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Influence of Strain Rates and Aging Time on Microstructure and Hardness of Integrally Compressed 6082 Aluminum Alloy

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SSRN 2023年

作者： Hu, Zhili Zheng, Jia Pang, Qiu Sun, Qian Zhao, Ning Hubei Long Zhong laboratory Hubei Xiangyang441000 China Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology Wuhan430070 China Hubei Research Center for New Energy & Intelligent Connected Vehicle Wuhan University of Technology Wuhan430070 China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China National & Local Joint Engineering Laboratory for Special Titanium Alloy Pressing Technologies Western Superconducting Technologies Co. Ltd. Xi’an710018 China

In this study, an in-depth analysis of the microstructure and hardness of 6082 aluminum alloy under a novel solution-forging integrated process is conducted by performing a series of isothermal uniaxial compression tests at various strain rates and aging durations. The results indicate that the highest hardness achieved is 125 HV at peak aging with a forming strain rate of 10 s-1, a 16.1% improvement compared to the conventional T6 forming process. The deformation shortens the subsequent peak aging time from 8 hours in the conventional process to 6 hours. In addition, the composite phases, including short-range disordered B'/U2 phase and composite phase with multiple structures, are also discovered under the condition of a strain rate of 10 s-1 and 6 hours of aging. While, as the strain rate increases, the degree of recrystallization decreases and then the refined grain size increases, accompanied by the increase in dislocation density. For the integrated process, the deformation microstructure inherited to the aging state, including grain morphology and dislocation density, as well as the aging precipitated phase, especially for the formation of composite phase, are the main reasons for the higher hardness after aging than the traditional T6 state. © 2023, The Authors. All rights reserved.

关键词： Strain rate

The Digestive Residues of Maize Starch-Caffeic Acid Complexes Significantly Change the Metabolites and Microbiota Composition During in Vitro Colon Fermentation

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SSRN 2024年

作者： Zheng, Yuxue Ye, Xingqian Hu, Yanyu Wang, Shaoyun Tian, Jinhu College of Biological Science and Engineering Institute of Food and Marine Bio-Resources Fuzhou University Fuzhou350108 China College of Biosystems Engineering and Food Science National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment Zhejiang Key Laboratory for Agro-Food Processing Integrated Research Base of Southern Fruit and Vegetable Preservation Technology Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control Fuli Institute of Food Science Zhejiang University Hangzhou310058 China Zhejiang University Zhongyuan Institute Zhengzhou450000 China

To investigate the effect of digestive residues of maize starch–caffeic complexes on the composition of human metabolites and gut microbiota, maize starch was extruded with caffeic acid, and subjected to in vitro gastrointestinal digestion. Then, the undigested parts were fermented with human faecal microbiota in vitro, and the morphology, short-chain fatty acids composition, microbiota communities and structural characteristics of the fermented residues were investigated. The results indicated that the amorphous area of the residues is preferentially utilized by gut microbiota and then the crystalline area. The acetate concentration in extruded maize residues with or without caffeic acid residues increased to 19.19 ± 0.40 and 23.10 ± 0.92 mmoL/L, respectively, after 24 h of fermentation. Microbiota analysis indicated that the digestive residue of maize starch-caffeic acid complexes promoted the growth of potentially beneficial microbiota, especially Bifidobacterium and Lactococcus genus. In general, extruded maize starch with caffeic acid might be a potential functional food substance for gut health. © 2024, The Authors. All rights reserved.

关键词： Fatty acids

Prebiotic Properties of Extruded Maize Starch-Caffeic Acid Complexes: A Study from the Small Intestine to Colon in Vitro

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SSRN 2024年

Our study aimed to investigate the probiotic effect of maize starch–caffeic complexes in the small intestine and colon in vitro. First, maize starch was extruded with caffeic acid, and subjected to in vitro digestion. The physicochemical properties of the complexes were explored. The undigested parts were fermented in vitro, and the structural characteristics, short chain fatty acids (SCFAs) and microbiota communities were investigated. The results showed that caffeic acid could reduce the long/short-range order of maize starch after extrusion, and the level of resistant starch was significantly increased to 30.35±2.36%. In vitro fermentation, the amorphous area of the digestive residues is utilized and then the crystalline area by microbiota, and promoted the production of SCFAs. Furthermore, the digestive residue promoted the growth of Bifidobacterium and Lactococcus genus. In general, the probiotic properties of extruded maize starch with caffeic acid might be a potential functional food substance for body health. © 2024, The Authors. All rights reserved.

关键词： Medicinal chemistry

An Optimize Adaptable Method for Determining the Monosaccharide Composition of Pectic Polysaccharides

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SSRN 2023年

作者： Wu, Jinghua Zhu, Kai Li, Junhui Hu, Xinxin Ye, Xingqian Chen, Shiguo College of Agriculture and Biotechnology Zhejiang University Zhejiang Hangzhou310058 China College of Biosystems Engineering and Food Science National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment Zhejiang Key Laboratory for Agro-Food Processing Integrated Research Base of Southern Fruit and Vegetable Preservation Technology Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control Zhejiang University Hangzhou310058 China Fuli Institute of Food Science Zhejiang University Hangzhou310058 China Ningbo Research Institute Zhejiang University Hangzhou315100 China

Monosaccharide composition analysis is an essential to characterize the structure and biological activities of complex polysaccharides. However, due to the acid-induced precipitates under the acidic condition, the incomplete hydrolysis is common in monosaccharide analysis of acidic polysaccharides (especially for pectin). The main aim of this paper is to provide an improved method for pectin’s monosaccharide analysis using optimized acid hydrolysis combined with high-performance anion exchange chromatography. Firstly, the acid-induced precipitates of pectin was remitted by reducing the concentration of samples to 0.5mg/mL. Then, the optimized hydrolysis condition was performed at 110 ℃ for 6 h with 2 mol/L TFA. Finally, five acidic polysaccharides from fruits were used to optimize and validate the method and showed the method’s reproducibility and ability to analyze complicated pectic polysaccharides. It suggests that this hydrolysis method could be applied to obtain accurate quantitation of monosaccharide composition analysis for acidic polysaccharides. © 2023, The Authors. All rights reserved.

关键词： Polysaccharides

Effects of Ultrasound Combined with Calcium Impregnation on Lycopene and Quality Properties of Cherry Tomatoes During Storage

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Journal of Food Science and technology (China) 2021年第1期39卷 54-64页

作者： Zhang, Lifen Zhang, Panpan Pan, Runsen Chen, Fusheng Liu, Donghong Lai, Shaojuan College of Food Science and Engineering Henan University of Technology Zhengzhou450052 China Co Ltd Luohe462600 China College of Biosystems Engineering and Food Science/National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment Zhejiang Key Laboratory for Agro-Food Processing/Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control Zhejiang University Hangzhou310058 China

Effects of ultrasound combined with calcium impregnation on physico-chemical properties and lycopene of cherry tomatoes during storage were studied, and the mechanisms were further elucidated. The handness, color, and lycopene content of cherry tomatoes were determined by texture analyzer, color difference meter and HPLC. Meanwhile, the structure of lycopene was also investigated by nuclear magnetic resonance(NMR). The results showed that ultrasound combined with calcium impregnation treatment could enhance the permeation of Ca2+ into the tissue of cherry tomatoes, which effectively delayed the decline of hardness, inhibited the increment of browning index, weight loss ratio and decay rate, and maintained titratable acid content, and vitamin C content of cherry tomatoes during storage. Compared to control, ultrasound combined with calcium impregnation treatment had no obvious influence on the all-trans lycopene contents. According to results from NMR, ultrasound combined with calcium impregnation treatment inhibited the oxidation of all-trans lycopene, 5-cis-lycopene and 9-cis-lycopene during storage and maintained theirs structural integrity. Ultrasound combined with calcium impregnation technology could effectively maintain the quality of cherry tomatoes. The results provided a theoretical basis for the application of ultrasound combined with calcium impregnation technology in fruit and vegetable preservation. © 2021, Editorial Department of Journal of Food Science and technology. All right reserved.

关键词： Ultrasonics

LAENet: Light-weight asymmetric encoder-decoder network for semantic segmentation

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Journal of Physics: Conference Series 2021年第1期1966卷

作者： Liangyi Hong Shukai Duan Lidan Wang Yongbin Pan College of Electronic and Information Engineering Southwest University Chongqing China Brain-inspired Computing & Intelligent Control of Chongqing Key Lab Chongqing China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing China Chongqing Brain Science Collaborative Innovation Center Chongqing China College of Artificial Intelligence Southwest University Chongqing China

Encode-decoder structure is used in deep learning for real-time dense segmentation task. On account of the limitation of calculation burden on mobile devices, we present a light-weight asymmetric encoder-decoder network in this paper, namely LAENet, which quickly and efficiently accomplish the task of real-time semantic segmentation. We employ an asymmetric convolution and group convolution structure combined with dilated convolution and dense connectivity to reduce computation cost and model size, which can guarantee adequate receptive field and enhance the model learning ability in encoder. On the other hand, feature pyramid networks (FPN) structure combine attention mechanism and ECRE block are utilized in the decoder to strike a balance between the network complexity and segmentation performance. Our approach achieves only have 0.84M parameters, and is able to reach 66 FPS in a single GTX 1080Ti GPU. Experiments on Cityscapes datasets demonstrate that superior performance of LAENet is better than the existing segmentation network, in terms of speed and accuracy trade-off without any post-processing.

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Ensemble of online sequential extreme learning machine based on cross-validation

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Journal of Physics: Conference Series 2020年第3期1550卷

作者： Liyun Wei Lidan Wang Yunfei Li Shukai Duan College of Electronic and Information Engineering Southwest University Chongqing 400715 China Brain-inspired Computing & Intelligent Control of Chongqing Key Lab Chongqing 400715 China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715 China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715 China College of Artificial Intelligence Southwest University Chongqing 400715 China

The online sequential extreme learning machine (OS-ELM) was proposed as an evolution of the Extreme learning machine (ELM) in 2006. The learning algorithm can learn data by fixing or changing the size of the chunk (a block of data). Compared with other online algorithms, it has faster training speed, and the generalization performance is better. The proposed ensemble of neural networks further demonstrates that the use of the neural network sets with multiple consensus schemes has a greater improvement over the stability of a single network. The basic idea of cross-validation is to group the original data sets, part of which is to train as the training set and the other part of which is to verify as the test set, so the algorithm can reduce the over-fitting problem of the data to a certain extent, and extract more valid information in the limited data set. In this paper, a new ensemble of online sequential extreme learning machine based on cross-validation (ENOS-ELM) is proposed. Through application of cross-validation and integration to the training stage, the accuracy of the algorithm in classification is further improved.

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Research and Implementation of Breast Cancer intelligent Recognition Algorithm Based on Deep Convolutional Neural Network

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Journal of Physics: Conference Series 2020年第1期1634卷

作者： Taixing Chen Lidan Wang Yunfei Li Shukai Duan College of Electronic and Information Engineering Southwest University Chongqing 400715 China Brain-inspired Computing & Intelligent Control of Chongqing Key Lab Chongqing 400715 China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715 China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715 China College of Artificial Intelligence Southwest University Chongqing 400715 China

Breast cancer is one of the most dangerous cancers with a particularly high mortality rate for women. In the face of thousands of female pathological pictures, how to use computer related control algorithms to quickly and efficiently intelligently idently female breast cancer images has become an urgent problem in the world. With the development of computer vision and deep convolutional neural networks, this paper applies the convolutional neural network (CNN) algorithm to solve the classification and recognition computer tasks of histological images for breast cancer, aiming to learn from tens of thousands of histological images features for breast cancer, and to assist doctors in diagnosing patients' disease was found by computer control algorithm. There are many well-known neural network computer algorithms, such as AlexNet, Inception-Net, ResNet. Image recognition for breast is a binary classification problem, and it is not appropriate to use a ResNet network with a large amount of parameters. Therefore, this paper borrowed Alexnet algorithm and redesigned the algorithm, then used it for breast cancer experiments. We compared with the capsule algorithm used by Anupama authors. Our experiment improves the accuracy rate by 2%, and reduces the amount of neural network parameters, which greatly speeds up the training time.

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Car Plate Detection Based on Yolov3

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Journal of Physics: Conference Series 2020年第1期1544卷

作者： Siyuan Shen Lidan Wang Shukai Duan Xin He College of Electronic and Information Engineering Southwest University Chongqing 400715 China Brain-inspired Computing & Intelligent Control of Chongqing Key Lab Chongqing 400715 China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715 China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715 China College of Artificial Intelligence Southwest University Chongqing 400715 China

An intelligent car plate detection method can make the travel more convenient and efficient. However, traditional methods are reasonably effective under the specific circumstances or strong assumptions only, and there are few databases for car plate detection. Therefore, a novel real-time car plate detection method based on improved Yolov3 has been proposed. In order to select the more precise number of candidate anchor boxed and aspect ratio dimensions, the K-Means algorithm is utilized. To solve the short of the available car plate database, a car plate database which has 6668 pictures has been established. As shown in the experimental results, the method which is proposed by this paper is better than original Yolov3. Thanks to the car plate database, the proposed method obtained better results even in the situation of inclination, too bright or too dark, different weather and so on.

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