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Differential beamforming has attracted much research since it can utilize an array with a small aperture size to form frequency-invariant beampatterns and achieve high directional gains. It has recently been applied to the loudspeaker line array to produce a broadside frequency-invariant radiation pattern. However, designing steerable frequency-invariant beampatterns for the loudspeaker line array has yet to be explored. This paper proposes a method to design a steerable differential beamformer with a loudspeaker line array. We first determine the target differential beampatterns according to the desired direction, the main lobe width, and the beampattern order. Then, we transform the target beampattern into the modal domain for representation. The Jacobi-Anger expansion is subsequently used to design the beamformer so that the resulting beampattern matches the target differential beampattern. Furthermore, based on the criterion of minimizing the mean square error between the synthesized beampattern and the ideal one, a multi-constraint optimization problem, which compromises between the robustness and the mean square error, is formulated to calculate the optimal desired weighting vector. Simulations and experimental results show that the proposed method can achieve steerable frequency-invariant beamforming from 300 Hz–4 kHz. Full article

(This article belongs to the Special Issue Signal Detection and Processing of Sensor Arrays)

14 pages, 2857 KiB

Open AccessArticle

Synthesis and Characterization of 3,4-Bis[3(2-azidoethoxy)furazan-4-yl]furoxan (DAeTF): A Novel Low-Melting Insensitive Energetic Material

by Yang Wu, Yuezhou Liu, Fulei Gao, Bin Chen, Tingting Lu and Yinglei Wang

Molecules 2024, 29(19), 4607; https://doi.org/10.3390/molecules29194607 (registering DOI) - 27 Sep 2024

Abstract

The synthesis and characterization of low-melting-point insensitive energetic materials are crucial due to their increasing applications in melt–cast explosives. In this work, a furazan-derived energetic compound, 3,4-bis[3(2-azidoethoxy)furazan-4-yl]furoxan (DAeTF), exhibiting insensitive and high-energy characteristics, is rationally designed and synthesized. The structure of DAeTF is characterized by nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, elemental analysis, mass spectrometry, and single-crystal X-ray diffraction. The thermal properties of DAeTF are investigated using differential scanning calorimetry, in situ FTIR spectroscopy and thermogravimetric-differential scanning calorimetry–Fourier transform infrared–mass spectrometry and thermal decomposition mechanism was elucidated in combination with bond energy calculations. The detonation performance of DAeTF is predicted by the EXPLO5 program. The results indicate that DAeTF has thermal stability (T_d = 251.7 °C), high energy level (D = 7270 m/s) and significant insensitivity (IS = 60 J). Additionally, its relatively low melting point (T_m = 60.5 °C) facilitates processing and loading. These characteristics indicate that DAeTF is a promising candidate as an insensitive melt–cast explosive in future applications. Full article

21 pages, 1794 KiB

Open AccessArticle

Al(SO₄)(OH)·5H₂O Stemming from Complexation of Aluminum Sulfate with Water-Soluble Ternary Copolymer and further Stabilized by Silica Gel as Effective Admixtures for Enhanced Mortar Cementing

by Zhiyuan Song, Zainab Bibi, Sidra Chaudhary, Qinxiang Jia, Xiaoyong Li and Yang Sun

Materials 2024, 17(19), 4762; https://doi.org/10.3390/ma17194762 - 27 Sep 2024

Abstract

A water-soluble ternary copolymer bearing carboxyl, sulfonic, and amide functional groups was synthesized using ammonium persulfate-catalyzed free radical polymerization in water, resulting in high monomer conversion. This copolymer was then complexed with aluminum sulfate, forming an admixture containing Al(SO₄)(OH)·5H₂O, which was subsequently combined with silica gel. Characterization revealed that the synthesized copolymer formed a large, thin membrane that covered both the aluminum compounds and the silica gel blocks. The introduction of this complex admixture, combining the copolymer and aluminum sulfate, not only reduced the setting times of the cement paste but also enhanced the mechanical strengths of the mortar compared to using aluminum sulfate alone. The complex admixture led to the formation of katoite, metajennite, and C₃A (tricalcium aluminate) in the mortar, demonstrating significant linking effects, whereas pure aluminum sulfate could not completely transform C₃S within 24 h. Further addition of silica gel to the complex admixture further shortened the setting times of the paste, slightly reduced compressive strength, but improved flexural strength compared to the initial complex admixture. The silicon components appeared to fill the micropores and mesopores of the mortar, accelerating cement setting and enhancing flexural strength, while slightly decreasing compressive strength. This study contributed to the development of new cementing accelerators with improved hardening properties. Full article

17 pages, 3553 KiB

Open AccessArticle

Fault Diagnosis Method for Vacuum Contactor Based on Time-Frequency Graph Optimization Technique and ShuffleNetV2

by Haiying Li, Qinyang Wang and Jiancheng Song

Sensors 2024, 24(19), 6274; https://doi.org/10.3390/s24196274 - 27 Sep 2024

Abstract

This paper presents a fault diagnosis method for a vacuum contactor using the generalized Stockwell transform (GST) of vibration signals. The objective is to solve the problem of low diagnostic performance efficiency caused by the inadequate feature extraction capability and the redundant pixels in the graph background. The proposed method is based on the time-frequency graph optimization technique and ShuffleNetV2 network. Firstly, vibration signals in different states are collected and converted into GST time-frequency graphs. Secondly, multi-resolution GST time-frequency graphs are generated to cover signal characteristics in all frequency bands by adjusting the GST Gaussian window width factor λ. The OTSU algorithm is then combined to crop the energy concentration area, and the size of these time-frequency graphs is optimized by 68.86%. Finally, considering the advantages of the channel split and channel shuffle methods, the ShuffleNetV2 network is adopted to improve the feature learning ability and identify fault categories. In this paper, the CKJ5-400/1140 vacuum contactor is taken as the test object. The fault recognition accuracy reaches 99.74%, and the single iteration time of model training is reduced by 19.42%. Full article

(This article belongs to the Special Issue Reliability Verification and Diagnosis Methods for Mechanical Equipment)

15 pages, 803 KiB

Open AccessArticle

Exploration of Deep-Learning-Based Approaches for False Fact Identification in Social Judicial Systems

by Yuzhuo Zou, Jiepin Chen, Jiebin Cai, Mengen Zhou and Yinghui Pan

Electronics 2024, 13(19), 3831; https://doi.org/10.3390/electronics13193831 - 27 Sep 2024

Abstract

With the many applications of artificial intelligence (AI) in social judicial systems, false fact identification becomes a challenging issue when the system is expected to be more autonomous and intelligent in assisting a judicial review. In particular, private lending disputes often involve false facts that are intentionally concealed and manipulated due to unique and dynamic relationships and their nonconfrontational nature in the judicial system. In this article, we investigate deep learning techniques to identify false facts in loan cases for the purpose of reducing the judicial workload. Specifically, we adapt deep-learning-based natural language processing techniques to a dataset over 100 real-world judicial rules spanning four courts of different levels in China. The BERT (bidirectional encoder representations from transformers)-based classifier and T5 text generation models were trained to classify false litigation claims semantically. The experimental results demonstrate that T5 has a robust learning capability with a small number of legal text samples, outperforms BERT in identifying falsified facts, and provides explainable decisions to judges. This research shows that deep-learning-based false fact identification approaches provide promising solutions for addressing concealed information and manipulation in private lending lawsuits. This highlights the feasibility of deep learning to strengthen fact-finding and reduce labor costs in the judicial field. Full article

(This article belongs to the Special Issue Data-Driven Intelligence in Autonomous Systems)

17 pages, 1759 KiB

Open AccessArticle

Microgravity as a Tool to Investigate Cancer Induction in Pleura Mesothelial Cells

by Valentina Bonetto, Corinna Anais Pagano, Maurizio Sabbatini, Valeria Magnelli, Massimo Donadelli, Emilio Marengo and Maria Angela Masini

Curr. Issues Mol. Biol. 2024, 46(10), 10896-10912; https://doi.org/10.3390/cimb46100647 - 27 Sep 2024

Abstract

The present work shows that the exposure of mesothelial cells to simulated microgravity changes their cytoskeleton and adhesion proteins, leading to a cell switch from normal towards tumoral cells. Immunohistochemical and molecular data were obtained from both MeT-5A exposed to simulated microgravity and BR95 mesothelioma cell lines. Simulated microgravity was found to affect the expression of actin, vinculin, and connexin-43, altering their quantitative and spatial distribution pattern inside the cell. The analysis of the tumoral markers p27, CD44, Fibulin-3, and NANOG and the expression of genes related to cancer transformation such as NANOG, CDH-1, and Zeb-1 showed that the simulated microgravity environment led to expression patterns in MeT-5A cells similar to those observed in BR95 cells. The alteration in both quantitative expression and structural organization of the cytoskeleton and adhesion/communication proteins can thus be considered a pivotal mechanism involved in the cellular shift towards tumoral progression. Full article

(This article belongs to the Special Issue Advances in Molecular Pathogenesis Regulation in Cancer 2024)

12 pages, 1210 KiB

Open AccessArticle

Influence of Calcination and Cation Exchange (APTES) of Bentonite-Modified Reinforced Basalt/Epoxy Multiscale Composites’ Mechanical and Wear Performance: A Comparative Study

by Saurabh Khandelwal, Vivek Dhand, Jaehoon Bae, Taeho Kim and Sanghoon Kim

Materials 2024, 17(19), 4760; https://doi.org/10.3390/ma17194760 - 27 Sep 2024

Abstract

In this study, bentonite clay was modified through silane treatment and calcination to enhance its compatibility with basalt fiber (BF) and epoxy in multiscale composites. The as-received bentonite (ARB) was subjected to silane treatment using APTES, producing silane-modified bentonite (STB), while calcination yielded calcined bentonite (CB). The modified clays were incorporated into basalt fiber-reinforced epoxy (BFRP) composites, which were fabricated using the vacuum-assisted resin transfer method (VARTM). Analytical techniques, including X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) spectroscopy, confirmed the structural changes in the clays. BET surface area analysis revealed a 314% increase in the surface area of STB and a 176% increase for CB. The modified clays also demonstrated reduced hydrophilicity and swelling behavior. Thermogravimetric analysis (TGA) indicated a minimal improvement in thermal stability, with the degradation onset temperatures increasing by less than 3 °C. However, tensile tests showed significant gains, with CB- and STB-reinforced composites achieving 48% and 21% higher tensile strength than ARB-reinforced composites. Tribological tests revealed substantial reductions in wear, with CB- and STB-reinforced composites showing 90% and 84% decreases in the wear volume, respectively. These findings highlight the potential of modified bentonite clays to improve the mechanical and wear properties of basalt fiber–epoxy composites. Full article

(This article belongs to the Special Issue Metal and Polymer Composites for Functional and Structural Applications)

19 pages, 10280 KiB

Open AccessArticle

Multiscale Analysis of Impact-Resistance in Self-Healing Poly(Ethylene-co-Methacrylic Acid) (EMAA) Plain Woven Composites

by Zhenzhen Zhang, Ying Tie, Congjie Fan, Zhihao Yin and Cheng Li

Polymers 2024, 16(19), 2740; https://doi.org/10.3390/polym16192740 - 27 Sep 2024

Abstract

A study combining multiscale numerical simulation and low-velocity impact (LVI) experiments was performed to explore the comprehensive effects on the impact-resistance of EMAA filaments incorporated as thermoplastic healing agents into a plain woven composite. A multiscale micro–meso–macro modeling framework was established, sequentially propagating mechanical performance parameters among micro–meso–macro models. The equivalent mechanical parameters of the carbon fiber bundles were predicted based on the microscopic model. The mesoscopic representative volume element (RVE) model was crafted by extracting the actual architecture of the monolayer EMAA filaments encompassing the plain woven composite. Subsequently, the fiber and matrix of the mesoscopic model were transformed into a monolayer-equivalent cross-panel model containing monolayers aligned at 0° and 90° by local homogenization, which was extended into a macroscopic equivalent model to study the impact-resistance behavior. The predicted force–time curves, energy–time curves, and damage profile align closely with experimental measurements, confirming the reliability of the proposed multiscale modeling approach. The multiscale analysis reveals that the EMAA stitching network can effectively improve the impact-resistance of plain woven composite laminates. Furthermore, there exist positive correlations between EMAA content and both impact-resistance and self-healing efficiency, achieving a self-healing efficiency of up to 98.28%. Full article

(This article belongs to the Section Smart and Functional Polymers)

24 pages, 4807 KiB

Open AccessArticle

A Novel FECAM-iTransformer Algorithm for Assisting INS/GNSS Navigation System during GNSS Outages

by Xinghong Kuang and Biyun Yan

Appl. Sci. 2024, 14(19), 8753; https://doi.org/10.3390/app14198753 - 27 Sep 2024

Abstract

In the field of navigation and positioning, the inertial navigation system (INS)/global navigation satellite system (GNSS) integrated navigation system is known for providing stable and high-precision navigation services for vehicles. However, in extreme scenarios where GNSS navigation data are completely interrupted, the positioning accuracy of these integrated systems declines sharply. While there has been considerable research into using neural networks to replace the GNSS signal output during such interruptions, these approaches often lack targeted modeling of sensor information, resulting in poor navigation stability. In this study, we propose an integrated navigation system assisted by a novel neural network: an inverted-Transformer (iTransformer) and the application of a frequency-enhanced channel attention mechanism (FECAM) to enhance its performance, called an INS/FECAM-iTransformer integrated navigation system. The key advantage of this system lies in its ability to simultaneously extract features from both the time and frequency domains and capture the variable correlations among multi-channel measurements, thereby enhancing the modeling capabilities for sensor data. In the experimental part, a public dataset and a private dataset are used for testing. The best experimental results show that compared to a pure INS inertial navigation system, the position error of the INS/FECAM-iTransformer integrated navigation system reduces by up to 99.9%. Compared to the INS/LSTM (long short-term memory) and INS/GRU (gated recurrent unit) integrated navigation systems, the position error of the proposed method decreases by up to 82.4% and 78.2%, respectively. The proposed approach offers significantly higher navigation accuracy and stability. Full article

12 pages, 1176 KiB

Open AccessArticle

Use of Bacterial Toxin–Antitoxin Systems as Biotechnological Tools in Plants

by Bernardo Rodamilans, Xiaofei Cheng, Carmen Simón-Mateo and Juan Antonio García

Int. J. Mol. Sci. 2024, 25(19), 10449; https://doi.org/10.3390/ijms251910449 - 27 Sep 2024

Abstract

Toxin–antitoxin (TA) systems in bacteria are key regulators of the cell cycle and can activate a death response under stress conditions. Like other bacterial elements, TA modules have been widely exploited for biotechnological purposes in diverse applications, such as molecular cloning and anti-cancer therapies. However, their use in plants has been limited, leaving room for the development of new approaches. In this study, we examined two TA systems previously tested in plants, MazEF and YefM-YoeB, and identified interesting differences between them, likely related to their modes of action. We engineered modifications to these specific modules to transform them into molecular switches that can be activated by a protease, inducing necrosis in the plant cells where they are expressed. Finally, we demonstrated the antiviral potential of the modified TA modules by using, as a proof-of-concept, the potyvirus plum pox virus as an activator of the death phenotype. Full article

(This article belongs to the Collection Advances in Molecular Plant Sciences)

15 pages, 2606 KiB

Open AccessArticle

SVX Spider Silk-Inspired Biopolymer and Enhanced Cosmetics Efficacy

by Konstantin Press, Noa Hadar, Ella Sklan, Alon Meir, Gregory Idelson, Tanya Karakouz, Miriam Gubelbank, Ali Abu Znaid and Shlomzion Shen

Cosmetics 2024, 11(5), 166; https://doi.org/10.3390/cosmetics11050166 - 27 Sep 2024

Abstract

The cosmetics industry is undergoing a shift towards sustainability and efficacy, driven by consumer demand for eco-friendly and safe products. This paper introduces SVX, a spider silk-inspired raw material intended to transform cosmetic formulations. Produced through fermentation, SVX is a biopolymer composed of self-assembled proteins characterized by a porous structure for delivering active ingredients safely to the skin. The study utilized in vitro and ex vivo methods to assess SVX’s ability to protect against oxidative stress, enhance skin hydration, and support ingredient delivery. Safety assays, including the HET-CAM, patch test, and HRIPT, demonstrated that SVX is non-irritating and safe for topical application. Additionally, FTIR analysis confirmed SVX’s capacity for sustained release of active ingredients, such as hyaluronic acid, over an 8 h period. Results showed that SVX significantly improved skin barrier protection and exhibited superior antioxidant properties compared to control formulations. Its biocompatibility, along with a vegan and biodegradable composition, aligns with the principles of sustainability, with over 60% biodegradability achieved within 10 days. Furthermore, SVX displayed antioxidant efficacy approximately 130 times greater than L-ascorbic acid, based on DPPH assay results. These findings suggest that SVX offers a versatile and sustainable solution for skincare formulations, combining environmental responsibility with benefits for skin health and performance. Full article

(This article belongs to the Special Issue Current and Future Trends in Cosmetics Research: The 10th Anniversary of Cosmetics)

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21 pages, 5986 KiB

Open AccessArticle

A Transformer-Based Image-Guided Depth-Completion Model with Dual-Attention Fusion Module

by Shuling Wang, Fengze Jiang and Xiaojin Gong

Sensors 2024, 24(19), 6270; https://doi.org/10.3390/s24196270 - 27 Sep 2024

Abstract

Depth information is crucial for perceiving three-dimensional scenes. However, depth maps captured directly by depth sensors are often incomplete and noisy, our objective in the depth-completion task is to generate dense and accurate depth maps from sparse depth inputs by fusing guidance information from corresponding color images obtained from camera sensors. To address these challenges, we introduce transformer models, which have shown great promise in the field of vision, into the task of image-guided depth completion. By leveraging the self-attention mechanism, we propose a novel network architecture that effectively meets these requirements of high accuracy and resolution in depth data. To be more specific, we design a dual-branch model with a transformer-based encoder that serializes image features into tokens step by step and extracts multi-scale pyramid features suitable for pixel-wise dense prediction tasks. Additionally, we incorporate a dual-attention fusion module to enhance the fusion between the two branches. This module combines convolution-based spatial and channel-attention mechanisms, which are adept at capturing local information, with cross-attention mechanisms that excel at capturing long-distance relationships. Our model achieves state-of-the-art performance on both the NYUv2 depth and SUN-RGBD depth datasets. Additionally, our ablation studies confirm the effectiveness of the designed modules. Full article

(This article belongs to the Special Issue Multi-Source Image Fusion, Restoration, and Understanding and Its Application in Sensing)

14 pages, 2280 KiB

Open AccessArticle

Impact of Adding Fast Switching Fault Current Limiter (FSFCL) to the Neutral Point of 220 kV Transformer

by Lujian Dai, Jun Zhao, Meng Guo, Shuguo Gao, Chenmeng Xiang, Bin Wei, Weiqi Qin, Guoming Ma and Yuan Tian

Energies 2024, 17(19), 4862; https://doi.org/10.3390/en17194862 - 27 Sep 2024

Abstract

In recent years, as the power grid continues to expand, the issue of asymmetrical short-circuit currents exceeding limits on the 220 kV medium-voltage side has become increasingly severe, and traditional current-limiting methods have certain limitations. Therefore, this paper explores the potential benefits and feasibility of installing a Fast Switching Fault Current Limiter (FSFCL) at the neutral point of a 220 kV transformer to effectively limit asymmetrical short-circuit currents on the medium-voltage side. The paper first analyzes the current-limiting performance of the FSFCL under different installation configurations, transformer operating conditions, and fault conditions through theoretical calculations. Subsequently, through simulation studies, the impact of different limiting reactance values on the overvoltage effect at the neutral point is discussed. The results show that the installation of the FSFCL has a significant effect on suppressing the asymmetrical short-circuit current on the medium-voltage side of the transformer, but this measure has also led to an increase in the voltage at the grounded neutral point. Finally, taking the No. 2 main transformer of a certain 220 kV substation as an example, to achieve the expected current-limiting effect, the limiting reactance value of the FSFCL needs to be at least 4 ohms. At this reactance value, the overvoltage level at the neutral point remains well below the withstand limit of its insulating material. Additionally, given the existing overvoltage protection devices at the neutral point, no further overvoltage protection measures are required. Full article

(This article belongs to the Section F: Electrical Engineering)

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15 pages, 2181 KiB

Open AccessArticle

A Deep Insight into the Micro-Mechanical Properties of Mortar through a Multi-Phase Model

by Qiang Li, Jin Huang, Chao Tang, Lingfeng Meng, Yanyan Yu and Kaiyuan Wei

Buildings 2024, 14(10), 3106; https://doi.org/10.3390/buildings14103106 - 27 Sep 2024

Abstract

This study investigates the micro-mechanical behavior of mortar under uniaxial compression using a three-phase model in PFC^3D. By simulating mortar as a composite of cement, sand, and the interfacial transition zone (ITZ), the research examines the impact of particle size on stress–strain behavior, crack propagation, porosity distribution, contact forces, and energy transformation. The simulations reveal that reducing sand particle size from 1–2 mm to 0.25–0.5 mm leads to a significant increase in uniaxial compressive strength, with peak strength values rising from 65.3 MPa to 89.6 MPa. The elastic modulus similarly improves by approximately 20% as particle size decreases. The study also finds that tensile cracks dominate failure, accounting for over 95% of total cracks, with their onset occurring at lower strains as the particle size is reduced. Porosity analysis shows that smaller particles result in a more uniform distribution, with the final porosity at peak strength ranging between 0.26 and 0.29, compared to 0.22 to 0.31 for larger particles. Additionally, energy dissipation patterns reveal that as particle size decreases, the boundary energy transformation into strain energy becomes more efficient, with a 15% increase in strain energy storage observed. These findings provide critical insights into optimizing mortar microstructure for enhanced mechanical performance in construction applications. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

14 pages, 3918 KiB

Open AccessArticle

Preparations of Polyurethane Foam Composite (PUFC) Pads Containing Micro-/Nano-Crystalline Cellulose (MCC/NCC) toward the Chemical Mechanical Polishing Process

by Yi-Shen Huang, Yu-Wen Huang, Qiao-Wen Luo, Chao-Hsing Lin, Penjit Srinophakun, Supanicha Alapol, Kun-Yi Andrew Lin and Chih-Feng Huang

Polymers 2024, 16(19), 2738; https://doi.org/10.3390/polym16192738 - 27 Sep 2024

Abstract

Polyurethane foam (PUF) pads are widely used in semiconductor manufacturing, particularly for chemical mechanical polishing (CMP). This study prepares PUF composites with microcrystalline cellulose (MCC) and nanocrystalline cellulose (NCC) to improve CMP performance. MCC and NCC were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD), showing average diameters of 129.7 ± 30.9 nm for MCC and 22.2 ± 6.7 nm for NCC, both with high crystallinity (ca. 89%). Prior to preparing composites, the study on the influence of the postbaked step on the PUF was monitored through Fourier-transform infrared spectroscopy (FTIR). After that, PUF was incorporated with MCC/NCC to afford two catalogs of polyurethane foam composites (i.e., PUFC-M and PUFC-N). These PUFCs were examined for their thermal and surface properties using a differential scanning calorimeter (DSC), thermogravimetric analysis (TGA), dynamic mechanical analyzer (DMA), and water contact angle (WCA) measurements. T_gs showed only slight changes but a notable increase in the 10% weight loss temperature (T_d10%) for PUFCs, rising from 277 °C for PUF to about 298 °C for PUFCs. The value of Tan δ dropped by up to 11%, indicating improved elasticity. Afterward, tensile and abrasion tests were conducted, and we acquired significant enhancements in the abrasion performance (e.g., from 1.04 mm/h for the PUF to 0.76 mm/h for a PUFC-N) of the PUFCs. Eventually, we prepared high-performance PUFCs and demonstrated their capability toward the practical CMP process. Full article

(This article belongs to the Special Issue Polymer Materials for Sensors)

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