodipine formulations, with [...] Read more.
Background/Objectives: Hot-melt extrusion (HME) has gained prominence for the manufacture of sustained-release oral dosage forms, yet the application of wax-based matrices and their resilience to alcohol-induced dose dumping (AIDD) remains underexplored. This study aimed to develop and characterise wax-based sustained-release felodipine formulations, with a particular focus on excipient functionality and robustness against AIDD. Methods: Felodipine sustained-release formulations were prepared via HME using Syncrowax HGLC as a thermally processable wax matrix. Microcrystalline cellulose (MCC) and lactose monohydrate were incorporated as functional fillers and processing aids. The influence of wax content and filler type on mechanical properties, wettability, and drug release behaviour was systematically evaluated. Ethanol susceptibility testing was conducted under simulated co-ingestion conditions (4%, 20%, and 40% v/v ethanol) to assess AIDD risk. Results: MCC-containing tablets demonstrated superior sustained-release characteristics over 24 h, showing better wettability and disintegration. In contrast, tablets formulated with lactose monohydrate remained structurally intact during dissolution, overly restricting drug release. This limitation was effectively addressed through granulation, where reduced particle size significantly improved surface accessibility, with 0.5–1 mm granules achieving a satisfactory release profile. Ethanol susceptibility testing revealed divergent behaviours between the two filler systems. Unexpectedly, MCC-containing tablets showed suppressed drug release in ethanolic media, likely resulting from inhibitory effect of ethanol on filler swelling and disintegration. Conversely, formulations containing lactose monohydrate retained their release performance in up to 20% v/v ethanol, with only high concentrations (40% v/v) compromising matrix drug-retaining functionality and leading to remarkably increased drug release. Conclusions: This study highlights the pivotal role of excipient type and constitutional ratios in engineering wax-based sustained-release formulations. It further contributes to the understanding of AIDD risk through in vitro assessment and offers a rational design strategy for robust, alcohol-resistant oral delivery systems for felodipine. Full article
(This article belongs to the Special Issue Advances in Hot Melt Extrusion Technology)
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24 pages, 1572 KiB  
Article
Optimizing DNA Sequence Classification via a Deep Learning Hybrid of LSTM and CNN Architecture
by Elias Tabane, Ernest Mnkandla and Zenghui Wang
Appl. Sci. 2025, 15(15), 8225; https://doi.org/10.3390/app15158225 - 24 Jul 2025
Viewed by 270
Abstract
This study addresses the performance of deep learning models for predicting human DNA sequence classification through an exploration of ideal feature representation, model architecture, and hyperparameter tuning. It contrasts traditional machine learning with advanced deep learning approaches to ascertain performance with respect to [...] Read more.
This study addresses the performance of deep learning models for predicting human DNA sequence classification through an exploration of ideal feature representation, model architecture, and hyperparameter tuning. It contrasts traditional machine learning with advanced deep learning approaches to ascertain performance with respect to genomic data complexity. A hybrid network combining long short-term memory (LSTM) and convolutional neural networks (CNN) was developed to extract long-distance dependencies as well as local patterns from DNA sequences. The hybrid LSTM + CNN model achieved a classification accuracy of 100%, which is significantly higher than traditional approaches such as logistic regression (45.31%), naïve Bayes (17.80%), and random forest (69.89%), as well as other machine learning models such as XGBoost (81.50%) and k-nearest neighbor (70.77%). Among deep learning techniques, the DeepSea model also accounted for good performance (76.59%), while others like DeepVariant (67.00%) and graph neural networks (30.71%) were relatively lower. Preprocessing techniques, one-hot encoding, and DNA embeddings were mainly at the forefront of transforming sequence data to a compatible form for deep learning. The findings underscore the robustness of hybrid structures in genomic classification tasks and warrant future research on encoding strategy, model and parameter tuning, and hyperparameter tuning to further improve accuracy and generalization in DNA sequence analysis. Full article
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22 pages, 3727 KiB  
Article
Johnson–Cook Constitutive Model Parameters Estimation of 22MnB5 Hot Stamping Steel for Automotive Application Produced via the TSCR Process
by Yuxin Song, Yaowen Xu and Gengwei Yang
Metals 2025, 15(7), 811; https://doi.org/10.3390/met15070811 - 20 Jul 2025
Viewed by 2828
Abstract
In the industrial practice of metal forming, the consistent and reasonable characterization of the material behavior under the coupling effect of strain, strain rate, and temperature on the material flow stress is very important for the design and optimization of process parameters. The [...] Read more.
In the industrial practice of metal forming, the consistent and reasonable characterization of the material behavior under the coupling effect of strain, strain rate, and temperature on the material flow stress is very important for the design and optimization of process parameters. The purpose of this work was to establish an appropriate constitutive model to characterize the rheological behavior of a hot-formed steel plate (22MnB5 steel) produced through the TSCR (Thin Slab Casting and Rolling) process under practical deformation temperatures (150–250 °C) and strain rates (0.001–3000 s−1). Subsequently, the material flow behavior was modeled and predicted using the Johnson–Cook flow stress constitutive model. In this study, uniaxial tensile tests were conducted on 22MnB5 steel at room temperature under varying strain rates, along with elevated-temperature tensile tests at different strain rates, to obtain the engineering stress–strain curves and analyze the mechanical properties under various conditions. The results show that during room-temperature tensile testing within the strain rate range of 10−3 to 300 s−1, the 22MnB5 steel exhibited overall yield strength and tensile strength of approximately 1500 MPa, and uniform elongation and fracture elongation of about 7% and 12%, respectively. When the strain rate reached 1000–3000 s−1, the yield strength and tensile strength were approximately 2000 MPa, while the uniform elongation and fracture elongation were about 6% and 10%, respectively. Based on the experimental results, a modified Johnson–Cook constitutive model was developed and calibrated. Compared with the original model, the modified Johnson–Cook model exhibited a higher coefficient of determination (R2), indicating improved fitting accuracy. In addition, to predict the material’s damage behavior, three distinct specimen geometries were designed for quasi-static strain rate uniaxial tensile testing at ambient temperature. The Johnson–Cook failure criterion was implemented, with its constitutive parameters calibrated through integrated finite element analysis to establish the damage model. The determined damage parameters from this investigation can be effectively implemented in metal forming simulations, providing valuable predictive capabilities regarding workpiece material performance. Full article
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20 pages, 1677 KiB  
Review
Froth Flotation of Lepidolite—A Review
by Xusheng Yang, Bo Feng and Longxia Jiang
Minerals 2025, 15(7), 750; https://doi.org/10.3390/min15070750 - 17 Jul 2025
Viewed by 234
Abstract
As one of the important lithium resource sources, lepidolite has become a new energy strategic resource research hot spot. The efficient flotation of lepidolite directly affects the recovery and economic value of lithium resources. This paper systematically reviews the flotation research progress of [...] Read more.
As one of the important lithium resource sources, lepidolite has become a new energy strategic resource research hot spot. The efficient flotation of lepidolite directly affects the recovery and economic value of lithium resources. This paper systematically reviews the flotation research progress of lepidolite, focusing on the influence of the type of capture agent and process parameters (pH, activator, and depressant) on flotation. In view of the separation problems caused by the similarity of the surface properties of lepidolite and its associated gangue minerals (albite, feldspar, and quartz), the strategies for regulating the crystal structure of the minerals and their surface properties are analyzed. In addition, the lepidolite flotation process and its challenges are summarized, including poor selectivity of chemicals, fine mineral embedded size, easy to form sludge, and insufficient environmental friendliness, etc. The future development direction of lepidolite flotation technology is also prospected, which provides theoretical support and reference for the efficient recovery of lepidolite. Full article
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
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33 pages, 4942 KiB  
Review
A Review of Crack Sealing Technologies for Asphalt Pavement: Materials, Failure Mechanisms, and Detection Methods
by Weihao Min, Peng Lu, Song Liu and Hongchang Wang
Coatings 2025, 15(7), 836; https://doi.org/10.3390/coatings15070836 - 17 Jul 2025
Viewed by 480
Abstract
Asphalt pavement cracking represents a prevalent form of deterioration that significantly compromises road performance and safety under the combined effects of environmental factors and traffic loading. Crack sealing has emerged as a widely adopted and cost-effective preventive maintenance strategy that restores the pavement’s [...] Read more.
Asphalt pavement cracking represents a prevalent form of deterioration that significantly compromises road performance and safety under the combined effects of environmental factors and traffic loading. Crack sealing has emerged as a widely adopted and cost-effective preventive maintenance strategy that restores the pavement’s structural integrity and extends service life. This paper presents a systematic review of the development of crack sealing technology, conducts a comparative analysis of conventional sealing materials (including emulsified asphalt, hot-applied asphalt, polymer-modified asphalt, and rubber-modified asphalt), and examines the existing performance evaluation methodologies. Critical failure mechanisms are thoroughly investigated, including interfacial bond failure resulting from construction defects, material aging and degradation, hydrodynamic scouring effects, and thermal cycling impacts. Additionally, this review examines advanced sensing methodologies for detecting premature sealant failure, encompassing both non-destructive testing techniques and active sensing technologies utilizing intelligent crack sealing materials with embedded monitoring capabilities. Based on current research gaps, this paper identifies future research directions to guide the development of intelligent and sustainable asphalt pavement crack repair technologies. The proposed research framework provides valuable insights for researchers and practitioners seeking to improve the long-term effectiveness of pavement maintenance strategies. Full article
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20 pages, 6029 KiB  
Article
Insights into Binding Mechanisms of Potential Inhibitors Targeting PCSK9 Protein via Molecular Dynamics Simulation and Free Energy Calculation
by Xingyu Wu, Xi Zhu, Min Fang, Fenghua Qi, Zhixiang Yin, John Z.H. Zhang, Shihua Luo, Tong Zhu and Ya Gao
Molecules 2025, 30(14), 2962; https://doi.org/10.3390/molecules30142962 - 14 Jul 2025
Viewed by 315
Abstract
The design of small-molecule inhibitors targeting proprotein convertase subtilisin/Kein type 9 (PCSK9) remains a forefront challenge in combating atherosclerosis. While various monoclonal antibodies have achieved clinical success, small-molecule inhibitors are hindered by the unique structural features of the PCSK9 binding interface. In this [...] Read more.
The design of small-molecule inhibitors targeting proprotein convertase subtilisin/Kein type 9 (PCSK9) remains a forefront challenge in combating atherosclerosis. While various monoclonal antibodies have achieved clinical success, small-molecule inhibitors are hindered by the unique structural features of the PCSK9 binding interface. In this study, a potential small-molecule inhibitor was identified through virtual screening, followed by molecular dynamics (MD) simulations to explore the binding mechanisms between the inhibitor and the PCSK9 protein. Binding free energies were calculated using molecular mechanics/Generalized Born surface area (MM/GBSA) with the interaction entropy (IE) method, and critical hot-spot residues were identified via alanine scanning analysis. Key residues, including ARG237, ILE369, ARG194 and PHE379, were revealed to form critical interactions with inhibitor and play dominant roles during the inhibitor’s binding. In addition, the polarization effect was shown to significantly influence PCSK9–ligand binding. The identified inhibitor exhibited highly similar binding patterns with two known active compounds, providing valuable insights for the rational design and optimization of small-molecule inhibitors targeting PCSK9. This work contributes to the development of more effective treatments for hyperlipidemia and associated cardiovascular diseases. Full article
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