Supercritical geothermal systems are appealing sources of sustainable and carbon-free energy located in volcanic areas. Recent successes in drilling and exploration have opened new possibilities and ...spiked interest in this technology. Experimental and numerical studies have also confirmed the feasibility of creating fluid conducting fractures in sedimentary and crystalline rocks at high temperature, paving the road towards Enhanced Supercritical Geothermal Systems. Despite their attractiveness, several important questions regarding safe exploitation remain open. We dedicate this manuscript to the first thermo-hydro-mechanical numerical study of a doublet geothermal system in supercritical conditions. Here we show that thermally-induced stress and strain effects dominate the geomechanical response of supercritical systems compared to pore pressure-related instabilities, and greatly enhance seismicity during cold water re-injection. This finding has important consequences in the design of Supercritical Geothermal Systems.
Display omitted
•Cellular ceramic structures have been extensively applied in catalysis supports, concentrated solar energy, thermal protection or thermal storage, heat exchangers, radiant burners, ...nuclear fusion, gas streams, and biomedical implants.•Additive manufacturing technologies based on stereolithography, extrusion free-forming, two-photo lithography have been extensively adopted to fabricate cellular ceramic structures.•Structural additively manufactured cellular ceramic lattices, as well as structure–function integrated additively manufactured cellular ceramic lattices, were comprehensively summarized.•Smart and flexible cellular ceramic structures may be the future trend in this field.
Cellular ceramic structures (CCSs) have promising application perspectives in various fields. Recently, additive manufacturing (AM), usually known as three-dimensional printing (3D printing), has been increasingly adopted to produce CCSs. Usually, the structural properties of additively manufactured cellular ceramic structures (AM-CCSs), i.e., lightweight characteristics, load-bearing capacity, toughness, unconventional properties, are traditionally investigated. Interestingly, AM technologies have a significant advantage in achieving the structure–function integration for CCSs. Functional properties, e.g., electromagnetic property, acoustic property, thermal property, of CCSs can be achieved during the structural design synchronously. In this review, firstly, the AM technologies for CCSs are comparatively introduced. Then, structural AM-CCSs are summarized. After that, structure–function integrated AM-CCSs are further introduced in detail. Finally, challenges and opportunities towards structure–function integrated AM-CCSs are forecasted. This review is believed to give some guidance for the research and development of CCSs.
•Different VIs and optical images are assessed for mangrove LAI estimation.•WV-2 acquires the best estimation accuracy, followed by Sentinel-2 and UAV.•VIs_RE1 can accurately estimate mangrove ...LAI.•The generic model could be deemed as a basic method for mangrove LAI mapping.
Accurate estimation of mangrove leaf area index (LAI) is fundamental for effective mangrove ecosystem management and protection. Remote sensing technology has showed its powerful potential in accurately retrieving mangrove LAI. The generic estimation model combining vegetation indices (VIs) with physically-based law, simplified as LAI-VIs model, has successfully estimated crop LAI. However, the capacity of estimating mangrove LAI using this model, so far, is unclear. Moreover, some studies have proved that estimation accuracy of terrestrial forests and crops LAI can be ameliorated with VIs based on red-edge band (VIs_RE) because of less affecting by canopy structure. However, little literature explores the ability of VIs_RE, especially, from different multispectral sensors, for estimating mangrove LAI. Therefore, our main purpose is to evaluate the robustness and sensitivity of the LAI-VIs_RE model from Sentinel-2, WorldView-2 (WV-2) and Unmanned Aerial Vehicle (UAV) multispectral imagery for estimating mangrove LAI. The estimation models with input variables of NDVI, NDVI_RE1 (band combination from red-edge and visible band), NDVI_RE2 (band combination from red-edge and near-infrared reflectance) from three types of multispectral imagery are used to calculate mangrove LAI of 99 plots. The results showed that the WV-2 imagery acquires the best estimation accuracy (R2 = 0.72, RMSE = 0.414), followed by Sentinel-2 imagery (R2 = 0.68, RMSE = 0.440), and UAV multispectral imagery (R2 = 0.48, RMSE = 0.570). The analyses display the good results of the LAI-NDVI model and LAI-NDVI_RE1 model from WV-2 and Sentinel-2 imagery with the range of R2 from 0.57 to 0.72, and the discrepant consequences of LAI-NDVI_RE2 model from UAV imagery with R2 of 0.15, WV-2 imagery with R2 of 0.67 and Sentienl-2 imagery with R2 of 0.65, 0.18 and 0.12. This study proves that the generic estimation model and NDVI_RE1 derived from WV-2 and Sentinel-2 multispectral imagery could be deemed as a basic method and input variables of mapping mangrove LAI.
Glycerol-3-phosphate acyltransferase is the first acyl esterifying enzyme in phosphatidylglycerol (PG) synthesis process. In this study, we isolated and characterized the glycerol-3-phosphate ...acyltransferase (GPAT) gene from
(
) and obtained the full length of the GPAT gene from
(
) by 5' and 3' RACE. The clone contained an open reading frame (ORF) of 1167 bp nucleotides that comprised of 388 amino acid residues. Real-time PCR revealed that the mRNA accumulation of
in
was induced by salt stress. The highest expression levels were observed when
leaves were exposed to 300 mM NaCl treatment. At the germination stage, the germination rate and root length of overexpressed Arabidopsis strains were significantly higher than WT under different concentrations of NaCl treatments, while the inhibitory effect was significantly severe in T-DNA insertion mutant strains. In the seedling stage, chlorophyll content, the photochemical efficiency of PSII, PSI oxidoreductive activity (ΔI/Io), and the unsaturated fatty acid content of PG decreased less in overexpressed strains and more in mutant strains than that in WT under salt stress. These results suggest that the overexpression of
in Arabidopsis enhances salt tolerance and alleviates the photoinhibition of PSII and PSI under salt stress by improving the unsaturated fatty acid content of PG.
Despite their high prediction accuracy, deep learning-based soft sensor (DLSS) models face challenges related to adversarial robustness against malicious adversarial attacks, which hinder their ...widespread deployment and safe application. Although adversarial training is the primary method for enhancing adversarial robustness, existing adversarial-training-based defense methods often struggle with accurately estimating transfer gradients and avoiding adversarial robust overfitting. To address these issues, we propose a novel adversarial training approach, namely domain-adaptive adversarial training (DAAT). DAAT comprises two stages: historical gradient-based adversarial attack (HGAA) and domain-adaptive training. In the first stage, HGAA incorporates historical gradient information into the iterative process of generating adversarial samples. It considers gradient similarity between iterative steps to stabilize the updating direction, resulting in improved transfer gradient estimation and stronger adversarial samples. In the second stage, a soft sensor domain-adaptive training model is developed to learn common features from adversarial and original samples through domain-adaptive training, thereby avoiding excessive leaning toward either side and enhancing the adversarial robustness of DLSS without robust overfitting. To demonstrate the effectiveness of DAAT, a DLSS model for crystal quality variables in silicon single-crystal growth manufacturing processes is used as a case study. Through DAAT, the DLSS achieves a balance between defense against adversarial samples and prediction accuracy on normal samples to some extent, offering an effective approach for enhancing the adversarial robustness of DLSS.
Abstract With the continuous development and application of online interactive activities and network transmission technology, online interactive behaviors such as online discussion meetings and ...online teaching have become indispensable in people’s studies and work. However, the effectiveness of working with online discussions and feedback from participants on their conference performance has been a major concern, and this is the issue examined in this post. Based on the above issues, this paper designs an online discussion activity-level evaluation system based on voiceprint recognition technology. The application system developed in this project is divided into two parts; the first part is to segment the online discussion audio into multiple independent audio segments by audio segmentation technology and train the voiceprint recognition model to predict the speaker’s identity in each separate audio component. In the second part, we propose a linear normalized online meeting activity-level calculation model based on the modified main indexes by traversing and counting each participant’s speaking frequency and total speaking time as the main indexes for activity-level evaluation. To make the evaluation results more objective, reasonable, and distinguishable, the activity score of each participant is calculated, and each participant’s activity-level in the discussion meeting is derived by combining the fuzzy membership function. To test the system’s performance, we designed an experiment with 25 participants in an online discussion meeting, with two assistants manually recording the discussion and a host moderating the meeting. The results of the experiment showed that the system’s evaluation results matched those recorded by the two assistants. The system can fulfill the task of distinguishing the level of activity of participants in online discussions.
The fusion of multi-modal medical images has great significance for comprehensive diagnosis and treatment. However, the large differences between the various modalities of medical images make ...multi-modal medical image fusion a great challenge. This paper proposes a novel multi-scale fusion network based on multi-dimensional dynamic convolution and residual hybrid transformer, which has better capability for feature extraction and context modeling and improves the fusion performance. Specifically, the proposed network exploits multi-dimensional dynamic convolution that introduces four attention mechanisms corresponding to four different dimensions of the convolutional kernel to extract more detailed information. Meanwhile, a residual hybrid transformer is designed, which activates more pixels to participate in the fusion process by channel attention, window attention, and overlapping cross attention, thereby strengthening the long-range dependence between different modes and enhancing the connection of global context information. A loss function, including perceptual loss and structural similarity loss, is designed, where the former enhances the visual reality and perceptual details of the fused image, and the latter enables the model to learn structural textures. The whole network adopts a multi-scale architecture and uses an unsupervised end-to-end method to realize multi-modal image fusion. Finally, our method is tested qualitatively and quantitatively on mainstream datasets. The fusion results indicate that our method achieves high scores in most quantitative indicators and satisfactory performance in visual qualitative analysis.
Silicon carbide (SiC) ceramic and related materials are widely used in various military and engineering fields. The emergence of additive manufacturing (AM) technologies provides a new approach for ...the fabrication of SiC ceramic products. This article systematically reviews the additive manufacturing technologies of SiC ceramic developed in recent years, including Indirect Additive Manufacturing (Indirect AM) and Direct Additive Manufacturing (Direct AM) technologies. This review also summarizes the key scientific and technological challenges for the additive manufacturing of SiC ceramic, and also forecasts its possible future opportunities. This paper aims to provide a helpful guidance for the additive manufacturing of SiC ceramic and other structural ceramics.
Abstract
To solve the problem that the traditional hyperspectral image classification method cannot effectively distinguish the boundary of objects with a single scale feature, which leads to low ...classification accuracy, this paper introduces the idea of guided filtering into hyperspectral image classification, and then proposes a multi-scale guided feature extraction and classification (MGFEC) algorithm for hyperspectral images. Firstly, the principal component analysis theory is used to reduce the dimension of hyperspectral image data. Then, guided filtering algorithm is used to achieve multi-scale spatial structure extraction of hyperspectral image by setting different sizes of filtering windows, so as to retain more edge details. Finally, the extracted multi-scale features are input into the support vector machine classifier for classification. Several practical hyperspectral image datasets were used to verify the experiment, and compared with other spectral feature extraction algorithms. The experimental results show that the multi-scale features extracted by the MGFEC algorithm proposed in this paper are more accurate than those extracted by only using spectral information, which leads to the improvement of the final classification accuracy. This fully shows that the proposed method is not only effective, but also suitable for processing different hyperspectral image data.
Dihydromyricetin (DMY) is the most abundant ingredient in vine tea. Here, we investigated the cytoprotective effects and possible mechanisms of DMY on hydrogen peroxide (H2O2)-induced oxidative ...stress damage in human umbilical vein endothelial cells (HUVECs).
The percentage of cell viability was evaluated using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. We determined the antioxidant properties of DMY by measuring the activity of superoxide dismutase (SOD) and malondialdehyde (MDA). Flow cytometry was used to measure apoptosis in HUVECs that were double stained with Hoechst 33342 and propidium iodide (PI). The generation of intracellular reactive oxygen species (ROS) was measured in 2′,7′-dichlorofluorescin diacetate (DCFH-DA)-loaded HUVECs using a fluorescent microscope. Moreover, the expression of apoptosis-related proteins was determined by Western blotting. In addition, the release of nitric oxide (NO) was analyzed using a commercial kit.
HUVECs treated with H2O2 had a notable decrease in cell viability that was attenuated when cells were pretreated with DMY (37.5–300μM). DMY pretreatment significantly attenuated H2O2-induced apoptosis in HUVECs and inhibited intracellular ROS overproduction. Finally, pretreatment of cells with DMY prior to H2O2 exposure resulted in the inhibition of p53 activation, followed by the regulation of the expression of Bcl-2 and Bax, the release of cytochrome c, the cleavage (activation) of caspase-9 and caspase-3, and then the suppression of PARP cleavage in H2O2-induced HUVECs.
Our study is the first to report that DMY can protect HUVECs from oxidative stress damage, an effect that is mediated by the mitochondrial apoptotic pathways.
PDF
