Three-dimensional thermohaline structure estimation derived from HY-2 satellite data over the Maritime Silk Road and its applications

Estimated ocean subsurface fields derived from satellite observations provide potential data sources for operational marine environmental monitoring and prediction systems.This study employs a statistic regression reconstruction method,in combination with domestic autonomous sea surface height and sea surface temperature observations from the Haiyang-2(HY-2)satellite fusion data,to establish an operational quasi-realtime three-dimensional(3D)temperature and salinity products over the Maritime Silk Road.These products feature a daily temporal resolution and a spatial resolution of 0.25°×0.25°and exhibit stability and continuity.We have demonstrated the accuracy of the reconstructed thermohaline fields in capturing the 3D thermohaline variations through comprehensive statistical evaluations,after comparing them against Argo observations and ocean analysis data from 2022.The results illustrate that the reconstructed fields effectively represent seasonal variations in oceanic subsurface structures,along with structural changes resulting from mesoscale processes,and the upper ocean’s responses to tropical cyclones.Furthermore,the incorporation of HY-2 satellite observations notably enhances the accuracy of temperature and salinity reconstructions in the Northwest Pacific Ocean and marginally improves salinity reconstruction accuracy in the North Indian Ocean when compared to the World Ocean Atlas 2018 monthly climatology thermohaline fields.As a result,the reconstructed product holds promise for providing quasi-real-time 3D temperature and salinity field information to facilitate fast decisionmaking during emergencies,and also offers foundational thermohaline fields for operational ocean reanalysis and forecasting systems.These contributions enhance the safety and stability of ocean subsurface activities and navigation.

Aerial Silk Road Soars The“Silk Road in the Air”promoted by China Eastern Airlines will reach around the world to bring people in BRI partner countries even closer together

Two thousand years ago,the Silk Road connecting Xi’an to Rome was a long journey that took more than a year.Today,China Eastern Airlines makes the journey in just over 10 hours with the world’s most advanced wide-body airliner.The power of civil aviation has made the Silk Road more convenient than ever before.Over the last decade of the Belt and Road Initiative(BRI),the“Aerial Silk Road”has connected more and more destinations around the world.

基于差分隐私的路网环境skyline查询

路网中的skyline查询在智慧交通、兴趣点发现和位置服务等领域具有重要的应用价值,但存在查询效率较低、未考虑查询结果的隐私性等问题。有鉴于此,文中提出了一种基于差分隐私的路网环境下skyline查询方法。首先,针对路网环境下的初始数据集数据量大和数据复杂的特点,对数据集进行预处理,利用基于距离属性划分的skyline层和路网Voronoi图的性质提出了3个剪枝规则,基于剪枝规则给出了路网环境下的数据集剪枝算法,从而有效地过滤掉大量冗余数据;其次,针对过滤后的数据集,利用网格索引的存储方式来节省存储空间,并设计了基于网格索引的skyline扩展树,基于扩展树和相应的剪枝规则提出了查询全局候选skyline点集的算法;最后,针对查询结果集,利用差分隐私预算分配模型来分配隐私预算,并基于信息散度进行结果集发布,有效提高了数据信息的隐私性。实验结果表明:所提出的查询方法的准确率在99%以上;其在数据集规模较大情况下的查询效率相较于传统skyline查询方法提升10%以上;在总差分隐私预算为0.01、0.10、0.50和1.00时,所提出的隐私预算分配方法的相对误差均低于等差分配和等比分配方法。

Research on Human-Vehicle-Road Friendliness Based on Improved SH-GH-ADD Control

The hub-driven virtual rail train is a novel urban transportation system that amalgamates the benefits of modern trams and buses.However,this system is plagued by issues such as decreased ride comfort and severe deformation of urban roads due to the increase in sprung mass and long-term rolling at the same position.To address these concerns and improve the human-vehicle-road friendliness of the virtual rail train,we propose an Improved Sky-Ground Hook and Acceleration-Driven Damper control(Improved SH-GH-ADD control)strategy for the semi-active suspension system.This control monitors the vibration acceleration signal of the unsprung mass in real-time and selects the mixed Sky-Hook and Acceleration-Driven Damper(SH-ADD)control or the mixed Ground-Hook and Acceleration-Driven Damper(GH-ADD)control based on the positive and negative values of the vibration acceleration of the unsprung mass.The Improved SH-GH-ADD control combines the advantages of SH-ADD control and GH-ADD control to achieve control of the sprung mass and unsprung mass in the full fre-quency band.Finally,through simulation and comparative analysis with traditional SH-ADD,GH-ADD,and mixed SH-GH control,we demonstrate the exceptional performance of the proposed algorithm.

Experimental,Numerical,and Analytical Studies on the Bending of Mechanically Lined Pipe

Mechanically lined pipe(MLP)is often used for offshore oil and gas transport because of its low cost and corrosion resistance.During installation and operation,the pipe may undergo severe bending deformation,which causes the liner to separate from the outer pipe and buckles,affecting the stability of the whole line.In this paper,the buckling response of MLP subjected to bending is investigated to clarify its bending characteristics by employing both experiments,numerical simulation,as theoretical methods.Two types of MLPs were manufactured with GB 45 carbon steel(SLP)and Al 6061(ALP)used as the outer pipe material,respectively.The hydraulic expansion and bending experiments of small-scale MLPs are conducted.In addition to the ovalized shape of the cross-section for the SLP specimens,the copper liner was found to wrinkle on the compressive side.In contrast,the liner of ALP remains intact without developing any wrinkling and collapse mode.In addition,a dedicated numerical framework and theoretical models were also established.It was found both the manufacturing and bending responses of the MLP can be well reproduced,and the predicted maximum moment and critical curvatures are in good agreement with the experimental results.

基于ROAD的租车订购系统业务流程建模

基于业务架构为中心的企业架构开发思路,采用开放组架构框架(TOGAF)业务架构ACF元模型的划分,提出了一种ROAD架构迭代建模方法。针对目前ROAD元架构中业务活动模型采用IDEF0的活动模型导致的面向场景业务能力的不足,文中通过使用BPMN模型来覆盖IDEF0的活动建模,避免在描述复杂的业务过程时可能存在的局限性,并且更好地捕捉和表示所有的细节和关系,不会使得模型过于抽象。从而实现面向场景的系统建模和管理,提高业务架构设计的效率和精度。最后,文章中以旅游出行租车订购系统为例的方法,采用ROAD元架构方法建立场景化业务架构模型组,并对其进行讨论和改进,为现有架构体系提供一种面向场景的扩展思路。

Contributions of Rotation,Expansion and Line Broadening to the Morphology and Kinematics of the Inner CSE of Oxygen-rich AGB Star R Hya

We use archival ALMA observations of the CO(2-1)and SiO(5-4)molecular line emissions of AGB star R Hya to illustrate the relative contributions of rotation,expansion and line broadening to the morphology and kinematics of the circumstellar envelope(CSE)within some~70 au(~0."5)from the centre of the star.We give evidence for rotation and important line broadening to dominate the inner region,within~14 au(~100 mas)from the centre of the star.The former is about an axis that projects a few degrees west of north and has a projected rotation velocity of a few km s^(-1).The latter occurs within some 7-14 au(50-100 mas)from the centre of the star,with the line width reaching two to three times its value outside this region.We suggest that it is caused by shocks induced by stellar pulsations and convective cell granulation.We show the importance of properly accounting for the observed line broadening when discussing rotation and evaluating the radial dependence of the rotation velocity.

A Miniaturized Broadband Wilkinson Power Divider Using Micro-Strip Branch Lines

A miniaturized broadband Wilkinson power divider is proposed. Micro-strip branch lines are introduced to replace multiple resistors used in multi-stage Wilkinson power dividers to increase the bandwidth of single-stage Wilkinson power dividers. To demonstrate its performance, an improved single-stage Wilkinson power divider with four micro-strip branch lines was designed. Simulated results show that the insert loss is better than 3.2 dB, the input return loss, output return loss, and isolation are better than 15 dB respectively, across a 76% bandwidth from 18 to 40 GHz. .

3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.

Automation in road distress detection,diagnosis and treatment

Road transportation plays a crucial role in society and daily life,as the functioning and durability of roads can significantly impact a nation's economic development.In the whole life cycle of the road,the emergence of disease is unavoidable,so it is necessary to adopt relevant technical means to deal with the disease.This study comprehensively reviews the advancements in computer vision,artificial intelligence,and mobile robotics in the road domain and examines their progress and applications in road detection,diagnosis,and treatment,especially asphalt roads.Specifically,it analyzes the research progress in detecting and diagnosing surface and internal road distress and related techniques and algorithms are compared.In addition,also introduces various road gover-nance technologies,including automated repairs,intelligent construction,and path planning for crack sealing.Despite their proven effectiveness in detecting road distress,analyzing diagnoses,and planning maintenance,these technologies still confront challenges in data collection,parameter optimization,model portability,system accuracy,robustness,and real-time performance.Consequently,the integration of multidisciplinary technologies is imperative to enable the development of an integrated approach that includes road detection,diagnosis,and treatment.This paper addresses the challenges of precise defect detection,condition assessment,and unmanned construction.At the same time,the efficiency of labor liberation and road maintenance is achieved,and the automation level of the road engineering industry is improved.

Derivative Spectroscopy and its Application at Detecting the Weak Emission/Absorption Lines

The development of spectroscopic survey telescopes like Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST),Apache Point Observatory Galactic Evolution Experiment and Sloan Digital Sky Survey has opened up unprecedented opportunities for stellar classification.Specific types of stars,such as early-type emission-line stars and those with stellar winds,can be distinguished by the profiles of their spectral lines.In this paper,we introduce a method based on derivative spectroscopy(DS)designed to detect signals within complex backgrounds and provide a preliminary estimation of curve profiles.This method exhibits a unique advantage in identifying weak signals and unusual spectral line profiles when compared to other popular line detection methods.We validated our approach using synthesis spectra,demonstrating that DS can detect emission signals three times fainter than Gaussian fitting.Furthermore,we applied our method to 579,680 co-added spectra from LAMOST Medium-Resolution Spectroscopic Survey,identifying 16,629 spectra with emission peaks around the Hαline from 10,963 stars.These spectra were classified into three distinct morphological groups,resulting in nine subclasses as follows.(1)Emission peak above the pseudo-continuum line(single peak,double peaks,emission peak situated within an absorption line,P Cygni profile,Inverse P Cygni profile);(2)Emission peak below the pseudo-continuum line(sharp emission peak,double absorption peaks,emission peak shifted to one side of the absorption line);(3)Emission peak between the pseudo-continuum line.

Local failure mechanism of sand-blocking fence in latticed dune along desert roads

The latticed dunes in the Tengger Desert are widely distributed,and the sand-blocking fence placed here are highly susceptible to local failure due to complex wind-sand activities,posing a serious threat to the safe operation of the highway.To explore the local failure mechanism of sand-blocking fence in the latticed dune area,the local failure of sand-blocking fence in the latticed dune areas along the Wuhai-Maqin Highway in China was observed.Taking the first main ridge of the latticed dune as the placement location,the structure of the wind-sand flow field of sand-blocking fence placed at top,the bottom and the middle of windward slope was analyzed by Computational Fluid Dynamics(CFD).The results show that when placed at top of the first main ridge,the wind speed near the sand-blocking fence is the highest,up to 15.23 m/s.Therefore,the wind load strength on the sand barrier is correspondingly larger,up to 232.61 N∙m-2.As the strength of material continues to decrease,the nylon net is prone to breakage.The roots of the angle steel posts are susceptible to hollowing by vortex action,which can cause sand-blocking fence to fall over in strong wind conditions.When placed at the bottom of windward slope,wind speed drop near sand-blocking fence is greatest,with the decrease of 12.48-14.32 m/s compared to the original wind speed.This is highly likely to lead to large-scale deposition of sand particles and burial of the sand-blocking fence.When placed in the middle of windward slope,sand-blocking fence is subjected to less wind load strength(168.61N∙m-2)and sand particles are mostly deposited at the bottom of windward slope,with only a small amount of sand accumulating at the root of sand-blocking fence.Based on field observations and numerical modelling results,when the sand-blocking fence is placed in latticed dune area,it should be placed in the middle of the windward slope of the first main ridge as a matter of priority.Besides the sand-blocking fence should be placed at the top of the first main ridge,and sand fixing measures should be added.

Petrology of Spinel-Lherzolite Xenoliths from Mazéléand Others Northen Xenoliths Localities of Cameroon Volcanic Line: Exchange Reactions and Equilibrium State

The alkaline volcanism of the Cameroon Volcanic Line in its northern domain has raised many fresh enclaves of peridotites. The samples selected come from five (05) different localities (Liri, in the plateau of Kapsiki, Mazélé in the NE of Ngaoundéré, Tello and Ganguiré in the SE of Ngaoundéré and Likok, locality located in the west of Ngaoundé). The peridotite enclaves of the above localities show restricted mineralogical variation. Most are four-phase spinel-lherzolites, indicating that this is the main lithology that forms the lithospheric mantle below the shallow zone. No traces of garnet or primary plagioclase were detected, which strongly limits the depth range from which the rock fragments were sampled. The textures and the wide equilibrium temperatures (884˚C - 1115˚C) indicate also entrainment of lherzolite xenoliths from shallow depths within the lithosphere and the presence of mantle diapirism. The exchange reactions and equilibrium state established in this work make it possible to characterize the chemical composition of the upper mantle of each region and test the equilibrium state of the phases between them. Variations of major oxides and incompatible elemental concentrations in clinopyroxene indicate a primary control by partial melting. The absence of typical “metasomatic” minerals, low equilibration temperatures and enriched LREE patterns indicate that the upper mantle below septentrional crust of Cameroun underwent an event of cryptic metasomatic enrichment prior to partial melting. The distinctive chemical features, LREE enrichment, strong U, Ce and Pr, depletion relative to Ba, Nb, La, Pb, and T, fractionation of Zr and Hf and therefore ligh high Zr/Hf ratio, low La/Yb, Nb/La and Ti/Eu are all results of interaction of refractory peridotite residues with carbonatite melts.

ConvNeXt-UperNet-Based Deep Learning Model for Road Extraction from High-Resolution Remote Sensing Images

When existing deep learning models are used for road extraction tasks from high-resolution images,they are easily affected by noise factors such as tree and building occlusion and complex backgrounds,resulting in incomplete road extraction and low accuracy.We propose the introduction of spatial and channel attention modules to the convolutional neural network ConvNeXt.Then,ConvNeXt is used as the backbone network,which cooperates with the perceptual analysis network UPerNet,retains the detection head of the semantic segmentation,and builds a new model ConvNeXt-UPerNet to suppress noise interference.Training on the open-source DeepGlobe and CHN6-CUG datasets and introducing the DiceLoss on the basis of CrossEntropyLoss solves the problem of positive and negative sample imbalance.Experimental results show that the new network model can achieve the following performance on the DeepGlobe dataset:79.40%for precision(Pre),97.93% for accuracy(Acc),69.28% for intersection over union(IoU),and 83.56% for mean intersection over union(MIoU).On the CHN6-CUG dataset,the model achieves the respective values of 78.17%for Pre,97.63%for Acc,65.4% for IoU,and 81.46% for MIoU.Compared with other network models,the fused ConvNeXt-UPerNet model can extract road information better when faced with the influence of noise contained in high-resolution remote sensing images.It also achieves multiscale image feature information with unified perception,ultimately improving the generalization ability of deep learning technology in extracting complex roads from high-resolution remote sensing images.

Evaluation of red soil-bentonite mixtures for compacted clay liners

Compacted clay liners are an integral part of the waste landfills,which are provided to contain the leachate within the landfills and protect the surrounding environment.Generally,locally available natural soils are used for the construction of compacted clay liners if they satisfy the design criteria.However,not all soils in their natural state satisfy all the design criteria for the liner materials.Thus,there is a definite need to modify the locally available natural soils by blending with bentonite to meet the required design criteria for the liners.In view of this,the present study evaluates the suitability of an Indian red soil enhanced with bentonite as a liner material.To achieve this,a series of experiments were carried out using locally available red soil and bentonite.First,the suitability of the red soil was evaluated as a liner material.The experimental results showed that the red soil met all the selection criteria stipulated by the Environmental Protection Agencies(EPAs)for the liners except the hydraulic conductivity criterion.Therefore,the red soil was mixed with bentonite contents of 10%,20%and 30%,and the red soil-bentonite mixtures were evaluated for their suitability for liners in their compacted state.Further,as the liners in the arid and semi-arid regions are subjected to moisture variations due to seasonal moisture fluctuations and other factors,the red soil-bentonite mixtures were subjected to wetdry cycles,and their suitability was evaluated after wet-dry cycles.The experimental results revealed that all the red soil-bentonite mixtures met the stipulated EPA criteria for the liners in the as-compacted state.However,the red soil-bentonite mixtures with 20%and 30%bentonite contents only satisfied the hydraulic conductivity requirement even after wet-dry cycles.The experimental findings were supplemented with the microstructural insights captured through digital camera images,scanning electron microscopy(SEM),and mercury intrusion porosimetry(MIP)studies.

ST-LaneNet: Lane Line Detection Method Based on Swin Transformer and LaneNet

The advancement of autonomous driving heavily relies on the ability to accurate lane lines detection.As deep learning and computer vision technologies evolve,a variety of deep learning-based methods for lane line detection have been proposed by researchers in the field.However,owing to the simple appearance of lane lines and the lack of distinctive features,it is easy for other objects with similar local appearances to interfere with the process of detecting lane lines.The precision of lane line detection is limited by the unpredictable quantity and diversity of lane lines.To address the aforementioned challenges,we propose a novel deep learning approach for lane line detection.This method leverages the Swin Transformer in conjunction with LaneNet(called ST-LaneNet).The experience results showed that the true positive detection rate can reach 97.53%for easy lanes and 96.83%for difficult lanes(such as scenes with severe occlusion and extreme lighting conditions),which can better accomplish the objective of detecting lane lines.In 1000 detection samples,the average detection accuracy can reach 97.83%,the average inference time per image can reach 17.8 ms,and the average number of frames per second can reach 64.8 Hz.The programming scripts and associated models for this project can be accessed openly at the following GitHub repository:https://github.com/Duane 711/Lane-line-detec tion-ST-LaneNet.

Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative

With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM(1,1) model is employed to predict risk values for 2022-2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decisionmaking recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative.

Characterization of the infectivity of an Indonesian Zika virus strain in mammalian cell lines

Objective:To characterize the infection patterns and growth characteristics of the Zika virus(ZIKV)strain JMB-185 from Indonesia in various mammalian cell lines.Methods:ZIKV was grown in human(A549,HEK293,HepG2,Huh7,Jurkat,and THP-1)and non-human mammalian(RAW264.7,Vero,and Vero76)cell lines.Viral replication kinetics were measured using plaque assay,while intra-and extracellular viral RNA concentrations were assessed using RT-PCR.Flow cytometry was used to quantify the infected cells and cell viability was measured using an MTT assay.The ability of ZIKV to infect cell lines was visualized using a fluorescence immunostaining assay.Results:This ZIKV strain preferentially infected the lung,kidney,and liver cell lines A549,HEK293,Huh7,Vero,and Vero76,but not the immune cells Jurkat,RAW264.7,and THP-1.By contrast,the ZIKV showed no sign of infection in HepG2 cells,while maintaining viral titer over 3 days post-infection,with no infection recorded in immunostaining,no increase in viral RNA,and no indication of cell deterioration.Conclusions:The Indonesian ZIKV strain has a similar infection profile as other strains,except for its poor infectivity on HepG2 cells.Information on the growth characteristics of Indonesia ZIKV will help expand our understanding of the biology of ZIKV which will be useful for various applications including antiviral discovery.

An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

Exploring the Factors Associated with 12-Month Non-Return to Work among Motorcyclists Involved in Road Accidents

Introduction: Motorcyclists bear a disproportionate burden of morbidity and mortality from road accidents. In addition, the consequences of these accidents affect the ability of victims to return to work. This study aimed to determine the prevalence and factors associated with non-return to work among surviving motorcyclists involved in road accidents 12 months after the event. Materials and Methods: It was a cross-sectional study conducted using data from a cohort of motorcyclists involved in accidents and recruited in five hospitals in Benin from July 2019 to January 2020. The dependent variable was non-return to work 12 months after the accident (yes vs no). The independent variables were categorized into two groups: baseline and 12-month follow-up variables. Logistic regression was used to determine the factors associated with non-return to work at 12 months among the participants. Results: Among the 362 participants, 55 (15.19%, 95% CI = 11.84 - 19.29) had not returned to work 12 months after the accident. Risk factors for non-return to work identified were: smoking (aOR = 4.41, 95% CI = 1.44 - 13.56, p = 0.010), hospitalization (aOR = 2.87, 95% CI = 1.14 - 7.24, p Conclusion: The prevalence of non-return to work at 12 months was high among surviving motorcyclists involved in road accidents in Benin. Integrated support for patients based on identified risk factors should effectively improve their return to work.