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Accurate understanding of urban land use change information is of great significance for urban planning, urban monitoring, and disaster assessment. The use of Very-High-Resolution (VHR) remote sensing images for change detection on urban land features has gradually become mainstream. However, most existing transfer learning-based change detection models compute multiple deep image features, leading to feature redundancy. Therefore, we propose a Transfer Learning Change Detection Model Based on Change Feature Selection (TL-FS). The proposed method involves using a pretrained transfer learning model framework to compute deep features from multitemporal remote sensing images. A change feature selection algorithm is then designed to filter relevant change information. Subsequently, these change features are combined into a vector. The Change Vector Analysis (CVA) is employed to calculate the magnitude of change in the vector. Finally, the Fuzzy C-Means (FCM) classification is utilized to obtain binary change detection results. In this study, we selected four VHR optical image datasets from Beijing-2 for the experiment. Compared with the Change Vector Analysis and Spectral Gradient Difference, the TL-FS method had maximum increases of 26.41% in the F1-score, 38.04% in precision, 29.88% in recall, and 26.15% in the overall accuracy. The results of the ablation experiments also indicate that TL-FS could provide clearer texture and shape detections for dual-temporal VHR image changes. It can effectively detect complex features in urban scenes. [ABSTRACT FROM AUTHOR]

Anthropogenic heat emissions, which are quantified as anthropogenic heat flux (AHF), have attracted significant attention due to their pronounced impacts on urban thermal environments and local climates. However, there remains a notable gap in research regarding the distinctions in the distribution of anthropogenic heat emissions (AHEs) along urban–rural gradients. To address this gap, the present study introduces a new concept—the anthropogenic urban heat island (ArUHI)—where the AHF within urban areas is higher than that in background areas. To quantitatively describe the magnitude and spatial extent of the ArUHI effect, two metrics—namely, ArUHI intensity (ArUHII) and ArUHI footprint (ArUHIFP)—are introduced. We conducted a comprehensive study across 208 cities in China to investigate the spatiotemporal patterns of AHF variations along urban–rural gradients during the period of 2000–2016. In addition, we explored how the complex interactions between land cover and building form components affect changes in the AHF along urban–rural gradients. Additionally, we analyzed how economic zones and city sizes alter the ArUHI intensity and ArUHI footprint. The results showed that 97% (201/208) of Chinese cities exhibited a significant ArUHI effect from 2000 to 2016. The modeled ArUHI intensity value exhibited a substantial increase of nearly fivefold, increasing from 5.55 ± 0.19 W/m2 to 26.84 ± 0.99 W/m2 over time. Regarding the spatial distribution of the ArUHI footprint, the analysis revealed that, for the majority of cities (86% or 179 out of 208), the ArUHI footprint ranged from 1.5 to 5.5 times that in urban areas. City sizes and economic zones yielded significant influences on the ArUHI intensity and ArUHI footprint values. Building forms were significantly positively correlated with AHF, with R2 values higher than 0.94. This study contributes to the understanding of ArUHI effects and their driving factors in China, providing valuable insights for urban climate studies and enhancing our understanding of surface urban heat island mechanisms. [ABSTRACT FROM AUTHOR]

Speech emotion recognition (SER) is not only a ubiquitous aspect of everyday communication, but also a central focus in the field of human–computer interaction. However, SER faces several challenges, including difficulties in detecting subtle emotional nuances and the complicated task of recognizing speech emotions in noisy environments. To effectively address these challenges, we introduce a Transformer-based model called MelTrans, which is designed to distill critical clues from speech data by learning core features and long-range dependencies. At the heart of our approach is a dual-stream framework. Using the Transformer architecture as its foundation, MelTrans deciphers broad dependencies within speech mel-spectrograms, facilitating a nuanced understanding of emotional cues embedded in speech signals. Comprehensive experimental evaluations on the EmoDB (92.52%) and IEMOCAP (76.54%) datasets demonstrate the effectiveness of MelTrans. These results highlight MelTrans's ability to capture critical cues and long-range dependencies in speech data, setting a new benchmark within the context of these specific datasets. These results highlight the effectiveness of the proposed model in addressing the complex challenges posed by SER tasks. [ABSTRACT FROM AUTHOR]

In this study, we prepared Mg-9Gd-2Nd-0.5Zr, referred to as alloy I, and Mg-9Gd-2Nd-1.5Zn-0.5Zr, referred to as alloy II. The effects of a long-period stacking ordered (LPSO) phase induced by Zn addition on the high-temperature mechanical properties and fracture morphology of alloy I and alloy II at different temperatures (25 °C, 200 °C, 225 °C, and 250 °C) were studied using optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). The results indicate that Mg5RE at the crystal boundary of the as-cast alloy I transformed into (MgZn)3RE (as-cast alloy II) by the addition of Zn. After solid solution treatment, the secondary phase in alloy I completely disappeared, and there were still residual secondary phases in block-like and needle-like structures in alloy II, while layered LPSO phases precipitated in the matrix. During the high-temperature tensile test, the yield and tensile strength of alloy I decreased significantly with the increase in temperature, while the elongation increased. Compared to alloy I, the yield strength of alloy II with an LPSO phase showed an increasing trend at 25 °C~200 °C and then decreased when the temperature reached around 250 °C. The thermal stability was significantly enhanced, and the elongation was also higher than that of alloy I. As the temperature increased, the fracture surface of alloy I showed increased folding, bending of scratches, and crack enlargement. However, the fracture surface of alloy II remained largely unchanged, with only minor wrinkles and cracks appearing at temperatures reaching 250 °C. [ABSTRACT FROM AUTHOR]

Yellow fever virus (YFV) infections can cause severe diseases in humans, resulting in mass casualties in Africa and the Americas each year. Secretory NS1 (sNS1) is thought to be used as a diagnostic marker of flavivirus infections, playing an essential role in the flavivirus life cycle, but little is known about the composition and structure of YFV sNS1. Here, we present that the recombinant YFV sNS1 exists in a heterogeneous mixture of oligomerizations, predominantly in the tetrameric form. The cryoEM structures show that the YFV tetramer of sNS1 is stacked by the hydrophobic interaction between β-roll domains and greasy fingers. According to the 3D variability analysis, the tetramer is in a semi-stable state that may contain multiple conformations with dynamic changes. We believe that our study provides critical insights into the oligomerization of NS1 and will aid the development of NS1-based diagnoses and therapies. [ABSTRACT FROM AUTHOR]

Sesuvium portulacastrum L. is a dicotyledonous halophyte belonging to the family Aizoaceae. Its young leaves are highly nutritious, and many ecotypes are used as leafy vegetable and medicinal crops. Additionally, due to their tolerance to soil salinity, flooding, and high temperatures, some ecotypes are used for the remediation of saline soils. As a result, there is an increasing need for a large number of disease-free S. portulacastrum propagules. This study developed an efficient protocol for the regeneration of S. portulacastrum through indirect shoot organogenesis. Leaf explants were cultured on Murashige and Skoog basal medium supplemented with different concentrations of zeatin (ZT) and indole-3-acetic acid (IAA). Callus was induced in all explants cultured with 1.5 mg/L ZT only or 1.5 mg/L ZT with 0.5 mg/L IAA. The callus was cut into small pieces and cultured on the same medium on which it was initially induced. ZT at 1.5 mg/L induced 73.7% of callus pieces to produce adventitious shoots, and the shoot numbers per callus piece were up to 20. To improve the in vitro rooting of adventitious shoots, commonly known as microshoots or microcuttings, an endophytic fungus, Cladosporium 'BF-F', was inoculated onto the rooting medium. 'BF-F' substantially enhanced rooting and plantlet growth, as the root numbers were three times more and plantlet heights were 70% greater than those without 'BF-F' inoculation. To detect the genes involved in the enhanced rooting and plantlet growth, qRT-PCR analysis was performed. Results showed that genes related to auxin responses and nitrogen uptake and metabolism were highly upregulated in 'BF-F'-inoculated plantlets. Plants inoculated with 'BF-F' grew vigorously after being transplanted into a sand–soil substrate. Thus, this study not only established an efficient protocol for the regeneration of S. portulacastrum but also developed a novel method for improving the rooting of microshoots and plantlet growth. The established propagation system could be used for producing a large number of S. portulacastrum plantlets for commercial use and also for genetic transformation. [ABSTRACT FROM AUTHOR]

Permanent magnet linear synchronous motors (PMLSMs) with stator segmented structures are widely used in the design of high-power propulsion systems. However, due to the inherent delay and segmented structure of the systems, there are parameter disturbances in the inductance and flux linkage of the motors. This makes the deadbeat predictive current control (DPCC) algorithm for a current loop less robust in the control system, leading to a decrease in control performance. Compensation methods such as compensation by observer and online estimation of parameters, are problematic to apply in practice due to the difficulty of parameter adjustment and the high complexity of the algorithm. In this paper, a robustness-improved incremental DPCC (RII-DPCC) method—which uses incremental DPCC (I-DPCC) to eliminate flux linkage parameters—is proposed. The stability of the current loop was evaluated through zero-pole analysis of the discrete transfer function. Current feedforward was introduced to improve the stability of I-DPCC. The inductance stability range of I-DPCC was increased from 0.8–1.25 times to 0–2 times the actual value, and the theoretical stability range was increased more than 4 times, effectively improving the robustness of the predictive model to flux linkage and inductance parameters. Finally, the effectiveness of the proposed method was verified through numerical simulation and experiment. [ABSTRACT FROM AUTHOR]

It is challenging to precisely measure the slow interseismic crustal-deformation rate from Synthetic Aperture Radar (SAR) data. The long-wavelength orbital errors, owing to the uncertainties in satellite orbit vectors, commonly exist in SAR interferograms, which degrade the precision of the Interferometric SAR (InSAR) products and become the main barrier to extracting interseismic tectonic deformation. In this study, we propose a novel temporal-network orbital correction method that is able to isolate the far-fault tectonic deformation from the mixed long-wavelength signals based on its spatio–temporal characteristic. The proposed approach is straightforward in methodology but could effectively separate the subtle tectonic deformation from glaring orbital errors without ancillary data. Both synthetic data and real Sentinel-1 SAR images are used to validate the reliability and effectiveness of this method. The derived InSAR velocity fields clearly present the predominant left-lateral strike-slip motions of the Tuosuo Lake segment of the Kunlun fault in western China. The fault-parallel velocity differences of 5–6 mm/yr across the fault between areas ~50 km away from the fault trace are addressed. The proposed method presents a significantly different performance from the traditional quadratic approximate method in the far field. Through the implementation of the proposed method, the root mean square error (RMSE) between the LOSGPS and our derived descending InSAR LOS (line of sight) measurements is reduced to less than one-third of the previous study, suggesting its potential to enhance the availability of InSAR technology for interseismic crustal-deformation measurement. [ABSTRACT FROM AUTHOR]

Using panel data from 30 provinces in China from 2005 to 2020, this paper uses a spatial double difference model to evaluate the policy impact of the "grain-to-feed" policy on feed grain production in pilot areas and adjacent spatial areas. Research has found that the "grain-to-feed" policy has a significant impact on the feed grain production in pilot areas and can significantly increase the feed grain production in pilot areas by about 2.71 million tons. The "grain-to-feed" policy has strengthened the positive connection between pilot areas and adjacent pilot areas, increased feed grain production, and has a significant spatial spillover effect. Robustness analysis shows that whether using different methods to measure spatial adjacency or using different standards to distribute subsidies, the "grain-to-feed" policy can significantly increase feed grain production, narrow the supply and demand gap of feed grain, and ensure feed grain security. Further analysis shows that the "grain-to-feed" policy can not only ensure the security of feed grain for the current and next periods but also promote the increase in farmers' income, which is long-term and sustainable. Compared with non-pilot areas, the "grain-to-feed" policy can mitigate the negative impact of wage–price signals on feed grain production in pilot areas. It is recommended that government departments accelerate the transformation of food security concepts, establish a "Big Food Perspective", gradually promote the pilot of the "grain-to-feed" policy nationwide, increase the subsidy amount of the "grain-to-feed" policy, increase financial support for scientific and technological research and achievement transformation in the field of feed grain, prevent the impact of economic price signal fluctuations on feed grain production, and effectively ensure the security of feed grain in China. [ABSTRACT FROM AUTHOR]

To realize accurate environment perception, which is the technological key to enabling autonomous vehicles to interact with their external environments, it is primarily necessary to solve the issues of object detection and tracking in the vehicle-movement process. Multi-sensor fusion has become an essential process in efforts to overcome the shortcomings of individual sensor types and improve the efficiency and reliability of autonomous vehicles. This paper puts forward moving object detection and tracking methods based on LiDAR—camera fusion. Operating based on the calibration of the camera and LiDAR technology, this paper uses YOLO and PointPillars network models to perform object detection based on image and point cloud data. Then, a target box intersection-over-union (IoU) matching strategy, based on center-point distance probability and the improved Dempster–Shafer (D–S) theory, is used to perform class confidence fusion to obtain the final fusion detection result. In the process of moving object tracking, the DeepSORT algorithm is improved to address the issue of identity switching resulting from dynamic objects re-emerging after occlusion. An unscented Kalman filter is utilized to accurately predict the motion state of nonlinear objects, and object motion information is added to the IoU matching module to improve the matching accuracy in the data association process. Through self-collected data verification, the performances of fusion detection and tracking are judged to be significantly better than those of a single sensor. The evaluation indexes of the improved DeepSORT algorithm are 66% for MOTA and 79% for MOTP, which are, respectively, 10% and 5% higher than those of the original DeepSORT algorithm. The improved DeepSORT algorithm effectively solves the problem of tracking instability caused by the occlusion of moving objects. [ABSTRACT FROM AUTHOR]

Traffic-sign detection and recognition (TSDR) is crucial to avoiding harm to pedestrians, especially children, from intelligent connected vehicles and has become a research hotspot. However, due to motion blurring, partial occlusion, and smaller sign sizes, pedestrian TSDR faces increasingly significant challenges. To overcome these difficulties, a CTM-YOLOv8n model is proposed based on the YOLOv8n model. With the aim of extracting spatial features more efficiently and making the network faster, the C2f Faster module is constructed to replace the C2f module in the head, which applies filters to only a few input channels while leaving the remaining ones untouched. To enhance small-sign detection, a tiny-object-detection (TOD) layer is designed and added to the first C2f layer in the backbone. Meanwhile, the seventh Conv layer, eighth C2f layer, and connected detection head are deleted to reduce the quantity of model parameters. Eventually, the original CIoU is replaced by the MPDIoU, which is better for training deep models. During experiments, the dataset is augmented, which contains the choice of categories 'w55' and 'w57' in the TT100K dataset and a collection of two types of traffic signs around the schools in Tianjin. Empirical results demonstrate the efficacy of our model, showing enhancements of 5.2% in precision, 10.8% in recall, 7.0% in F1 score, and 4.8% in mAP@0.50. However, the number of parameters is reduced to 0.89M, which is only 30% of the YOLOv8n model. Furthermore, the proposed CTM-YOLOv8n model shows superior performance when tested against other advanced TSDR models. [ABSTRACT FROM AUTHOR]

In this paper, a patch array antenna with wideband circular polarization and high gain is proposed by utilizing a hybrid metasurface (MS). A corner-cut slotted patch antenna was chosen as the source due to the possible generation of CP mode. The hybrid MS (HMS), consisting of a receiver MS (RMS) arranged in a 2 × 2 array of squared patches and a linear-to-circular polarization conversion (LCPC) MS surrounding it was then utilized as the superstrate driven by the source. The LCPC MS cell is a squared-corner-cut patch with a 45° oblique slot etched, which has the capability for wideband LCPC. The LCPC unit cell possesses wideband PC capabilities, as demonstrated by the surface current analysis and S-parameter simulations conducted using a Floquet–port setup. The LP EM wave radiated by the source antenna was initially received by the RMS, then converted to a CP wave as it passed through the LCPC MS, and ultimately propagated into space. To further enhance the LCPC properties, an improved HMS (IHMS) was then proposed with four cells cut at the corners, based on the original HMS design. To verify this design, both CMA and E-field were utilized to analyze the three MSs, indicating that the IHMS possessed a wideband LCPC capability compared to the other two MSs. The proposed antenna was then arranged in a 2 × 2 array with sequential rotation to further enhance its properties. As demonstrated by the measurements, the array antenna achieved an S11 bandwidth of 60.5%, a 3 dB AR bandwidth of 2.85 GHz, and a peak gain of 15.1 dBic, all while maintaining a low profile of only 0.09λ0. [ABSTRACT FROM AUTHOR]

As a common vegetable variety, asparagus is rich in B vitamins, vitamin A, and trace elements such as folate, selenium, iron, manganese, and zinc. With the increasing market demand, China has become the world's largest cultivated area for asparagus production and product exportation. However, traditional asparagus grading mostly relies on manual visual judgment and needs a lot of manpower input to carry out the classification operation, which cannot meet the needs of large-scale production. To address the high labor cost and labor-intensive production process resulting from the large amount of manpower input and low accuracy of existing asparagus grading devices, this study proposed an improved asparagus grading system and method based on TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) objective evaluation and SVM (support vector machine) prediction. The key structure of classification device was analyzed first, the key components were designed, and the structural parameters were determined by theoretical calculation. Through analysis of the factors affecting asparagus quality, three key attributes were determined: length, diameter, and bruises, which were used as reference attributes to conduct experimental analysis. Then, the graded control groups were set up, combining the TOPSIS principle with weighting, and a score for each asparagus sample was determined. These scores were compared with those of a graded control group to derive the grade of each asparagus, and these subsets of the dataset were used as the training set and the test set, excluding the error caused by the subjectivity of the manual judgment. Based on a comparison of the accuracies of different machine learning models, the support vector machine (SVM) was determined to be the most accurate, and four SVM methods were used to evaluate the test set: linear SVM, quadratic SVM, cubic SVM, and medium Gaussian SVM. The test results showed that the grading device was feasible for asparagus. The bruises had a large influence on asparagus quality. The training accuracy of the medium Gaussian SVM method was high (96%), whereas its test accuracy was low (86.67%). The training accuracies and test accuracy of the quadratic and cubic SVM methods were 93.34%. The quadratic SVM and cubic SVM were demonstrated to have better generalization ability than the medium Gaussian SVM method for predicting unknown grades of asparagus and meeting the operational requirements of the asparagus grading. [ABSTRACT FROM AUTHOR]

Automatic Container Code Recognition (ACCR) is critical for enhancing the efficiency of container terminals. However, existing ACCR methods frequently fail to achieve satisfactory performance in complex environments at port gates. In this paper, we propose an approach for accurate, fast, and compact container code recognition by utilizing YOLOv4 for container region localization and Deeplabv3+ for character recognition. To enhance the recognition speed and accuracy of YOLOv4 and Deeplabv3+, and to facilitate their deployment at gate entrances, we introduce several improvements. First, we optimize the feature-extraction process of YOLOv4 and Deeplabv3+ to reduce their computational complexity. Second, we enhance the multi-scale recognition and loss functions of YOLOv4 to improve the accuracy and speed of container region localization. Furthermore, we adjust the dilated convolution rates of the ASPP module in Deeplabv3+. Finally, we replace two upsampling structures in the decoder of Deeplabv3+ with transposed convolution upsampling and sub-pixel convolution upsampling. Experimental results on our custom dataset demonstrate that our proposed method, C-YOLOv4, achieves a container region localization accuracy of 99.76% at a speed of 56.7 frames per second (FPS), while C-Deeplabv3+ achieves an average pixel classification accuracy (MPA) of 99.88% and an FPS of 11.4. The overall recognition success rate and recognition speed of our approach are 99.51% and 2.3 ms per frame, respectively. Moreover, C-YOLOv4 and C-Deeplabv3+ outperform existing methods in complex scenarios. [ABSTRACT FROM AUTHOR]

Acidified CO2 fracturing is a viable method for increasing production in deep, tight sandstone reservoirs. However, the potential mechanism of changes in pore structure and mechanical properties of sandstone under acidified CO2 supercritical composite is not clear. Understanding this mechanism is important for the study of crack initiation and extension in tight sandstone reservoirs. This study utilizes sandstone samples from the Xujiahe Formation reservoir in Rongchang District as experimental specimens. The primary focus is to analyze the changes in pore structure and mechanical properties of these samples after acidification–supercritical CO2 composite action. Nuclear magnetic resonance (NMR) and uniaxial compression tests are employed as the main investigative techniques. The results show that there was a physicochemical synergy between the acidification–supercritical CO2 composite effect; the crack initial stress, damage stress, and peak stress of the sandstone after 16 MPa supercritical CO2 acidification treatment were reduced by 20%, 49.5%, and 49.8%, respectively; the crack volumetric strain accelerated and the sandstone evolved from brittle to ductile damage; and the larger pore space and microcracks of the sandstone increased significantly after the treatment, which can be attributed to the gradual dissolution of intergranular cement leading to the formation of new pores connected to the existing pore network. The change mechanism of sandstone after acidification–supercritical CO2 compound treatment is also proposed. [ABSTRACT FROM AUTHOR]

Simple Summary: This study investigates the functional adaptation and underlying molecular mechanisms of hemoglobins (Hbs) in the two species of Eremias lizards dwelling on the Qinghai-Tibet Plateau. By measuring O2 equilibrium curves of purified Hbs at different pH and temperature in the absence and presence of ATP and/or Cl−, the study found that the high-altitude populations of the two species of Eremias lizards exhibit convergent high Hb-O2 affinity compared to the respective lowland counterparts while demonstrating distinct ATP-mediated allosteric regulation. Hbs of the highland E. argus showed high ATP sensitivity and ATP-dependent strong Bohr effect compared to E. multiocellata. The underlying mechanisms of these functional variations may be attributed to the varying β2/β1 globin ratios, combined with substitutions on the β2-type globin, as suggested by Hb isoform identification and structural analysis of tetrameric Hbs. In addition, Hbs of these Eremias lizards have similarly low temperature sensitivities and relatively high Bohr effects at lower temperatures, which could minimize the impact of temperature fluctuations on Hb-O2 affinity and facilitate the release of O2 in the cold extremities at low temperatures. The functional adaptation and underlying molecular mechanisms of hemoglobins (Hbs) have primarily concentrated on mammals and birds, with few reports on reptiles. This study aimed to investigate the convergent and species-specific high-altitude adaptation mechanisms of Hbs in two Eremias lizards from the Qinghai-Tibet Plateau. The Hbs of high-altitude E. argus and E. multiocellata were characterized by significantly high overall and intrinsic Hb-O2 affinity compared to their low-altitude populations. Despite the similarly low Cl− sensitivities, the Hbs of high-altitude E. argus exhibited higher ATP sensitivity and ATP-dependent Bohr effects than that of E. multiocellata, which could facilitate O2 unloading in respiring tissues. Eremias lizards Hbs exhibited similarly low temperature sensitivities and relatively high Bohr effects at lower temperatures, which could help to stably deliver and release O2 to cold extremities at low temperatures. The oxygenation properties of Hbs in high-altitude populations might be attributed to varying ratios of β2/β1 globin and substitutions on the β2-type globin. Notably, the Asn12Ala in lowland E. argus could cause localized destabilization of the E-helix in the tetrameric Hb by elimination of hydrogen bonds, thereby resulting in its lowest O2 affinity. This study provides a valuable reference for the high-altitude adaptation mechanisms of hemoglobins in reptiles. [ABSTRACT FROM AUTHOR]

Liquid hydrogen is one of the high-quality energy carriers, but a large leak of liquid hydrogen can pose significant safety risks. Understanding its diffusion law after accidental leakage is an important issue for the safe utilization of hydrogen energy. In this paper, a series of open-space large-volume liquid hydrogen release experiments are performed to observe the evolution of visible clouds during the release, and an array of hydrogen concentration sensors is set up to monitor the fluctuation in hydrogen concentration at different locations. Based on the experimental conditions, the diffusion of hydrogen clouds in the atmosphere under different release hole diameters and different ground materials is compared. The results show that with the release of liquid hydrogen, the white visible cloud formed by air condensation or solidification is generated rapidly and spread widely, and the visible cloud is most obvious near the ground. With the termination of liquid hydrogen release, solid air is deposited on the ground, and the visible clouds gradually shrink from the far field to the release source. Hydrogen concentration fluctuations in the far field in the case of the cobblestone ground are more dependent on spontaneous diffusion by the hydrogen concentration gradient. In addition, compared with the concrete ground, the cobblestone ground has greater resistance to liquid hydrogen extension; the diffusion of hydrogen clouds to the far field lags. The rapid increase stage of hydrogen concentration at N8 in Test 7 lags about 3 s behind N12 in Test 6, N3 lags about 7.5 s behind N1, and N16 lags about 8.25 s behind N14. The near-source space is prone to high-concentration hydrogen clouds. The duration of the high-concentration hydrogen cloud at N12 is about 15 s, which is twice as long as the duration at N8, increasing the safety risk of the near-source space. [ABSTRACT FROM AUTHOR]

Biodegradable vascular stents (BVS) are deemed as great potential alternatives for overcoming the inherent limitations of permanent metallic stents in the treatment of coronary artery diseases. The current study aimed to comprehensively compare the mechanical behaviors of four poly(lactic acid) (PLA) BVS designs with varying geometries via numerical methods and to clarify the optimal BVS selection. Four PLA BVS (i.e., Absorb, DESolve, Igaki-Tamai, and Fantom) were first constructed. A degradation model was refined by simply including the fatigue effect induced by pulsatile blood pressures, and an explicit solver was employed to simulate the crimping and degradation behaviors of the four PLA BVS. The degradation dynamics here were characterized by four indices. The results indicated that the stent designs affected crimping and degradation behaviors. Compared to the other three stents, the DESolve stent had the greatest radial stiffness in the crimping simulation and the best diameter maintenance ability despite its faster degradation; moreover, the stent was considered to perform better according to a pilot scoring system. The current work provides a theoretical method for studying and understanding the degradation dynamics of the PLA BVS, and it could be helpful for the design of next-generation BVS. [ABSTRACT FROM AUTHOR]

(1) Background: Diabetes is a common metabolic disease that seriously endangers human health. In the present study, we investigated the therapeutic effects of the active ingredient Eleutheroside B (EB) from the traditional Chinese medicine Eleutheroside on diabetes mellitus in a zebrafish model. Concomitant hepatic injury was also analysed, along with the study of possible molecular mechanisms using metabolomics technology. This work should provide some theoretical references for future experimental studies. (2) Methods: A zebrafish diabetes model was constructed by soaking in a 1.75% glucose solution and feeding a high-fat diet. The intervention drug groups were metformin (100 μg∙mL−1) and EB (50, 100, and 150 μg∙mL−1) via water-soluble exposure for 30 days. Glucose, TG, TC, LDL-C, and HDL-C were evaluated in different treatment groups. GLUT4 protein expression was also evaluated in each group, and liver injury was observed by HE staining. Metabolomics techniques were used to investigate the mechanism by which EB regulates endogenous markers and metabolic pathways during the development of diabetes. (3) Results: All EB treatment groups in diabetic zebrafish showed significantly reduced body mass index (BMI) and improved blood glucose and lipid profiles. EB was found to upregulate GLUT4 protein expression and ameliorate the liver injury caused by diabetes. Metabolomics studies showed that EB causes changes in the metabolic profile of diabetic zebrafish. These were related to the regulation of purine metabolism, cytochrome P450, caffeine metabolism, arginine and proline metabolism, the mTOR signalling pathway, insulin resistance, and glycerophospholipid metabolism. (4) Conclusions: EB has a hypoglycaemic effect in diabetic zebrafish as well as significantly improving disorders of glycolipid metabolism. The mechanism of action of EB may involve regulation of the mTOR signalling pathway, purine metabolism, caffeine metabolism, and glycerophospholipid metabolism. [ABSTRACT FROM AUTHOR]

Recently, the application of cryogenic hoses in the field of cryogenic media has become a hot topic, especially in the industry of offshore liquefied natural gas and aerospace field. However, the structure of cryogenic hoses is complex, and reasonable structural properties are required due to the harsh working conditions. There is still plenty of scope for further development to improve the performance in all aspects. In this paper, the current development status of cryogenic hoses for liquefied natural gas (LNG) transportation is reviewed first, including the types, manufacturers, structural forms, performance, and key technical challenges. And then, the recent progress and prospect of cryogenic hoses for cryogenic liquid transportation (such as LNG and liquid oxygen) are summarized, including structure design, low-temperature resistant polymers, liquid oxygen compatible polymers, and leakage monitoring technologies. This paper provides a comprehensive overview of the research development and application of cryogenic hoses. Moreover, future research directions have been proposed to facilitate its practical applications in aerospace. [ABSTRACT FROM AUTHOR]

The census and management of hazard-bearing entities, along with the integrity of data quality, form crucial foundations for disaster risk assessment and zoning. By addressing the challenge of feature confusion, prevalent in single remotely sensed image recognition methods, this paper introduces a novel method, Spatially Constrained Deep Learning (SCDL), that combines deep learning with spatial constraint strategies for the extraction of disaster-bearing bodies, focusing on dams as a typical example. The methodology involves the creation of a dam dataset using a database of dams, followed by the training of YOLOv5, Varifocal Net, Faster R-CNN, and Cascade R-CNN models. These models are trained separately, and highly confidential dam location information is extracted through parameter thresholding. Furthermore, three spatial constraint strategies are employed to mitigate the impact of other factors, particularly confusing features, in the background region. To assess the method's applicability and efficiency, Qinghai Province serves as the experimental area, with dam images from the Google Earth Pro database used as validation samples. The experimental results demonstrate that the recognition accuracy of SCDL reaches 94.73%, effectively addressing interference from background factors. Notably, the proposed method identifies six dams not recorded in the GOODD database, while also detecting six dams in the database that were previously unrecorded. Additionally, four dams misdirected in the database are corrected, contributing to the enhancement and supplementation of the global dam geo-reference database and providing robust support for disaster risk assessment. In conclusion, leveraging open geographic data products, the comprehensive framework presented in this paper, encompassing deep learning target detection technology and spatial constraint strategies, enables more efficient and accurate intelligent retrieval of disaster-bearing bodies, specifically dams. The findings offer valuable insights and inspiration for future advancements in related fields. [ABSTRACT FROM AUTHOR]

This paper presents a practical and straightforward control strategy for robotic manipulators with unknown dynamics to achieve prescribed tracking performance, which has implementation advantages compared with previous work. In particular, an improved extended state observer (ESO) synthesized with a continuously differentiable friction model and time-varying gains is presented to estimate system states and unknown dynamics. This ESO outperforms the conventional ones in dealing with friction mutations while avoiding peaking estimation values in the initial stage. By combining the prescribed performance function and the proposed ESO, an independent joint control scheme is proposed for a robotic manipulator to keep the tracking error within a predefined performance bound based only on position measurements. The effectiveness of the proposed control scheme is verified by comparative simulation and experimental results on a six-degrees-of-freedom robotic manipulator with active disturbance rejection controller and PID methods. [ABSTRACT FROM AUTHOR]

Featured Application: The present study can be applied to the study of the influence of a Hall thruster plume on the spacecraft surface. This article aims to conduct an in-depth investigation into the environmental impact of Hall thruster plumes on spacecraft surface charging. The non-uniform plasma plume generated by Hall thrusters may trigger charging and discharging effects, making the assessment of surface charging risks crucial. Through numerical simulations using SPIS system, this study evaluates the surface charging characteristics of a complex spacecraft in orbit, simulating the effects of turning on and off the thrusters, as well as varying distances between the thrusters and the spacecraft. The simulation demonstrates that turning on the thrusters significantly affects spacecraft charging, reducing the potential difference between spacecraft surfaces from 3740 V to 19.2 V, effectively alleviating electrostatic discharge on the spacecraft surface. The closer the thruster is to the spacecraft, the more CEX ions are collected on the surface, influenced by the beam ions, resulting in a surface potential change of 1.3 V, with minor effects on surface potential but contributing to increased deposition contamination on the spacecraft surface. [ABSTRACT FROM AUTHOR]

Regeneration has been considered as an ideal way for the post-treatment of waste FCC catalyst (ECat). In this work, the degeneration mechanism of ECat was firstly researched and attributed to the increasing of strong acid sites accessibility of ECat in contrast with fresh FCC catalyst by adsorption FTIR. Based on the proposed degeneration mechanism, ECat was successfully regenerated through suitable weakening for strong acid sites by boron modification. Characterization and evaluation results suggested that, the strong acid sites of regenerated ECat (R-ECat) were apparently decreased by boron modification which had significantly improve the heavy oil catalytic cracking performance of R-ECat. Because of the excellent performance, R-ECat in this work could successfully substitute for partial fresh FCC catalyst in FCC unit, which would provide a practicable way for the reutilization of ECat. [ABSTRACT FROM AUTHOR]

Intelligentization is the development trend of the future automobile industry. Intelligentization requires that the dynamic control of the vehicle can complete the trajectory tracking according to the trajectory output of the decision planning the driving state of the vehicle and ensure the driving safety and stability of the vehicle. However, trajectory limit planning and harsh road conditions caused by emergencies will increase the difficulty of trajectory tracking and stability control of unmanned vehicles. In view of the above problems, this paper studies the trajectory tracking and stability control of distributed drive unmanned vehicles. This paper applies a hierarchical control framework. Firstly, in the upper controller, an adaptive prediction time linear quadratic regulator (APT LQR) path following algorithm is proposed to acquire the desired front-wheel-steering angle considering the dynamic stability performance of the tires. The lateral stability of the DDAUV is determined based on the phase plane, and the sliding surface, in the improved sliding mode control (SMC), is further dynamically adjusted to obtain the desired additional yaw moment for coordinating the path following and lateral stability. Then, in the lower controller, considering the slip and the working load of four tires, a comprehensive cost function is established to reasonably distribute the driving torque of four in-wheel motors (IWMs) for producing the desired additional yaw moment. Finally, the proposed control algorithm is verified by the hardware-in-the-loop (HIL) experiment platform. The results show the path following and lateral stability can be coordinated effectively under different driving conditions. [ABSTRACT FROM AUTHOR]

Cellulose crystallinity is a crucial factor influencing stem strength and, consequently, wheat lodging. However, the genetic dissection of cellulose crystallinity is less reported due to the difficulty of its measurement. In this study, VIS/NIR spectra and cellulose crystallinity were measured for a wheat accession panel with diverse genetic backgrounds. We developed a reliable VIS/NIR model for cellulose crystallinity with a high determination coefficient (R2) (0.95) and residual prediction deviation (RPD) (4.04), enabling the rapid screening of wheat samples. A GWAS of the cellulose crystallinity in 326 wheat accessions revealed 14 significant SNPs and 13 QTLs. Two candidate genes, TraesCS4B03G0029800 and TraesCS5B03G1085500, were identified. In summary, this study establishes an efficient method for the measurement of cellulose crystallinity in wheat stems and provides a genetic basis for enhancing lodging resistance in wheat. [ABSTRACT FROM AUTHOR]

China possesses abundant wild germplasm resources and a wide range of cultivated strains of Stropharia rugosoannulata. However, issues such as genetic diversity and unclear genetic relationships have had an impact on the classification and preservation of germplasm resources, the breeding of new varieties, and the promotion of superior strains. There is an urgent need for genetic diversity analysis and assessment of germplasm resources. In this study, we conducted whole-genome resequencing of 50 cultivated and wild strains collected from various regions across the country. After applying a series of filtering parameters, we obtained 888,536 high-quality Single Nucleotide Polymorphism (SNP) markers. Using these SNP markers, we performed principal component analysis, population structure analysis, and phylogenetic clusters analysis on the 50 strains. Most cultivated strains exhibited high genetic similarity, while significant genetic diversity was observed among wild strains. Based on factors such as marker distribution throughout the entire genome and marker quality, we selected 358 core SNP markers to construct SNP fingerprints. Two-dimensional barcodes were generated for each strain to enable specific identification. Additionally, the mycelial growth rate of strains was evaluated on Potato Dextrose Agar (PDA) and substrate culture media. We also assessed their lignin degradation capability using guaiacol agar plates assay. It was observed that the mycelial growth rate on PDA and substrate culture medium exhibited a significant correlation with the diameter of the mycelial colony on guaiacol agar medium. Additionally, the correlation between the mycelial growth rate on the substrate medium and that on the guaiacol agar plate was stronger than that on PDA medium. This study provided molecular-level identification and assessment of germplasm resources. It clarified the genetic relationships among strains and the characteristics of mycelium growth-related agronomic traits of each strain. This research contributed to the enrichment and development of utilizable germplasm resources and breeding materials for S. rugosoannulata, offering a scientific basis for further research. [ABSTRACT FROM AUTHOR]

The physical properties of Ti6Al4V powder affect the spreadability of the powder and uniformity of the powder bed, which had a great impact on the performance of built parts made by powder bed fusion technology. Micro-computed tomography is a well-established technique used to analyze the non-destructivity of the objects' interior. Ti6Al4V powders were scanned with micro-CT to show the internal and external information of all the particles. The morphology, particle size distribution, hollow particle ratio, density, inclusion, and specific surface area of the powder samples were quantitatively characterized, and the relationship of flowability with these physical properties was analyzed in this work. The research results of this article showed that micro-CT is an effective way to characterize these items, and can be developed as a standard method of powder physical properties in the future. [ABSTRACT FROM AUTHOR]

Advancements in astronomical telescopes and cutting-edge technologies, including deep ultraviolet (DUV) and extreme ultraviolet (EUV) lithography, have escalated demands and imposed stringent surface quality requirements on optical system components. Achieving near-ideal optical components requires ultra-smooth surfaces with sub-nanometer roughness, no sub-surface damage, minimal surface defects, low residual stresses, and intact lattice integrity. This necessity has driven the rapid development and diversification of ultra-smooth surface fabrication technologies. This paper summarizes recent advances in ultra-smooth surface processing technologies, categorized by their material removal mechanisms. A subsequent comparative analysis evaluates the roughness and polishing characteristics of ultra-smooth surfaces processed on various materials, including fused silica, monocrystalline silicon, silicon carbide, and sapphire. To maximize each process's advantages and achieve higher-quality surfaces, the paper discusses tailored processing methods and iterations for different materials. Finally, the paper anticipates future development trends in response to current challenges in ultra-smooth surface processing technology, providing a systematic reference for the study of the production of large-sized freeform surfaces. [ABSTRACT FROM AUTHOR]

In this work, squeeze casting experiments of flywheel housing components with a large wall thickness difference and a complex shape were carried out with AlSi9Mg aluminum alloy. The defects, microstructures, and mechanical properties under different process parameters were investigated. Furthermore, the local pressurization process was applied to the thick-walled positions to force-feed the cast defects. The mechanical properties and microstructures at these positions were analyzed. The results showed that the surface quality of formed components was good and that local pressurization could effectively reduce the shrinkage cavity and shrinkage porosity in thick walls, but the scope and effect of forced feeding were limited. The optimum process parameters were a pouring temperature of 650 °C, a specific pressure of 48 MPa, a mold temperature of 220 °C, a local pressurization of 800 MPa, and pressure delay times of 15 s (side A) and 17 s (side B). The ultimate tensile strength, yield strength, and elongation of the formed component under validation experiments of the optimum process parameters were 201 MPa, 103 MPa, and 5.1%. Meanwhile, the fine grains of primary α-Al were mainly rosette and equiaxed grains, and the average grain size was about 40 μm. The microstructure of the eutectic silicon was acicular and was prone to segregation under pressure. According to profile morphology, the positions after pressurization were divided into a deformation zone, a direct action zone, and an indirect action zone. The coexistence of as-cast and plastic deformation microstructures was observed. The effect of local pressurization mainly involved a change in the solidification process, plastic deformation, and forced feeding. [ABSTRACT FROM AUTHOR]