Evaluating the influence of 6 MV and 15 MV photon beams on prostate intensity-modulated radiation therapy plans

Objective We aimed to determine the ef ects of low- and high-energy intensity-modulated radiation therapy （IMRT） photon beams on the target volume planning and on the critical organs in the case of prostate can-cer. Methods Thirty plans were generated by using either 6 MV or 15 MV beams separately, and a combination of both 6 and 15 MV beams. Al plans were generated by using suitable planning objectives and dose con-straints, which were identical across the plans, except the beam energy. The plans were analyzed in terms of their target coverage, conformity, and homogeneity, regardless of the beam energy. Results The mean percentage values of V70 Gy for the rectal wal for the plans with 6 MV, 15 MV, and mixed-energy beams were 16.9%, 17.8%, and 16.4%, respectively, while the mean percentage values of V40 Gy were 53.6%, 52.3%, and 50.4%. The mean dose values to the femoral heads for the 6 MV, 15 MV, and mixed-en-ergy plans were 30.1 Gy, 25.5 Gy, and 25.4 Gy, respectively. The mean integral dose for the 6 MV plans was 10% larger than those for the 15 MV and mixed-energy plans.Conclusion These preliminary results suggest that mixed-energy IMRT plans may be advantageous with respect to the dosimetric characteristics of low- and high-energy beams. Although the reduction of dose to the organs at risk may not be clinical y relevant, in this study, IMRT plans using mixed-energy beams exhibited better OAR sparing and overal higher plan quality for deep-seated tumors.

Analysis of the Application of Static Load Test in Bridge Bearing Capacity Testing

This article uses real engineering projects as examples to analyze how static load test technology is applied in testing the bridge-bearing capacity.The analysis covers aspects such as testing section layout,test load and efficiency coefficient,loading plan,evaluation optimization,test result modification,and result evaluation.The aim is to support the accurate detection and evaluation of bridge-bearing capacity.

Dosimetric consequences of tumor volume changes after kilovoltage cone-beam computed tomography for non-operative lung cancer during adaptive intensity-modulated radiotherapy or fractionated stereotactic radiotherapy

Objective The aim of this study was to investigate tumor volume changes with kilovoltage cone-beam computed tomography （kV-CBCT） and their dosimetric consequences for non-operative lung cancer during intensity-modulated radiotherapy （IMRT） or fractionated stereotactic radiotherapy. Methods Eighteen patients with non-operative lung cancer who received IMRT consisting of 1.8-2.2 Gy/fraction and five fractions per week or stereotactic radiotherapy with 5-8 Gy/fraction and three fractions a week were studied, kV-CBCT was performed once per week during IMRT and at every fraction during stereotactic radiotherapy. The gross tumor volume （GTV） was contoured on the kV-CBCT images, and adaptive treatment plans were created using merged kV-CBCT and primary planning computed tomogra- phy image sets. Tumor volume changes and dosimetric parameters, including the minimum dose to 95% （D95） or 1% （D1） of the planning target volume （PTV）, mean lung dose （MLD）, and volume of lung tissue that received more than 5 （Vs）, 10 （Vl0）, 20 （V20）, and 30 （V30） Gy were retrospectively analyzed. Results The average maximum change in GTV observed during IMRT or fractionated stereotactic radio- therapy was -25.85% （range, -13.09% --56.76%）. The D95 and Dr of PTV for the adaptive treatment plans in all patients were not significantly different from those for the initial or former adaptive treatment plans. In patients with tumor volume changes of 〉20% in the third or fourth week of treatment during IMRT, adap- tive treatment plans offered clinically meaningful decreases in MLD and V5, V10, V20, and V30; however, in patients with tumor volume changes of 〈 20% in the third or fourth week of treatment as well as in patients with stereotactic radiotherapy, there were no significant or clinically meaningful decreases in the dosimetric parameters. Conclusion Adaptive treatment planning for decreasing tumor volume during IMRT may be beneficial for patients who experience tumor volume changes of 〉20% in the third or fourth week of treatment.

Comparison between 4D robust optimization methods for carbon-ion treatment planning

Intensity-modulated particle therapy(IMPT)with carbon ions is comparatively susceptible to various uncertainties caused by breathing motion,including range,setup,and target positioning uncertainties.To determine relative biological effectiveness-weighted dose(RWD)distributions that are resilient to these uncertainties,the reference phase-based four-dimensional(4D)robust optimization(RP-4DRO)and each phase-based 4D robust optimization(EP-4DRO)method in carbon-ion IMPT treatment planning were evaluated and compared.Based on RWD distributions,4DRO methods were compared with 4D conventional optimization using planning target volume(PTV)margins(PTV-based optimization)to assess the effectiveness of the robust optimization methods.Carbon-ion IMPT treatment planning was conducted in a cohort of five lung cancer patients.The results indicated that the EP-4DRO method provided better robustness(P=0.080)and improved plan quality(P=0.225)for the clinical target volume(CTV)in the individual respiratory phase when compared with the PTV-based optimization.Compared with the PTV-based optimization,the RP-4DRO method ensured the robustness(P=0.022)of the dose distributions in the reference breathing phase,albeit with a slight sacrifice of the target coverage(P=0.450).Both 4DRO methods successfully maintained the doses delivered to the organs at risk(OARs)below tolerable levels,which were lower than the doses in the PTV-based optimization(P<0.05).Furthermore,the RP-4DRO method exhibited significantly superior performance when compared with the EP-4DRO method in enhancing overall OAR sparing in either the individual respiratory phase or reference respiratory phase(P<0.05).In general,both 4DRO methods outperformed the PTV-based optimization in terms of OAR sparing and robustness.

基于改进动态窗口的车库AGV路径规划及仿真

针对在智能车库环境下,移动机器人(AGV)在作业过程中面临着复杂路径环境下的路径规划和实时避障,提出一种改进的蚁群算法与动态窗口法(DWA)相结合的混合算法。在全局规划中引入自适应调整信息素挥发系数,融合角度参数建立车库方向信息素矩阵,增大目标点引导能力,扩大蚂蚁的方向选择性;在局部规划中设计基于椭圆方程的障碍物距离评价子函数的改进动态窗口法,并提取改进蚁群算法的全局关键节点作为新增的路径评价子函数,在全局路径的约束下,保持动态规划的最优性。仿真结果表明:改进算法较传统算法能够较好地应对突发的动静态障碍物,更符合AGV实际作业过程中在多重环境因素的影响下的动态规划要求。

风机叶片巡检机器人快速检测路径规划算法

提出一种基于风力机叶片仿真分析的巡检机器人快速检测方法,通过对风机叶片进行静强度仿真分析得到其应力云图,基于云图模型进行环境建模,针对传统A^(*)算法提出改进,进行了权重值改进、拐角优化以及路径平滑处理,并针对不同情况分别进行仿真分析对比实验。实验结果表明,所设计方案可以改进算法搜索效率,在完成既定目标的前提下缩短了路径长度,减少了搜索时间,可以实现风机叶片巡检机器人快速检测任务。

计及静态电压稳定性的风光电站选址定容协同规划方法

为了降低风光电站并网给电力系统电压稳定性带来的负面影响,提出了计及静态电压稳定性的风光电站选址定容协同规划方法。分析了风光电站的发电特性,并对其建立数学模型;考虑并网等值阻抗和静态电压稳定性的内在制约关系,进一步综合风光电站及其汇集站选址定容、并网点位置等优化目标,建立了风光电站选址定容协同规划模型;基于地图栅格化和分段线性化方法,将所提规划模型转换为混合整数线性规划模型;在此基础上,利用K-means算法提取典型场景,并给出了所提模型的求解流程。基于西南某地区的实际数据进行算例验证,结果表明所提规划方法能够充分发挥规划区域内自然资源的禀赋特性和风光发电互补性,有效提高了风光电站并网后的静态电压稳定性。

基于MDP的无人机避撞航迹规划研究

无人机(UAV)进行避撞前提下的目标搜索航迹规划是指在复杂且众多的环境障碍约束中通过合理规划飞行路径,以更快、更高效的形式找到目标;研究了无障碍环境条件下有限位置马尔科夫移动的规律,构建了相应的马尔科夫移动分布模型;在借鉴搜索系统航迹规划的前沿研究成果之上,结合马尔科夫决策过程理论(MDP),引入了负奖励机制对Q-Learning策略算法迭代;类比“风险井”的可视化方式将障碍威胁区域对无人机的负奖励作用直观地呈现出来,构建了复杂障碍约束环境下单无人机目标搜索航迹规划模型,并进行仿真实验证明该算法可行,对航迹规划算法的设计具有一定的参考意义。

Status quo and Existing Problems of Seismic Prevention Planning in Counties and Districts——a Case Study of Hongsibao District, Wuzhong City,Ningxia Hui Autonomous Region

This paper introduced domestic and overseas status, the historical evolution and the development history of earthquake disaster reduction planning. The urgencies and realistic significance were analyzed to carry out earthquake disaster reduction planning for districts or countries in the northwest. With Hongsibao District in Wuzhong City, Ningxia Province as an example, this article analyzed in detail the present situation and the special problems of earthquake disaster reduction planning in Northwest China. The relevant solving measures were put forward in order to offer a reference for the scientific establishment and effective implementation of earth- quake disaster reduction planning in Northwest China. The foundation of earthquake disaster reduction in the Hongsibao District is still very weak, there is a single earthquake monitoring means, the emergency rescue system is not complete, the working mechanism is not perfect, and the lack of funding for the work of earthquake disaster reduction.

基于SLAM算法和动静态规划的电厂智能巡检机器控制研究

巡检机器控制是电厂巡检自动化和智能化技术的核心,但现行方法在实际应用中存在一些不足和缺陷,不仅控制路径平滑系数较低,而且存在碰撞问题,智能巡检机器避障性能较差,无法达到预期的控制效果,为此提出基于SLAM(Simultaneous Localization And Mapping)算法和动静态规划的电厂智能巡检机器控制方法。利用激光雷达和相机获取巡检环境信息,采用YOLOv3对图像增强,通过点云旋转去除激光点云中离散点,实现对点云数据增强,采用SLAM算法对巡检环境图像和激光点云融合,构建巡检地图和定位巡检机器,采用动静态规划根据环境信息动态调整巡检机器运动轨迹,从而实现对电厂智能巡检机器导航跟踪控制。经实验证明,应用设计方法后,巡检机器路径平滑系数在0.9以上,未发生碰撞,该方法在电厂智能巡检机器控制方面具有良好的应用前景。

考虑电量出力行为的输电线路规划方法研究

为了解决传统输电线路规划方法存在的网损电量较大、规划效果不佳的问题,设计了考虑电量出力行为的输电线路规划方法。首先,通过非线性方程拟合,建立了电量出力行为约束条件。然后,通过计算电网潮流量的方式,完成了电量出力行为量化计算。最后,根据电量出力行为的数值水平,确定静态电压灵敏度指标的数值水平;联合规划系数修正表达式,实现了输电线路规划方法设计。对比试验结果表明:所提方法可以准确计算35 kV、110 kV电网组织中的电量出力行为,能够将网损电量控制在既定数值标准之下。应用此方法规划电力网络输电线路,能够有效控制网损电量,实现对应用电网的合理规划。该方法满足实际应用需求。

久坐及不同运动方案对静态平衡能力的影响

目的:评定久坐以及核心稳定性练习(CSE)、骨骼肌肥大练习(MHE)、无氧间歇练习(AER)和持续性有氧练习(ANA)对平衡能力的影响,为警校学员精准运动训练提供依据。方法:采用文献资料法、实验法、数理统计法等研究方法,随机选择30名健康青年男性受试者分别完成6 h间歇久坐测试和4个不同的运动方案后进行平衡能力测试,并记录运动中的心率(HR)、运动后过量氧耗(EPOC)和运动冲量(TRIMP)。结果:(1)运动负荷方面,相较安静状态,4种运动方案运动后HR、EPOC和TRIMP均显著增加(P<0.05)。其中,AER和ANA运动方案运动后HR和EPOC显著高于CSE和MHE(P<0.05),ANA运动方案运动后TRIMP显著高于其他3种运动方案(P<0.05)。(2)平衡能力方面,与晨测值相比,久坐后的动摇总轨迹长、X轴动摇轨迹长和最大动摇径以及Y轴重心偏移指标显著增加(P<0.05);4种运动方案运动后动摇总轨迹长、X轴轨迹长和Y轴轨迹长均显著增加(P<0.05);与久坐相比,4种运动方案运动后Y轴重心偏移均显著降低(P<0.05)。(3)不同运动方案之间,AER和ANA运动方案运动后除动摇角度和重心偏移指标外,其余指标均显著高于CSE和MHE(P<0.05)。其中,CSE运动方案运动后Y轴轨迹长、Y轴最大动摇径和单位面积轨迹长均显著高于MHE(P<0.05),ANA运动方案运动后动摇总轨迹和Y轴轨迹长较AER运动方案运动后显著增加(P<0.05)。除AER运动方案外,其余运动方案在20 min休息后,平衡能力基本恢复至久坐后的状态。结论:整体上,6 h间歇久坐后,躯干前倾,可对静态平衡能力产生不利的影响;4个常用运动方案均可用于抵消久坐带来的不利影响,但影响幅度存在不同。

基于群智能优化算法的船舶最优运输路线规划

为规避海洋运输环境中潜在的静态障碍风险区域,并进行平滑、动态避障,降低船舶碰撞风险,研究基于群智能优化算法的船舶最优运输路线规划方法。利用正六边形网格划分方法构建船舶运输所处海洋环境模型;建立基于群智能优化算法的运输航线规划模型,在构建的正六边形网格海洋环境中,动态规划运输避障路径,规划目标为避障过程航行距离与复航路径长度最小化,使用蜘蛛猴算法,求解满足目标函数以及约束条件的本船航行至动态避障转向点的时间、动态避障航向变动量、动态避障转向行为至复航的时间、复航时航向变动量4个规划变量,作为船舶最优运输路线规划方案,实现船舶最优运输路线规划。经测试,所研究方法在存在静态障碍、动态障碍的海况中,规划运输路线后,船舶未出现碰撞风险,且路线平滑。

基于DDPG算法的海运船舶避碰路径规划方法

针对多船舶会遇情况,以提高避碰路径规划能力,本文提出了一种基于深度确定策略梯度算法(deep deterministic policy gradient,DDPG)的海运船舶避碰路径规划方法。利用栅格法建立船舶航行路线的静态全局环境,并利用人工蜂群算法设计静态初始路径。针对多船会遇情况,计算海运船舶与其他船舶发生碰撞的危险程度,以危险程度作为DDPG算法的输入参数,通过训练与学习输出海运船舶避碰路径的规划结果。实验表明:经过本文方法的规划后,海运船舶安全避开了另外三艘船舶,未发生碰撞事故,安全到达目标点,证明本文方法规划的线路避碰性能更强,提高了海运船舶航行的安全性。

Seismic performance evaluation procedure of asymmetric plan structures

Plan asymmetry leads to lateral-rotational coupled effects on structural response characteristics.This investigation deals with a simplified method for performance estimation of structures with asymmetric plan.By taking the eccentric characteristics of structures into account,an equivalent triple-degree of freedom (ETDOF) system,which is constructed by eccentric mass,rigid links and springs,is proposed.The modal pushover analysis (MPA) method for asymmetric plan structures is proposed.The target displacement is determined by constant strength spectrum.The applicability of proposed method is discussed.A generic mass eccentric 4-story steel frame is analyzed by the proposed MPA procedure and nonlinear time history analysis (NTHA).The results show that the maximum deformation obtained from MPA has a good agreement with the NTHA results.The proposed MPA procedure is reliable and effective for evaluating the performance of asymmetric plan structures.

The collision-free trajectory planning for the space robot to capture a target based on the wavelet interpolation algorithm

In the research of path planning for manipulators with many DOF, generally there is a problem in most traditional methods, which is that their computational cost (time and memory space) increases exponentially as DOF or resolution of the discrete configuration space increases. So this paper presents the collision-free trajectory planning for the space robot to capture a target based on the wavelet interpolation algorithm. We made wavelet sample on the desired trajectory of the manipulator’s end-effector to do trajectory planning by use of the proposed wavelet interpolation formula, and then derived joint vectors from the trajectory information of the end-effector based on the fixed-attitude-restrained generalized Jacobian matrix of multi-arm coordinated motion, so as to control the manipulator to capture a static body along the desired collision-free trajectory. The method overcomes the shortcomings of the typical methods, and the desired trajectory of the end-effector can be any kind of complex nonlinear curve. The algorithm is simple and highly effective and the real trajectory is close to the desired trajectory. In simulation, the planar dual-arm three DOF space robot is used to demonstrate the proposed method, and it shows that the algorithm is feasible.

基于多目标PSO-ACO融合算法的无人艇路径规划

【目的】针对河蟹养殖过程中,水位变化以及无人艇路径规划算法收敛慢、精度低的问题,为提高算法适应性与寻优能力,提出一种多目标粒子群−蚁群融合的无人艇路径规划算法。【方法】首先,分析蟹塘环境及养殖规律等因素,建立静态水深栅格环境模型;其次,针对覆盖遍历式投饵存在局部点投喂不足及路径次优的问题,通过对惯性参数与学习因子的非线性调整,提出基于多目标的改进粒子群算法(Particle swarm optimization,PSO);然后,调整蚁群算法的初始信息素,并对蚁群算法的信息素挥发因子和启发期望函数自适应改进,提出自适应优化蚁群算法(Ant colony optimization,ACO);最后,为解决单一算法寻优不足,利用融合PSO-ACO算法,实现无人艇多目标全局路径规划。【结果】仿真结果表明:不同环境投饵策略下,PSO-ACO算法在对多目标路径寻优时,不仅环境适应性好,而且提高了寻优效率和精度,运行时间节省了32%,路径距离缩短了9.78%,迭代次数降低了62.88%,拐点数目减少了44.45%。【结论】所提出多目标点的路径规划算法适用于环境可变的蟹塘养殖,具有较好的应用价值。

基于宏微结合的田间作业机器人路径规划

农业机器人对推动农业现代化加速变革和实现智慧农业有重要作用。高精度定位技术是保障机器人安全高效完成各类作业的基础,而作业路径准确规划是实现农业场景下导航的核心。针对田间作业机器人复杂环境下因测绘误差与局部障碍进而造成作物损伤率较大这一问题,本文提出一种基于宏微结合的路径规划算法,该算法首先基于作业区域宏观测绘信息生成全局静态作业路径,同时利用雷达传感器对机器人局部作业环境进行实时动态监测进而生成局部动态最优路径,将全局静态路径与局部动态路径进行有机融合以实现作业路径优化修正,保障田间作业的顺利进行,最终应用MPC算法控制机器人对规划后的路径进行追踪。经试验验证,当机器人田间作业两侧安全距离分别为0.2、0.1 m时,本算法可将作业过程中平均作物损伤率由3.405 8%、1.276 3%降低到0.677 2%、0.188 9%,保证了机器人作业的安全可靠,为大田稳产条件下的高效作业奠定基础。同时,本算法提升了精准农业要求下田间作业精度,对实现农业高产高效高质目标有重要意义。

美国大学校园静态交通规划的经验与启示

“停车难,乱停车”等静态交通问题是日益突出的大学校园规划难题。针对大学校园静态交通,美国较早就开始了其探索过程,拥有丰富的规划理论与实践经验。基于对近年内发布的美国大学校园规划更新文件与交通专项规划文件的研读与分析,系统总结美国大学校园静态交通规划设计策略,包括成体系的校园静态交通规划架构、精准量化的研究分析法、全面的交通需求管理策略、合理的静态交通规划设计模式、完善的静态交通管理策略。进而,提出对我国大学校园静态交通规划的几点启示,建议调整单向线性设计思维,构建多维体系设计思维;改变“一刀切”的粗放计算,探索精准量化的停车需求预测方法;引入适应性交通需求管理策略,重点倡导公交出行;静态交通规划设计注重发挥“以静制动”作用;逐步完善静态交通管理机制与策略。

输电线路智能融冰辅助决策关键技术研究与实现

冰雪天气是对电力系统稳定运行影响最大的自然灾害之一,会造成输电线路覆冰,危害电网安全运行。本文围绕输电线路融冰方案编制的流程展开,针对流程中的重点和难点步骤,研究辅助决策的智能技术,以提高电网调控中心融冰方案编制质量和时效性。具体如下:针对实际电网运行数据和覆冰数据进行预处理,实现了多源数据融合,基于深度优先算法进行可停电融冰线路分析;采用加权均值综合评判的方法,基于多指标对融冰线路进行优先级排序和组合;基于直流潮流支路开断分布因子的评估方法,对融冰方案进行快速校核;基于多机多任务并行处理技术,对融冰方案进行详细校核,以此来提高输电线路融冰方案安排效率,保证电网在冰雪天气的安全稳定运行。