Driving risk assessment under the connected vehicle environment:a CNN-LSTM modeling approach

Connected vehicle(CV)is regarded as a typical feature of the future road transportation system.One core benefit of promoting CV is to improve traffic safety,and to achieve that,accurate driving risk assessment under Vehicle-to-Vehicle(V2V)communications is critical.There are two main differences concluded by comparing driving risk assessment under the CV environment with traditional ones:(1)the CV environment provides high-resolution and multi-dimensional data,e.g.,vehicle trajectory data,(2)Rare existing studies can comprehensively address the heterogeneity of the vehicle operating environment,e.g.,the multiple interacting objects and the time-series variability.Hence,this study proposes a driving risk assessment framework under the CV environment.Specifically,first,a set of time-series top views was proposed to describe the CV environment data,expressing the detailed information on the vehicles surrounding the subject vehicle.Then,a hybrid CNN-LSTM model was established with the CNN component extracting the spatial interaction with multiple interacting vehicles and the LSTM component solving the time-series variability of the driving environment.It is proved that this model can reach an AUC of 0.997,outperforming the existing machine learning algorithms.This study contributes to the improvement of driving risk assessment under the CV environment.

New Strategy of Collaborative Acquisition for Connected GNSS Receivers in Deep Urban Environments

Collaborative Positioning (CP) is a better localization technique used to locate a user in challenged environments, which is driven by the increasing presence of cellular phones and mobile devices in urban areas. The basic idea is that the mobile devices can cooperate with each other to improve their ability to determine their position. In this concept, a network of GNSS (Global Navigation Satellite System) receivers can collectively receive available satellite signals, and each receiver can receive signal measurements from other receivers via a communication link. This work shows how to use the Collective Detection (CD) approach to deal with the concept of collaborative or cooperative positioning. Specifically, this paper develops a new strategy allowing a receiver in deep urban environment to locate using the CD approach, while overcoming the implementation complexity problem. The idea consists in applying the CD approach in the case of multiple GNSS receivers to assist a receiver in a difficult situation. A typical case of two connected receivers assisting a receiver in difficulty in a deep urban area shows the effectiveness of this strategy. This strategy is tested with real GNSS signals to analyze its feasibility. The overall gain in complexity can reach up to 46% of what has been achieved in previous works.

Response Mechanism of Water Ecosystem under the Influence of Urbanization: A Case Study of the Connection Zone between Shenyang and Fushun

Taking the connection zone between Shenyang and Fushun as an example,urbanization indicator system was established from the aspects of population,economy,space and society,and the comprehensive evaluation indicator system of water ecological environment was also established from the aspects of water ecological environmental pressure,state and response. Based on the evaluation of comprehensive level of urbanization and the comprehensive quality of water ecological environment,their changing trends during 2000-2014 were analyzed,and the response model between them was established. The composite index of urbanization in the connection zone between Shenyang and Fushun always increased from 2000 to 2014,and urbanization developed rapidly after 2004. The comprehensive quality of water ecological environment decreased firstly and then increased during 2000-2014. The response relationship between urbanization comprehensive index and water ecological comprehensive index during 2000-2014 could be expressed by a cubic curve.

Numerical Simulation of U-Shaped Metal Rings in a Wind-Sand Environment

The interaction of U-shaped rings used for power transmission hardware with a wind-sand field is simulated numerically.A standard k
turbulence model is used in synergy with an Eulerian-Lagrangian approach.The results show that the wind pressure on the windward side of the U-shaped ring is the highest,a negative pressure zone appears on both sides of the U-shaped ring,while a Kármán Vortex Street is created on its leeward side.There are three possible regimes of motion for the sand grains in the wind field.Sand grains with size below 0.125 mm can follow the airflow directly into the contact area of two U-shaped rings.When the sand size is about 0.1 mm,the number of sand grains that are blown into the contact area attains a maximum.Through the simulation of U-shaped rings in the wind-sand field,the dynamics of such processes are explained in detail,thereby providing relevant information for the subsequent protection and design of connecting hardware used for power transmission.

职场正念的人际影响及作用机制

职场正念在人际领域的益处日渐凸显,有必要厘清其在概念发展和人际作用方面的新趋势,为组织塑造积极的职场环境提供启发。研究揭示目前存在两种不同的职场正念概念发展趋势:结果导向和过程导向,前者关注职场背景下概念与测量的统一趋势以探索有益的结果集合,后者侧重挖掘正念嵌入人际互动的过程机制;职场正念通过4种关联机制对质量和功能相关的人际结果产生影响:(1)在互动中通过开放的注意力捕捉信息以协调相互依赖工作的知识关联;(2)降低与内外部情绪体验相关的自我推断并强化与他人之间归属、支持和关怀的情感关联;(3)在互动中促进资源积累与抑制资源流失的资源关联;(4)导航资源流动方向与影响价值交换意愿的交换关联;资源和交换关联机制可辅助促进知识和情感关联机制。未来需更深入地探讨职场正念在数字化和AI技术、远程办公及职场多样化、公平与包容性文化和污名化管理等挑战性工作领域的人际作用。

基于双曲嵌入的露天矿区暗光环境下道路多目标检测模型

露天矿环境特殊,道路场景复杂多变,在光照不足时会导致矿区道路多目标识别不清、定位不准,进而影响检测效果,给矿区无人矿用卡车的安全行驶带来严重安全隐患。目前的道路障碍物检测模型不能有效解决矿区暗光环境对模型检测效果的影响,同时对矿区小目标障碍物的识别也有较大误差,不适用于矿区特殊环境下障碍物的检测与识别。针对上述问题,提出了一种基于双曲嵌入的露天矿区暗光环境下多目标检测模型。首先,在模型的图像预处理阶段引入卷积神经网路Retinex-Net对暗图像进行增强,提高图像清晰度;然后,针对数据集中特征过多而无重点偏好的问题,在加强特征提取部分添加全局注意力机制,聚集3个维度上更关键的特征信息;最后,在检测模型预测阶段引入双曲全连接层,以减少特征丢失,并防止过拟合现象。实验结果表明:(1)基于双曲嵌入的露天矿区暗光环境下道路多目标检测模型不仅对露天矿区暗光环境下的大尺度目标具有较高的分类与定位精度,对矿用卡车及较远距离的小尺度目标即行人也可准确检测与定位,能够满足无人矿用卡车在矿区特殊环境下驾驶的安全需求。(2)模型的检测准确率达98.6%,检测速度为51.52帧/s,较SSD、YOLOv4、YOLOv5、YOLOx、YOLOv7分别提高20.31%,18.51%,10.53%,8.39%,13.24%,对于矿区道路上的行人、矿用卡车及挖机的检测精度达97%以上。

城市道路网联混驾车辆分阶段动态轨迹控制方法

随着城市的进步和不断发展,智能驾驶车辆逐渐代替路段中的部分人工驾驶车辆,但在未来较长时间内人工驾驶车辆并不会被完全取代,此时出现网联车与人工驾驶车辆的混驾环境,即目前以及未来时间内我们面临的驾驶环境。网联车与人工驾驶车辆驾驶行为在路段内相互干扰,造成混合车流行驶效率低下。为减弱2种车辆间的相互作用,提出一种分离混驾环境下网联车和人工驾驶车辆的分阶段动态车道引导算法(dynamic lane guidance algorithm for separating CAVs and HDVs in mixed traffic environment,SCHME)。通过该算法分离在交叉口上游路段的混合流车辆集合,调整智能驾驶车辆的行驶路线并进行实时动态更新,在满足运动学约束收敛的条件下,人工驾驶车辆根据网联车的动态路线进行相应调整,实现在每辆车广义安全损失成本最小的情况下提高路段内混驾环境下车辆运行效率。通过MATLAB模拟车辆在进入交叉口前的车辆运行状态,结果表明,SCHME算法可在广义安全损失成本最小的情况下提高路段内平均车辆通行效率(17.29%),同时当车辆优化数组越大,车辆集合距离交叉口越远时,智能驾驶车辆渗透率越低,每辆车的道路广义安全损失成本越低。

行人过街事件网联HUD预警系统对驾驶行为的影响

为探索行人过街事件网联环境下平视显示预警系统在不同天气条件下对驾驶行为的影响,以论证预警系统的有效性。文中首先设计基线条件(Baseline)、低头显示(HDD)、平视显示(HUD)3种预警系统,依托驾驶模拟平台开发晴天和雾天天气条件下城市道路网联场景,通过实验测试提取驾驶行为参数;然后,从微观层面刻画行人过街事件网联HUD预警系统作用下驾驶行为的整个空间变化过程,分析预警系统和天气状况两种因素对驾驶行为的作用规律,构建包含避险阶段和恢复阶段的驾驶行为影响模式,提出了反映避险阶段安全水平、恢复阶段恢复水平以及全过程稳定水平等3个层面的综合指标体系,包括首次制动距离、最小冲突距离、恢复稳定时间、速度恢复量、最大减速度和最大加速度;最后,量化不同预警系统(Baseline/HDD/HUD)、天气状况(晴天/雾天)以及两因素间交互作用对驾驶行为的影响。结果表明:行人过街网联HUD预警系统对驾驶人在避险阶段和恢复阶段中的驾驶行为存在显著性作用,显著提高避险阶段驾驶行为的安全水平,同时对恢复阶段恢复效率具有明显的提升作用,也显著影响全过程运行特性的稳定水平;在雾天条件下行人过街网联HUD预警系统表现出更为明显的优势。

平陆运河内河段沿线河流水生生态影响识别

运河开发对区域交通改善和经济发展具有显著促进效应,然而其较大的开发强度和复杂的建设内容所造成的消极环境影响,已经受到越来越多的关注。针对运河水生生态影响的识别问题,通过对平陆运河内河段工程建设内容的分析归类,结合航道整治及航电枢纽建设的生态影响分析,采用类比分析、生态因子识别等方法,提出平陆运河内河段水生生态影响的3类重点评价内容,分析了建设内容对主要生态因子的影响,并从工程设计和生态修复两种维度梳理了水生生态保护措施体系。研究成果可为运河开发建设项目的生态环境影响识别与修复提供参考和借鉴。

营商环境与企业社会责任——基于中国私营企业调查的研究

已有研究探讨了营商环境组成部分的变化与企业社会责任(CSR)之间的关系,但尚未有文献研究整体营商环境的改善对CSR的影响。使用中国私营企业调查数据,研究发现,营商环境改善对企业的CSR履行有积极影响,而企业家政治关联则会削弱营商环境改善对CSR的积极影响。这一结论在经过一系列稳健性检验后仍然成立。进一步分析发现,营商环境改善仅会对企业的环境社会责任和公益社会责任(未扣除抵税效应)产生正向影响,但对企业的员工社会责任没有显著影响。同时,营商环境改善对CSR的积极影响在营商环境水平较高地区中更大。此外,机制分析表明,营商环境改善会通过经济激励和利他主义两个机制提高企业的CSR表现。

功能磁共振成像评估抑郁症心理治疗后脑功能变化研究进展

心理治疗是抑郁症广泛使用的疗法之一,但目前暂无明确的生物标志物作为疗效指标。使用功能磁共振成像(functional magnetic resonance imaging,fMRI)对抑郁症不同心理治疗前后进行影像学标志物评估,可见对应不同脑区激活及功能连接的改变,如认知行为疗法后患者前额叶皮质激活和动态功能连接变异性改变,正念疗法后颞叶部分脑区可见特征性改变。此外探讨特殊人群及结合互联网的心理干预研究发现其经心理治疗后存在脑区激活及功能连接的改变,这对相应心理治疗的疗效评估有指导意义。本文对不同心理治疗后抑郁症患者fMRI特征性脑区或脑网络改变进行综述,以期为抑郁症患者心理治疗结合脑影像学研究的未来方向做出探讨。

三峡工程运行背景下洞庭湖近25年来水生态环境的动态研究

三峡工程自2003年运行以来,对长江中下游水环境的影响备受关注。本研究基于25年来对洞庭湖11个点位的监测结果,分析了三峡工程运行背景下洞庭湖水情、水环境质量的时空变化特征,明确了洞庭湖水环境演变的主控因素。结果显示,1996—2015年,长江三口年均水量和输沙量分别为(1.83~10.46)×10^(10) m^(3)、(1.07~147)×10^(6) t,三峡工程运行后的入湖水量和输沙量分别降低了27%和87%;湖体主要水质指标总氮(total nitrogen,TN)浓度在1999—2022年显著上升,而总磷(total phosphorus,TP)浓度则明显下降,全湖处于中营养水平,而东洞庭湖则处于轻度富营养化水平;浮游藻类密度变化范围为(9.00~272.03)×10^(4) ind./L,且逐年上升,藻的优势类群逐渐由硅藻、隐藻向绿藻和蓝藻演替。整体来看,水文调节是维持洞庭湖营养平衡和水环境安全的关键要素。此外,加强农业面源污染控制,推进全面清洁生产,通过生境改善和生态修复来有效拦截入湖口及上游河流污染物是洞庭湖环湖经济带管理部门进行洞庭湖综合治理与水质提升的主要抓手。

卫星主动段力学环境监测系统设计

为精确获取卫星发射主动段星箭界面的加速度与界面力,设计了卫星主动段力学环境监测系统。系统由振动监测单元、振动传感器及应变片组成,其中,振动监测单元设计有3种工作模式——主动段测量模式、在轨振动数据分析模式及振动数据传输模式,采用基于应变的星箭界面动态载荷识别技术,具备6路振动力学传感器数据采集和24路应变数据采集能力。地面试验验证表明,该系统的振动测量精度达到10%,应变测量与LMS(LabVIEW Measurement Studio)系统应变采集数据之间的误差最大不超过4%。实际搭载中获得的星上主动段力学环境测量结果可为优化卫星分析模型和完善卫星地面力学环境模拟试验条件提供参考依据,并为卫星的后续研发与应用提供重要的技术支持。

基于思维导图的临床技能教学研究与应用——以心肺复苏课为例

在高等医学院校的临床教学中,师生间创建有效的教学联系对于提高临床教学效率和教学质量具有重要意义。本研究借助思维导图展现师生间的教学联系,将课前学情与学生需求、课堂出勤、课后学生反馈和教师反馈等复杂抽象的教学元素转变为直观形象的教学关系图,使师生间联系更加可视化、脉络化。结合临床实验教学要求,通过将思维导图应用在2016级本科生心肺复苏术临床技能课程教学中,协助师生建立了有效的教学联系,加强教学沟通,同时优化了临床教学方案,应用效果显著。

Three-phase Enriched Environment Improves Post-stroke Gait Dysfunction via Facilitating Neuronal Plasticity in the Bilateral Sensorimotor Cortex:A Multimodal MRI/PET Analysis in Rats

The three-phase Enriched Environment(EE)paradigm has been shown to promote post-stroke functional improvement,but the neuronal mechanisms are still unclear.In this study,we applied a multimodal neuroimaging protocol combining magnetic resonance imaging(MRI)and positron emission tomography(PET)to examine the effects of post-ischemic EE treatment on structural and functional neuroplasticity in the bilateral sensorimotor cortex.Rats were subjected to permanent middle cerebral artery occlusion.The motor function of the rats was examined using the DigiGait test.MRI was applied to investigate the EE-induced structural modifications of the bilateral sensorimotor cortex.[^(18)F]-fluorodeoxyglucose PET was used to detect glucose metabolism.Blood oxygen level-dependent(BOLD)-functional MRI(fMRI)was used to identify the regional brain activity and functional connectivity(FC).In addition,the expression of neuroplasticity-related signaling pathways including neurotrophic factors(BDNF/CREB),axonal guidance proteins(Robo1/Slit2),and axonal growth-inhibitory proteins(NogoA/NgR)as well as downstream proteins(RhoA/ROCK)in the bilateral sensorimotor cortex were measured by Western blots.Our results showed the three-phase EE improved the walking ability.Structural T2 mapping imaging and diffusion tensor imaging demonstrated that EE benefited structure integrity in the bilateral sensorimotor cortex.PET-MRI fused images showed improved glucose metabolism in the corresponding regions after EE intervention.Specifically,the BOLD-based amplitude of low-frequency fluctuations showed that EE increased spontaneous activity in the bilateral motor cortex and ipsilateral sensory cortex.In addition,FC results showed increased sensorimotor connectivity in the ipsilateral hemisphere and increased interhemispheric motor cortical connectivity and motor cortical-thalamic connectivity following EE intervention.In addition,a strong correlation was found between increased functional connectivity and improved motor performance of limbs.Specifically,EE regulated the expression of neuroplasticity-related signaling,involving BDNF/CREB,Slit2/Robo1,as well as the axonal growth–inhibitory pathways Nogo-A/Nogo receptor and RhoA/ROCK in the bilateral sensorimotor cortex.Our results indicated that the three-phase enriched environment paradigm enhances neuronal plasticity of the bilateral sensorimotor cortex and consequently ameliorates post-stroke gait deficits.These findings might provide some new clues for the development of EE and thus facilitate the clinical translation of EE.

交叉口网联车速度与信号协同优化控制

网联环境下,为了提升信号交叉口绿灯利用效率,根据网联车与交通设施之间交互的车辆速度、位置及信号状态信息,提出一种单点信号交叉口网联车速度与信号配时协同优化控制方法。该方法基于车队离散理论,预测交叉口车辆到达率并根据预测结果优化交叉口信号配时。在此基础上,以周期内总排队车辆数最小为优化目标,对每辆网联车通过交叉口速度进行判断,按照车辆编号次序求解网联车的最佳行驶速度,实现速度引导与交叉口信号控制有效协调。采用MATLAB软件对模型进行仿真分析。研究结果表明,经信号优化与速度引导协同优化后,提出的速度引导与信号协同控制方法能够在相同时间内增加通过交叉口的车辆数,减少车辆延误,并有效提升交叉口交通效率。

国外城市建成环境与共享单车研究评述与展望

文章对国外城市建成环境与共享单车的研究主题、研究方法、研究趋势展开了综述。首先阐述了交通路网、社会经济因素、土地利用、绿化空间四类建成环境与共享单车的联系;其次,对比了传统与新兴的研究方法,并分析各类研究方法的适用性以及不足;最后,总结了国外共享单车的研究现状,并对未来的研究重点进行了探究与展望。

基于Dilated ADU-Net的开放环境下的舌象分割算法

舌象的精准分割是能否获得正确舌象诊断结果的重要前提。针对在自然光照条件下传统分割算法难以精确、稳定地分割舌体图像的难题,构建一种融合空洞卷积双注意力机制与密集连接机制的改进型U-Net舌象分割模型(Dilated Attention&Dense U-Net,Dilated ADU-Net)。首先,基于U-Net网络的对称结构搭建主干网络;然后,下采样模块采用空洞型混合注意力模块,使网络聚焦于舌体特征,上采样模块采用密集连接机制融合多层特征信息;最后,采用开放环境下的舌象数据集对网络进行训练获得舌象分割模型。通过实验验证,和其他先进的分割方法相比,本文构建的舌象分割模型平均交并比(mean Intersection over Union,mIoU)达到96.73%,相似系数(Dice Similarity Coefficient,DSC)达到98.08%,具有更好的分割性能,可以实现复杂环境下舌象的精准分割。

多路水电混用快速插拔系统的设计及应用

为了实现多路水、电连接与断开的自动化操作,开发了一种多路水电混用快速插拔系统。系统由插拔板、驱动机构、控制模块等组成,核心部件插拔板结构包括动板、定板、电连接器、流体连接器、导向结构、浮动对接结构等。采用了一种双流道密封直插直拔式流体连接器,解决了流体带压插拔的技术难题,设计了浮动对接结构,在一定位置偏差情况下插拔板仍能准确对接。为测试样机产品使用效果,同步研发并加工了测试试验机。测试结果表明,导向的最优配合间隙为0.2mm,经2000次插拔测试,产品运行稳定,使用效果良好。

生态环境“两法衔接”中检察监督的困境与出路

从生态环境“两法衔接”中检察监督的制度现状看,检察监督存在着法律制度的供给不足、保障机制不完善和监督手段刚性不足三个方面的问题。法律制度的供给不足主要表现为移送监督缺乏上位法基础、检察监督程序不健全、检察监督的启动标准不明确问题。保障机制的不完善主要体现为信息共享机制不顺、内部衔接工作不畅以及检察队伍专业性不强的问题。建议首先要健全“两法衔接”中检察监督的相关立法,在法律层面明确移送监督、完善检察监督的程序性规定、明晰检察监督的启动标准;其次,信息共享平台的建设由司法行政机关联合工信部门和环境执法部门协同建设,完善法律监督的数字化建设,招募环境学科的人员以充实检察队伍;最后,借助同级政府和同级党委的力量强化检察监督手段的刚性。