Mechanical properties and thermal shock in thin ZrO2–Y2O3–Al2O3 films obtained by the sol-gel method

Thin multilayer coatings of ZrO₂–Y₂O₃–Al₂O₃ were prepared using the sol-gel method and dip-coating technique in order to advance in the study of what influence the incorporation of Al₂O₃ has on films of Y₂O₃-doped ZrO₂, investigating its role in the synthesis of the solutions and in the characteristics and properties of the coatings. After the characterization of the solutions used in the process, the microstructure of the films was studied and their mechanical behaviour and resistance to thermal shock were determined so as to optimize the characteristics and functionality of these coatings. With increased alumina content, 3YSZ-Al₂O₃ (20 mol%), the cubic phase of the zirconia disappeared completely at the sintering temperature used (700 °C), resulting in the tetragonal phase with Al in solution. There was also a decrease in the coatings' hardness and Young's modulus, and an increase in toughness and resistance to thermal shock. These results allow guidelines to be established for the design of multilayer structures that are, tougher, more resistant, and have improved surface properties.     

Effect of suspension characteristics on the performance of thermal barrier coatings deposited by suspension plasma spray

This paper investigates the influence of suspension characteristics on microstructure and performance of suspensions plasma sprayed (SPS) thermal barrier coatings (TBCs). Five suspensions were produced using various suspension characteristics, namely, type of solvent and solid load content, and the resultant suspensions were utilized to deposit five different TBCs under identical processing conditions. The produced TBCs were evaluated for their performance i.e. thermal conductivity, thermal cyclic fatigue (TCF) and thermal shock (TS) lifetime. This experimental study revealed that the differences in the microstructure of SPS TBCs produced using varied suspensions resulted in a wide-ranging overall TBC performance. All TBCs exhibited thermal conductivity lower than 1 W/(m. K) except water-ethanol mixed suspension produced TBC. The TS lifetime was also affected to a large extent where 10 wt % solid loaded ethanol and 25 wt % solid loaded water suspensions produced TBCs exhibited the highest and the lowest lifetime, respectively. On the contrary, TCF lifetime was not as significantly affected as thermal conductivity and TS lifetime, and all ethanol suspensions showed marginally better TCF lifetime than water and ethanol-water mixed suspensions deposited TBCs.     

Mechanisms of Reciprocal Regulation of Gonadotropin-Releasing Hormone (GnRH)-Producing and Immune Systems: The Role of GnRH,Cytokines and Their Receptors in Early Ontogenesis in Normal and Pathological Conditions

Different aspects of the reciprocal regulatory influence on the development of gonadotropin-releasing hormone (GnRH)-producing- and immune systems in the perinatal ontogenesis and their functioning in adults in normal and pathological conditions are discussed. The influence of GnRH on the development of the immune system, on the one hand, and the influence of proinflammatory cytokines on the development of the hypothalamic-pituitary-gonadal system, on the other hand, and their functioning in adult offspring are analyzed. We have focused on the effects of GnRH on the formation and functional activity of the thymus, as the central organ of the immune system, in the perinatal period. The main mechanisms of reciprocal regulation of these systems are discussed. The reproductive health of an individual is programmed by the establishment and development of physiological systems during critical periods. Regulatory epigenetic mechanisms of development are not strictly genetically controlled. These processes are characterized by a high sensitivity to various regulatory factors, which provides possible corrections for disorders.     

一种低载噪比突发扩频信号的快速捕获方法实现

针对突发扩频信号用户资源扩大、终端功率降低、系统容量提升等需求,提出了一种低载噪比突发扩频信号的快速捕获硬件实现方法。采用分段匹配滤波器加多普勒并行相干积累的方法,基于硬件实现从算法到工程进行全流程优化设计,最终实现最优的捕获性能。应用结果表明,该硬件设计实现方案的快速捕获性能优越,设计方案正确、可行,已成功应用于工程建设中。     

Improving water retention of chicken breast meats by CaCl2 combined with pulsed electric fields

Frozen poultry meat is the most widely consumed animal-based food. However, water loss often leads to quality loss of poultry meat. Therefore, the present study sought to investigate the combined effect of calcium chloride (CaCl₂) and pulsed electric fields (PEF) treatment on chicken breast meats and the mechanisms underlying protein degradation. The results showed that the synergistic effect was superior to the single treatment. Compared with the untreated group, the combination of CaCl₂ and PEF increased water holding capacity of chicken breast meats by 16.61% and decreased cooking loss by 28.93%. Low-field nuclear magnetic resonance (LF-NMR) results indicated that the synergistic treatment promoted water molecules' binding capacity in myofibrils of poultry meat, which exhibited higher immobilised water. Additionally, the combination of CaCl₂ and PEF led to increased degradation of proteins of high-molecular weight and surface hydrophobicity of myofibrillar protein. Furthermore, the extension of the protein molecule and microenvironmental changes promoted interaction between protein and water. In conclusion, the synergistic treatment of CaCl₂ and PEF enhanced water retention and improved physicochemical properties of the myofibrillar protein in chicken breast meats.     

A Feature Extraction Method for scRNA-seq Processing and Its Application on COVID-19 Data Analysis

Single-cell RNA-sequencing (scRNA-seq) is a rapidly increasing research area in biomedical signal processing. However, the high complexity of single-cell data makes efficient and accurate analysis difficult. To improve the performance of single-cell RNA data processing, two single-cell features calculation method and corresponding dual-input neural network structures are proposed. In this feature extraction and fusion scheme, the features at the cluster level are extracted by hierarchical clustering and differential gene analysis, and the features at the cell level are extracted by the calculation of gene frequency and cross cell frequency. Our experiments on COVID-19 data demonstrate that the combined use of these two feature achieves great results and high robustness for classification tasks.     

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.     

Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

基于卷积神经网络的5G蜂窝网络无线定位方法

5G蜂窝网络发展迅猛，其覆盖面积将逐渐增大，因此使用5G蜂窝网络进行定位是有研究潜力的研究方向。本文提出一种新的深度学习技术来实现高效、高精度和低占用的定位，以代替传统指纹定位过程中繁重的指纹库生成以及距离计算。该方法建立了一个特殊的卷积神经网络，并根据5G天线信号的接收信号强度指示、相位和到达角等特征量，选择合适的输入数据格式构造样本组建训练集，对该卷积神经网络进行训练。训练得到的卷积神经网络可以替代指纹定位中的庞大指纹库，非常有利于直接在5G移动设备端实现定位。虽然卷积神经网络在训练过程中需要大量时间，但在训练完毕后直接进行分类定位的速度非常快，可以保障定位实现的实时性。本文所实现的卷积神经网络权重与偏置所占内存不到0.5 MB，且能够在实际应用环境中以95%的定位准确率以及0.1 m的平均定位精度实现高精度定位。     

Can hydrogen be the sustainable fuel for mobility in India in the global context?

This article provides a critical assessment of H₂ from the standpoint of more widespread use as a sustainable fuel for Indian mobility applications in the global context. The potential techno-economic advantages of utilizing H₂ for automobiles rather than battery electric vehicles or conventional internal combustion engine vehicles are emphasized. The present assessment demonstrates that H₂ production, storage, and distribution costs are the primary challenges, and a significant improvement is still necessary for H₂ to compete either against the internal combustion engine vehicle or the battery electric vehicle to win the race, arguably. The secondary challenges have also been demonstrated, which include the cost of the fuel cell stack and the modifications associated with internal combustion engine vehicles, as well as regulatory and safety concerns, which impede the widespread usage of H₂. It is critical that policy-making for sustainable mobility in India is possible with the aid of a National H₂ Energy Road-Map. This in turn can achieve a cost target of $0.5/kg for H₂.