基于纸浆纤维的贵重物品内包装塑造系统研究

为解决贵重物品与其内包装“契合度”不高的问题，提出基于纸浆纤维的贵重物品内包装塑造系统。系统通过三维扫描获取待包装物品的点云信息，经主控计算机进行数据处理，以下位机为执行中枢，辅之其他外部设备，利用纸浆纤维为贵重物品塑造“量身定制”的内包装，提升内包装契合度，增强保护效果，绿色环保，安全稳定。     

南美白对虾肝胰腺蛋白提取方法优化及无水保活环境胁迫对细胞凋亡蛋白的影响

为提高Western Blotting结果的可靠性，以蛋白溶出率和凝胶电泳蛋白条带完整性为指标，比较提取液种类、研磨方式、酶抑制剂种类及其体积分数和提取时间对南美白对虾肝胰腺蛋白提取效果的影响。采用优化后的提取方法获得高质量蛋白样品，并采用Western Blotting法分析无水环境胁迫后南美白对虾肝胰腺组织中细胞凋亡信号通路相关蛋白的表达水平。结果表明：RIPA裂解液作为提取溶剂所得的蛋白溶出率高于水提和磷酸盐缓冲液，电动匀浆和液氮研磨所得蛋白条带更完整，4%蛋白酶磷酸酶混合抑制剂能有效抑制肝胰腺内源酶引起的蛋白降解；采用Western Blotting法分析无水保活期间南美白对虾肝胰腺蛋白，发现低温诱导休眠的同时会引起细胞轻微凋亡，且凋亡水平呈应激时间依赖性增加，环境胁迫解除后有所回调。     

Acid–base transport model depicting the dynamic pH response of interfacial reactions

Acid–base transport is integral to many important interfacial reactions in various fields of chemistry, but its theoretical foundation is lacked. Herein, a common acid–base transport model is established owing to the success in deriving buffer transport equations. This model is applicable to most buffer systems by flexibly integrating the transport equations in terms of buffer components, and is verified through the model relationships of buffer transport limiting current by using hydrogen evolution reaction experiments. Based on model calculations, two diagram approaches are proposed to depict the dynamic pH response and aid buffer operation optimizations. The model and methods allow us to quantify the rate-limiting effect of acid–base transport on interfacial reactions and to precisely control the effect through medium regulations. Furthermore, the model has laid the foundation of dynamic pH effect on species transformation and process mechanism, which can be of wide interest in the chemistry encompassing interfacial reactions.     

Sparse spectrum fitting algorithm using signal covariance matrix reconstruction and weighted sparse constraint

Multidimensional Systems and Signal Processing - Although sparse spectrum fitting algorithm has good multi-target resolution, the performance is decreased under the influence of strong...     

基于推理注意力机制的二阶段网络图像修复

现有的图像修复方法在处理大面积缺失或高度纹理化的图像时，通常会产生扭曲的结构或与周围区域不一致的模糊纹理，无法重建合理的图像结构。为此，提出了一种基于推理注意力机制的二阶段网络图像修复方法。首先通过边缘生成网络生成合理的幻觉边缘信息，然后在图像补全网络完成图像的重建工作。为了进一步生成视觉效果更逼真的图像，提高图像修复的精确度，在图像补全网络采用推理注意力机制，有效控制了生成特征的不一致性，从而生成更有效的信息。所提方法在多个数据集上进行了实验验证，结果表明该图像修复方法的结构相似性指数达到了88.9%，峰值信噪比达到了25.56 dB，与现有的图像修复方法相比，该方法具有更高的图像修复精确度，生成的图像更逼真。