Split Enzyme-Based Biosensors for Structural Characterization of Soluble and Insoluble β-Glucans

β-Glucan is widely distributed in various plants and microorganisms and is composed of β-1,3-linked d-glucose units. It may have a branched short or long side chain of glucose units with β-1,6- or β-1,4-linkage. Numerous studies have investigated different β-glucans and revealed their bioactivities. To understand the structure-function relationship of β-glucan, we constructed a split-luciferase complementation assay for the structural analysis of long-chain β-1,6-branched β-1,3-glucan. The N- and C-terminal fragments of luciferase from deep-sea shrimp were fused to insect-derived β-1,3-glucan recognition protein and fungal endo-β-1,6-glucanase (Neg1)-derived β-1,6-glucan recognition protein, respectively. In this approach, two β-glucan recognition proteins bound to β-glucan molecules come into close proximity, resulting in the assembly of the full-length reporter enzyme and induction of transient luciferase activity, indicative of the structure of β-glucan. To test the applicability of this assay, β-glucan and two β-glucan recognition proteins were mixed, resulting in an increase in the luminescence intensity in a β-1,3-glucan with a long polymer of β-1,6-glucan in a dose-dependent manner. This simple test also allows the monitoring of real-time changes in the side chain structure and serves as a convenient method to distinguish between β-1,3-glucan and long-chain β-1,6-branched β-1,3-glucan in various soluble and insoluble β-glucans.     

基于音频特征的工程车辆工况识别研究

高效率地使用工程车辆是工程项目管理中节约成本的有效方法，无人监管环境下工程车辆的工况识别，是实现工程车辆高效率使用的有效手段。目前以GPS等技术为核心的车辆智能管理系统未对工程车辆进行工况识别，提出一种基于GRU循环神经网络的工程车辆工况识别方法，通过对工程车辆在不同工况下产生的音频信号进行分析，从中提取Mel倒谱系数作为主要特征，构建GRU循环神经网络模型进行训练和识别。实验结果表明，该方法可以实现对工程车辆工况的有效识别。     

空间曲线的特征识别与高质量非均匀采样

为避免传统均匀采样方法因忽视曲线重要特征而生成不理想的采样结果,获得给定数量且由特征点和辅助点组成的采样点序列,提出基于特征识别的高质量空间曲线非均匀采样方法.首先使用抛物线插值法得到曲线上所有曲率极大值点和挠率极大值点的近似位置,经筛选后产生特征点,以更好地抓住空间曲线的轮廓特征.然后定义基于弧长、曲率和挠率加权组合的特征函数,并以此自适应地选取曲线上的辅助点.与3种主流采样方法比较的实验结果表明,该方法能够获得更高质量的采样结果且具有更好的实用性,从而进一步改善空间曲线的B样条拟合效果.     

基于表情识别技术的用户研究方法

目的为了以更加客观的方式评估用户体验,拓展用户研究的途径,引入表情识别技术对已有用户研究方法进行优化与探索。方法以阅读APP为研究载体,以表情识别与卷积神经网络算法为技术手段,通过设计人机交互实验将其应用于用户研究过程中,建立用户面部表情与用户主观满意度的映射关系。结果针对阅读APP"X",开展了基于表情识别技术和传统问卷访谈的双向设计研究,并采用对比验证的方法得出了基于表情识别技术的用户满意度客观度量方法的有效性和可行性,进而挖掘了基于表情识别方法的用户研究优势。结论基于表情识别技术的用户研究方法在产品交互设计中具有一定的通用性。通过识别分析用户与产品进行人机交互时的面部表情动态变化,可以使用户体验评估更加客观并容易解读,准确定位产品交互体验问题,为设计领域中的用户研究和认识提供了新思路,同时也为表情识别技术与产品设计的交叉融合提供了理论和实践意义的参考。     

国际橄榄理事会的定位和使命及相关标准（网络首发、推荐阅读）

The International Olive Council(IOC) is an international intergovernmental organization dedicated to olive oil and table olives, aiming at modernizing olive production, coordinating olive policies, improving the regulation of international trade, defending the quality of the olive sector and promoting olive oil and table olives to increase their consumption. The IOC grants recognition of laboratories and tasting panels in annual trials when they meet the conditions given in the decisions adopting the IOC certificate for laboratories for the physico–chemical testing of olive oil and laboratories for the sensory analysis of virgin olive oils. The IOC establishes analysis methods applying to olive oils and olive pomace oils for purity, quality and organoleptic assessment. The IOC elaborates guides of storage conditions for olive oils and olive pomace oils, of managing virgin olive oil tasting panels and of sensory testing laboratories. In future works, the IOC includes activities to identify analytical criteria for detecting fraud and guaranteeing the quality of olive oils and olive pomace oils.     

针对细微特征进行K-means聚类的电台分选识别技术

现代战场中的无线通信设备日益增多，精准获取个体信息已成为研究热点，但也是难点。针对通信电台，提出了一种分选识别技术。该技术从电台物理层特性出发，对其辐射信号的细微特征进行K-means聚类以实现分选，分选的同时提取各个个体的特征属性值，未知信号通过与特征属性值相关运算实现个体识别。该技术无需先验知识，无需训练运算，通过实验验证，其可行、高效，易于工程实现。     

智能假肢膝关节的研发要点及其研究进展综述

目的 介绍国内外智能假肢膝关节研究的主要进展,为相关领域的研发提供可借鉴的思路.方法 基于机械结构、调控方式、驱动方式,对典型假肢膝关节进行了分类比较,并从假肢穿戴者的运动意图识别、驱动控制、人机协调控制等方面做了分析.此外,对假肢膝关节在智能化研究与安全性、个性化与通用性、人机共融技术、科学伦理、关键技术等方面需要注意的问题,提出了研发要点和技术思路.结论 智能假肢膝关节应注重安全性与稳定性,规避用户在使用过程中的潜在危险因素;实现假肢控制参数的自整定和灵活适配,在个性化与通用性上达到平衡;综合考虑人—机—环境因素,实现协调控制;坚持"以人为本",在技术方法和科学伦理两个方面开展医工结合的研究;突破关键技术限制,建立完善的社会医疗康复保障服务体系.     

基于评价函数和BP网络的CRDM滚轮状态评估方法

针对采集的控制棒驱动机构（CRDM）振动信号中存在非平稳、强噪声失真信号，提出一种基于评价函数和误差反向传播（BP）网络的CRDM滚轮状态评估方法。信号经半软阈值去噪、局部均值分解（LMD）提取特征向量，特征向量组成的样本集经BP网络进行状态识别，引入评价函数对状态识别结果进行评价，依据评价结果进行失真样本剔除，保留新形成的样本集进行状态识别。结果表明，基于评价函数和BP网络的CRDM滚轮状态评估方法能有效对滚轮缺陷状态进行识别，解决了控制棒驱动机构滚轮状态难以进行准确识别的问题。      

Molecularly imprinted macroporous polymer monolithic layers for L-phenylalanine recognition in complex biological fluids

In present work, the development of macroporous monolithic layers bearing the artificial recognition sites toward L-phenylalanine has been carried out. The set of macroporous poly(2-aminoethyl methacrylate-co-2-hydroxyethyl methacrylate-co-ethylene glycol dimethacrylate) materials with average pore size ranged in 340–1200 nm was synthesized. The applicability of Hildebrand's and Hansen's theories for the prediction of polymer compatibility with porogenic solvents was evaluated. The dependences of average pore size on theoretically calculated parameters were plotted. The linear trend detected for Hansen's theory has indicated the high suitability of this approach to select appropriate porogens. The synthesized monolithic MIP layers were tested toward the ability to rebind phenylalanine-derivative in microarray format. The influence of such factors as average pore size of the material, the concentration of template molecule in polymerization mixture, interaction time of analyte with its imprinted sites on binding efficiency were studied. The developed materials demonstrated good analyte rebinding from buffer solution with recognition factors 2.5–3.4 depending on the MIP sample. The comparable rebinding efficiency was also detected when the analysis was carried using complex biological media. The selectivity of phenylalanine binding from the equimolar mixture of structural analogues was 81.9% for free amino acid and 91.2% for labeled one.