Search Results (31)

Dryopteris fragrans (L.) Schott synthesizes volatile sesquiterpenes through the mevalonate pathway (MVA), in which 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) serves as the key rate-limiting enzyme. Although HMGR plays a crucial role in terpenoid biosynthesis, its functional characteristics in D. fragrans and its involvement in stress responses remain unclear. This study identified three HMGR genes (DfHMGR1/2/3) from the transcriptome data of D. fragrans. Bioinformatics analysis revealed that the encoded proteins are localized to the endoplasmic reticulum and share high sequence similarity with fern homologs. Under abiotic stress conditions, DfHMGRs exhibited differential expression patterns, with marked upregulation under salt and drought stress. To validate the functions of these genes, we generated transgenic Nicotiana tabacum L. plants overexpressing DfHMGRs. Compared with wild-type controls, the transgenic lines showed enhanced tolerance to drought and heat stress. Promoter analysis identified functional regulatory regions controlling DfHMGR expression, and co-expression network analysis predicted 21 potential transcriptional regulators. This study validates the function of D. fragrans HMGRs in a heterologous system and provides candidate genes for improving stress resistance in plants. Full article

Ground-based synthetic aperture radar (GBSAR) has been widely used in the fields of early warning of geologic hazards and deformation monitoring of engineering structures due to its characteristics of high spatial resolution, zero spatial baseline, and short revisit period. However, in the continuous monitoring process of GBSAR, due to the sudden failure of radar equipment, such as power failure, or the influence of alternating work between multiple regions, it often leads to discontinuous data collection, and this problem caused by missing data is collectively called “inspection mode”. The problem of missing data in the inspection mode not only destroys the spatial and temporal continuity of the data but also affects the accuracy of the subsequent deformation analysis. In order to solve this problem, in this paper, we propose a data reconstruction method that combines Sage–Husa Kalman adaptive filtering and the Rauch–Tung–Striebel (RTS) smoothing algorithm. The method is based on the principle of Kalman filtering and solves the problem of “model mismatch” caused by the fixed noise statistics of traditional Kalman filtering by dynamically adjusting the noise covariance to adapt to the non-stationary characteristics of the observed data. Subsequently, the Rauch–Tung–Striebel (RTS) smoothing algorithm is used to process the preliminary filtering results to eliminate the cumulative error during the period of missing data and recover the complete and smooth deformation time series. The experimental and simulation results show that this method successfully restores the spatial and temporal continuity of the inspection data, thus improving the overall accuracy and stability of deformation monitoring. Full article

This study proposes a deep learning-based vertical decomposition model for ionospheric Total Electron Content (TEC), which establishes a nonlinear mapping from macroscale TEC data to vertically layered electron density (Ne) spanning 60–800 km by integrating geomagnetic indices (AE, SYM-H) and solar activity parameters (F10.7). Utilizing global TEC grid data (spatiotemporal resolution: 1 h/5.625° × 2.8125°) provided by the International GNSS Service (IGS), a Multilayer Perceptron (MLP) model was developed, taking spatiotemporal coordinates, altitude, and space environment parameters as inputs to predict logarithmic electron density ln(Ne). Experimental validation against COSMIC-2 radio occultation observations in 2019 demonstrates the model’s capability to capture ionospheric vertical structures, with a prediction performance significantly outperforming the International Reference Ionosphere model IRI-2020: root mean square error (RMSE) decreased by 34.16%, and the coefficient of determination (R²) increased by 28.45%. This method overcomes the reliance of traditional electron density inversion on costly radar or satellite observations, enabling high-spatiotemporal-resolution global ionospheric profile reconstruction using widely available GNSS-TEC data. It provides a novel tool for space weather warning and shortwave communication optimization. Current limitations include insufficient physical interpretability and prediction uncertainty in GNSS-sparse regions, which could be mitigated in future work through the integration of physical constraints and multi-source data assimilation. Full article

As a relatively weak part of cable insulation, T-type cable terminals will have insulation defects due to process, installation, and other problems, resulting in partial discharge. Therefore, this paper uses Deep Convolution Neural Network (DCNN) and Empirical Mode Decomposition (EMD) to identify the partial discharge type of a 10 kV T-type cable terminal. This method uses the partial discharge experimental platform of the T-type cable terminal to collect the partial discharge signal. After the original signal that is difficult to identify is decomposed by EMD, a series of intrinsic mode components (IMFs) that are easy to locate are obtained. The deep learning network model is used to identify the defect type of the IMF signal. The results show that the overall defect recognition rate of this method reaches 95.3%. Compared with the traditional random forest algorithm (RF), the 10 kV T-type terminal partial discharge type recognition method based on EMD–DCNN is considered in this paper. The recognition accuracy of the main insulation scratch, bushing fouling, and joint loosening defects is higher than that of the traditional mechanical learning algorithm, RF, indicating that the method adopted in this paper can more effectively and accurately identify the defect type. Full article

For the new type of CFRP (Carbon Fiber Reinforced Plastic) thin-walled components with a large size and weak rigid structure, due to the integration of geometric features and the reduction in the amount of parts, the assembly size transmission chain is short compared to traditional metal assembly structures. In addition, the manufacturing errors and layer parameters of large composite parts in different regions are different, and they also have a lower forming accuracy. For the current assembly method that mainly concerns geometric dimensions and tolerances, it is difficult to support precise analysis and accurate geometric error forms for different local and global regions. As a result, in practical engineering, the forced method of applying a local clamping force is inevitably adopted to passively reduce and compensate for assembly errors. However, uneven stress distribution and possible internal damage occur. To avoid the assembly quality problems caused by forced clamping operations, the research status on the optimization of forced clamping process parameters before assembly, the flexible position–force adjustment of fixtures during assembly, and gap compensation and strengthening before assembly completion was analyzed systematically. The relevant key technologies, such as force limit setting, geometric gap reduction, stress/damage evolution prediction, the reverse optimization of clamping process parameters, and precise stress/damage measurement, are proposed and resolved in this paper. With the specific implementation solutions, geometric and mechanical assembly status coupling analysis, active control, and a collaborative guarantee could be achieved. Finally, future research work is proposed, i.e., dynamic evolution behavior modeling and the equalization of the induction and control of physical assembly states. Full article

This study explores modern residential buildings in rural areas of Wuhan and Guangzhou to assess the feasibility of achieving net zero energy buildings (NZEBs) through the transformation of existing buildings in southern China’s hot-summer–cold-winter and hot-summer–warm-winter regions. Energy simulations under various climatic scenarios identify effective energy-saving measures, such as the use of photovoltaic power generation. The results highlight substantial renovation potential, with energy reductions of approximately 85 kWh/m² (RCP2.6), 90 kWh/m² (RCP4.5), and 115 kWh/m² (RCP8.5). Living patterns significantly influence energy use, especially in buildings with more rooms, where the gaps in the energy demand with net zero standards can reach 560.56 kWh. At the monthly scale, different climate scenarios impact the feasibility of achieving NZEBs, particularly under RCP8.5, where eight rural housing types fail to meet the requirements, with six exceeding 200 kWh energy deficits and the largest energy deficit occurs in June 2090 in Guangzhou, reaching 592.53 kWh, while under RCP2.6, only two buildings with more rooms fail to meet NZE. In summary, in the hot-summer cold-winter region, the energy demand is higher but so is the solar yield. Therefore, under the most adverse RCP8.5 scenario, NZEBs are achievable for 9 months of the year, which is 2 months more compared to Guangzhou under similar conditions. Even after net zero transformation, new rural housing will face greater energy-saving challenges in future climatic conditions, especially under higher concentration pathways. Full article

Vibrating flip-flow screens (VFFSs) provide an effective solution for deeply screening moist and fine-grained minerals, and an accurate dynamic model of VFFSs is critical for its dynamic analysis and optimization, thereby improving the vibration stability and symmetry of VFFSs. In this paper, uniaxial tension, uniaxial compression, plane tension, and shear stress relaxation experiments were conducted on screen panel samples to illustrate that the third-order Ogden model and the generalized Maxwell model can accurately describe the hyperelasticity and viscoelasticity of screen panels. Then, the coupling method of finite element and discrete element was adopted to establish the simulation model of the screen panel and material group coupling system, and the dynamics of the coupling system under different loading conditions were explored. Finally, the dynamic model of the coupling system of VFFSs mass, screen panel, and material group was proposed, and the non-dominated sorting genetic algorithm II was applied to optimize the system’s dynamic response. The results reveal that the use of optimized shear springs can reduce the relative amplitude change rate of the main and floating screen frame by 44.30% while maintaining the periodic motion of the VFFSs under operation conditions, greatly enhancing the stability of the VFFSs system. Full article

As a crucial component of many natural language processing tasks, extracting entities and relations transforms unstructured text information into structured data, providing essential support for constructing knowledge graphs (KGs). However, current entity relation extraction models often prioritize the extraction of richer semantic features or the optimization of relation extraction methods, overlooking the significance of positional information and subject characteristics in this task. To solve this problem, we introduce the subject position-based complex exponential embedding for entity relation extraction model (SPECE). The encoder module of this model ingeniously combines a randomly initialized dilated convolutional network with a BERT encoder. Notably, it determines the initial position of the predicted subject based on semantic cues. Furthermore, it achieves a harmonious integration of positional encoding features and textual features through the adoption of the complex exponential embedding method. The experimental outcomes on both the NYT and WebNLG datasets reveal that, when compared to other baseline models, our proposed SPECE model demonstrates significant improvements in the F1 score on both datasets. This further validates its efficacy and superiority. Full article

As deep learning has evolved, larger and deeper neural networks are currently a popular trend in both natural language processing tasks and computer vision tasks. With the increasing parameter size and model complexity in deep neural networks, it is also necessary to have more data available for training to avoid overfitting and to achieve better results. These facts demonstrate that training deep neural networks takes more and more time. In this paper, we propose a training acceleration method based on gradually freezing the parameters during the training process. Specifically, by observing the convergence trend during the training of deep neural networks, we freeze part of the parameters so that they are no longer involved in subsequent training and reduce the time cost of training. Furthermore, an adaptive freezing algorithm for the control of freezing speed is proposed in accordance with the information reflected by the gradient of the parameters. Concretely, a larger gradient indicates that the loss function changes more drastically at that position, implying that there is more room for improvement with the parameter involved; a smaller gradient indicates that the loss function changes less and the learning of that part is close to saturation, with less benefit from further training. We use ViTDet as our baseline and conduct experiments on three remote sensing target detection datasets to verify the effectiveness of the method. Our method provides a minimum speedup ratio of 1.38×, while maintaining a maximum accuracy loss of only 2.5%. Full article

Ultra-high-performance concrete (UHPC) is an advanced cement-based material with excellent mechanical properties and durability. However, with the improvement of UHPC’s compressive properties, its insufficient tensile properties have gradually attracted attention. This paper reviews the tensile properties of steel fibers in UHPC. The purpose is to summarize the existing research and to provide guidance for future research. The relevant papers were retrieved through three commonly used experimental methods for UHPC tensile properties (the direct tensile test, flexural test, and splitting test), and classified according to the content, length, type, and combination of the steel fibers. The results show that the direct tensile test can better reflect the true tensile strength of UHPC materials. The tensile properties of UHPC are not only related to the content, shape, length, and hybrids of the steel fibers, but also to the composition of the UHPC matrix, the orientation of the fibers, and the geometric dimensions of the specimen. The improvement of the tensile properties of the steel fiber combinations depends on the effectiveness of the synergy between the fibers. Additionally, digital image correlation (DIC) technology is mainly used for crack propagation in UHPC. The analysis of the post-crack phase of UHPC is facilitated. Theoretical models and empirical formulas for tensile properties can further deepen the understanding of UHPC tensile properties and provide suggestions for future research. Full article

Andrographis paniculata is a medicinal plant traditionally used to produce diterpene lactones and flavonoids, which possess various biological activities. Widely distributed in China, India, and other Southeast Asia countries, A. paniculata has become an important economic crop, significantly treating SARS-CoV-2, and is being cultivated on a large scale in southern China. The biosynthesis of active ingredients in A. paniculata are regulated and controlled by genes, but their specific roles are still not fully understood. To further explore the growth regulation factors and utilization of its medicinal parts of this industrial crop, chemical and transcriptome analyses were conducted on the roots, stems, and leaves of A. paniculata to identify the biosynthesis pathways and related candidate genes of the active ingredients. The chemical analysis revealed that the main components of A. paniculata were diterpene lactones and flavonoids, which displayed potential ability to treat SARS-CoV-2 through molecular docking. Moreover, the transcriptome sequencing annotated a total of 40,850 unigenes, including 7962 differentially expressed genes. Among these, 120 genes were involved in diterpene lactone biosynthesis and 60 genes were involved in flavonoid biosynthesis. The expression of diterpene lactone-related genes was the highest in leaves and the lowest in roots, consistent with our content determination results. It is speculated that these highly expressed genes in leaves may be involved in the biosynthesis pathway of diterpenes. Furthermore, two class Ⅰ terpene synthases in A. paniculata transcriptome were also annotated, providing reference for the downstream pathway of the diterpene lactone biosynthesis. With their excellent market value, our experiments will promote the study of the biosynthetic genes for active ingredients in A. paniculata and provide insights for subsequent in vitro biosynthesis. Full article

The development of antibiotic-resistant microorganisms is a major global health concern. Recently, there has been an increasing interest in antimicrobial peptides as a therapeutic option. This study aimed to evaluate the triple-action (broad-spectrum antibacterial, anti-biofilm, and anti-quorum sensing activities) of melittin, a membrane-active peptide present in bee venom. The minimum inhibitory concentration and minimum bactericidal concentration of the melittin were determined using the microdilution method and agar plate counting. Growth curve analysis revealed that melittin showed a concentration-dependent antibacterial activity. Scanning electron microscope analysis revealed that melittin treatment altered the morphology. Confocal laser scanning microscope revealed that melittin increased the membrane permeability and intracellular ROS generation in bacteria, all of which contribute to bacterial cell death. In addition, the crystal violet (CV) assay was used to test the anti-biofilm activity. The CV assay demonstrated that melittin inhibited biofilm formation and eradicated mature biofilms. Biofilm formation mediated by quorum sensing (QS) plays a major role in this regard, so molecular docking and molecular dynamics analysis confirmed that melittin interacts with LasR receptors through hydrogen bonds, and further evaluates the anti-QS activity of melittin through the production of virulence factors (pyocyanin, elastase, and rhamnolipid), exopolysaccharides secretion, and bacterial motility, that may be the key to inhibiting the biofilm formation mechanism. The present findings highlight the promising role of melittin as a broad-spectrum antibacterial, anti-biofilm agent, and potential QS inhibitor, providing a new perspective and theoretical basis for the development of alternative antibiotics. Full article

Due to global temperature increases, terraced house (TH) residents face a threat to their health due to poor indoor thermal environments. As buildings are constructed by low-income residents without professional guidance, this study aims to investigate the indoor thermal comfort and energy resilience of THs under the future climate and determine the optimal passive design strategies for construction and retrofitting. By exploring the effects of building envelope structures, adjusting the window-to-wall ratio (WWR) and designing shading devices, EnergyPlus version 22.0 was used to optimize the thermal environment and cooling load of THs throughout their life cycle under future climate uncertainties. Unimproved THs will experience overheating for nearly 90% of the hours in a year and the cooling load will exceed 60,000 kWh by 2100 under the Representative Concentration Pathways (RCP) 8.5 scenario. In contrast, optimization and improvements resulted in a 17.3% reduction in indoor cooling load by increasing shading devices and the WWR, and using building envelope structures with moderate thermal insulation. This study can guide TH design and renovation, significantly reducing indoor cooling load and enabling residents to better use active cooling to combat future overheating environments. Full article

Flexural testing on two prestressed segmental ultra–high–performance concrete channels and reinforced conventional concrete deck composite girders (PSUC–RCCD) was carried out. One was made up of four segments with dry joints, and the other was formed of one channel beam without a dry joint. Both of them poured a conventional concrete deck slab on site. The mechanical behaviors of the girders, including the whole loading process, the crack pattern, and the failure mode were investigated and compared. The effect of the number of segments and the steel fiber volume fraction of UHPC on the bending behavior of the PSUC–RCCD girder was explored using the finite element method. This study showed that the loading process of semi-segmental and integral girders is similar; the whole loading process of the girders can be divided into the elastic phase, crack development, and the failure phase. The only notable difference between the two girders was the stage of crack development; specifically, after cracking, the stiffness of the semi-segmental girder reduced rapidly, while the “bridging effect” of the steel fibers in the integrated girder caused a slow reduction in rigidity. The flexural cracks in the semi-segmental girder were significantly less than those in the integral girder in terms of the number of cracks, and were present only at the joints. The finite element analysis showed that the number of segments had little influence on the flexural capacity of the girders, but the girders with even numbers of segments cracked earlier than those with odd segments. Increasing the steel fiber volume fraction in UHPC (ultra–high–performance concrete) had a small effect on the cracking load of the semi-segmental girders but enhanced its ultimate flexural capacity. Based on this experiment, a calculated method for estimating the flexural capacity of semi-sectional girders was proposed. The calculated values were in good agreement with the experimental and finite element values. In the preliminary design, the flexural capacity of the semi-segmental section could be estimated by multiplying the flexural capacity of the integral section by a resistance factor of 0.95. Full article

The Ordovician strike-slip faults system in the Tahe area of the Tarim Basin provides an important opportunity for using 3D seismic data to document the structural characteristics, formation, and evolution of strike-slip faults and their relationship with oil and gas. With high-resolution 3D seismic data, the strike-slip faults are interpreted, classified, and described using the seismic coherence technique. The geometric characteristics, active periods, formation, and evolution process of strike-slip faults are analyzed, and the relationship between strike-slip faults and hydrocarbon accumulation and charging is discussed in this research project. On the map, the primary strike-slip faults on the east and west sides of the Tahe area are relatively sheared to each other, showing an “X” type conjugate fault, and the secondary strike-slip faults are scattered. In the cross-section, the primary strike-slip faults are inserted downward into the Cambrian basement and up to Devonian, and “Single line”, “Y”, “Flower”, and “Parallel lines” structures are observed. Bounded by the top of Ordovician, the deep and shallow parts are vertically segmented, with different structure styles. The switch of the structural style of strike-slip faults is attributed to principal stress. A deep “positive flower” shape of faults was developed in the mid-Ordovician period under the effect of compressive stress. Meanwhile, a shallow “negative flower” shape of faults was developed from the late Ordovician to the mid-Devonian period under tensile stress. The “Compound Flower” shape of deep “positive flower” shape and shallow “negative flower” shape formed by compressive and tensile activities has a wider fracture range, which leads to deep fluid migration and shallow karstification. There are two combinations of deep Ordovician strike-slip faults in the section: “Lower single branch-upper flower type” and “lower single branch-upper single branch type”. The primary faults of the former insertion into the Cambrian basement are associated with homologous secondary faults, while the latter has no derived secondary faults. It has an important impact on reservoir reconstruction and distribution, and the reservoir is controlled by faults. Strike-slip faults not only control the channel of oil and gas migration, but also the horizontal and vertical distribution of oil and gas. The closer the carbonate reservoir is to the primary fault, the more likely it is to form a high yield area. There are four types of oil and gas charging models controlled by strike-slip faults. In the area where the structure is high and the strike-slip faults are sheared relatively to each other, the larger the scale of faults, the more conducive it would be to oil and gas migration and accumulation. Among them, the charging model related to the primary fault has higher oil and gas migration efficiency. This research contributes to analyzing the relationship between strike-slip faults and oil and gas as well as playing a significant role in applications of oil and gas exploration in practical works. Full article