A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches

Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.

     

A hybrid damage model for simulating adiabatic shear bands

International Journal of Fracture - Adiabatic shear band (ASB) is one of the most important failure modes under high strain-rate deformation. In this work, we propose a hybrid damage model to...     

Establishment of a color tolerance for yarn-dyed fabrics from different color-depth yarns

Yarn-dyed fabric is often woven from warp and weft yarns in the same color depth to ensure a uniform color appearance. The difference in color depth between warp and weft tends to result in the uneven color of the yarn-dyed fabric. This article aims to establish a color tolerance for yarn-dyed fabric that can be woven with a qualified color appearance but from the warp and weft yarns in different color depths. A total of 27 yarn-dyed fabric samples in three color series (red, yellow, and blue) were evaluated by using the yarn-dyed fabric from warp and weft yarns in the same color depth of 2% (on weight of fabric, owf) as the standard. Visual assessment and instrumental measurement of color were carried out to establish the color tolerance ellipse that was defined as CMC (Color Measurement Committee) color differences (2:1) of no more than 1.00. It was found that the color strengths (K/S) and color differences (ΔE_CMC(2:1)) of these fabric samples for each color series had linear relationships with the color depths of warp and weft yarns. The color tolerance ellipses indicated that, even though the warp and weft yarns had an apparent color difference, they could be woven in fabrics with relatively uniform color appearance and meet the requirements for yarn-dyed fabric. This work provided valuable insight into the production of qualified yarn-dyed fabrics from unqualified dyed yarns.     

Learning from crowds with decision trees

Knowledge and Information Systems - Crowdsourcing systems provide an efficient way to collect labeled data by employing non-expert crowd workers. In practice, each instance obtains a multiple noisy...     

Modification of the wood-plastic composite for enhancement of formaldehyde clearance and the 3D printing application

As the formaldehyde is one of the main indoor pollutants, the purpose of this study is to effectively remove indoor formaldehyde pollution by using environmentally friendly 3D printing ornaments. The wood 3D printing filaments cellulose/polylactic acid composite (Cellu/P) was selected as the starting material, and 3-aminopropyltriethoxysilane (APTES) was used for chemical modification to obtain a series of cellulose composite materials with amino groups. The modified composite materials (APTES@Cellu/P) were characterized by Fourier transform infrared, X-ray diffraction, scanning electron microscope, energy dispersive spectroscopy, thermogravimetric analysis, and mechanical tests, and a formaldehyde removal experiment was performed. The feasibility of 3D printing was evaluated, and the process of 3D printing-functionalized customized ornaments was proposed, and then a school emblem was used for modeling, printing, and surface modification. Compared with the commercially traditional activated carbon, 3D printing-customized ornaments of APTES@Cellu/P material has a better formaldehyde removal effect, and can even avoid the secondary pollution that is common to the activated carbon.     

基于ABAQUS的EBZ260掘进机切割部结构性能分析

针对EBZ260掘进机切割部运行过程中出现的结构失效问题,基于EBZ260掘进机的结构特点,建立切割部三维模型与仿真模型,对掘进机切割部运行过程中的结构性能进行仿真研究.研究结果显示:切割部中减速箱轴承座、前端支撑座、套环等区域是整个结构的薄弱部位,极易出现结构变形、开裂等失效现象,为此从多个角度开采了掘进机切割部的优化改进,以提高切割部的结构强度及使用寿命.