Impact of prehospital medical evacuation (MEDEVAC) transport time on combat mortality in patients with noncompressible torso injury and traumatic amputations: a retrospective study

Background: In combat operations, patients with traumatic injuries require expeditious evacuation to improve survival. Studies have shown that long transport times are associated with increased morbidity and mortality. Limited data exist on the influence of transport time on patient outcomes with specific injury types. The objective of this study was to determine the impact of the duration of time from the initial request for medical evacuation to arrival at a medical treatment facility on morbidity and mortality in casualties with traumatic extremity amputation and noncompressible torso injury(NCTI).Methods: We completed a retrospective review of MEDEVAC patient care records for United States military personnel who sustained traumatic amputations and NCTI during Operation Enduring Freedom between January 2011 and March 2014. We grouped patients as traumatic amputation and NCTI(AMP+NCTI), traumatic amputation only(AMP),and neither AMP nor NCTI(Non-AMP/NCTI). Analysis was performed using chi-squared tests, Fisher's exact tests,Cochran-Armitage Trend tests, Shapiro-Wilks tests, Wilcoxon and Kruskal-Wallis techniques and Cox proportional hazards regression modeling.Results: We reviewed 1267 records, of which 669 had an injury severity score(ISS) of 10 or greater and were included in the analysis. In the study population, 15.5% sustained only amputation injuries(n=104, AMP only), 10.8% sustained amputation and NCTI(n=72, AMP+NCTI), and 73.7% did not sustain either an amputation or an NCTI(n=493,Non-AMP/NCTI). AMP+NCTI had the highest mortality(16.7%) with transport time greater than 60 min. While the AMP+NCTI group had decreasing survival with longer transport times, AMP and Non-AMP/NCTI did not exhibit the same trend.Conclusions: A decreased transport time from the point of injury to a medical treatment facility was associated with decreased mortality in patients who suffered a combination of amputation injury and NCTI. No significant association between transport time and outcomes was found in patients who did not sustain NCTI. Priority for rapid evacuation of combat casualties should be given to those with NCTI.

An experimental analysis on the turnover time of railway freight transportation based on the impact strength of factors

Based on the factors impact strength model(FISM), we studied on calculation formulas of influence strength and key elements of FISM, and analyzed the turnover time of railway freight transportation of China. The results show that wagon transfer time is the most critical factor among the three subjective factors of wagons turnover time. The FISM based analysis of wagon transfer time show that the wagon turnover time is significantly correlated with transit time with resorting. Among the seven factors of detention time of transit time with resorting, the time of waiting to departing, converging, and waiting to break-up are key factors, while the time of make-up, break-up, arrival and departure are general factors. We carried out one empirical research based on the data of Baoji East Railway Station in 2015. The results of empirical research and FISM are consistent completely.

Optimal paths planning in dynamic transportation networks with random link travel times

A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.

New Procedure of Finding an Initial Basic Feasible Solution of the Time Minimizing Transportation Problems

Minimization of transportation time is a great concern of the transportation problems like the cost minimizing transportation problems. In this writing, a transportation algorithm is developed and applied to obtain an Initial Basic Feasible Solution (IBFS) of transportation problems in minimizing transportation time. The developed method has also been illustrated numerically to test the efficiency of the method where it is observed that the proposed method yields a better result.

New Approach to Find Initial Basic Feasible Solution (IBFS) for Optimal Solution in Transportation Problem

Minimizing transportation time and getting optimal solutions are always considered as important factors while solving transportation problem. This paper shows a new approach for finding initial basic solution for transportation problem which reduces cost of transportation more than any transportation method such as LCM, northwest, Vogel’s approximation and so on. This method has been illustrated by taking an example;afterwards, it compares basic initial feasible solution with other methods IBF and optimal dictate solutions such as MODI and Steppingstone method.

Time-Dependent Sediment Transport Subjected to Downward Seepage

Experiments were conducted using cohesionless sand particles with median diameter of 0.48 mm to investigate the time variation of sediment transport rate under the influence of local downward seepage.The experimental results show that the bedload transport rate in terms of volumetric sediment transport rate per unit width increased rapidly with time in the presence of suction,eventually reaching a peak beyond which it started to decrease.The trend of reduction was significantly reduced beyond 8 400 s after the test started.The analytical expression was derived in terms of dimensionless sediment transport rate and dimensionless time.The hypothesized relationships were compared with the experimental data,indicating a good agreement with each other.

基于信息传输时变时延的车辆队列纵向稳定性控制算法

智能网联车辆队列行驶面临复杂的交通环境,所引发的时延、丢包等信息传输问题将导致队列车辆行驶稳定性降低而亟待解决.针对复杂交通环境,引入信息新鲜度(age of information, AoI)并提出了一种适应时变时延的智能网联车辆队列行驶稳定性控制算法.该控制算法根据队列中多前车信息新鲜度来调整其对队列车辆车头间距影响的权重,同时依据时变时延信息预测队列中跟驰车辆与前车的车头间距,队列车辆按照请求周期向路侧单元(road side unit, RSU)实时发送请求,RSU依据车辆间距从小到大依次回应请求队列中的各个车辆,以控制其因时变时延可能造成的碰撞.数值仿真结果显示,相对智能驾驶员模型(intelligent driver model, IDM)而言,所提出的队列纵向稳定性控制算法具有更好的控制效果.针对时变时延发生概率20%的车车通信,队列车辆车头间距偏差的降低比例达6.4%,平均峰值信息新鲜度的降低比例达8.7%.同时,分析了队列车辆请求周期和回应请求车辆数量对队列纵向稳定性的影响,随着两者数值增加,控制算法给出的队列纵向稳定性分别呈现降低和增加的趋势.最后,实车测试了队列切出场景下车辆行驶数据和车辆接收信息的时延数据,将其引入数值仿真实验中.结果表明,车头间距偏差降低比例达15%.

含不相关机的多目标混合流水车间调度

考虑不相关机和传送等因素的多阶段混合流水车间问题,以最小化最大完工时间和总能耗为优化目标建立整数规划模型。针对该问题,提出一种多目标离散灰狼优化算法来求解。设计基于机器分配码和速度选择码的编码方式和基于最短处理时间原则的解码方案;采用反向学习策略改进初始灰狼种群质量;将基于多点变异的自走模式和基于均匀两点交叉与多点交叉的跟随模式结合构成搜索模式以协调开发和搜索能力;引入精英保留策略确保优良个体不丢失。通过一系列的仿真实验验证了该算法的有效性。

Jump Drive, Replicators, Transporters, and Time Travel

Jumping from place to place, replicating food, biological or mechanical parts or beaming up somebody, may not be fiction, rather an issue of practical implementation as shall be observed in this paper. Devices like transporter, food replicators or warp drive intrigue our imagination. This paper is intended to show that Jump drive is an issue of coordinate transformation. Changing location from planet X to planet Y does not necessarily require travelling a distance D connecting between the two planets. The theoretical knowledge of changing the location from coordinate X to coordinate Y exists;we do that in signal processing, but, we have not yet developed such a machine. The present paper shows the feasibility of jump drive;however, much work needs to be done on the implementation.

带运输的混合流水车间调度问题的改进遗传算法

为实现分布式制造环境中上下游工序和机器间的协同生产,研究了带有运输的混合流水车间调度问题。以包含加工时间、运输时间和加工等待时间的完工时间最小为目标,建立了带有运输约束的混合流水车间调度模型,基于Q-learning设计了改进的遗传算法(QGA)求解该模型。在该算法中,首先基于工件序号设计编码和遗传算子等遗传操作;然后根据种群适应度函数构建种群的状态集合,以交叉概率和变异概率的取值作为动作,以最佳个体适应度和种群平均适应度作为奖励;最后采用Q-learning对交叉和变异参数进行智能调整,提高算法的收敛速度与全局搜索能力。仿真实验结果表明,与改进的遗传算法(GA-TS)相比,本文QGA的最大完工时间平均减少了2.0%,收敛速度提升了18.1%。

基于改进时空图卷积网络的道路行程时间预测模型

为提高道路网行程时间预测精度,综合考虑行程时间的空间依赖性、时间依赖性和天气因素影响,提出了基于属性增强和注意力机制的时空图卷积网络模型.首先,构建属性增强单元,将行程时间和天气信息融合;然后,利用图卷积网络捕获空间依赖性,利用门控递归单元捕获时间依赖性,并利用注意力机制增强模型对特征的学习;最后,利用该模型在真实数据集上对未来15、30、45和60 min的行程时间进行预测.结果表明:预测结果的均方根误差(RMSE)分别为0.0453、0.0456、0.0457和0.0468,与其他模型相比表现更优;考虑了时间、空间和天气因素后,相较于不考虑天气的情况,预测误差降低了约10.3%;相较于不考虑空间依赖性的情况,降低了约24.2%,表明所提模型能更好表达时空依赖性和外部条件影响.

基于CiteSpace的公交停靠时间影响因素分析

为了降低公交停靠时的延误,以便于合理地进行公交站规划设计。通过利用CiteSpace对公交停靠时间领域文献进行研究。根据得到的图谱对当前的研究热点和以后的研究方向进行总结分析。结果表明,我国对公交停靠时间的研究可分为两个阶段,探索发展和钻研创新阶段,而近期研究热点偏向遗传算法和智能交通方向。精读文献后得出影响公交停靠时间的因素为乘客上下车时间和公交车加减速时间,同时结合站台形式这个特殊的影响因素进行了分类分析,为今后的公交停靠站设计提供参考。

基于HPO-LSTM的公交周转时间预测

公交周转时间的准确预测是公交智能排班的基础和前提,是制定行车时刻表的关键。为提高公交周转时间的预测精度,提出了基于猎人猎物优化长短时记忆神经网络(HPO-LSTM)的公交周转时间预测模型,将长短时记忆神经网络(LSTM)中的超参数(隐含层节点数、迭代循环数以及初始学习率)映射为猎人猎物优化算法(HPO)种群的位置;以LSTM模型预测值与真实值产生的均方根误差E_(RMS)作为种群适应度函数,优化种群位置,实现LSTM神经网络超参数寻优;用最优超参数构建LSTM神经网络,进行公交周转时间预测。采用某市公交1号线数据对模型进行验证分析,结果表明:相比于BP、LSTM、FA-BP、HPO-BP模型,HPO-LSTM模型平均绝对百分比误差E_(MAP)分别降低10.44%、4.00%、3.61%、2.04%。

规范手术病人边缘时间安全转运交接的品管圈实践

目的:通过品管圈的方式研究手术病人边缘时间的安全转运交接,并评价其效果。方法:选取2022年1月—7月转运交接手术病人443例为研究对象,按转运时间分成改善前(220例)、改善后(223例),前者采用传统的转运交接方式,后者采用品管圈的方式,建立规范化的转运交接模式应用于临床。比较活动前后不良事件发生率、缺陷发生率。结果:建立了手术病人边缘时间规范的转运交接模式,目标达标率为108.42%,进步率达到20.11%。活动后不良事件发生率、缺陷发生率均低于活动前。结论:品管圈活动提高手术病人边缘时间的安全转运交接正确率,保障手术病人的转运安全,减少交接遗漏。

基于改进浮动单元的城市职住平衡时间尺度估计——以广州市为例

已有研究对城市职住平衡的测度往往存在可塑性面积单元问题,且忽略了交通网络在职住联系中的媒介作用。提出一种改进的浮动单元法,构建基于道路和城市轨道交通网络的数据集,以时间为职住分析尺度生成浮动单元,运用手机信令数据对职住平衡进行测度。以广州市为例,对就业中心和居住区的职住平衡时间尺度进行估计。研究发现:广州市中心城区职住平衡时间尺度分布呈圈层式空间特征,职住平衡时间尺度从一级就业中心向外围先减小再增大;城市轨道交通缩小了就业中心的职住平衡时间尺度;一级、二级(不处于一级就业中心的辐射范围内)和三级就业中心的职住平衡时间尺度分别为32~40 min、14~28 min和10~20 min,而居住组团的职住平衡时间尺度主要依附于就业中心且受到城市轨道交通的影响。最后,提出在合适的时间尺度下对职住空间结构进行评估和优化住房和就业等资源配置,并重视城市轨道交通对职住空间结构的影响。

融合多特征神经网络的城市道路交通速度预测

针对城市道路交通速度特性分析不全面的问题,本研究考虑到气象因素和空气污染因素对交通速度的影响提出了一种多源特征融合结合Informer模型的道路交通速度预测模型(MFInformer,Multi Feature Informer)。采用成都市浮动车数据及气象数据、空气污染数据,通过提取数据集的交通流特征,天气特征以及空气污染特征对道路交通速度进行预测。研究表明:在以10分钟为间隔的预测中,基于浮动车数据结合外源因素的多特征数据的Informer模型相较于仅使用浮动车数据的Informer模型以及常用的时间序列预测模型循环神经网络和长短期记忆网络来说预测的准确度有着显著的改善,结合多源特征的Informer模型预测交通速度平均绝对误差,均方误差和平均绝对百分比误差分别为1.38、5.32%、1.74,均优于其它模型。

大规模矿山的长距离胶带输送系统设计探讨

国外某大型矿山,生产规模达6 000万t/a,且地处内陆地区,矿体狭长,距离选矿工业场地较远、地势起伏陡峭、地形自然坡度大。该项目矿石运输兼具运量大、运距长、运输难度大等特点。对于大规模矿山而言,带式输送机因其具有运输量大、可长距离运输、自动化程度高、并能实现连续运输的优势,在矿山生产过程中发挥着极其重要的作用。与此同时,由于需要输送的距离越来越长,单段带式输送机很难满足矿山整体的散料输送要求,大运量、大角度接力运输的带式输送机系统得到普遍应用。本文借鉴现有矿山带式输送机接力系统的生产数据,以该大型矿山为背景,对带式输送机系统的可靠性和能耗情况进行分析计算,为类似项目提供参考。

A Preliminary Study of Just-in-Time Methods for a Seamless Public Transportation Information Framework

A seamless multimodal transit system has been a goal for transportation planners and users. Owing to the developments of advanced public transportation and telecom technologies such as automatic vehicle location (AVL) and real-time passenger information system, key just-in-time (JIT) concepts can now be realized in process design and coordinated scheduling to shape a seamless multimodal transit system. JIT refers to a production system that times both movements of goods during production and delivery from suppliers together. It meets the same logic for seamless multimodal services. Therefore, this study innovatively analyzes possible public transportation technologies for JIT uses;moreover, to layout the possible application frame-work of a transportation technology based JIT multimodal transit system for main station area in Taipei city. With this innovative framework, multimodal transit services can deliver to the right place at right time.

基于不同动力集装箱船的支线运输综合调度优化

在“双碳减排”战略和绿色航运背景下,为了对使用不同动力集装箱船的支线运输进行调度优化,以LNG动力船和燃油动力船为例,引入模糊时间窗刻画货主满意度,同时考虑支线船舶运输容量、港口限制时间等实际约束条件,综合考虑运输成本、货主满意度和碳排放量,构建了一种基于不同动力船型的混合整数规划模型。结合问题特征设计混合遗传算法进行求解,通过引入局部搜索策略提高求解质量,测试算例表明设计的混合遗传算法与最优解的平均误差为1.4%,案例计算结果表明:与遗传算法相比,混合遗传算法的收敛速度和寻优能力更强,可降低运输成本29 520元,减少碳排放38.474 t。可见,基于局部搜索的混合遗传算法的求解精度明显优于传统遗传算法,说明在实际应用中该方法可以实现船舶调度优化;同时与燃油动力船相比,使用LNG动力船可以实现降低运输成本和减少碳排放的目标。