P wave onset time picking with the B-spline biorthogonal wavelet

The seismic wave consists of many seismic phases, which contain rich geophysical information from the hypocenter, medium of seismic wave passing through and so on. It is very important to detect and pick these seismic phases for understanding the mechanism of earthquake, the Earth structure and property of seismic waves. In order to reduce or avoid the loss resulted from the earthquake, one of the important goals of seismic event detecting is to obtain its related information before and after it occurs. Because of the particularity of P wave and S wave the seismic event detecting focuses on distinguishing P and S waves and picking their onset time, it has been becoming one of the research hotspots for many geophysicists to pick the P and S wave arrival accurately and effectively.

Effects of Different Picking Time and Different Geographical Provenances on Oil Content of Camellia oleifera

This paper studied effects of different picking time and different geographical provenances on oil content of Camellia oleifera. The results showed that different picking time had significant effects on the oil content of cold dew seeds and frost's descent seeds. With the delay of picking time,the oil content of cold dew seeds,frost's descent seeds,dry seeds and oil content of seed kernels were significantly increased.There was a significantly positive correlation between the oil content of fresh fruit of cold dew seeds and frost's descent seeds and the dry seed yield of fresh seeds and the oil content of fresh fruit( P < 0. 05),and the correlation coefficient was greater than 0. 85. Besides,the oil content of seed kernels of cold dew seeds was closely correlated with the seed yield of fresh seeds,oil content of fresh fruit,and oil content of fresh seeds. In the process of C. oleifera breeding,the thin coat,high seed yield and high oil content can be taken as the key research directions for future breeding. The oil content of ordinary C. oleifera seeds in 18 counties( cities) was 36. 42%-63. 33%,indicating that there were significant differences in the oil content of C. oleifera in different geographical provenances. In conclusion,according to the study of different picking time,the recommended picking time of cold dew seeds in Hunan area is around October 10,while the best picking time of frost's descent seeds is about October 30. The oil content of C. oleifera fruit in different geographical provenances is quite different. During the development of C. oleifera fruit,the cultivation and management of C. oleifera should be strengthened to increase the oil content of C. oleifera.

基于Nevanlinna-Pick插值的时滞系统鲁棒控制器设计

针对时滞系统,提出一种基于Nevanlinna-Pick插值的鲁棒控制器设计方法.它首先通过互质分解得到控制器和灵敏度函数的参数化形式,将控制器的设计转化为灵敏度函数成型;然后利用同伦法求解具有阶次约束的Nevanlin-na-Pick插值问题,从而求得控制器和灵敏度函数.仿真实验结果表明,闭环系统的灵敏度函数由被控对象的非最小相位零点和不稳定极点决定.

Taboo Search Algorithm for Item Assignment in Synchronized Zone Automated Order Picking System

The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.

Impact of time lags on diurnal estimates of canopy transpiration and canopy conductance from sap-flow measurements of Populus cathayana in the Qinghai–Tibetan Plateau

Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to the capacitive exchange between the transpiration stream and stem water storage. Significant errors will be introduced in canopy conductance （gc） and canopy transpiration estimation if the time lag is neglected. In this study, a cross-correlation analysis was used to quantify the time lag, and the sap flowbased transpiration was measured to pararneterize Jarvistype models of gc and thus to simulate Ec of Populus cathayana using the Penman-Monteith equation. The results indicate that solar radiation （Rs） and vapor pressure deficit （VPD） are not fully coincident with sap flow and have an obvious lag effect; the sap flow lags behind Rs and precedes VPD, and there is a 1-h time shift between Eo and sap flow in the 30-min interval data set. A parameterized Jarvis-type gc model is suitable to predict P. cathayana transpiration and explains more than 80% of the variation observed in go, and the relative error was less than 25%, which shows a preferable simulation effect. The root mean square error （RMSEs） between the predicted and measured Ec were 1.91×10^-3 （with the time lag） and 3.12×10^-3cm h^-1 （without the time lag）. More importantly, Ec simulation precision that incorporates time lag is improved by 6% compared to the results without the time lag, with the mean relative error （MRE） of only 8.32% and the mean absolute error （MAE） of 1.48 × 10^-3 cm h^-1.

Real-time crash prediction on freeways using data mining and emerging techniques

Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.

A Numerical Algorithm Based on Quadratic Finite Element for Two-Dimensional Nonlinear Time Fractional Thermal Diffusion Model

In this article,a high-order scheme,which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme,is developed for looking for the numerical solution of a two-dimensional nonlinear time fractional thermal diffusion model.The time Caputo fractional derivative is approximated by using the L2-1formula,the first-order derivative and nonlinear term are discretized by some second-order approximation formulas,and the quadratic finite element is used to approximate the spatial direction.The error accuracy O(h3+
t2)is obtained,which is verified by the numerical results.

多能源混合车队生鲜品配送车辆路径问题研究

针对同时考虑取送货和分时电价的电动车与燃油车混合车队车辆路径问题,以车辆固定成本、行驶成本、制冷成本、货损成本、时间窗成本、碳排放成本和充电成本之和最小为目标,构建生鲜品配送车辆路径优化模型,设计融合邻域搜索的遗传模拟退火混合算法并求解。结果表明:相比于取送分离,同时取送货模式能够显著提升配送效率,提高车辆装载率;通过技术升级适当增加电动车的电池容量,能够弱化车辆路径方案对充电设施的依赖程度,有效降低配送成本;通过与遗传算法、遗传变邻域混合算法运行结果对比,验证本文算法的有效性,为冷链物流企业在配送环节实现节能减排、降本增效提供借鉴和参考。

基于SBL-PRM算法的柑橘采摘机器人实时路径规划

针对动态非结构化环境下的柑橘采摘机器人实时路径规划问题,采用单次查询、双向采样与延迟碰撞检测相结合的SBL-PRM(Single-query,Bi-directional,Lazy collision checking,Probabilistic Roadmap Method)算法,对无遮挡和遮挡两种场景下的柑橘采摘情况进行仿真试验,分析最大采样点数S、邻域阈值ρ、局部路径检测阈值ε、路径平滑次数N等参数对规划时间和成功率的影响。结果表明,在S=3000,ρ=0.6,ε=0.03,N=10时,无遮挡和遮挡两种场景下路径规划的平均时间分别为1ms、60ms左右,规划成功率均为100%。仿真试验证明了SBL-PRM算法在柑橘采摘机器人实时路径规划中的有效性。

考虑波次订单动态释放的B2C电商订单合并配送决策方法

本文针对动态释放、异质性强的B2C电商波次订单的物流配送决策难题,以提高车辆满载率、降低配送成本为目标,研究考虑波次订单动态释放的B2C电商订单城区物流合并配送问题。首先,将原动态问题建模为一阶马尔可夫决策过程以表达其多阶段时序序贯决策的特点;其次,基于状态转移具有的时序特征,提出一种基于时序预测的前向动态规划方法用于寻找最优策略,将时序预测信息融入到合并配送决策的模型中,并结合定性启发式规则与定量优化模型以兼顾方法的决策效率与优化能力;最后,基于标准算例下的数值实验和某B2C电商平台的实例分析,验证了所提方法的有效性和实用性。此研究可为B2C电商订单物流配送提供决策支持,同时对于状态转移具有时序特征的马尔可夫决策问题提供了求解的新思路。

准确求取VSP时间-深度关系的探讨

介绍了VSP计算时间 -深度关系的原理 ,从深度测量、初至拾取、观测系统 3个方面分析了计算误差的来源 ,并提出了在野外采集和处理解释过程中应采取的预防和校正措施。

人5-羟色胺2c受体基因实时荧光定量PCR方法的建立

目的建立5-羟色胺2c受体（5-HTR2c）基因mRNA表达水平的TaqMan real—time PcR检测方法。方法以β-actin为内参基因，根据GenBank中人5-HTR2c及β-actin基因序列，分别设计了2套特异性引物和TaqMan探针，接着对反应的退火温度、引物浓度、探针浓度、Mg^2＋浓度进行优化，然后以优化的条件建立相对定量标准曲线，并对该方法的稳定性进行了分析。结果5-HTR2c及β-actin基因的real—time PCR扩增效率分别为99.9％和100.0％；相对定量标准曲线的CT值线性范围分别为12．2～35．1和11．5～31．5，相关系数分别为0．999及1．000；批内及批问变异系数（8．0％。结论本研究所建立的针对5-HTR2c mRNA表达水平的Taqman real-time PCR检测方法具有扩增效率高、稳定性好等特点，为进一步探索5-HTR2c的功能及其mRNA表达水平的变化和各种疾病发生、发展的相关性提供了有用的方法学基础。

基于交流注入法的大容量铅碳电池内阻测量

电池内阻是判断电池健康程度和放电能力的重要参数,而目前针对大容量铅碳电池内阻检测方面的相关研究较少,因此提出一种大容量铅碳电池的交流注入检测法。首先对铅碳电池等效电路模型进行推导分析;其次应用Simulink软件建立检测系统仿真模型,验证其电阻检测过程,仿真结果与被测铅碳电池内阻一致,说明该检测系统方案可行;最后采用新威高性能电池检测系统作为标准检测仪器进行对比测试验证,达到实际应用要求。该测试方法对大容量铅碳电池内阻的检测具有一定的借鉴作用。

不同采摘时间天胡荽挥发油成分GC-MS分析

目的:分析不同采收时间对天胡荽挥发油成分的影响。方法:以2019年生长的湖南产天胡荽为原料,选择3月、4月、5月、6月、7月、8月的每月中旬为采摘时间点,采用水蒸气蒸馏法提取所采集天胡荽样本的挥发油,利用气相色谱-质谱法(GC-MS)对其挥发性成分进行分析比对,结合NIST库进行成分的分析鉴定,以峰面积归一化法确定各组分的相对含量。结果:天胡荽挥发油中含量最高的成分为镰叶芹醇,其含量从3月的44.68%提高到5月的85.19%,5-8月较为稳定,均在80%以上;其余含量较低成分不同月份有所差异;天胡荽挥发油种类以醇类和烯烃为主,3-8月样品含量均在90%~94%之间。结论:不同采摘时间对天胡荽挥发油的主要成分表现出一定的时间差异性,该研究结果为天胡荽采摘时间的选择提供了一定的依据。

基于RPA与滚动时间窗的零售电商订单动态调度仿真

为了提高零售电商订单的整体交付效率,提出基于RPA与滚动时间窗的零售电商订单动态调度方法。在RPA机器人技术框架的应用层逻辑端中,通过基于滚动时间窗的订单调度优先级排序方法,将订单以滚动时间窗划分的方式,分解为多个订单调度任务,并执行订单优先级排序。将排序后订单作为零售电商订单拣选与配送车辆联合动态调度方法的调度对象,构建订单交付时间最小化、全部订单均被交付的订单动态调度目标函数。由改进共同进化遗传算法,从订单拣选、配送车辆联合动态调度的角度,求解满足条件的订单拣选与配送车辆联合动态调度方案。实验验证,此方法调度下,零售电商客户订单配送交付时,交付时间均靠近客户对订单产品期望时间窗下界,无订单遗漏问题,全部订单均被高效拣选、配送。

MALDI-TOF-MS法对重组人内皮抑素蛋白分子质量测定

肿瘤的生长依赖于血管的生成,新生血管不仅为肿瘤生长提供必需的营养物质,而且为肿瘤细胞扩散提供了重要的途径[1].1997年哈佛大学的O'Reilly等[2]发现了一种内源性新血管生成抑制因子内皮抑素(Endostatin),显示出特异抑制激活的血管内皮细胞增殖和肿瘤新血管生成的生物学活性,其抗肿瘤作用具有高效、低毒、无耐药性的优点.……

鄂西产区重齿毛当归需肥规律与采收期研究

[目的]为鄂西产区重齿毛当归科学施肥与适时采收提供理论依据。[方法]在重齿毛当归移栽后定期采样,研究氮、磷、钾元素与4种香豆素类化合物的积累规律。[结果]重齿毛当归群体的氮、磷元素积累量呈线性上升趋势,钾元素积累量在8月中旬达到峰值;生产100 kg重齿毛当归干燥根需要N、P_(2)O_(5)、K_(2)O分别为1.61、1.25、2.70 kg。二氢欧山芹醇含量在6月中旬达到最高,9月中旬后基本稳定;异欧前胡素含量在8月中旬达到最高,之后持续下降;二氢欧山芹醇当归酸脂含量在8月中旬之前波动较大,9月中旬之后缓慢提高;蛇床子素含量在7月达到最低,9月中旬以后含量持续提高,在12月中旬达到最高。除异欧前胡素外,其他3种香豆素积累量均随着时间的推移而不断升高,在12月中旬达到最高。[结论]重齿毛当归N∶P_(2)O_(5)∶K_(2)O供给比例以1.29∶1.00∶2.17为宜,6~10月为氮、磷吸收关键期,6~8月为钾吸收关键期,12月或之后采收为宜。

基于高分辨率时频分析的核爆地震信号能量统计初至检测算法

核爆地震波检测是禁核试核查的关键环节之一。常用的短时长时能量均值比、赤池信息准则、傅里叶变换等方法虚警率都比较高,为此,提出一种基于高分辨率时频分析的核爆地震信号能量统计初至检测算法。其基本原理是根据核爆地震事件信号与噪声的频域分布差异,采用窄带分频技术将信号时域波形变换到时频域,在各频带计算局部能量均值与全局能量均值之比并进行二值化处理,当结果大于设定的阈值时,认为此频带该时刻属于地震事件信号的一部分,如果在某一阈值下出现二值化结果相同的情况,只需继续增大阈值进行检测,直到最终只有一个时间点检测到频段的数量最多即可,最大值的跳跃点即认为是初值时刻。利用地下核爆产生的地震信号进行实验研究,结果表明本文方法能够在提高检测准确率的同时解决高虚警问题,在低信噪比信号条件下具有较好的适用性与鲁棒性。