Tuning of emission by effect of local symmetry in BaLaLiWO6:Dy3+/Eu3+ for WLEDs

The luminescence center energy transfer, crystal field strength, and covalency are limited by the crystal structure of the host and subsequently affect the luminescence efficiency, color, and intensity. Here, we report an excellent red phosphor BaLaLiWO₆:0.40Eu³⁺ and the dependence between symmetry and luminous performance. A model for changing symmetry is drawn by analyzing the Coulomb potential and structure for the application of a double-perovskite phosphor BLLWO: Dy³⁺, Eu³⁺ in white light LEDs. The addition of Dy³⁺/Eu³⁺ makes the W-O bond formed by the B-site and oxygen ion longer and the Li-O bond shorter, and the difference between the eight octahedral around the A-site is reduced, increasing the symmetry of the A-site. Local symmetry was successfully modulated by changing the Eu³⁺ concentration to control the Y/B ratio of Dy³⁺ and the R/O ratio of Eu³⁺ and smoothly achieved (0.382, 0.373) warm white light color coordinate. The phosphor has excellent thermal stability and still has 92.3% intensity at 475 K. The above results show that the wavelength composition of the luminescence is tunable by changing the symmetry of the environment in which the doped ions are located. It applies to single hosts for the regulation of white light emission.     

面向分拣机器人的珍珠形状视觉检测方法

针对人工进行珍珠形状分拣效率低、精度不稳定等问题,提出基于机器视觉的珍珠形状检测方法;采用背光成像方式消除珍珠表面纹理和光泽的影响,对获取的珍珠图像进行同态滤波等预处理算法,提高图像对比度;为了解决相互接触珍珠影响珍珠轮廓提取的问题,采用分水岭算法对珍珠图像进行分割,得到了独立存在的珍珠个体,再通过连通域标记、质心算法对珍珠进行定位;根据国家标准对珍珠形状的规定,基于珍珠图像信息建立珍珠形状参数模型,对珍珠形状进行量化;实验结果表明,不同形状的珍珠样本的检测误差为0.63%,形状统计精度为100%,算法耗时24 ms;该方法可准确高效地对珍珠进行分拣分级,具有一定的实用价值。     

TGFβ-1 Induced Cross-Linking of the Extracellular Matrix of Primary Human Dermal Fibroblasts

Excessive cross-linking is a major factor in the resistance to the remodelling of the extracellular matrix (ECM) during fibrotic progression. The role of TGFβ signalling in impairing ECM remodelling has been demonstrated in various fibrotic models. We hypothesised that increased ECM cross-linking by TGFβ contributes to skin fibrosis in Systemic Sclerosis (SSc). Proteomics was used to identify cross-linking enzymes in the ECM of primary human dermal fibroblasts, and to compare their levels following treatment with TGFβ-1. A significant upregulation and enrichment of lysyl-oxidase-like 1, 2 and 4 and transglutaminase 2 were found. Western blotting confirmed the upregulation of lysyl hydroxylase 2 in the ECM. Increased transglutaminase activity in TGFβ-1 treated ECM was revealed from a cell-based assay. We employed a mass spectrometry-based method to identify alterations in the ECM cross-linking pattern caused by TGFβ-1. Cross-linking sites were identified in collagens I and V, fibrinogen and fibronectin. One cross-linking site in fibrinogen alpha was found only in TGFβ-treated samples. In conclusion, we have mapped novel cross-links between ECM proteins and demonstrated that activation of TGFβ signalling in cultured dermal fibroblasts upregulates multiple cross-linking enzymes in the ECM.     

基于K-means和SOM的水下传感器数据采集方法

随着海洋资源勘探和海洋污染物监控工作的开展，水文数据的监测和采集等已经成为重要的研究方向。其中，水下无线传感器网络在水文数据采集过程中起着举足轻重的作用。本文研究的是水下无线传感器二维监测网络模型中，传感器节点数据采集的问题，其设计方法是通过自组织映射（Self-organizing mapping，SOM）对传感器节点进行路径最优化处理，结合优化的路径图形和K-means算法找到路径内部聚合点，利用聚合点和传感器的节点得到传感器通信半径内的数据采集点，最后通过SOM得到水下机器人（Autonomous underwater vehicle，AUV）到各个数据采集点采集数据的最优路径。经过实验验证，在水下1 200 m×1 750 m范围内布置52个传感器节点的情景下，数据采集点相比于传感器节点路径规划采用相同的采集顺序得到的路径优化了6.7%；对数据采集点重新进行自组织路径规划得到的路径比传感器结点路径的最优解提高了12.2%。增加传感器节点的数量，其结果也大致相同，因此采用该方法可以提高水下机器人采集数据的效率。     

Molecular Characteristics of Amyloid Precursor Protein (APP) and Its Effects in Cancer

Amyloid precursor protein (APP) is a type 1 transmembrane glycoprotein, and its homologs amyloid precursor-like protein 1 (APLP1) and amyloid precursor-like protein 2 (APLP2) are highly conserved in mammals. APP and APLP are known to be intimately involved in the pathogenesis and progression of Alzheimer’s disease and to play important roles in neuronal homeostasis and development and neural transmission. APP and APLP are also expressed in non-neuronal tissues and are overexpressed in cancer cells. Furthermore, research indicates they are involved in several cancers. In this review, we examine the biological characteristics of APP-related family members and their roles in cancer.