Tissue Doppler Imaging and Two-dimensional Speckle Tracking of Left Ventricular Function in Horses Affected with Recurrent Airway Obstruction before and after Clenbuterol Treatment

Cardiac effects of the β₂-adrenergic agent clenbuterol have been the focus of many studies, but effects on myocardial velocities and myocardial deformation parameters have not yet been evaluated in horses affected with recurrent airway obstruction (RAO) using tissue Doppler imaging (TDI) and two-dimensional speckle tracking (2DST). In our study, 7 horses affected by RAO were treated over 14 days with clenbuterol, 0.8 μg/kg every 12 hours. Standard echocardiographic, TDI (pulsed wave and color TDI), and 2DST examinations were performed before and after the treatment period. Myocardial function was recorded in the right parasternal short-axis view. Percent of fractional shortening and two-dimensional echocardiography (2DE) measurements did not show any significant changes after 2 weeks of treatment. Early diastolic velocity, E, increased significantly after clenbuterol in the left ventricular free wall (LVFW; P = .001). The E/late diastolic velocity (A) quotient (P = .003) and the isovolumetric contractility (P = .035) also increased significantly after treatment. Time parameters, particularly the time interval between the Q-wave in the echocardiograph and atrial release, the time of diastole and Tei index (parameter of global ventricular function), decreased significantly after clenbuterol administration in the LVFW (P = .014/P = .028/P = .015, respectively). The 2DE speckle tracking revealed a significant increase of the early diastolic systolic strain rate (P = .01) in the LVFW after therapy. In conclusion, 2 weeks of treatment with clenbuterol at a dosage of 0.8 μg/kg every 12 hours led to improved cardiac function in severely RAO-affected horses. This could be a sign of myocardial restoration (re-remodeling) after therapy.     

Modelling advection of cod eggs and larvae on the Newfoundland Shelf

We investigate interannual variations in dispersion for the drift and retention of cod eggs and larvae on the Newfoundland Shelf using a two-dimensional Lagrangian tracking model. The velocity field for the drift model is obtained from a diagnostic calculation of objectively analysed density data. Time-dependent currents are generated using an inertial-current slab model driven by observed winds. Eggs and larvae are treated as passive drifters seeded in a dispersion model of the Newfoundland Shelf region. We identify favourable and unfavourable zones of retention on the Newfoundland Shelf. We show that northerly, shelf-break spawning locations are more favourable than southerly shelf-break spawning locations for northern cod, ( Gudus morhua , in NAFO divisions 2J3KL).     

Modeling the egg and larval transport pathways of the Antarctic toothfish (Dissostichus mawsoni) in the East Antarctic region: New insights into successful transport connections

The Antarctic toothfish (Dissostichus mawsoni) is an important fishery species widely distributed in the Southern Ocean, especially in areas covered by sea ice. Understanding fish distributions and life cycles, including the transport and survival of eggs and larvae, is essential for the assessment and sustainable management of the fishery. However, owing to difficulties with in situ winter observations, information on the early life stages of D. mawsoni is lacking. Here, we investigated the transport pathways of fish eggs and larvae through a particle tracking study, using satellite-derived ocean surface velocities in the East Antarctic region, which includes important D. mawsoni habitats and exploratory fisheries. Our results indicate that particles released from continental slopes are more likely to be successfully transported to suitable settlement grounds than those released from the BANZARE Bank (the southern region of the Kerguelen Plateau), which is situated further north and has been hypothesized to be a potential spawning ground for D. mawsoni. This study demonstrates successful source–settlement connections in relation to ocean recirculation and suggests important settlement regions for D. mawsoni larvae in the East Antarctic region.     

基于LS-SVM的光伏最大功率跟踪控制方法

为解决自然环境剧烈变化条件下,传统光伏最大功率跟踪控制中存在的控制精度低和误跟踪现象,建立了基于最小二乘支持向量机的最大工作点电压预测模型,通过该模型预测光伏发电系统的最大工作点电压,并用预测电压来修正恒电压控制法的参考电压,从而实现光伏发电系统的最大功率跟踪控制。仿真结果表明预测模型具有较高的精度,相对误差在0.04以内,控制方法能够快速、稳定地实现光伏发电系统的最大功率跟踪,有效避免误跟踪现象。     

高炮催化区跟踪方法在湖南的个例分析

简要介绍了湖南人影高炮作业情况与效果评估方法,并对高炮催化区跟踪方法进行个例检验,结合湖南实例,实现该算法在湖南的个例运用分析.利用长沙、岳阳2个降水过程,对多个回波跟踪区域进行连续跟踪,详细分析了回波跟踪的合理性;选择湖南郴州的一次高炮防雹作业,对其催化区进行跟踪,并对催化区内最大反射率和垂直液态含水量进行统计分析.结果表明,利用TREC算法,能够合理跟踪回波在空间的垂直位置与水平位置,较好地跟踪作业时催化区域移动,从而为高炮作业效果评估提供了一个有意义的参考.     

基于改进DeepSORT的群养生猪行为识别与跟踪方法

为改善猪只重叠与遮挡造成的猪只身份编号（Identity,ID）频繁跳变,在YOLO v5s检测算法基础上,提出了改进DeepSORT行为跟踪算法。该算法改进包括两方面：一针对特定场景下猪只数量稳定的特点,改进跟踪算法的轨迹生成与匹配过程,降低ID切换次数,提升跟踪稳定性;二将YOLO v5s检测算法中的行为类别信息引入跟踪算法中,在跟踪中实现准确的猪只行为识别。实验结果表明,在目标检测方面,YOLO v5s的mAP为99.3%,F1值为98.7%。在重识别方面,实验的Top-1准确率达到99.88%。在跟踪方面,改进DeepSORT算法的MOTA为91.9%,IDF1为89.2%,IDS为33;与DeepSORT算法对比,MOTA和IDF1分别提升了1.0、16.9个百分点,IDS下降了83.8%。改进DeepSORT算法在群养环境下能够实现稳定ID的猪只行为跟踪,能够为无接触式的生猪自动监测提供技术支持。     

基于模糊Stanley模型的农机全田块路径跟踪算法研究

为实现农业机械全田块高效自主作业,提出一种增益系数自适应的Stanley模型路径跟踪算法。以横向偏差和航向偏差为输入变量构建隶属度函数,设计模糊推理和解模糊化过程实时确定控制模型增益系数,提高Stanley模型对不同曲率路径的自适应能力。为验证所提算法有效性,以移动小车为平台开展联合收获机回字形全田块自主作业路径跟踪试验,结果表明所提算法显著改善Stanley模型路径跟踪精度,直线作业速度2.5m/s、转弯速度1m/s时,直线段和曲线段最大跟踪误差均小于3cm。大初始横向偏差路径跟踪试验表明,模糊Stanley模型较Stanley模型大幅度减小路径跟踪上线距离,满足农业机械全田块高效自动导航作业要求。     

基于嵌入式控制的农机自动驾驶系统布局研究

以农用耕地机为研究对象,设计一款基于嵌入式的自动驾驶控制系统。其控制原理是利用预瞄跟随算法对耕地机进行横向控制,使其根据方向盘的转角调整耕地机转弯半径;利用PID算法对耕地机进行纵向控制,使其根据油门脚踏的开合度、制动脚踏的开合度及挡位状态调整耕地机的行驶速度,从而使耕地机按最佳的运行轨迹行驶。系统以单片机最小系统为处理核心,利用周围的传感器设备和GPS接收设备等将耕地机的位置、速度信息通过解码器和串口通信的方式发送给单片机,进行逻辑运算后通过CAN接口将结果发送给方向盘、油门、制动及挡位驱动电机,从而控制耕地机的运行。仿真实验表明:系统能够减小耕地机行驶过程中的横向误差,可根据土地实况自动调整行驶速度,实现了耕地机的自动驾驶。     

基于卡尔曼滤波的橘小实蝇成虫运动轨迹优化跟踪

为了实现橘小实蝇虫口密度的精准监测,该文将机器视觉技术作为田间橘小实蝇成虫入侵自动化监测的感知方法。通过对监测区域内运动目标和背景的颜色分析,提出了基于卡尔曼(Kalman)滤波的运动目标颜色均值漂移跟踪算法,优化了多目标运动轨迹跟踪效果。该算法通过图像处理和匹配技术提取了橘小实蝇成虫在虫口监测区域二维平面X轴和Y轴方向上的位置坐标和速度分量,推算了橘小实蝇成虫运动轨迹递推关系。基于动态系统的状态序列线性最小方差估计理论和成虫运动轨迹关系分析,构建了卡尔曼滤波状态估计模型,并建立其预测和修正方程实现了橘小实蝇成虫运动目标位置估计。通过在虫口监测区域开展单目标和多目标分散及粘连条件下的成虫跟踪试验,试验结果表明颜色均值漂移跟踪算法对橘小实蝇成虫单目标跟踪具有较好的适应性,成虫监测计数准确率达100%,对于多目标分散和粘连情况跟踪处理效果较差,计数准确率分别下降至86%和76%;通过在颜色空间均值漂移跟踪算法的基础上引入Kalman滤波器估算目标运动的近似位置,实现了对橘小实蝇成虫分散和粘连多目标运动的持续跟踪优化,监测计数准确率分别提升至96%和93%。机器视觉技术实时跟踪橘小实蝇成虫在虫口监测区域运动轨迹试验进一步验证了橘小实蝇成虫虫口密度监测的可行性,为田间橘小实蝇成虫发生自动化监测技术研究提供了参考。