Electrochemical Quantification of Neurotransmitters in Single Live Cell Vesicles Shows Exocytosis is Predominantly Partial

Exocytosis plays an essential role in the communication between cells in the nervous system. Understanding the regulation of neurotransmitter release during exocytosis and the amount of neurotransmitter content that is stored in vesicles is of importance, as it provides fundamental insights to understand how the brain works and how neurons elicit a certain behavior. In this minireview, we summarize recent progress in amperometric measurements for monitoring exocytosis in single cells and electrochemical cytometry measurements of vesicular neurotransmitter content in individual vesicles. Important steps have increased our understanding of the different mechanisms of exocytosis. Increasing evidence is firmly establishing that partial release is the primary mechanism of release in multiple cell types.     

Distance and similarity measures of Pythagorean fuzzy sets based on the Hausdorff metric with application to fuzzy TOPSIS

Pythagorean fuzzy sets (PFSs) were proposed by Yager in 2013 to treat imprecise and vague information in daily life more rigorously and efficiently with higher precision than intuitionistic fuzzy sets. In this paper, we construct new distance and similarity measures of PFSs based on the Hausdorff metric. We first develop a method to calculate a distance between PFSs based on the Hasudorff metric, along with proving several properties and theorems. We then consider a generalization of other distance measures, such as the Hamming distance, the Euclidean distance, and their normalized versions. On the basis of the proposed distances for PFSs, we give new similarity measures to compute the similarity degree of PFSs. Some examples related to pattern recognition and linguistic variables are used to validate the proposed distance and similarity measures. Finally, we apply the proposed methods to multicriteria decision-making by constructing a Pythagorean fuzzy Technique for Order Preference by Similarity to an Ideal Solution and then present a practical example to address an important issue related to social sector. Numerical results indicate that the proposed methods are reasonable and applicable and also that they are well suited in pattern recognition, linguistic variables, and multicriteria decision-making with PFSs.     

湖州南方中转仓储及输送工程建设特点

介绍了湖州南方物流有限公司中转仓储及输送工程项目的建设背景、建设条件,以及线路规划、主要技术方案,该项目是国内采用长距离越野曲线带式输送机系统运输熟料距离最长的绿色环保工程。项目以电力驱动运输替代汽车运输,日输送量达4.5~5万吨。采用密闭廊道输送,粉尘排放量低,噪声<50dB,日均减少汽车运输3000辆次,年节约燃油2000余吨,减少了尾气排放,缓解了沿线的交通拥堵,实现了良好的经济效益和社会效益。     

Chest X-ray enhancement to interpret pneumonia malformation based on fuzzy soft set and Dempster–Shafer theory of evidence

Image enhancement algorithms are commonly used to increase the contrast and visual quality of low-dose x-ray images. This paper proposes an automated enhancement method using soft fuzzy sets with a new decision-making scheme based on Dempster-Shafer theory of evidence for the visual interpretation of pneumonia malformation in low-dose x-ray images, called as XEFSDS. The XEFSDS model first generates an original source x-ray image into a complementary image, then each original and complement image is applied to the characterized image object and background areas of fuzzy space. The S-function is utilized to define fuzzy soft sets for the classification of gray level ambiguity in both images, and hence a decision criterion via Dempster-Shafer approach and fuzzy interval has been adapted to discriminate uncertainties on the pixel intensity and the spatial information. Modified membership grade operations have been performed on each object/background area, and Werner’s AND/OR operator (an aggregation operator) has been utilized to build a new membership function from two modified membership functions. Finally, an enhanced image is obtained from the new membership function via defuzzification. Experiments on different pneumonia X-ray images demonstrate that the XEFSDS scheme produces better results than the existing methods. To show the advantages of the XEFSDS scheme, we have executed a segmentation based examination on enhanced image for the detection of pneumonia malformation as well as abnormal lobe (lobar pneumonia) or bronchopneumonia.     

基于工业机器人的液压支架导向套柔性制造系统

自动化技术在小批量多品种的产品制造中，存在兼容难、换产时间长、人工干预多等问题，导致生产线难以高效率运行。设计的柔性制造系统，在充分分析了导向套不同结构、不同规格的基础上，以一套六关节机器人和行走地轨作为物流搬运设备，同时负责3台数控设备、自动辊道上料设备、自动堆垛下料设备、翻转机构、打标机构及抽检机构的上下料，并通过使用机器人双工位卡爪、机床六爪卡盘、自动刀补等卡具及技术，实现了一键换产，极大提高了制造系统的柔性。     

闭口闪点测定方法的对比分析

对我国常用的闭口闪点测定方法宾斯基-马丁闭口杯法、阿贝尔闭口杯法和泰格闭口杯法的测定原理进行对比分析，并采用这3种方法分别对2种有证标准样品、4种有机试剂样品和7种喷气燃料样品的闭口闪点进行测定。结果表明：这3种方法在适用范围、仪器结构、升温速率和点火操作要求等方面都有一定差异，导致采用这3种方法测定同一样品的闭口闪点结果略有差异，闪点测定结果之间的最大差值与样品闪点的高低呈正相关；与阿贝尔闭口杯法相比，宾斯基-马丁闭口杯法测得的闪点结果较高，对于3号喷气燃料，二者之差为0～1.0 ℃，阿贝尔闭口杯法更适合3号喷气燃料闭口闪点的测定；对于纯有机试剂样品，阿贝尔闭口杯法和宾斯基-马丁闭口杯法测得的闪点结果呈现较好的线性关系。     

Traffic video‐based intelligent traffic control system for smart cities using modified ant colony optimizer

Road traffic congestion is a serious problem in today's world and it happens because of urbanization and population growth. The traffic reduces the transport efficiency in the city, increases the waiting time and travel time, and also increases the usage of fuel and air pollution. To overcome these issues this papers propose an intelligent traffic control system using the Internet of Vehicles (IoV). The vehicles or nodes present in the IoV can communicate between themselves. This technique helps in determining the traffic intensity and the best route to reach the destination. The area of study used in this paper is Vellore city in Tamilnadu, India. The city map is separated into many segments of equal size and Ant Colony Algorithm (AOC) is applied to the separated maps to find the optimal route to reach the destination. Further, Support Vector Machine (SVM) is used to calculate the traffic density and to model the heavy traffic. The proposed algorithm performs better in finding the optimal route when compared to that of the existing path selection algorithms. From the results, it is evident that the proposed IoV‐based route selection method provides better performance.     

面向文本数据的正则化交叉验证方法

面向文本数据建模时,交叉验证方法是特征选择及模型比较任务中的常用方法。许多研究表明,文本数据模型的性能估计对交叉验证的数据切分方式较为敏感,不合理的切分方式可能会导致不稳定的性能估计值,使得实验结果可复现性差。该文试图论证基于多次重复(m次)的2折交叉验证,通过引入对训练集、验证集分布差异的约束,所构造的正则化m×2交叉验证方法(简记为m×2 BCV)可以改善模型的性能指标的估计,适宜于模型比较。该文首先针对文本数据引入训练集与验证集分布差异的卡方度量,基于该度量构建数据切分的正则化条件,以最大化模型性能指标的信噪比为目标,给出了满足正则化条件的m×2 BCV的数据切分优化算法。最后,以自然语言处理中汉语框架语义角色标注任务为例,验证了基于m×2 BCV方法的有效性。