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.     

Analysis and proposition of limiting current density measurement protocol

Limiting current density at different temperatures, backpressures, and balance gases can be used to separate molecular diffusion resistance, Knudsen diffusion resistance and local transport resistance of membrane electrode assembly (MEA). However, the measurement of limiting current density has no unified protocol. The diverse choices in the literature, either in the control of current or voltage or in the atmosphere like relative humidity and O₂ concentrations, make it difficult to compare the results and identify the true bottleneck hindering the mass transport. In this work, the current-voltage curves obtained by current scanning/stepping and voltage scanning/stepping methods under dilute O₂ of different concentrations and a wide range of relative humidity were measured and analyzed systematically. It is found that the voltage stepping method is superior to the other three ways of control for the reliable determination of the limiting current density. Aided with simultaneous electrochemical impedance spectroscopy measurement, the limiting current density can be determined with pinpoint accuracy. When the limiting current density is just used to qualitatively evaluate different MEA, the voltage scanning method can be used instead for its high time efficiency. The selection of the atmosphere also plays an important role in suppressing the distortion from excessive water and reducing the spurious contribution from proton conduction resistance. It is found that O₂ concentrations at 0.5 vol% and relative humidity at 90% can give the best estimation of O₂ transport resistance in membrane electrode assembly.     

Microcrack healing in zirconia ceramics under a DC electric field/current

Flash event caused by a DC electric field/current was applied to the crack healing in 8 mol % Y₂O₃ stabilized cubic ZrO₂ polycrystals (8Y-CSZ). The flash event, which occurred by applying the DC power higher than a critical value of 100 mW/mm³, successfully healed the microcrack within several minutes without any healing agents at a furnace temperature of 800 °C. As compared to the healing treatment under static annealing, the healing phenomena were accelerated about 2 times under the flash treatment even at the same temperatures, suggesting that the enhanced healing phenomena cannot be explained only by the temperature effect. Since the rate of grain growth was accelerated under the flash treatment, the flash healing would be accelerated through the current-enhanced diffusional processes. This study shows for the first time that the flash event has a potential to apply to the crack healing process in the ceramic materials and composites.     

FeOOH–CoS composite catalyst with high catalytic performances for oxygen evolution reaction at high current density

Water electrolysis is an efficient approach for high-purity hydrogen production. However, the anodic sluggish oxygen evolution reaction (OER) always needs high overpotential and thus brings about superfluous electricity cost of water electrolysis. Therefore, exploiting highly efficient OER electrocatalysts with small overpotential especially at high current density will undoubtedly boost the development of industrial water electrolysis. Herein, we used a simple hydrothermal method to prepare a novel FeOOH–CoS nanocomposite on nickel foam (NF). The as-prepared FeOOH–CoS/NF catalyst displays an excellent OER performance with extremely low overpotentials of 306 and 329 mV at 500 and 1000 mA cm⁻² in 1.0 M KOH, respectively. In addition, the FeOOH–CoS/NF catalyst can maintain excellent catalytic stability for more than 50 h, and the OER catalytic activity shows almost no attenuation no matter after 1000 repeated CV cycles or 50 h of stability test. The high catalytic activity and stability have exceeded most non-noble metal electrocatalysts reported in literature, which makes the FeOOH–CoS/NF composite catalyst have promising applications in the industrial water electrolysis.     

Influence of anode current density on carbon parasitic reactions during electrolysis

In the electro-deoxidation process, carbon parasitic reaction (CO₃^2- + 4e^-=C + 3O^2-) usually occurs when using carbon materials as the anode, which leads to increase of the carbon content in the final metal and decrease of the current efficiency of the process. The aim of this work is to reduce the negative effect of carbon parasitic reaction on the electrolysis process by adjusting anode current density. The results indicate that lower graphite anode area can achieve higher current density, which is helpful to increase the nucleation site of CO₂ bubbles. Most of CO₂ would be released from the anode instead of dissolution in the molten CaCl₂ and reacting with O^2- to form CO₃^2-, thus decreasing the carbon parasitic reaction of the process. Furthermore, the results of the compared experiments show that when the anode area decreases from 172.78 to 4.99 cm², CO₂ concentration in the released gases increases significantly, the carbon mass content in the final metal product decreased from 1.09% to 0.13%, and the current efficiency increased from 6.65% to 36.50%. This study determined a suitable anode current density range for reducing carbon parasitic reaction and provides a valuable reference for the selection of the anode in the electrolysis process.