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.

     

Bacteriophages vB_Sen-TO17 and vB_Sen-E22, Newly Isolated Viruses from Chicken Feces,Specific for Several Salmonella enterica Strains

Two newly discovered bacteriophages, isolated from chicken feces and infecting Salmonella enterica strains, are described in this report. These phages have been named vB_Sen-TO17 and vB_Sen-E22, and we present their molecular and functional characterization. Both studied viruses are able to infect several S. enterica strains and develop lytically, but their specific host ranges differ significantly. Electron microscopic analyses of virions have been performed, and full genome sequences were determined and characterized, along with molecular phylogenetic studies. Genomes of vB_Sen-TO17 (ds DNA of 41,658 bp) and vB_Sen-E22 (dsDNA of 108,987 bp) are devoid of homologs of any known or putative gene coding for toxins or any other proteins potentially deleterious for eukaryotic cells. Both phages adsorbed efficiently (>95% adsorbed virions) within 10 min at 42 °C (resembling chicken body temperature) on cells of most tested host strains. Kinetics of lytic development of vB_Sen-TO17 and vB_Sen-E22, determined in one-step growth experiments, indicated that development is complete within 30–40 min at 42 °C, whereas burst sizes vary from 9 to 79 progeny phages per cell for vB_Sen-TO17 and from 18 to 64 for vB_Sen-E22, depending on the host strain. Virions of both phages were relatively stable (from several percent to almost 100% survivability) under various conditions, including acidic and alkaline pH values (from 3 to 12), temperatures from −80 °C to 60 °C, 70% ethanol, chloroform, and 10% DMSO. These characteristics of vB_Sen-TO17 and vB_Sen-E22 indicate that these phages might be considered in further studies on phage therapy, particularly in attempts to eliminate S. enterica from chicken intestine.     

Effect of Acute Sprint Exercise on Myokines and Food Intake Hormones in Young Healthy Men

Physical exercise is known to influence hormonal mediators of appetite, but the effect of short-term maximal intensity exercise on plasma levels of appetite hormones and cytokines has been little studied. We investigated the effect of a 30 s Wingate Test, followed by a postprandial period, on appetite sensations, food intake, and appetite hormones. Twenty-six physically active young males rated their subjective feelings of hunger, prospective food consumption, and fatigue on visual analogue scales at baseline, after exercise was completed, and during the postprandial period. Blood samples were obtained for the measurement of nesfatin-1, ghrelin, leptin, insulin, pancreatic polypeptide (PP), human growth factor (hGH) and cytokine interleukin-6 (IL-6), irisin and plasma lactate concentrations, at 30 min before exercise, immediately (210 s) after exercise, and 30 min following a meal and at corresponding times in control sedentary males without ad libitum meal intake, respectively. Appetite perceptions and food intake were decreased in response to exercise. Plasma levels of irisin, IL-6, lactate, nesfatin-1 and ghrelin was increased after exercise and then it was returned to postprandial/control period in both groups. A significant rise in plasma insulin, hGH and PP levels after exercise was observed while meal intake potentiated this response. In conclusion, an acute short-term fatiguing exercise can transiently suppress hunger sensations and food intake in humans. We postulate that this physiological response involves exercise-induced alterations in plasma hormones and the release of myokines such as irisin and IL-6, and supports the notion of existence of the skeletal muscle–brain–gut axis. Nevertheless, the detailed relationship between acute exercise releasing myokines, appetite sensations and impairment of this axis leading to several diseases should be further examined.     

A Stochastic Petri Net-Based Model of the Involvement of Interleukin 18 in Atherosclerosis

Interleukin 18 (IL-18) is a proinflammatory and proatherogenic cytokine with pleiotropic properties, which is involved in T and NK cell maturation and the synthesis of other inflammatory cytokines and cell adhesion molecules. It plays a significant role in orchestrating the cytokine cascade, accelerates atherosclerosis and influences plaque vulnerability. To investigate the influence of IL-18 cytokine on atherosclerosis development, a stochastic Petri net model was built and then analyzed. First, MCT-sets and t-clusters were generated, then knockout and simulation-based analysis was conducted. The application of systems approach that was used in this research enabled an in-depth analysis of the studied phenomenon. Our results gave us better insight into the studied phenomenon and allow revealing that activation of macrophages by the classical pathway and IL-18-MyD88 signaling axis is crucial for the modeled process.     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.     

Training neural networks on high-dimensional data using random projection

Pattern Analysis and Applications - Training deep neural networks (DNNs) on high-dimensional data with no spatial structure poses a major computational problem. It implies a network architecture...     

A quadratic boundedness approach to a neural network-based simultaneous estimation of actuator and sensor faults

Neural Computing and Applications - The paper is devoted to the problem of a neural network-based robust simultaneous actuator and sensor faults estimator design for the purpose of the fault...     

An Image Super-Resolution Reconstruction Method with Single Frame Character Based on Wavelet Neural Network in Internet of Things

Mobile Networks and Applications - The application of the traditional single frame character image super-resolution reconstruction method has some problems, such as noise can not be removed...     

The Numerical Comparison of Heat Transfer in a Coated and Fixed Bed of an Adsorption Chiller

Ecological adsorption technology is becoming a focus of attention by industry due to the utilization of low grade thermal energy sources for cooling production. It can be a promising part of sustainable development concept of the global economy. Therefore, research aiming at improving their performance i.e. Coefficient of Performance (COP) by optimizing the construction of sorption beds with a built in heat exchanger system is crucial. The heat transfer characteristics between the bed of porous media (sorbent) and surface of the heat exchanger system determine the heating power of an adsorption chiller. The HP increase can be obtained by heat transfer intensification due to the increase in the thermal conductivity of the sorbent layer in the vicinity of the heat exchanger’s surface. The novel modification of the sorbent layer structure is proposed in the paper in order to improve the heat transfer processes in the heat exchanger boundary layer. The analysis of desorption process conditions in the parametric model of a coated and fixed adsorption bed design is presented in the paper. The computational fluid dynamics (CFD) with conjugate heat transfer analysis is used to determine the crucial input parameters (temperature distribution in the sorbent bed) for further analytical calculations. The commercial code Ansys Fluent was used to perform numerical simulations. The developed computational model consisted of three subdomains representing heating water, heat exchanger material (copper) and sorbent (silica gel). The comparison of a novel coated design and a conventional fixed bed is discussed in the paper. The numerical analysis is based on experimental thermal conductivity measurements of the sorbent layer in different configurations, which were performed using Laser Flash Method.