相干测风激光雷达带通采样方法的仿真研究

根据相干测风雷达回波信号载频高、带宽窄的特点,尤其星载相干测风雷达回波信号数千兆赫兹,采用传统采样方式对采集卡的采样率要求很高.鉴于采集卡的采样率和分辨力互相制约,提出将带通采样引入到相干测风雷达系统.本文以1.5 μm全光纤相干测风激光雷达的实测数据作为仿真输入,经Simulink滤波、带通采样,结果表明,在对探测距离影响不大的情况下,与低通采样方式相比径向风速反演结果最大相差0.5 μm/s;数据处理的时间复杂度降低,其下降值是带通采样频率与低通采样频率的比值;但信噪比会恶化,其下降值介于1~3 dB.      

考虑表面应力的微悬臂梁质量传感器的建模与仿真

为了考虑悬臂梁谐振器表面吸附层或者不同材料涂层引起的表面应力的影响,进而提高质量传感器的精度和性能,基于瑞利-里兹法提出了考虑表面应力的悬臂梁质量传感器的理论方法.在悬臂梁振动的控制方程中引入应力系数对其振型函数进行修正,并系统地分析对悬臂梁振动频率的影响,再根据瑞利法建立微悬臂梁质量传感器的理论模型.应用该方法,纳米颗粒的位置和质量可以通过颗粒吸附前后悬臂梁的频率移动来精确确定.该方法的准确性和可行性通过有限元仿真进行了验证.     

生物正交反应在我国的研究进展

生物正交反应是指能够在生物体系中进行、且不会与天然生物化学过程相互干扰的一类化学反应.这类反应的出现为科学家对生命进程的原位研究带来了革命性的技术,已经成为化学生物学这一新兴交叉领域的核心方向之一.自这一概念提出的近二十年里,生物正交化学经历了反应类型由单一的"偶联反应"向成键偶联、断键剪切反应并重,应用场景由简单的活细胞体系向更为复杂的生物活体升级的一系列发展历程.同时,在生命科学研究、医药研发、临床诊疗等多个领域展示出了广阔的应用前景.我国化学生物学领域的学者们积极参与并推动了生物正交反应的快速发展,在反应开发、体系优化和实际应用等方面开展了一系列原创工作,取得了瞩目的成绩;尤其是在"生物正交剪切反应"概念的提出与开发应用等方面产生了重要的国际影响.本综述中,分别按照金属介导、光介导和化学小分子介导的生物正交偶联反应以及生物正交剪切反应,对近五年来我国学者在该领域的代表性成果进行系统介绍.最后对生物正交反应的进一步发展与应用加以展望.我们期待更多高效、兼容的生物正交反应得以发展,并提出"遥控生物正交化学"的未来发展目标,期待更多的化学家能够加入生物正交反应的开发拓展与应用探索当中.     

AP Shadow Net: A Remote Sensing Shadow Removal Network Based on Atmospheric Transport and Poisson’s Equation

Shadow is one of the fundamental indicators of remote sensing image which could cause loss or interference of the target data. As a result, the detection and removal of shadow has already been the hotspot of current study because of the complicated background information. In the following passage, a model combining the Atmospheric Transport Model (hereinafter abbreviated as ATM) with the Poisson Equation, AP ShadowNet, is proposed for the shadow detection and removal of remote sensing images by unsupervised learning. This network based on a preprocessing network based on ATM, A Net, and a network based on the Poisson Equation, P Net. Firstly, corresponding mapping between shadow and unshaded area is generated by the ATM. The brightened image will then enter the Confrontation identification in the P Net. Lastly, the reconstructed image is optimized on color consistency and edge transition by Poisson Equation. At present, most shadow removal models based on neural networks are significantly data-driven. Fortunately, by the model in this passage, the unsupervised shadow detection and removal could be released from the data source restrictions from the remote sensing images themselves. By verifying the shadow removal on our model, the result shows a satisfying effect from a both qualitative and quantitative angle. From a qualitative point of view, our results have a prominent effect on tone consistency and removal of detailed shadows. From the quantitative point of view, we adopt the non-reference evaluation indicators: gradient structure similarity (NRSS) and Natural Image Quality Evaluator (NIQE). Combining various evaluation factors such as reasoning speed and memory occupation, it shows that it is outstanding among other current algorithms.     

基于空地协同采样的植被覆盖度随机森林估算方法

基于无人机高光谱影像,建立地形复杂地区植被覆盖度的非参数随机森林回归估算模型。为获得构建随机森林模型所需的足够数量的训练样本,利用低空无人机搭载的光学相机,在从地面难以到达的山地、水域和植被茂密区,通过垂直拍摄获得厘米分辨率的航拍影像,作为对地面样方采样的补充。首先计算地面数码相机照片和无人机可见光影像的红绿蓝植被指数(red-green-bluevegetationindex,RGBVI),然后使用大津分割法提取样方的植被覆盖信息,得到构建模型所需的训练样本。在此基础上,基于2018年8月16—18日在内蒙古自治区察右中旗油娄沟矿区获取的GaiaSky-mini2无人机高光谱影像数据,利用递归特征消除算法优选参与随机森林回归的特征变量集,利用空地协同获取的训练样本构建植被覆盖度的随机森林回归估算模型。该模型在测试集上的确定系数R2为0.923,均方根误差为0.087,优于常用的像元二分模型,可用于矿区植被动态信息的精细化监测。     

Pillar-Layered Metal-Organic Frameworks for Sensing Specific Amino Acid and Photocatalyzing Rhodamine B Degradation

Metal-organic frameworks (MOFs) have presented potential for detection of specific species and catalytic application due to their diverse framework structures and functionalities. In this work, two novel pillar-layered MOFs [Cd₆(DPA)₂(NTB)₄(H₂O)₄]_n·n(DPA·5DMA·H₂O) (1) and [Cu₂(DPA)(OBA)₂]_n·n(2.5DMF·H₂O) (2) [DPA = 2,5-di(pyridin-4-yl)aniline, H₃NTB = 4,4′,4′′-nitrilotribenzoic acid, H₂OBA = 4,4′-oxydibenzoic acid, DMA = N,N-dimethylacetamide, DMF = N,N-dimethylformamide] were successfully synthesized and structurally characterized. Both 1 and 2 have three-dimensional framework structures. The fluorescent property of 1 makes it possible for sensing specific amino acid such as L-glutamic acid (Glu) and L-aspartic acid (Asp). While MOF 2 was found to be suitable for photocatalytic degradation of Rhodamine B (RhB) in the presence of H₂O₂. The results imply that MOFs are versatile and metal centers are important in determining their properties.     

Anti-Quorum Sensing and Anti-Biofilm Activity of Pelargonium × hortorum Root Extract against Pseudomonas aeruginosa: Combinatorial Effect of Catechin and Gallic Acid

HPLC-UV was used to compare the major constituents of two Pelargonium × hortorum cultivars and Pelargonium sidoides root extract. It revealed the presence of catechin and gallic acid in high concentrations and the absence of umckalin in P. × hortorum root extracts. The antibacterial activity of these extracts was screened against 19 Pseudomonas aeruginosa clinical isolates. P. × hortorum root extracts showed the lowest MIC values (512–1024 µg/mL). This activity was concluded to be attributable to the high concentrations of catechin and gallic acid. The anti-biofilm activity of catechin, gallic acid, and their combination was examined by a crystal violet assay. The combination reduced the percentage of strong and moderate biofilm-forming isolates from 52.63% to 5.26%. The impact on lasI and lasR genes expression using qRT-PCR and simultaneous docking against LasR protein was explored. The combination downregulated lasI and lasR gene expression in eight and six P. aeruginosa isolates, respectively, and showed the greatest docking score. Additionally, the in vivo protection capability of this combination in infected mice showed enhancement in the survival rate. Our study revealed the potential biofilm and quorum-sensing-inhibitory activity of the catechin and gallic acid combination as a novel alternative to inhibit bacterial pathogenicity.     

Preparation of Nitrogen and Sulfur Co-Doped Fluorescent Carbon Dots from Cellulose Nanocrystals as a Sensor for the Detection of Rutin

The poor water solubility, large particle size, and low accessibility of cellulose, the most abundant bioresource, have restricted its generalization to carbon dots (CDs). Herein, nitrogen and sulfur co-doped fluorescent carbon dots (N, S-CDs) were hydrothermally synthesized using cellulose nanocrystals (CNC) as a carbon precursor, exhibiting a small particle size and excellent aqueous dispersion. Thiourea was selected as a nitrogen and sulfur dopant to introduce abundant fluorescent functional groups into N, S-CDs. The resulting N, S-CDs exhibited nanoscale size (6.2 nm), abundant functional groups, bright blue fluorescence, high quantum yield (QY = 27.4%), and high overall yield (16.2%). The excellent optical properties of N, S-CDs endowed it to potentially display a highly sensitive fluorescence “turn off” response to rutin. The fluorescence response for rutin allowed a wide linear range of 0–40 mg·L⁻¹, with a limit of detection (LOD) of 0.02 μM, which revealed the potential of N, S-CDs as a rapid and simple sensing platform for rutin detection. In addition, the sustainable and large-scale production of the N, S-CDs in this study paves the way for the successful high-value utilization of cellulose.     

A Bregman-Split-Based Compressive Sensing Method for Dynamic Harmonic Estimation

In order to overcome the spectral interference of the conventional Fourier transform in the International Electrotechnical Commission framework, this paper introduces a Bregman-split-based compressive sensing (BSCS) method to estimate the Taylor–Fourier coefficients in a multi-frequency dynamic phasor model. Considering the DDC component estimation, this paper transforms the phasor problem into a compressive sensing model based on the regularity and sparsity of the dynamic harmonic signal distribution. It then derives an optimized hybrid regularization algorithm with the Bregman split method to reconstruct the dynamic phasor estimation. The accuracy of the model was verified by using the cross entropy to measure the distribution differences of values. Composite tests derived from the dynamic phasor test conditions were then used to verify the potentialities of the BSCS method. Simulation results show that the algorithm can alleviate the impact of dynamic signals on phasor estimation and significantly improve the estimation accuracy, which provides a theoretical basis for P-class phasor measurement units (PMUs).     

Improved Stretchable and Sensitive Fe Nanowire-Based Strain Sensor by Optimizing Areal Density of Nanowire Network

Flexible strain sensors, when considering high sensitivity and a large strain range, have become a key requirement for current robotic applications. However, it is still a thorny issue to take both factors into consideration at the same time. Here, we report a sandwich-structured strain sensor based on Fe nanowires (Fe NWs) that has a high GF (37–53) while taking into account a large strain range (15–57.5%), low hysteresis (2.45%), stability, and low cost with an areal density of Fe NWs of 4.4 mg/cm². Additionally, the relationship between the contact point of the conductive network, the output resistance, and the areal density of the sensing unit is analyzed. Microscopically, the contact points of the conductive network directly affect the sensor output resistance distribution, thereby affecting the gauge factor (GF) of the sensor. Macroscopically, the areal density and the output resistivity of the strain sensor have the opposite percolation theory, which affects its linearity performance. At the same time, there is a positive correlation between the areal density and the contact point: when the stretching amount is constant, it theoretically shows that the areal density affects the GF. When the areal density reaches this percolation threshold range, the sensing performance is the best. This will lay the foundation for rapid applications in wearable robots.