灌注桩基础工程质量事故的处理

灌注桩基础是珠江三角洲地区工业与民用建筑广泛采用的基础形式之一,但由于各种原因,发生质量问题的灌注桩基础屡见不鲜.本文简明地介绍了灌注桩基础工程质量事故概况、灌注桩质量检测和评价方法以及灌注桩质量事故处理的常用方法.     

浅析如何在溶剂萃取机理研究中正确使用斜率法

斜率法是萃取机理研究最为常用的方法之一。尽管其理论基础和使用方法非常简单,但该方法却常常被误用,导致其非但不能有效的确定萃取机理,反而产生了误导性结论。本文以t-BAMBP萃取碱金属离子(K~+、Rb~+、Cs~+)体系为例讨论了常见的错误用法以及造成这类情况的根源问题,之后对其他萃取体系中类似错误用法进行了简要评述,表明斜率法的错误使用主要源于对萃取反应方程式的错误假定及对工作方程推导过程中引入的近似处理理解不当。最后总结了在萃取机理研究中正确使用斜率法的几点注意事项。     

Characterization of Turbot(Scophthalmus maximus) Skin and the Extracted Acid-Soluble Collagen

The biochemical composition of the turbot skin was investigated. The moisture level of the skin was found to be 51.4%. Based on dry matter content, there were relatively high protein(82.1%) and lipid(13.1%) concentrations in the turbot skin. Mineral element analysis revealed that the turbot skin had high Ca content(2069.0 mg kg^-1), and the concentrations of toxic heavy metals Hg and Pb were less than 0.005 mg kg^-1, which indicates that the turbot skin is a safe resource for collagen production. The sodium dodecyl sulfate-polyacrylamide gel electrophoresis(SDS-PAGE) analysis showed that acid-soluble collagen(ASC) extracted from the turbot skin was type-I collagen. The imino acid content of the ASC was 241.6 per 1000 amino acids, which suggests a relatively high denaturation temperature. The Fourier transform infrared(FTIR) spectra of ASC reflected a highly stable structure, and the measured denaturation temperature of ASC was 29.5℃, which is higher than those from many temperate fishes. ASC was the most soluble at pH 4.0, and when the pH values were below or above 4.0, the solubility decreased rapidly. The ASC exhibited a relatively high solubility when NaCl concentration was lower than 2%. These results show that turbo skin can be employed as a source for producing collagen with high quality.     

Evolution and driving forces of rural functions in urban agglomeration: A case study of the Chang-Zhu-Tan region

Journal of Geographical Sciences - As the Rural Revitalization Strategy is gradually implemented, China’s rural areas are set to have more diverse function requirements. This paper selects...     

番红砗磲外套膜色素提取条件优化及成分分析

以番红砗磲(Tridacna crocea)为实验对象,通过单因素对比实验对其外套膜色素的提取条件进行了优化,并利用薄层层析色谱法对色素组成进行了初步分析。结果表明:丙酮和乙醇为适宜的番红砗磲外套膜色素提取剂;使用丙酮为提取剂时,浸提时间为4 h,提取温度为25℃,料液比为1︰40。使用乙醇为提取剂时,浸提时间为4 h,提取温度为30℃,料液比为1︰200;利用薄层色谱法分离外套膜颜色为蓝色和红棕色的番红砗磲外套膜色素后发现,蓝色番红砗磲外套膜色素由9种色素组分构成,红棕色个体番红砗磲外套膜色素由10种色素组分构成。     

Isolation of protein from Chlorella sorokiniana CY1 using liquid biphasic flotation assisted with sonication through sugaring-out effect

Microalgae,a sustainable source of multi beneficial components has been discovered and could be utilised in pharmaceutical,bioenergy and food applications.This study aims to investigate the sugaring-out effect on the recovery of protein from wet green microalga,Chlorella sorokiniana CY1 which was assisted with sonication.A comparison of monosaccharides and disaccharides as one of the phaseforming constituents shows that the monosaccharides,glucose was the most suitable sugar in forming the phases with acetonitrile to enhance the production of protein(52% of protein).The protein productivity of microalgae was found to be significantly influenced by the volume ratio of both phases,as the yield of protein increased to 77%.The interval time between the sonication as well as the sonication modes were influencing the protein productivity as well.The optimum protein productivity was obtained with 10s of resting time in between sonication.Pulse mode of sonication was suitable to break down the cell wall of microalgae compared to continuous mode as a lower protein yield was obtained with the application of continuous mode.The optimum condition for protein extraction were found as followed:200g/L glucose as bottom phase with volume ratio of 1:1.25,10s of resting time for ultrasonication,5s of ultrasonication in pulse mode and 0.25g of biomass weight.The high yield of protein about 81% could be obtained from microalgae which demonstrates the potential of this source and expected to play an important role in the future.     

大面积水深异常检测的条件变化自编码算法

针对大面积海底地形数据缺失或异常的复杂及多变性特点,结合条件变分自编码器(CVAE)与深度卷积生成对抗网络(DCGAN),构建了条件变分自编码生成对抗网络(CVAE-GAN)大面积海底伪地形的检测与剔除方法。本文方法利用条件变分自编码算法改变原有的样本分布,通过对训练样本的学习重新构建样本之间的分布规律,有效提高了高维到低维映射的稳定性;结合生成对抗网络,提高了整体算法的稳健性,最终得到较优的检测与剔除结果。采用水深格网数据进行试验,并与中值滤波法、趋势面滤波法进行比较。结果表明,本文方法在精度、稳定性及噪声稳健性方面有所提高,验证了本文方法在海底地形数据处理上具有可行性。     

结合深度学习和图割法的遥感影像建筑物检测

提出一种基于卷积神经网络和图割法的自动提取高分影像建筑物的方法。首先,通过卷积神经网络定位与检测建筑物的位置,逐一提取单个建筑物轮廓,利用检测结果分别建立建筑物和非建筑物的高斯混合模型（GMM）,然后结合最大流最小割的图像分割方式实现全局优化,完成建筑物初步提取,最后用形态学进行优化。通过试验证明了该方法的可行性。     

A literature synthesis of LiDAR applications in transportation: feature extraction and geometric assessments of highways

Interest in using Light Detection and Ranging (LiDAR) technology in Transportation Engineering has grown over the past decade. The high accuracy of LiDAR datasets and the efficiency by which they can be collected has led many transportation agencies to consider mobile LiDAR as an alternative to conventional tools when surveying roadway infrastructure. Nonetheless, extracting semantic information from LiDAR datasets can be extremely challenging. Although extracting roadway features from LiDAR has been considered in previous research, the extraction of some features has received more attention than others. In fact, for some roadway design elements, attempts to extract those elements from LiDAR have been extremely scarce. To document the research that has been done in this area, this paper conducts a thorough review of existing studies while also highlighting areas where more research is required. Unlike previous research, this paper includes a thorough review of the previous attempts at data extraction from LiDAR while summarizing the detailed steps of the extraction procedure proposed in each study. Moreover, the paper also identifies common tools and techniques used to extract information from LiDAR for transportation applications. The paper also highlights common limitations in existing algorithms that could be improved in future research. This paper represents a valuable resource for researchers and practitioners interested in knowing the current state of research on the applications of LiDAR in the field of Transportation Engineering while also understanding the opportunities and challenges that lie ahead.