钠金属负极由于其理论比容量高(1 165 mA·h·g-1)、氧化还原电势低(-2.71 V vs.标准氢电极)和成本低，被认为是超越锂离子电池技术的理想候选材料。然而钠金属负极在实际应用中表现出钠枝晶生长和体积膨胀，导致其Coulomb效率低、循环寿命短等问题，这限制了其进一步发展。针对这些问题，研究者进行了大量工作，发现降低钠金属负极局部电流密度、增加钠成核位点、适当构建集流体孔隙缓解体积膨胀等手段，可以有效提高钠金属负极的循环稳定性。为此，本综述讨论了钠金属负极的主要问题；总结归纳了电沉积钠金属负极集流体的改性策略，包括三维集流体设计，掺杂、缺陷工程，晶种引入，缓冲层修饰；最后对高安全、高比能钠金属电池的未来发展提出展望。

利用光纤熔融拉锥技术，对一种中心对称、具有较大芯间距的多芯光纤进行了优化。融锥后的光纤具有倏逝场强、传感灵敏度高的特点，但由于其柔韧性差难于用作弯曲传感测量。本文设计了一种柔性传感器，使优化后的融锥光纤可用于弯曲传感测量。利用超模耦合理论对优化后多芯光纤传感器的透射谱进行了分析，并对其弯曲传感特性进行了实验研究。实验结果表明，该柔性融锥光纤传感器的干涉条纹与弯曲曲率有很好的线性关系。优化后的融锥光纤弯曲传感器的灵敏度为2.90 nm/m^-1。

针对YOLOv4目标检测网络结构复杂, 参数量以及计算量大等问题, 提出了一种轻量化目标检测算法(YOLOv4-GC)。首先, 使用ghostnet结构替换原始YOLOv4的主干网络, 降低了获取冗余特征图像的计算量, 在SPP与PANet模块中使用深度可分离卷积, 使模型的计算量和参数量比原始YOLOv4分别降低82%和80%; 再结合PyConv多尺度卷积设计出Py-PANet金字塔结构, 提高了模型对于图像特征的提取和融合能力。在Pascal VOC数据集上的实验结果表明, 在保证模型精度的情况下模型的参数量和计算量相比原始有明显降低。

Previous studies have already shown that Raman spectroscopy can be used in the encoding of suspension array technology. However, almost all existing convolutional neural network-based decoding approaches rely on supervision with ground truth, and may not be well generalized to unseen datasets, which were collected under different experimental conditions, applying with the same coded material. In this study, we propose an improved model based on CyCADA, named as Detail constraint Cycle Domain Adaptive Model (DCDA). DCDA implements the classification of unseen datasets through domain adaptation, adapts representations at the encode level with decoder-share, and enforces coding features while leveraging a feat loss. To improve detailed structural constraints, DCDA takes downsample connection and skips connection. Our model improves the poor generalization of existing models and saves the cost of the labeling process for unseen target datasets. Compared with other models, extensive experiments and ablation studies show the superiority of DCDA in terms of classification stability and generalization. The model proposed by the research achieves a classification with an accuracy of 100% when applied in datasets, in which the spectrum in the source domain is far less than the target domain.

为系统研究粉煤灰掺量、硅灰掺量及养护温度对湿喷混凝土力学性能的影响规律, 通过设计正交试验对湿喷混凝土抗压强度进行极差和方差分析。结果表明: 湿喷混凝土抗压强度随养护龄期增加而增大, 但抗压强度增幅随养护龄期延长而减弱; 增加硅灰和粉煤掺量均能有效提高湿喷混凝土抗压强度, 但粉煤灰掺量超过10%(质量分数, 下同)后, 粉煤灰掺量的增加对混凝土后期抗压强度没有显著的影响; 三因素对湿喷混凝土抗压强度影响程度顺序为硅灰掺量>养护温度>粉煤灰掺量; 湿喷混凝土抗压强度对矿物掺合料的敏感性与养护温度呈正相关, 增大养护温度能够提高矿物掺合料对湿喷混凝土抗压强度的改善效果; 随着养护温度的提高, 团絮状胶凝物质大量生成, 水化产物黏结得更为密实, 混凝土的抗压强度和承载性能得到进一步增强; 构建多元非线性回归模型能够对混凝土抗压强度进行预测, 并且湿喷混凝土在硅灰掺量、粉煤灰掺量及养护温度分别为15%、15%和10 ℃时具有最佳的抗压强度。

高压输电线的弧垂是线路设计和运行的重要指标，关系到线路的运行安全，必须控制在设计规定的范围内。输电线弧垂测量是国内外电力部门和研究机构的重点研究内容。基于毛细管光纤设计了一种新型的高压电线弧垂传感器。该传感器具有模场面积大、抗电磁干扰能力强、可实时在线监测的优点。实验结果表明，当传感器的弧垂曲率半径小于15 cm时，监测灵敏度为2.552 dB/cm，线性相关系数为0.9635。传感器的弧垂曲率半径越小，弯曲程度越大，毛细管光纤传感器的灵敏度就越高。该实验现象与理论分析结果相一致，验证了其在实际应用中的可行性。

针对现有高光谱遥感图像卷积神经网络分类算法空谱特征利用率不足的问题，提出一种多特征融合下基于混合卷积胶囊网络的高光谱图像分类策略。首先，联合使用主成分分析和非负矩阵分解对高光谱数据集进行降维；然后，将降维所得主成分通过超像素分割和余弦聚类生成一个多维特征集；最后，将叠加后的特征集通过二维、三维多尺度混合卷积网络进行空谱特征提取，并使用胶囊网络对其进行分类。通过在不同高光谱数据集下的实验结果表明，在相同 20维光谱维度下，所提策略相比于传统分类策略在总体精度、平均精度以及 Kappa系数上均有明显提升。

The size and shape of the foveal avascular zone (FAZ) have a strong positive correlation with several vision-threatening retinovascular diseases. The identification, segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment. We presented an adaptive watershed algorithm to automatically extract FAZ from retinal optical coherence tomography angiography (OCTA) images. For the traditional watershed algorithm, "over-segmentation" is the most common problem. FAZ is often incorrectly divided into multiple regions by redundant "dams". This paper analyzed the relationship between the "dams" length and the maximum inscribed circle radius of FAZ, and proposed an adaptive watershed algorithm to solve the problem of "over-segmentation". Here, 132 healthy retinal images and 50 diabetic retinopathy (DR) images were used to verify the accuracy and stability of the algorithm. Three ophthalmologists were invited to make quantitative and qualitative evaluations on the segmentation results of this algorithm. The quantitative evaluation results show that the correlation coefficients between the automatic and manual segmentation results are 0.945 (in healthy subjects) and 0.927 (in DR patients), respectively. For qualitative evaluation, the percentages of "perfect segmentation" (score of 3) and "good segmentation" (score of 2) are 99.4% (in healthy subjects) and 98.7% (in DR patients), respectively. This work promotes the application of watershed algorithm in FAZ segmentation, making it a useful tool for analyzing and diagnosing eye diseases.

电性能优良且成本低廉的铜微纳结构在柔性电子领域中展现出广阔的应用前景。激光直写因其快速灵活且可控性高等优势,成为铜微纳结构的高效加工方法之一。概述了微纳结构激光加工的技术特点,随后针对激光直写铜微纳结构展开论述。重点分析了前驱体成分及激光工艺参数对铜微/纳观结构及电性能的影响,探讨了激光直写在铜微纳结构可控制备中的优势。列举了所得结构在柔性电子器件制造中的典型应用场景,分析了典型器件的工作机理。此外,对激光直写微纳结构的未来发展趋势进行了展望。

Segmentation of layers in retinal images obtained by optical coherence tomography (OCT) has become an important clinical tool to diagnose ophthalmic diseases. However, due to the susceptibility to speckle noise and shadow of blood vessels etc., the layer segmentation technology based on a single image still fail to reach a satisfactory level. We propose a combination method of structure interpolation and lateral mean filtering (SI-LMF) to improve the signal-to-noise ratio based on one retinal image. Before performing one-dimensional lateral mean filtering to remove noise, structure interpolation was operated to eliminate thickness fluctuations. Then, we used boundary growth method to identify boundaries. Compared with existing segmentations, the method proposed in this paper requires less data and avoids the influence of microsaccade. The automatic segmentation method was verified on the spectral domain OCT volume images obtained from four normal objects, which successfully identified the boundaries of 10 physiological layers, consistent with the results based on the manual determination.