Survival of Listeria monocytogenes on a conveyor belt material with or without antimicrobial additives, in the absence or presence of food debris from meat, fish and vegetables and at temperatures of 10, 25 and 37 degrees C was investigated. The pathogen survived best at 10 degrees C, and better at 25 degrees C than at 37 degrees C on both conveyor belt materials. The reduction in the numbers of the pathogen on belt material with antimicrobial additives in the first 6h at 10 degrees C was 0.6 log unit, which was significantly higher (P<0.05) than the reduction of 0.2 log unit on belt material without additives. Reductions were significantly less (P<0.05) in the presence of food residue. At 37 degrees C and 20% relative humidity, large decreases in the numbers of the pathogen on both conveyor belt materials during the first 6h were observed. Under these conditions, there was no obvious effect of the antimicrobial substances. However, at 25 degrees C and 10 degrees C and high humidity (60-75% rh), a rapid decrease in bacterial numbers on the belt material with antimicrobial substances was observed. Apparently the reduction in numbers of L. monocytogenes on belt material with antimicrobial additives was greater than on belt material without additives only when the surfaces were wet. Moreover, the presence of food debris neutralized the effect of the antimicrobials. The results suggest that the antimicrobial additives in conveyor belt material could help to reduce numbers of microorganisms on belts at low temperatures when food residues are absent and belts are not rapidly dried.
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http://dx.doi.org/10.1016/j.ijfoodmicro.2010.06.021 | DOI Listing |
Sci Rep
January 2025
School of Intelligent Manufacturing and Modern Industry (School of Mechanical Engineering), Xinjiang University, Ürümqi, 830017, China.
The rapid expansion of the coal mining industry has introduced significant safety risks, particularly within the harsh environments of open-pit coal mines. The safe and stable operation of belt conveyor idlers is crucial not only for ensuring efficient coal production but also for safeguarding the lives of coal mine workers. Therefore, this paper proposes a method based on deep learning for real-time detection of conveyor idler faults.
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January 2025
School of Mechanical Engineering, Xinjiang University, Urumqi, 830000, China.
Real-time detection of conveyor belt tearing is of great significance to ensure mining in the coal industry. The longitudinal tear damage problem of conveyor belts has the characteristics of multi-scale, abundant small targets, and complex interference sources. Therefore, in order to improve the performance of small-size tear damage detection algorithms under complex interference, a visual detection method YOLO-STOD based on deep learning was proposed.
View Article and Find Full Text PDFMin Metall Explor
November 2024
Miller Consulting, Spokane, WA, USA.
Occupational exposures to respirable dusts and respirable crystalline silica (RCS) is well established as a health hazard in many industries including mining, construction, and oil and gas extraction. The U.S.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Graduate School of Artificial Intelligence, Pohang University of Science and Technology, Pohang 37673, Republic of Korea.
Belt conveyor idlers are freely rotating idlers supporting the belt of a conveyor, and can induce severe frictional damage to the belt as they fail. Therefore, fast and accurate detection of idler faults is crucial for the effective maintenance of belt conveyor systems. In this article, we implement and evaluate the performance of an idler stall detection system based on a multivariate deep learning model using accelerometers and microphone sensor data.
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December 2024
College of Safety Science and Engineering, Liaoning Technical University, 47 Zhonghua Road, Xihe District, Fuxin City, 123000, Liaoning Province, China.
Based on the engineering example of Linsheng coal mine, this paper uses TF1M3D computer simulation platform to systematically analyze the process of smoke flow spreading and air flow disorder disaster from the perspective of the whole mine network, and puts forward corresponding plans and measures. A small scale similar experiment was carried out to study the updraft flow fire in the mine. Through the analysis of the collected experimental data, the variation law of the air volume of the fire source in the main air path, side branch road and total air path with different air volume and the variation characteristics of the temperature at the monitoring point with time were obtained under different air volume conditions, and the critical air volume was fitted as 1.
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