针对基山砂体沉积微相认识不清、控砂机制不明确的问题，在高分辨率层序地层格架划分的基础上，综合利用岩心、粒度、测井以及地震等资料，对惠民凹陷沙三中亚段的沉积特征进行识别，分析不同层序时期的沉积相及砂体展布情况，探讨砂体展布的控制因素。研究结果表明：1）沙三中亚段基山砂体可以划分为7个四级层序和21个五级层序。2）研究区以三角洲前缘沉积亚相为主，发育有水下分流河道、河口坝、席状砂、滑塌浊积等沉积微相。不同层序时期的沉积相及砂体展布情况不同，其中Psq7～Psq4层序时期，三角洲不断向南以及向东延伸，水下分流河道砂体逐渐增厚，浊积岩的分布范围逐步扩大。3）在高分辨率层序地层格架的控制下，砂体具有多种叠置样式——靠近物源发育坝上河砂体叠置，远离物源发育孤立河道砂体叠置，浊积砂体在垂向上多套叠置、平面上迭合连片。4）砂体展布受构造调节带及坡折带的控制，构造调节带控制着入盆水系的方向；断裂坡折带控制着滑塌浊积岩的分布，使其主要分布在低水位时期的斜坡低部位。
To avoid redundant data collection,break down data silos,and achieve cross-system information interoperability,data sharing have been implemented among many universities through technical means including data interfaces and data exchange protocols.This paper analyzes the existing problems in current sharing models,including insufficient data openness capabilities and uncoordinated data request processes.An architectural design for a data-sharing platform was carried out and a four-pronged approach was proposed to enhance data utility and security:constructing a data resource catalog,streamlining the data request workflow,implementing rigorous quality control mechanisms,and strengthening data security management systems.The purpose of these lies in improving data availability and security,standardizing data sharing procedures and ultimately improving the over-all sharing capacity of university data platforms.
Aerodynamic drag(FA)of high-speed trains increases significantly with the elevated speed,but a con-tradiction between space utilization and drag reduction efficiency exists in traditional streamlined design.Taking the CR400BF high-speed train(HST)as the research subject,the original streamlined smooth structure on the roof section was replaced with convex hull type non-smooth structure.The aerodynamic drag reduction perfor-mance was optimized using the response surface method(RSM).Through analysis of the impact of different structural parameters on FA,the key parameters influencing FA were determined.RSM was employed to con-struct a mathematical model between FA and the key parameters for the convex hull type roof structure of the HST.An accurate and reliable response surface model was obtained via designing experimental schemes,collect-ing data,and performing regression analysis.On this basis,an optimization algorithm was applied to enhance the aerodynamic drag reduction performance of the convex hull type roof structure.The results demonstrate that a multi-parameter collaborative optimization model for the convex hull structure was established based on RSM,improving optimization efficiency by 95%compared to traditional methods.The optimal parameter combination(convex radius:109.6 mm,convex height:580.1 mm,convex array spacing:347.8 mm)reduces aerodynamic drag by 25.1%,with a simulation-experimental error<3%.The convex hull structure achieves drag reduction by delaying boundary layer separation and reconstructing the wake vortex structure,resulting in an 18.1%reduc-tion in trailing vortex length.
As a chronic,systemic autoimmune disease,rheumatoid arthritis(RA)brings serious threats to patients'health and imposes a heavy burden on individuals and society.Despite the large variety of drugs for treating RA,problems still exist,such as poor therapeutic effects and strong side effects.The novel hydrogel drug delivery system with unique structure and properties such as good biocompatibility,large drug loading capacity,flexible drug loading methods,improved drug tar-geting,and controlled drug release,holds great potential to be widely used in the delivery of RA treatment drugs and exhibits a positive promoting effect on the treatment of RA.This article focuses on the research of novel intelligent hydrogels for intra-articular injection and their application in the treatment of RA,aiming to provide reference and guidance for the continuous research of hydrogel drug delivery systems for RA treatment.
In the present work,a dataset was formed by collecting 136 measured samples of the failure height of overlying rock strata to accurately predict the failure height of overlying rock strata in deep-thick coal seams under thick loose layers.The main influencing factors selected for the failure height of overlying rock strata include min-ing height,mining depth,the inclined length of working face,the proportion coefficient of hard rock,and the dip angle of coal seam.The weights of each factor were obtained through grey relational analysis and importance.Using the CS-RF optimized prediction model,the determination coefficient(R2),mean absolute error(MAE),mean square error(MSE),and out-of-bag error(OOB)were employed as evaluation indicators for the regres-sion model to determine the optimal hyperparameters of the RF model.A comparative analysis of the prediction performance of the CS-RF and RF prediction models was conducted using 10-fold cross-validation.The results show that compared to the RF prediction model,the CS-RF prediction model achieves an improvement of 0.31%in R2 on the training set,with reductions of 2.37%and 9.50%in MAE and MSE,respectively.On the cross-validation set,the CS-RF model improves R2 by 0.55%,with reductions of 90.16%and 5.23%in MAE and MSE,respectively.On the test set,the CS-RF model improves R2 by 0.43%,with reductions of 6.78%and 6.47%in MAE and MSE,respectively.The violin plot of relative errors on the training set has the largest width,indicating that the relative error data are the most concentrated in this region,and the mean relative error is the smallest.The mean relative error between the predicted and measured values of the failure height of overly-ing rock strata for the CS-RF prediction model is less than the corresponding value for the RF model.The aver-age predicted relative error for the failure height of overlying rock strata is 6.85%across 25 test working faces,demonstrating that the CS algorithm improves the accuracy of the RF model.This provides important insights for the training and prediction of failure height of overlying rock strata models.
为解决传统湿度传感器在动态温湿环境中存在的迟滞误差与测量不稳定问题，设计了一种融合“循环热扰动-双路径解耦-智能补偿”机制的高精度湿度传感器。采用双湿度传感器交替进行升温与降温路径测量，结合露点反演技术，对不同温度点的湿度数据进行反推，实现将湿度值统一映射到参考温度，并结合计算流体动力学（computational fluid dynamics,CFD）热仿真确定最优加热功率与结构参数，实现高效稳定的周期性加热与自然冷却。引入粒子群优化（particle swarm optimization,PSO）支持向量机（support vector machine,SVM）回归算法建立多特征非线性修正模型，实现对迟滞误差的精确建模与路径权重自适应融合。实验结果表明，所提出的高精度湿度测量系统对湿度测量的平均绝对误差为0.52%RH，均方根误差为0.57%RH。
To address the issues of the insufficient stability and the structural weakness of shear hinges in existing precast short steel spring floating slab track systems,a novel wet-joint precast assembly steel spring floating slab track was proposed.Optimization design and mechanical modeling analysis were conducted to reveal the static characteristics,dynamic responses,modal features,and vibration damping performance of the track system.The steel spring floating slab track forms long-slab assembly units by casting ultra-high performance concrete(UHPC)wet joints between precast short floating slabs,combining the high-quality factory production of precast short floating slabs with the integral stability of cast-in-place track beds,which significantly reduces the number of shear hinges.Under train loads,the track stresses remain below material strength limits with a maximum verti-cal displacement of 3.8 mm in the rail and minimal angular deflection at slab joints,demonstrating favorable mechanical performance.Within the speed range of 100-140 km/h,the vertical vibration accelerations of vehicles and floating slabs rise by 10.9%and 24.7%,respectively,as the speed increases.On the other hand,other dynamic response indicators show negligible changes,and all system dynamic response indicators comply with regulatory limits.The first-order modal frequency of the track system is 11.04 Hz,and a Z-vibration level reduc-tion of it is 20.11 dB,satisfying special vibration damping requirements.
Expandable tubular open hole clad technology,which adopts physical methods to quickly and effi-ciently seal complex formations such as severe leakage,and realize the well bore structure expansion,is of great significance for safe and efficient drilling of deep and complex wells.Herein,the application field,process prin-ciple and key technologies of expandable tubular open hole clad technology were analyzed and the indoor experi-ments on 299 mm(outside diameter)expandable tubular was conducted.The experimental results indicated that the expansion pressures were 10～12 MPa and 8～10 MPa for the tubular and the thread expansion,respectively.The sealing pressure after thread expansion was higher than 30 MPa when expansion cone with 286 mm diameter was adopted for the 299 mm×14 mm expansion tube.In addition,299 mm(outside diameter)expandable tube was used to seal the severe leakage formation with a length of 666.12 m,aiming to solve the leakage problems of Jialingjiang Formation in the 311.2 mm well bore in Well A in Southwest Oil and Gas Field.The expansion pressure was 8～12 MPa in the field application,which was consistent with the laboratory experimental data.After the installation of the expandable tubular,the density of the drilling fluid for the third drilling stage was increased from 1.17 g/cm3 to 1.85 g/cm3,which ensured the safe drilling of the subsequent formation and realized the drill-ing of the target formation with 215.9 mm bit according to the original design at the same time.The field applica-tion showed that the open-hole plugging technology of expandable tube was an efficient petroleum engineering technology to solve complex problems.It is suggested to consider the expansion scheme in advance in the drilling experience design of complex wells,deep wells and ultra deep wells to deal with risky formations,optimize and expand the well bore structure,which can effectively reduce the complex treating time.
Transforming optical facial images into sketches while preserving realism and facial features poses a significant challenge. The current methods that rely on paired training data are costly and resource-intensive. Furthermore, they often fail to capture the intricate features of faces, resulting in substandard sketch generation. To address these challenges, we propose the novel hierarchical contrast generative adversarial network (HCGAN). Firstly, HCGAN consists of a global sketch synthesis module that generates sketches with well-defined global features and a local sketch refinement module that enhances the ability to extract features in critical areas. Secondly, we introduce local refinement loss based on the local sketch refinement module, refining sketches at a granular level. Finally, we propose an association strategy called “warmup-epoch” and local consistency loss between the two modules to ensure HCGAN is effectively optimized. Evaluations of the CUFS and SKSF-A datasets demonstrate that our method produces high-quality sketches and outperforms existing state-of-the-art methods in terms of fidelity and realism. Compared to the current state-of-the-art methods, HCGAN reduces FID by 12.6941, 4.9124, and 9.0316 on three datasets of CUFS, respectively, and by 7.4679 on the SKSF-A dataset. Additionally, it obtained optimal scores for content fidelity (CF), global effects (GE), and local patterns (LP). The proposed HCGAN model provides a promising solution for realistic sketch synthesis under unpaired data training.
In order to explore the feasibility of the double load cell self-balanced method in loess areas,two compressive test piles of an urban overpass project in Shaanxi province were taken as the research objects and the vertical bearing capacity of pile foundation was tested.Additionally,the difference of the lifting degree and composition of the bearing capacity of pile foundation before and after pile bottom grouting was analyzed.Furthermore,the load transfer law was studied in terms of pile axial force,pile side friction resistance and pile end resistance.The results show that the ultimate bearing capacity of pile foundation after grouting is increased by 51.74%compared with that before grouting,and the resistance value of pile end is increased by 2.5 times before grouting,and its proportion in the bearing capacity of pile foundation is increased obviously.In the double load cell self-balanced test,the axial force of the pile body is generated and reaches its maximum value at the upper load cell,and gradually decays towards the top and bottom of the pile.The lateral friction of pile is found to start from the upper load cell and decreases to the minimum value in the process of transmission along the pile body due to the gradual decrease of the relative displacement of pile and soil.The reaction and displace-ment curve of the pile end is similar to the load displacement curve of the traditional static load test,while the differences lie in the soil stress field around the pile.
In order to reduce the noise of a multi-blade centrifugal fan and improve its aerodynamic performances,the effects of groove distribution on the aerodynamic performance and noise of a multi-blade centrifugal fan were studied by numerical simulation.The results show that the grooves weaken the interference between the impeller outlet jet wake and the tongue wall,the high vortic-ity in the channel between the impeller and the tongue decreases,while the flow stability increases.The thickness of the volute wall boundary layer decreases,and reflux and vortex conditions were improved.The flow resistance caused by reverse pressure difference and the flow loss decrease,and the outlet flow kinetic energy and the air volume increase.The air volume of L50G11 model multi-blade centrifugal fan increases by 3.17%,the total pressure efficiency decreases by 4.81%,and the aerodynamic performance changes little.The average noise of the monitoring points is reduced,the maximum average noise reduction is 4.7 dB,and the noise reduction effect is the most prominent.The average noise value of the monitoring point of L75G22 model multi-blade centrifugal fan decreases to 3.51 dB,and the noise condition is improved.The increase of air volume is 4.30%,and the increase of total pressure efficiency is 3.34%,indicating a superior aerodynamic performance.
Aiming at the improvement of the interfacial bond strength between steel pipe and concrete of steel pipe-concrete compos-ite structure,and the investigation of the influence of different forms of internally welded reinforcement on the bond strength between the two interface,the steel pipe-concrete members with four different steel pipe-wall internally welded reinforcement structures were set up for the push-out test.The parameters were set on the test results to compare the influences of different forms of internally welded reinforcing bars on the bond performance between the two interface,and the combination of the curves and the test results described slipping process.ABAQUS software was used to perform finite element simulation to compare and analyse the effects of different structural measures on the bond-slip performance of welded reinforcement inside the steel pipe,and the calculation method of the shear capacity of steel pipe with built-in welded reinforcement was proposed.The results show that the structural measures of the internal welded reinforcement can greatly improve the bond strength of the steel pipe-concrete interface,and the interface bond strength gradually increases with the increase of the number of reinforcement rings.
To address the issue of the inadequate accuracy of current lightweight human pose estimation network when detecting under reduced parameter count and computational complexity,a lightweight human pose estimation network based on dynamic ghost(dynamic ghost network,DGNet)was proposed.DGNet employs an innovative approach to succinctly and effectively extract con-textual information,enhancing the model's representation capability and consequently improving performance without increasing parameter count and computational complexity.Specifically,the model utilizes dynamic shuffling and ghost operations to construct two novel lightweight modules:the dynamic ghost neck module(DGNeck)and the dynamic ghost basicblock module(DGBlock).DGNeck replaces convolution operations with less costly linear operations to reduce network parameters and computational complex-ity.Simultaneously,DGBlock dynamically aggregates multiple channels and shuffles them to obtain accurate positional information in the feature map,thus improving detection accuracy.Experimental results under comparable conditions show that,compared to existing Lite-HRNet models,DGNet model achieves a 4.8%reduction in computational complexity and a 2.3%elevation in accu-racy on the COCO validation set,while on the MPII validation set,it achieves a 3.7%reduction in computational complexity and a 0.7%increase in accuracy.
To address the problems of poor applicability,low knowledge utilization and difficulty in dealing with diverse attack threats for current attack prediction methods,an attack prediction method based on knowledge graph and reinforcement learning was proposed.Firstly,a cyber security knowledge graph and an attack scenario knowledge graph were constructed.Secondly,the knowledge representation learning and deep reinforcement learning methods were integrated to propose an attack prediction knowl-edge reasoning model RLBTransE.Based on the attack scenario network topology and attack scenario knowledge graph,inter-host attack paths and single-host attack paths were generated respectively,and finally the complete attack path prediction was realized.Experimental results on the simulated experimental scenario data set show that,compared with current typical advanced methods,RLBTransE improves the mean reciprocal rank(MRR)and Hits@1 by 10.1%and 9.3%,respectively.Comparative experiments with other attack prediction methods also verify the better applicability and interpretability of this method.
The present work aims at the study of the closed-loop Dα-type iterative learning consensus tracking problem under differ-ent communication topology protocols of a class of singular nonlinear fractional-order multi-agent systems with disturbances.Firstly,a sufficient condition for the convergence of consensus error of nonlinear generalized fractional-order multi-agent systems under fixed communication topology was given based on the characteristics of fractional calculus and generalized Gronwall inequality.Subsequently,the obtained theoretical results were extended to the case where the communication topology changed with the itera-tion axis,and the convergence characteristics of the consensus tracking error of the controlled multi-agent system were analyzed.Finally,the effectiveness of the proposed closed-loop Dα-type iterative learning consensus control protocol was verified by two numerical simulation examples.
To investigate the problem related to spontaneous combustion of leftover coal in goaf,Donghuantuo gas coal was taken as the model material and pre-oxidizations at 80,160,and 230℃were carried out to study the difference in spontaneous combustion characteristics.In this paper,low-temperature nitrogen adsorption,temperature-programmed gas chromatography and thermogravi-metric(TG)experiments were used to study the pore changes of coal samples at different pre-oxidation temperatures,the changes of characteristic gases and activation energy in the early stage of spontaneous combustion oxidation,based on which the change of spontaneous combustion tendency of coal samples were explored.The results show that the higher the degree of pre-oxidization,the higher the content of macropores and the higher the risk of spontaneous combustion.The main gases are CO,CH4,C2H4 and C2H2 in the programmed temperature test.The initial production temperatures of all kinds of gases rise with the increase of pre-oxidization temperature.Among them,the rate of CO and CH4 gas released by pre-oxidized coal sample has a tendency to surpass that of raw coal.It is found that the characteristic temperature points(T1,T2,T3)of coal sample decrease with the increase of pre-oxidization temperature and the activation energy of coal sample decreases after low temperature oxidation.It is concluded that the spontaneous combustion oxidation capacity of preoxidized coal sample is stronger than that of raw coal.Additionally,the tendency of coal sponta-neous combustion of the coal sample is affected by the structural changes of coal voids and internal energy changes in low temperature oxidization environment.
Large-scale shaking table model tests on a group of piles with elevated caps were used to simulate the vibration response of pile group foundations under seismic action.Excess pore pressure ratio(pore pressure ratio for short),acceleration,and founda-tion soil displacement were used to study the effects of vertical load on the lateral displacement of pile foundations in saturated sand soil liquefaction sites.The findings indicate that the near-pile region is most significantly impacted by the pile foundation's vertical load.Specifically,the pore pressure ratio decreases as the vertical load increases.The shallow acceleration of the foundation soil and the difference in pore pressure ratios between the superstates on either side of the pile foundation are the primary causes of the pile foundation's lateral displacement.Moreover,the acceleration output of the table surface is mostly amplified by the foundation soil,and the acceleration amplification coefficient falls noticeably as the vertical load increases.The lateral flow and considerable deforma-tion of foundation soil brought on by ground vibration has a major impact on the lateral movement of the pile foundation under the same input and vertical load conditions.Under the condition of a 9%vertical load,the tilt angle of the pile foundation is 4.80°,and the lateral displacement is small.Furthermore,the best overturning resistance can be expected if combining with the liquefaction-resistant ability of the foundation soil.
Current digital office documents involve huge amount of table data.Accordingly,increasing demand on intelligent table recognition emerges.Nonetheless,the table structure is complex and closely linked,leading to the ultrahigh difficulty in table struc-ture detection.To address this problem,a new table row-column cell structure detection method was proposed based on YOLOv8,in which the ICDAR19-cTDaR table cell structure and the TabStructDB table row-column structure were taken as object.Firstly,in order to enhance the extraction of table cells and row and column features,this paper introduced deformable convolution network(DCN).Secondly,the introduction of spatial and channel reconstruction convolution(SCConv)not only had a strong feature extrac-tion capability,but also reduced redundant features to reduce the complexity and computational cost.Based on the above introduced convolution,a new module DSC module was designed to replace the Bottlenck module in C2f and named as C2fDSC module.Addi-tionally,in order to further enhance the corner local feature extraction of the table structure,a explicit visual center feature adjust-ment(EVC)module was added to the backbone network of YOLOv8.Finally,the loss function of the original model was replaced by MPDIoU.When the problem of dense objective regression accuracy is being solved,the MPDIoU loss function bounding box regression is more accurate and efficient compared to the original model loss function.Experimental results show that the table struc-ture detection algorithm in the dataset ICDAR19-cTDaR achieves the best detection results so far.The cell checking rate,checking rate and F1 value are 91.7%,82.3%and 86.7%,respectively.Moreover,the proposed algorithm also performed well in the data-set TabStructDB table row and column detection.
In order to study the influence of bimodal pore structure on the mechanical properties of unsaturated soil,two typical bimodal pore structure clays in Nanning and Guilin in Guangxi were selected as target materials and the shear strength characteristics under different saturation conditions were analyzed.The effect mechanism of pore water distribution status on the strength of two kinds of soils with bimodal pore structure was explored by filter paper method and nuclear magnetic resonance(NMR)technique.The results show that the T2 distribution curves of the two samples have bimodal structure under saturated condition.Moreover,on the whole,the water retention characteristics of soil samples show bimodal soil-water characteristic curve.The stress-displacement relationship of the two kinds of soil is similar and the shear strength is closely related to saturation.The change trend of soil sample cohesion changes when the saturation is 40%,while the internal friction angle reaches the minimum at a saturation of 80%.
In order to study the effects of composite modification by high content rubber powder-SBS on the high-temperature rheo-logical properties of matrix asphalt,the trend of the performance of high content crumb rubber-SBS composite modified asphalt with the change of crumb rubber content was studied firstly by three indexes and Brookfield rotational viscosity.Subsequently,six test schemes were designed and the high temperature rheological properties of six kinds of asphalt were explored by dynamic shear rheom-eter,based on which a detailed comparative study was carried out.The results show that the high and low temperature performance of high content crumb rubber-SBS composite modified asphalt increases with the increase of crumb rubber content.When the con-tent of crumb rubber is 42%,good performance and satisfaction of construction requirements can be achieved simultaneously.In the high temperature rheological property test,compared with the single modified asphalt,the complex shear modulus(G*),rutting fac-tor(G*/sin(δ))and creep recovery rate(R)of the matrix asphalt are significantly improved by the composite modification,and the phase angle(δ)and irrecoverable flexibility(Jnr)are reduced.Meanwhile,stronger elastic properties,high temperature rutting resis-tance,deformation recovery ability,and deformation resistance are obtained.In addition,with the increase of rubber powder content from 21%to 42%,the elastic components of rubber powder-SBS composite modified asphalt also increase,the deformation recov-ery ability and deformation resistance are stronger,and the high temperature rheological properties are improved.
