Comparative Analysis of Platelet-Derived Extracellular Vesicles Using Flow Cytometry and Nanoparticle Tracking Analysis

Growing interest in extracellular vesicles (EVs) has prompted the advancements of protocols for improved EV characterization. As a high-throughput, multi-parameter, and single particle technique, flow cytometry is widely used for EV characterization. The comparison of data on EV concentration, however, is hindered by the lack of standardization between different protocols and instruments. Here, we quantified EV counts of platelet-derived EVs, using two flow cytometers (Gallios and CytoFLEX LX) and nanoparticle tracking analysis (NTA). Phosphatidylserine-exposing EVs were identified by labelling with lactadherin (LA). Calibration with silica-based fluorescent beads showed detection limits of 300 nm and 150 nm for Gallios and CytoFLEX LX, respectively. Accordingly, CytoFLEX LX yielded 40-fold higher EV counts and 13-fold higher counts of LA⁺CD41⁺ EVs compared to Gallios. NTA in fluorescence mode (F-NTA) demonstrated that only 9.5% of all vesicles detected in scatter mode exposed phosphatidylserine, resulting in good agreement of LA⁺ EVs for CytoFLEX LX and F-NTA. Since certain functional characteristics, such as the exposure of pro-coagulant phosphatidylserine, are not equally displayed across the entire EV size range, our study highlights the necessity of indicating the size range of EVs detected with a given approach along with the EV concentration to support the comparability between different studies.     

Residual attention-based tracking-by-detection network with attention-driven data augmentation

Tracking-by-detection (TBD) is a significant framework for visual object tracking. However, current trackers are usually updated online based on random sampling with a probability distribution. The performance of the learning-based TBD trackers is limited by the lack of discriminative features, especially when the background is full of semantic distractors. We propose an attention-driven data augmentation method, in which a residual attention mechanism is integrated into the TBD tracking network as supplementary references to identify discriminative image features. A mask generating network is used to simulate changes in target appearances to obtain positive samples, where attention information and image features are combined to identify discriminative features. In addition, we propose a method for mining hard negative samples, which searches for semantic distractors with the response of the attention module. The experiments on the OTB2015, UAV123, and LaSOT benchmarks show that this method achieves competitive performance in terms of accuracy and robustness.     

气藏平均地层压力跟踪计算新方法

平均地层压力是产能评价和动态分析的基础，准确、快速获取平均地层压力对高效开发气藏意义重大。基于地层压力随时间变化的规律，分析了平均地层压力的变化规律。研究结果表明：平均地层压力等效点仅随时间发生改变，平均地层压力的下降速率等于或者近似等于井底流压的下降速率。从封闭弹性驱动气藏的物质平衡方程出发，考虑偏差系数和井底流压随平均地层压力的变化，推导建立了平均地层压力跟踪计算新方法，根据生产数据可迭代计算平均地层压力。方法验证结果显示，采气速度和采出程度共同影响模型的计算结果。应用实例表明，跟踪计算法与压力恢复试井和物质平衡法之间的相对误差均较小，满足工程计算精度要求，且跟踪计算法不需依托生产测试数据，节约了测试费用，避免了测试占产。     

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

This paper aims to provide a review of the conceptual design and theoretical framework of the main control schemes proposed in the literature for unmanned underwater vehicles (UUVs). Additionally, the objective of the paper is not only to present an overview of the recent control architectures validated on UUVs but also to give detailed experimental-based comparative studies of the proposed control schemes. To this end, the main control schemes, including proportional–integral–derivative (PID) based, sliding mode control (SMC) based, adaptive based, observation-based, model predictive control (MPC) based, combined control techniques, are revisited in order to consolidate the principal efforts made in the last two decades by the automatic control community in the field. Besides implementing some key tracking control schemes from the classification mentioned above on Leonard UUV, several real-time experimental scenarios are tested, under different operating conditions, to evaluate and compare the efficiency of the selected tracking control schemes. Furthermore, we point out potential investigation gaps and future research trends at the end of this survey.     

Double-layer fuzzy adaptive NMPC coordinated control method of energy management and trajectory tracking for hybrid electric fixed wing UAVs

The energy management and trajectory tracking control are crucial to realize long-endurance autonomous flight for hybrid electric UAVs. This study aims to comprehensively consider energy management and trajectory tracking for hybrid electric fixed wing UAVs with photovoltaic panel/fuel cell/battery. A double-layer fuzzy adaptive nonlinear model predictive control method (DFNMPC) is proposed. Separated by the surplus demand power, energy management and trajectory tracking problem are decoupled into the high-layer fuzzy adaptive nonlinear model predictive controll problem (H-FNMPC) and low-layer fuzzy adaptive nonlinear model predictive controll problem (L-FNMPC). H-FNMPC solves the trajectory tracking and navigation control probelm for the greatest benefit of solar energy. L-FNMPC solves the power allocation problem of hybrid energy system for minimum equivalent hydrogen consumption. A fuzzy adaptive prediction horizon adjustment method based on UAV maneuvering degree is proposed to effectively improve proposed method adaptability to different mission profiles. Analogously, a fuzzy adaptive equivalent hydrogen consumption factor adjustment method in L-FNMPC is proposed to ensure the flexible utilization of battery. In addition, an equivalent hydrogen flow rate calculation method based on the real-time current ratio is proposed for PV/FC/Battery hybrid energy system. Numerical simulation results including a spiral trajectory tracking and a quadrilateral trajectory tracking, demonstrate that DFNMPC can simultaneously handle energy management and trajectory tracking problem for hybrid electric UAVs. Compared to hierarchical fuzzy state machine strategy, DFNMPC can save 13.3% hydrogen for the spiral trajectory tracking, and 56.9% for the quadrilateral trajectory tracking. It indicates that the energy efficiency can be improved from both levels of energy management and flight motion. The proposed method prospected for exploring high-energy-efficiency autonomous flight of hybrid electric UAVs in the future.     

Adaptive compensation of persistent actuator failures of nonlinear systems

In this article, adaptive compensation designs are developed for nonlinear systems with uncertainties from the system functions and persistent actuator failures of characterizations that (i) some unknown system inputs are stuck at some unknown fixed or varying values at unknown time instants and (ii) the failure pattern always switches from one to another and the switching does not stop. Such a controlled plant is described by an uncertain time-varying nonlinear system, and some robust adaptive feedback linearization based failure compensation results are studied for closed-loop system stabilization and bounded output tracking for some specific conditions. To improve the tracking performance in the presence of persistent actuator failures, a new adaptive control scheme is developed, using the failure indicator function which contains the failure pattern and failure time in the formulation. Detailed stability and tracking performance are shown. Simulation results are shown to verify the effectiveness of the proposed adaptive actuator failure compensation method.     

Colostrum source and passive immunity transfer in dairy bull calves

Colostrum is essential for good neonate health; however, it is not known whether different calves absorb the nutrients from colostrum equally well. In this study, the absorption of protein, IgG, and γ-glutamyl transferase was compared in newborn dairy bull calves for 1 wk after feeding colostrum from different sources. Thirty-five Holstein-Friesian bull calves were randomly allocated into 3 groups and fed colostrum within 4 h after birth. Group A calves (n = 12) were bottle fed colostrum from their own dam for 3 d. Colostrum from these group A cows was also used as foster cow colostrum for the group B calves (n = 12), such that each group A and B calf pair received identical colostrum from each milking of the respective group A dam (10% of birth weight per day). The group C calves (n = 11) were fed 1 bottle (2 L) of pooled colostrum and transition milk (referred to as pooled colostrum), as was the standard practice on the dairy farm. The pooled colostrum was collected from the other dairy cows on the farm 0 to 4 d postpartum and stored at 4°C for less than 12 h. Blood was sampled from calves before the first feeding and at 1, 2, 3, and 7 d after birth. Levels of total solids, total protein, and IgG were higher in the dam colostrum than in the pooled colostrum. At birth, there were no differences between the calf groups for any measurements, and all calves had very low IgG levels. After receiving colostrum, the glucose, plasma γ-glutamyl transferase, serum total protein, and IgG concentrations increased significantly in all calves. There were no differences in any blood measurements at any time point between the pairs of group A and group B calves that received colostrum from the same cow except for the IgG concentration 2 d after birth. However, the group A calves had a higher total serum protein level and IgG concentration than the group C calves for all the time points after the first feeding. The group B calves had a higher IgG concentration than the group C calves on d 1, 2, and 7 after birth. Compared with groups A and B, there was no difference in the proportion of calves in group C that failed to have passive immunity transferred adequately based on the IgG threshold (<10 g/L). Thus, the calves receiving identical colostrum from the same cow had the same levels of IgG, and even the pooled colostrum provided sufficient transfer of IgG as the calves were fed within 4 h after birth.     

Anti-corrosive properties of waterborne polyurethane/poly(o-toluidine)-ZnO coatings in NaCl solution

The aim of this research was to prepare waterborne polyurethane (WPU) coating blended with a series of poly(o-toluidine)-nano ZnO composites and study its anti-corrosion performance after its application over carbon steel. The synthesized composites were characterized by X-ray diffractometry (XRD), Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). The corrosion resistance of coatings with and without nano ZnO were studied in 3.5% NaCl solution at a temperature of 25?°C, by electro-chemical techniques such as potentiodynamic polarization measurements and electrochemical impedance spectroscopy (EIS). It was observed that the composite coating containing 7% poly(o-toluidine)-nano ZnO composite had higher corrosion resistance than poly(o-toluidine) and 14% poly(o-toluidine)-nano ZnO composite. The presence of appropriate amount of ZnO significantly improved the corrosion resistance, due to the formation of passive layer on steel surface and the synergistic effects of poly(o-toluidine) along with a suitable amount of nano-ZnO reduced the porosity of the coating surface.     

A high-throughput chaotic advection microreactor for preparation of uniform and aggregated barium sulfate nanoparticles

A high-throughput (105.5 g/h) passive four-stage asymmetric oscillating feedback microreactor using chaotic mixing mechanism was developed to prepare aggregated Barium sulfate (BaSO₄) particles of high primary nanoparticle size uniformity. Three-dimensional unsteady simulations showed that chaotic mixing could be induced by three unique secondary flows (i.e., vortex, recirculation, and oscillation), and the fluid oscillation mechanism was examined in detail. Simulations and Villermaux–Dushman experiments indicate that almost complete mixing down to molecular level can be achieved and the prepared BaSO₄ nanoparticles were with narrow primary particle size distribution (PSD) having geometric standard deviation, σ_g, less than 1.43 when the total volumetric flow rate Q_total was larger than 10 ml/min. By selecting Q_total and reactant concentrations, average primary particle size can be controlled from 23 to 109 nm as determined by microscopy. An average size of 26 nm with narrow primary PSD (σ_g = 1.22) could be achieved at Q_total of 160 ml/min.     

DCNN深度特征与交替方向乘子的相关滤波跟踪

针对采用相关滤波的判别式目标跟踪遇到的瓶颈问题：由于目标快速移动引起边界效应，使得相关滤波器在学习与更新过程中可能会引入错误，最终错误的累积将导致跟踪失败。在采集深度学习特征与样本相似性度量的基础上，提出一种引入交替方向乘子方法的改进相关滤波目标跟踪算法，选择DCNN深度特征有效地表征待跟踪目标的初始状态，通过在线分类过程中样本相似性比对与半监督学习，辅助解决相关滤波器在学习过程中存在的自学习问题。所提目标跟踪算法特别适合训练样本为持续获得的、同时存储空间较小的机器学习过程，提高目标在快速运动与部分遮挡等复杂情况下的跟踪成功率，针对VOT2016标准测试视频的实验表明：当目标面临快速运动时，对比CN、SAMF、STC算法，所提DA-CFT跟踪算法将跟踪成功率分别由60.4%～73.4%、67.2%～82.9%、80.9%～88.1%提升至85.6%～91.0%。