Three-dimensional structural models,evolution and petroleum geological significances of transtensional faults in the Ziyang area,central Sichuan Basin,SW China

With drilling and seismic data of Transtensional(strike-slip)Fault System in the Ziyang area of the central Sichuan Basin,SW China plane-section integrated structural interpretation,3-D fault framework model building,fault throw analyzing,and balanced profile restoration,it is pointed out that the transtensional fault system in the Ziyang 3-D seismic survey consists of the northeast-trending F_(I)19 and F_(I)20 fault zones dominated by extensional deformation,as well as 3 sets of northwest-trending en echelon normal faults experienced dextral shear deformation.Among them,the F_(I)19 and F_(I)20 fault zones cut through the Neoproterozoic to Lower Triassic Jialingjiang Formation,presenting a 3-D structure of an“S”-shaped ribbon.And before Permian and during the Early Triassic,the F_(I)19 and F_(I)20 fault zones underwent at least two periods of structural superimposition.Besides,the 3 sets of northwest-trending en echelon normal faults are composed of small normal faults arranged in pairs,with opposite dip directions and partially left-stepped arrangement.And before Permian,they had formed almost,restricting the eastward growth and propagation of the F_(I)19 fault zone.The F_(I)19 and F_(I)20 fault zones communicate multiple sets of source rocks and reservoirs from deep to shallow,and the timing of fault activity matches well with oil and gas generation peaks.If there were favorable Cambrian-Triassic sedimentary facies and reservoirs developing on the local anticlinal belts of both sides of the F_(I)19 and F_(I)20 fault zones,the major reservoirs in this area are expected to achieve breakthroughs in oil and gas exploration.

Effects of three-dimensional quality assessment nursing intervention on efficacy and disease management of patients undergoing esophageal cancer surgery

BACKGROUND Esophageal cancer is one of the most common malignant tumors.The three-dimensional quality structure model is a quality assessment theory that includes three dimensions:Structure,process,and results.AIM To investigate the effects of nursing interventions with three-dimensional quality assessment on the efficacy and disease management ability of patients undergoing esophageal cancer surgery.METHODS In this prospective study,the control group received routine nursing,and the intervention group additionally received a three-dimensional quality assessment intervention based on the above routine care.Self-efficacy and patient disease management abilities were evaluated using the General Self-Efficacy Scale(GSES)and Exercise of Self-Care Agency scale,respectively.IBM SPSS Statistics for Windows,version 17.0,was used for the data processing.RESULTS This study recruited 112 patients who were assigned to the control and experi-mental groups(n=56 per group).Before the intervention,there was no significant difference in GSES scores between the two groups(P>0.05).After the inter-vention,the GSES scores of both groups increased,with the experimental group showing higher values(P<0.05).At the time of discharge and three months after discharge,the scores for positive attitudes,self-stress reduction,and total score of health promotion in the experimental group were higher than those in the control group(P<0.05).CONCLUSION The implementation of a three-dimensional quality structure model for postoperative patients with esophageal cancer can effectively improve their self-management ability and self-efficacy of postoperative patients.

Head Pursuit Variable Structure Guidance Law for Three-dimensional Space Interception

This article aims to develop a head pursuit （HP） guidance law for three-dimensional hypervelocity interception, so that the effect of the perturbation induced by seeker detection can be reduced. On the basis of a novel HP three-dimensional guidance model, a nonlinear variable structure guidance law is presented by using Lyapunov stability theory. The guidance law positions the interceptor ahead of the target on its tlight trajectory, and the speed of the interceptor is required to be lower than that of the target, A numerical example of maneuvering ballistic target interception verifies the rightness of the guidance model and the effectiveness of the proposed method.

Data Logic Structure and Key Technologies on Intelligent High-precision Map

Taking autonomous driving and driverless as the research object,we discuss and define intelligent high-precision map.Intelligent high-precision map is considered as a key link of future travel,a carrier of real-time perception of traffic resources in the entire space-time range,and the criterion for the operation and control of the whole process of the vehicle.As a new form of map,it has distinctive features in terms of cartography theory and application requirements compared with traditional navigation electronic maps.Thus,it is necessary to analyze and discuss its key features and problems to promote the development of research and application of intelligent high-precision map.Accordingly,we propose an information transmission model based on the cartography theory and combine the wheeled robot’s control flow in practical application.Next,we put forward the data logic structure of intelligent high-precision map,and analyze its application in autonomous driving.Then,we summarize the computing mode of“Crowdsourcing+Edge-Cloud Collaborative Computing”,and carry out key technical analysis on how to improve the quality of crowdsourced data.We also analyze the effective application scenarios of intelligent high-precision map in the future.Finally,we present some thoughts and suggestions for the future development of this field.

Construction and Analysis of Three-dimensional Graphic Model of Single-chain Fv Derived from an Anti-human Placental Acidic Isoferritin Monoclonal Antibody by Computer

Summary: A three-dimensional (3D) graphic model of a single-chain Fv (scFv) which was derived from an anti-human placental acidic isoferritin (PAF) monoclonal antibody (MAb) was construct- ed by a homologous protein-predicting computer algorithm on Silicon graphic computer station. The structure, surface static electricity and hydrophobicity of scFv were investigated. Computer graphic modelling indicated that all regions of scFv including the linker, variable regions of the heavy (VH) and light (VL) chains were suitable. The VH region and the VL region were involved in composing the 'hydrophobic pocket'. The linker was drifted away VH and VL regions. The complementarity determining regions (CDRs) of VH and VL regions surrounded the 'hydrophobic pocket'. This study provides a theory basis for improving antibody affinity, investigating antibody structure and analyzing the functions of VH and VL regions in antibody activity.

Technological anxiety:Analysis of the impact of industrial intelligence on employment in China

Employment is the greatest livelihood.Whether the impact of industrial robotics technology materialized in machines on employment in the digital age is an“icing on the cake”or“adding fuel to the fire”needs further study.This study aims to analyze the impact of the installation and application of industrial robots on labor demand in the context of the Chinese economy.First,from the theoretical logic and the economic development law,this study gives the prior judgment and research hypothesis that industrial intelligence will increase jobs.Then,based on the panel data of 269 cities in China from 2006 to 2021,we use the two-way fixed effect model,dynamic threshold model,and two-stage intermediary effect model.The objective is to investigate the impact of industrial intelligence on enterprise labor demand and its path mechanism.Results show that the overall effect of industrial intelligence on the labor force with the installation density index of industrial robots as the proxy variable is the“creation effect”.In other words,advanced digital technology has created additional jobs,and the overall supply of employment in the labor market has increased.The conclusion is still valid after the endogeneity identification and robustness test.In addition,the positive effect has a nonlinear effect on the network scale.When the installation density of industrial robots exceeds a particular threshold value,the division of labor continues to deepen under the combined action of the production efficiency and compensation effects,which will cause enterprises to increase labor demand further.Further research showed that industrial intelligence can increase employment by promoting synergistic agglomeration and improving labor price distortions.This study concludes that in the digital China era,the introduction and installation of industrial robots by enterprises can affect the optimal allocation of the labor market.This phenomenon has essential experience and reference significance for guiding industrial digitalization and intelligent transformation and promoting the high-quality development of people’s livelihood.

Three-dimensional coupled-mode model and characteristics of low-frequency sound propagation in ocean waveguide with seamount topography

Large-scale topography, such as a seamount, substantially impacts low-frequency sound propagation in an ocean waveguide, limiting the application of low-frequency acoustic detecting techniques. A three-dimensional(3D) coupledmode model is developed to calculate the acoustic field in an ocean waveguide with seamount topography and analyze the3D effect. In this model, a correction is introduced in the bottom boundary, theoretically making the acoustic field satisfy the energy conservation. Furthermore, a large azimuth angle calculation range is obtained by using the operator theory and higher-order Pade approximation. Additionally, the model has advantages related to the coupling mode and parabolic equation theory. The couplings corresponding to the effects of range-dependent environment are fully considered, and the numerical implementation is kept feasible. After verifying the accuracy and reliability of the model, low-frequency sound propagation characteristics in the seamount environment are analyzed. The results indicate lateral variability in bathymetry can lead to out-of-plane effects such as the horizontal refraction phenomenon, while the coupling effect tends to restore the abnormal sound field and produces acoustic field diffraction behind the seamount. This model effectively considers the effects of the horizontal refraction and coupling, which are proportional to the scale of the seamount.

Mathematical Modeling of the Influence of the Wind Field Structure in the Atmosphere on the Cloud Formation Processes

The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the clouds to the stage of studying the formation of macro- and microstructural characteristics of clouds as a whole, taking into account their system properties. The main directions of the development of cloud physics at the upcoming stage of its development are discussed. The paper points out that one of these areas is the determination of the structure-forming factors for the clouds and the study of their influence on their formation and evolution. It is noted that one of such factors is the interaction of clouds with their surrounding atmosphere, and the main method of studying its role in the processes of cloud formation is mathematical modeling. A three-dimensional nonstationary model of convective clouds is presented with a detailed account of the processes of thermohydrodynamics and microphysics, which is used for research. The results of modeling the influence of the wind field structure in the atmosphere on the formation and evolution of clouds are presented. It is shown that the dynamic characteristics of the atmosphere have a significant effect on the formation of macro- and microstructural characteristics of convective clouds: the more complex the structure of the wind field in the atmosphere (i.e., the more intense the interaction of the atmosphere and the cloud), the less powerful the clouds are formed.

Spatial distribution modeling of subsurface bedrock using a developed automated intelligence deep learning procedure:A case study in Sweden

Due to associated uncertainties,modelling the spatial distribution of depth to bedrock(DTB) is an important and challenging concern in many geo-engineering applications.The association between DTB,the safety and economy of design structures implies that generating more precise predictive models can be of vital interest.In the present study,the challenge of applying an optimally predictive threedimensional(3D) spatial DTB model for an area in Stockholm,Sweden was addressed using an automated intelligent computing design procedure.The process was developed and programmed in both C++and Python to track their performance in specified tasks and also to cover a wide variety of diffe rent internal characteristics and libraries.In comparison to the ordinary Kriging(OK) geostatistical tool,the superiority of the developed automated intelligence system was demonstrated through the analysis of confusion matrices and the ranked accuracies of different statistical errors.The re sults showed that in the absence of measured data,the intelligence models as a flexible and efficient alternative approach can account for associated uncertainties,thus creating more accurate spatial 3D models and providing an appropriate prediction at any point in the subsurface of the study area.

An Intelligent Graph Edit Distance-Based Approach for Finding Business Process Similarities

There are numerous application areas of computing similarity between process models.It includes finding similar models from a repository,controlling redundancy of process models,and finding corresponding activities between a pair of process models.The similarity between two process models is computed based on their similarity between labels,structures,and execution behaviors.Several attempts have been made to develop similarity techniques between activity labels,as well as their execution behavior.However,a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between them.However,neither a benchmark dataset exists for the structural similarity between process models nor there exist an effective technique to compute structural similarity.To that end,we have developed a large collection of process models in which structural changes are handcrafted while preserving the semantics of the models.Furthermore,we have used a machine learning-based approach to compute the similarity between a pair of process models having structural and label differences.Finally,we have evaluated the proposed approach using our generated collection of process models.

Gait planning and intelligent control for a quadruped robot

We present a method for designing free gaits for a structurally symmetrical quadruped robot capable of performing statically stable, omnidirectional walking on irregular terrain. The robot＇s virtual model is constructed and a control algorithm is proposed by applying virtual components at some strategic locations. The deliberative-based controller can generate flexible sequences of leg transferences while maintaining walking speed, and choose optimum foothold for moving leg based on integration data of exteroceptive terrain profile. Simulation results are presented to show the gait＇s efficiency and system＇s stability in adapting to an uncertain terrain.

Heuristic Quasi-physical Algorithm for Protein Structure Prediction

A three-dimensional off-lattice protein model with two species of monomers, hydrophobic and hydrophilic, is studied. Enligh- tened by the law of reciprocity among things in the physical world, a heuristic quasi-physical algorithm for protein structure prediction problem is put forward. First, by elaborately simulating the movement of the smooth elastic balls in the physical world, the algorithm finds low energy configurations for a given monomer chain. An ＂off-trap＂ strategy is then proposed to get out of local minima. Experimental results show promising performance. For all chains with lengths 13≤n ≤55, the proposed algorithm finds states with lower energy than the putative ground states reported in literatures. Furthermore, for chain lengths n = 21, 34, and 55, the algorithm finds new low energy configurations different from those given in literatures.

Mobile and Context-Aware GeoBI Applications: A Multilevel Model for Structuring and Sharing of Contextual Information

With the requirements for high performance results in the today’s mobile, global, highly competitive, and technology-based business world, business professionals have to get supported by convenient mobile decision support systems (DSS). To give an improved support to mobile business professionals, it is necessary to go further than just allowing a simple remote access to a Business Intelligence platform. In this paper, the need for actual context-aware mobile Geospatial Business Intelligence (GeoBI) systems that can help capture, filter, organize and structure the user mobile context is exposed and justified. Furthermore, since capturing, structuring, and modeling mobile contextual information is still a research issue, a wide inventory of existing research work on context and mobile context is provided. Then, step by step, we methodologically identify relevant contextual information to capture for mobility purposes as well as for BI needs, organize them into context-dimensions, and build a hierarchical mobile GeoBI context model which (1) is geo-spatial-extended, (2) fits with human perception of mobility, (3) takes into account the local context interactions and information-sharing with remote contexts, and (4) matches with the usual hierarchical aggregated structure of BI data.

高层剪力墙结构多目标智能设计方法

高层剪力墙结构智能设计包括智能建模和智能优化两个环节。目前智能建模环节缺乏梁自动化布置和荷载自动化布置;智能优化环节只考虑材料成本而未考虑施工的便捷性。此外,现有的智能设计方法均局限于单标准层的高层剪力墙结构。为此,该文提出了高层剪力墙结构多目标智能设计方法,包括多标准层高层剪力墙结构的智能建模和多目标优化。多标准层高层剪力墙结构智能建模包含剪力墙智能布置、梁自动化布置、板自动化布置和荷载自动化布置;以材料成本和施工便捷性为目标,采用分步优化策略和基于小生境技术的遗传算法对高层剪力墙结构进行多目标优化。通过实际工程算例对所提出的方法进行了验证,结果表明,所提出的高层剪力墙结构多目标智能设计方法稳定、可靠,可以较好地兼顾材料成本和施工的便捷性,并能显著缩短设计周期。

面向综合评估的船舶工装设计方法

针对船舶建造工装设计标准化程度低、设计不规范以及设计管理落后等问题,提出一种面向综合评估的工装设计方法。从工装库构建、智能设计、仿真评估与优化等角度开展工装数字化设计研究。基于工装模型库实现设计模型的有效管理和调用,并通过集成寻优算法实现工装最优布局,在此基础上基于有限元仿真和工艺仿真技术,结合具体指标,实现工装结构力学性能和工艺仿真评估,同时利用结构优化技术对设计结果进行优化,在满足使用需求的基础上降低了加工成本。基于达索三维体验平台开发数字化工装设计系统,固化设计流程,并通过分段吊马设计的实际应用,实现设计效率提升200%,同时重量减轻12.8%。

人工智能缓释用户信息焦虑——以ChatGPT为例

文章从信息传播视角出发,以ChatGPT为例,探究ChatGPT缓释用户信息焦虑影响因素。研究基于自我决定理论,从外因与内因两个维度,通过修订已有成熟信息焦虑量表,采用实证分析法对370名互联网用户进行调查,构建结构方程,聚焦ChatGPT对信息焦虑的影响因素。研究表明:ChatGPT能够缓释用户信息焦虑行为;ChatGPT提供的信息质量、数量、素养和获取是影响用户信息焦虑情绪的主要因素;自我效能感与元认知在ChatGPT缓释信息焦虑的过程中起到了积极的调节作用。研究拓展了人工智能与用户信息焦虑情绪的研究范畴,并为用户焦虑情绪缓释的实践治理提供参考。

基于主体基建模(ABM)的中国智能制造装备产业演化研究

智能制造装备面向的是具有复杂决策机制的制造企业,因此其产业演化规律相较于其他新兴产业有更强的特殊性。目前中国智能制造装备的市场份额较少、缺乏竞争优势,智能制造装备企业难以实现可持续发展。因此,在关键核心技术短期无法突破场景下,探讨政府高效推动智能制造装备市场结构变化、对智能制造装备产业演化的作用机制。通过问卷调查收集智能制造装备市场真实数据,在主体基建模方法(ABM)框架下构建国内外智能制造装备企业决策模型与制造企业决策模型,模拟智能制造装备产业演化过程,分析智能制造装备企业数量、市场需求数量和市场需求分布等市场结构核心参量变化特征,并进一步探究不同扶持政策对产业演化的作用效果。结果发现:在智能制造装备产业演化过程中,市场需求结构的变化是改变国产智能制造装备企业市场份额的关键要素,国产智能制造装备企业市场需求数量经历“增长—下跌—再增长”3个阶段,市场需求在空间上呈“分散—集聚—扩散”分布;在无外部力量干预的情境下,国产智能制造装备企业的市场份额存在显著的持续下降趋势,无论是面向市场需求数量还是面向产品质量提升的政策措施都有利于提升国产智能制造装备企业在产业中的市场状况;不同的政策策略对产业演化进程产生的效果不同,面向产品质量提升的政策对提升国产智能制造装备企业的市场份额效果更显著。

基于扩散模型的联珠团窠纹再生设计研究

生成式人工智能正广泛应用于图像生成领域,为解决传统纹样设计方法创作联珠团窠纹耗时耗力的问题,研究扩散模型应用于联珠团窠纹再生设计的方法。通过对联珠团窠纹艺术结构特征的提取和扩散模型中交叉注意力模块的研究,设计有效的描述文本并重构扩散模型,提出以结构相似度作为参考标准,采用高斯函数确定阈值进行筛选的再生设计方法。主客观评价结果证明了运用重构的扩散模型进行纹样再生设计的可行性。为联珠团窠纹的再生设计提供了新的思路与方法。

基于UTAUT的MaaS一体化支付的接受度研究

为探究用户对MaaS一体化支付的接受度,列出MaaS一体化支付框架,分析其中的关键部分及问题,通过整合技术接受度模型(UTAUT),构建MaaS一体化支付接受度模型,在武汉市的三个大型火车站发放问卷以收集数据,运用结构方程模型来具体分析检验各维度之间的关系,并分析各因素对用户使用意向的影响程度,结果表明社群影响与个人创新性对使用意向的影响程度最大,标准化路径系数为0.363与0.325,除社群影响与个人创新性以外,努力期望、促成因素对使用意向的影响程度适中,标准化路径系数为0.202与0.215,而绩效期望对使用意向的影响程度较小,标准化路径系数为0.096,并根据此数据结果分析MaaS一体化支付的发展模式。

人工智能时代的教育评价改革

随着人工智能技术的飞速发展,教育评价改革面临着前所未有的机遇与挑战。本文从认知心理模型视角出发,深入探讨人工智能技术在教育评价中的应用渊源、价值及其所带来的创新性变革。传统教育评价方法已不足以应对当前教育的复杂需求,人工智能技术提供了更为科学、客观和专业化的途径。同时,学生和教师的能力结构转型已成为教育评价改革的重要方向,大数据、自适应学习、深度学习与智能分析等技术在教育评价中发挥着关键作用。此外,多元化、个性化、大数据驱动、过程导向和聚焦高阶思维能力已成为教育评价的重要发展趋势。人工智能带来的变革不仅提高了教育评价的效率和精确度,也为教育评价体系的现代化开辟了新路径。