Oxidative characteristics and gel properties of porcine myofibrillar proteins affected by l-lysine and l-histidine in a dose-dependent manner at a low and high salt concentration

This study investigated the effects of l -lysine (Lys) and l -histidine (His) on the oxidative characteristics and gel properties of porcine myofibrillar proteins (MP). Results showed that Lys and His had a strong ferrous ion-chelating ability and hydroxyl radical-scavenging activity. Moreover, Lys and His inhibited the protein carbonyl formation and MP aggregation at 0.2 M and 0.6 M NaCl, respectively, in a dose-dependent manner. Furthermore, 2 and 4 mg mL⁻¹ Lys and His decreased the oxidation-induced loss of the tertiary structure of MP accompanied by the lower surface hydrophobicity. The water-holding capacity and gel strength of MP gels increased with increasing Lys and His concentrations due to more regular and lamellar structures with smaller and homogeneous pores at 0.6 M NaCl and more orderly crosslinking via fibrous filament at 0.2 M NaCl. In summary, Lys and His chelated the ferrous ions and scavenged hydroxyl radicals, decreased the oxidation-induced physicochemical changes, thus preventing oxidative damage during the formation of a three-dimensional gel network, which resulted in better gel quality.     

Learning user-emotion and user-feature couplings for image emotion classification

Multimedia Tools and Applications - Over the past few years, image emotion classification (IEC) has received increasing research interest. Existing works usually define IEC as a multi-class...     

Substrate temperature-controlled precursor reaction mechanism of PEALD-deposited MoOx thin films

Journal of Materials Science - Molybdenum oxide (MoOx) films had been grown by using plasma-enhanced atomic layer deposition (PEALD) with Mo(CO)6 precursor and O2 plasma reactant in a substrate...     

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。     

A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction,segmentation, classification and detection approaches

With the development of Computer-aided Diagnosis (CAD) and image scanning techniques, Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis. Therefore, WSI analysis has become the key to modern digital histopathology. Since 2004, WSI has been used widely in CAD. Since machine vision methods are usually based on semi-automatic or fully automatic computer algorithms, they are highly efficient and labor-saving. The combination of WSI and CAD technologies for segmentation, classification, and detection helps histopathologists to obtain more stable and quantitative results with minimum labor costs and improved diagnosis objectivity. This paper reviews the methods of WSI analysis based on machine learning. Firstly, the development status of WSI and CAD methods are introduced. Secondly, we discuss publicly available WSI datasets and evaluation metrics for segmentation, classification, and detection tasks. Then, the latest development of machine learning techniques in WSI segmentation, classification, and detection are reviewed. Finally, the existing methods are studied, and the application prospects of the methods in this field are forecasted.