Pub Date : 2023-04-01DOI: 10.1051/wujns/2023282177
Tingting Mu, Tao Wang, Zhenyu Gao, Xin Pan, Yingxue Liu
Islet-1 (Isl1), a LIM homeodomain protein, is expressed in the embryonic pancreatic epithelium. As a key transcription factor, Isl1 can not only regulate insulin gene expression in normal glucose condition but also maintain β-cell function and impact pancreatic β-cell target genes. Some experiments have suggested that MicroRNA (miRNA) can play a critical role during the induction of insulin-producing cells (IPCs). However, it is unclear whether miRNA may regulate Isl1 expression during differentiation of human umbilical cord mesenchymal stem cells (HUMSCs) into IPCs. In this investigation, we induced HUMSCs into IPCs with a modified two-step protocol, activin A, retinoic acid (step1) and conophylline, nicotinamide (step2). To find the miRNA regulating Isl1 expression, we respectively used TargetScan, miRDB and RNAhybrid to predict and got the result, miR-128 and miR-216a. The miRNAs can inhibit Isl1 expression by dual luciferase assay. The results of real-time Polymerase Chain Reaction (PCR) showed that Isl1 expression level was almost reciprocal to that of miR-128 and miR-216a during differentiation of HUMSCs into IPCs. Furthermore, over-expression of miR-128 or miR-216a down-regulated expression levels of Isl1 and MafA. Therefore, miR-128 or miR-216a may regulate expression of islet-specific transcription factors to control differentiation of HUMSCs into IPCs.
{"title":"Role of miR-128/216a Regulating Isl1 Expression during Differentiation of Human Umbilical Cord Mesenchymal Stem Cells into Insulin-Producing Cells","authors":"Tingting Mu, Tao Wang, Zhenyu Gao, Xin Pan, Yingxue Liu","doi":"10.1051/wujns/2023282177","DOIUrl":"https://doi.org/10.1051/wujns/2023282177","url":null,"abstract":"Islet-1 (Isl1), a LIM homeodomain protein, is expressed in the embryonic pancreatic epithelium. As a key transcription factor, Isl1 can not only regulate insulin gene expression in normal glucose condition but also maintain β-cell function and impact pancreatic β-cell target genes. Some experiments have suggested that MicroRNA (miRNA) can play a critical role during the induction of insulin-producing cells (IPCs). However, it is unclear whether miRNA may regulate Isl1 expression during differentiation of human umbilical cord mesenchymal stem cells (HUMSCs) into IPCs. In this investigation, we induced HUMSCs into IPCs with a modified two-step protocol, activin A, retinoic acid (step1) and conophylline, nicotinamide (step2). To find the miRNA regulating Isl1 expression, we respectively used TargetScan, miRDB and RNAhybrid to predict and got the result, miR-128 and miR-216a. The miRNAs can inhibit Isl1 expression by dual luciferase assay. The results of real-time Polymerase Chain Reaction (PCR) showed that Isl1 expression level was almost reciprocal to that of miR-128 and miR-216a during differentiation of HUMSCs into IPCs. Furthermore, over-expression of miR-128 or miR-216a down-regulated expression levels of Isl1 and MafA. Therefore, miR-128 or miR-216a may regulate expression of islet-specific transcription factors to control differentiation of HUMSCs into IPCs.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47060026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/wujns/2023282129
Lan Wang, C. Wang, Juan Xue
This paper mainly studies the optimal investment problem of defined contribution (DC) pension under the self-protection and minimum security. First, we apply [see formula in PDF] theorem to obtain the differential equation of the real stock price after discounting inflation. Then, under the constraint of external guarantee of DC pension terminal wealth, self-protection is introduced to study the maximization of the expected utility of terminal wealth at retirement time and any time before retirement. The explicit solution of the optimal investment strategy of DC pension at retirement time and any time before retirement should be derived by martingale method. Finally, the influence of self-protection on the optimal investment strategy of DC pension is numerically analyzed.
{"title":"Optimal Investment of Defined Contribution Pension Based on Self-Protection and Minimum Security","authors":"Lan Wang, C. Wang, Juan Xue","doi":"10.1051/wujns/2023282129","DOIUrl":"https://doi.org/10.1051/wujns/2023282129","url":null,"abstract":"This paper mainly studies the optimal investment problem of defined contribution (DC) pension under the self-protection and minimum security. First, we apply [see formula in PDF] theorem to obtain the differential equation of the real stock price after discounting inflation. Then, under the constraint of external guarantee of DC pension terminal wealth, self-protection is introduced to study the maximization of the expected utility of terminal wealth at retirement time and any time before retirement. The explicit solution of the optimal investment strategy of DC pension at retirement time and any time before retirement should be derived by martingale method. Finally, the influence of self-protection on the optimal investment strategy of DC pension is numerically analyzed.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41774961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/wujns/2023282141
Qiaoyue Huang, Chaoying Tang, Tianshu Zhang
Since the outbreak of Coronavirus Disease 2019 (COVID-19), people are recommended to wear facial masks to limit the spread of the virus. Under the circumstances, traditional face recognition technologies cannot achieve satisfactory results. In this paper, we propose a face recognition algorithm that combines the traditional features and deep features of masked faces. For traditional features, we extract Local Binary Pattern (LBP), Scale-Invariant Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) features from the periocular region, and use the Support Vector Machines (SVM) classifier to perform personal identification. We also propose an improved Convolutional Neural Network (CNN) model Angular Visual Geometry Group Network (A-VGG) to learn deep features. Then we use the decision-level fusion to combine the four features. Comprehensive experiments were carried out on databases of real masked faces and simulated masked faces, including frontal and side faces taken at different angles. Images with motion blur were also tested to evaluate the robustness of the algorithm. Besides, the experiment of matching a masked face with the corresponding full face is accomplished. The experimental results show that the proposed algorithm has state-of-the-art performance in masked face recognition, and the periocular region has rich biological features and high discrimination.
{"title":"Periocular Biometric Recognition for Masked Faces","authors":"Qiaoyue Huang, Chaoying Tang, Tianshu Zhang","doi":"10.1051/wujns/2023282141","DOIUrl":"https://doi.org/10.1051/wujns/2023282141","url":null,"abstract":"Since the outbreak of Coronavirus Disease 2019 (COVID-19), people are recommended to wear facial masks to limit the spread of the virus. Under the circumstances, traditional face recognition technologies cannot achieve satisfactory results. In this paper, we propose a face recognition algorithm that combines the traditional features and deep features of masked faces. For traditional features, we extract Local Binary Pattern (LBP), Scale-Invariant Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) features from the periocular region, and use the Support Vector Machines (SVM) classifier to perform personal identification. We also propose an improved Convolutional Neural Network (CNN) model Angular Visual Geometry Group Network (A-VGG) to learn deep features. Then we use the decision-level fusion to combine the four features. Comprehensive experiments were carried out on databases of real masked faces and simulated masked faces, including frontal and side faces taken at different angles. Images with motion blur were also tested to evaluate the robustness of the algorithm. Besides, the experiment of matching a masked face with the corresponding full face is accomplished. The experimental results show that the proposed algorithm has state-of-the-art performance in masked face recognition, and the periocular region has rich biological features and high discrimination.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48370916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As one of the hot topics in the field of new energy, short-term wind power prediction research should pay attention to the impact of meteorological characteristics on wind power while improving the prediction accuracy. Therefore, a short-term wind power prediction method based on the combination of meteorological features and CatBoost is presented. Firstly, morgan-stone algebras and sure independence screening(MS-SIS) method is designed to filter the meteorological features, and the influence of the meteorological features on the wind power is explored. Then, a sort enhancement algorithm is designed to increase the accuracy and calculation efficiency of the method and reduce the prediction risk of a single element. Finally, a prediction method based on CatBoost network is constructed to further realize short-term wind power prediction. The National Renewable Energy Laboratory (NREL) dataset is used for experimental analysis. The results show that the short-term wind power prediction method based on the combination of meteorological features and CatBoost not only improve the prediction accuracy of short-term wind power, but also have higher calculation efficiency.
{"title":"Short-Term Wind Power Prediction Method Based on Combination of Meteorological Features and CatBoost","authors":"Xingyu Mou, Hui Chen, Xinjing Zhang, Xin Xu, Qingbo Yu, Yun Li","doi":"10.1051/wujns/2023282169","DOIUrl":"https://doi.org/10.1051/wujns/2023282169","url":null,"abstract":"As one of the hot topics in the field of new energy, short-term wind power prediction research should pay attention to the impact of meteorological characteristics on wind power while improving the prediction accuracy. Therefore, a short-term wind power prediction method based on the combination of meteorological features and CatBoost is presented. Firstly, morgan-stone algebras and sure independence screening(MS-SIS) method is designed to filter the meteorological features, and the influence of the meteorological features on the wind power is explored. Then, a sort enhancement algorithm is designed to increase the accuracy and calculation efficiency of the method and reduce the prediction risk of a single element. Finally, a prediction method based on CatBoost network is constructed to further realize short-term wind power prediction. The National Renewable Energy Laboratory (NREL) dataset is used for experimental analysis. The results show that the short-term wind power prediction method based on the combination of meteorological features and CatBoost not only improve the prediction accuracy of short-term wind power, but also have higher calculation efficiency.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42100684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1051/wujns/2023281035
Zerui Wen, Zhidong Shen, Hui Sun, Baiwen Qi
As deep learning models have made remarkable strides in numerous fields, a variety of adversarial attack methods have emerged to interfere with deep learning models. Adversarial examples apply a minute perturbation to the original image, which is inconceivable to the human but produces a massive error in the deep learning model. Existing attack methods have achieved good results when the network structure is known. However, in the case of unknown network structures, the effectiveness of the attacks still needs to be improved. Therefore, transfer-based attacks are now very popular because of their convenience and practicality, allowing adversarial samples generated on known models to be used in attacks on unknown models. In this paper, we extract sensitive features by Grad-CAM and propose two single-step attacks methods and a multi-step attack method to corrupt sensitive features. In two single-step attacks, one corrupts the features extracted from a single model and the other corrupts the features extracted from multiple models. In multi-step attack, our method improves the existing attack method, thus enhancing the adversarial sample transferability to achieve better results on unknown models. Our method is also validated on CIFAR-10 and MINST, and achieves a 1%-3% improvement in transferability.
{"title":"Adversarial Example Generation Method Based on Sensitive Features","authors":"Zerui Wen, Zhidong Shen, Hui Sun, Baiwen Qi","doi":"10.1051/wujns/2023281035","DOIUrl":"https://doi.org/10.1051/wujns/2023281035","url":null,"abstract":"As deep learning models have made remarkable strides in numerous fields, a variety of adversarial attack methods have emerged to interfere with deep learning models. Adversarial examples apply a minute perturbation to the original image, which is inconceivable to the human but produces a massive error in the deep learning model. Existing attack methods have achieved good results when the network structure is known. However, in the case of unknown network structures, the effectiveness of the attacks still needs to be improved. Therefore, transfer-based attacks are now very popular because of their convenience and practicality, allowing adversarial samples generated on known models to be used in attacks on unknown models. In this paper, we extract sensitive features by Grad-CAM and propose two single-step attacks methods and a multi-step attack method to corrupt sensitive features. In two single-step attacks, one corrupts the features extracted from a single model and the other corrupts the features extracted from multiple models. In multi-step attack, our method improves the existing attack method, thus enhancing the adversarial sample transferability to achieve better results on unknown models. Our method is also validated on CIFAR-10 and MINST, and achieves a 1%-3% improvement in transferability.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45916349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1051/wujns/2023281077
S. Luo, Jianhua Zhang, Hufang Zhang, Qin Zheng, Yongping Gao, Meihong Li
In order to explore the response of soil respiration in grassland to global warming, we carried out a warming experiment with open top chambers (OTCs) in the subalpine meadow, Mount Wutai in north China. Our results showed in the subalpine meadow across 2 500-2 700 m above the sea level (ASL), with OTCs, soil respiration increased by 2.00 μmol·m-2·s-1 as soil temperature increased by 1.25 ℃ on average. Warming decreased soil moisture over the experiment periods except in October 2019 when snow melted in OTCs. Warming effect on soil respiration peaked at 178.31% in October 2019. In control and warming treatment, based on exponential regression equations, soil temperature alone accounted for 85.3% and 61.2% of soil respiration variation, respectively. In control treatment soil moisture alone explained 23.2% of soil respiration variation based on the power regression equation while in warming treatment they were not significantly correlated with each other. The response of soil respiration to warming relied on altitudes as well as the time of the year, but was not inhibited by soil moisture, labile carbon pool, and available nitrogen. We concluded soil temperature was the main factor influencing soil respiration, and global warming would stimulate soil respiration in the subalpine meadows of Mount Wutai in the future. Our analysis provided new data on characteristics and mechanisms of the response of soil respiration to warming, and helped to further understand the relationship between carbon cycle and climate change.
{"title":"Warming Stimulated Soil Respiration in a Subalpine Meadow in North China","authors":"S. Luo, Jianhua Zhang, Hufang Zhang, Qin Zheng, Yongping Gao, Meihong Li","doi":"10.1051/wujns/2023281077","DOIUrl":"https://doi.org/10.1051/wujns/2023281077","url":null,"abstract":"In order to explore the response of soil respiration in grassland to global warming, we carried out a warming experiment with open top chambers (OTCs) in the subalpine meadow, Mount Wutai in north China. Our results showed in the subalpine meadow across 2 500-2 700 m above the sea level (ASL), with OTCs, soil respiration increased by 2.00 μmol·m-2·s-1 as soil temperature increased by 1.25 ℃ on average. Warming decreased soil moisture over the experiment periods except in October 2019 when snow melted in OTCs. Warming effect on soil respiration peaked at 178.31% in October 2019. In control and warming treatment, based on exponential regression equations, soil temperature alone accounted for 85.3% and 61.2% of soil respiration variation, respectively. In control treatment soil moisture alone explained 23.2% of soil respiration variation based on the power regression equation while in warming treatment they were not significantly correlated with each other. The response of soil respiration to warming relied on altitudes as well as the time of the year, but was not inhibited by soil moisture, labile carbon pool, and available nitrogen. We concluded soil temperature was the main factor influencing soil respiration, and global warming would stimulate soil respiration in the subalpine meadows of Mount Wutai in the future. Our analysis provided new data on characteristics and mechanisms of the response of soil respiration to warming, and helped to further understand the relationship between carbon cycle and climate change.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48070288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1051/wujns/2023281061
Yifan Yang, Tao Zhang, Di Wu, Yu Zhao
Sparse coding has achieved great success in various image restoration tasks. However, if the sparse representation coefficients of the structure (low-frequency information) and texture (high-frequency information) components of the image are under the same penalty constraint, the restoration effect may not be ideal. In this paper, an image denoising model combining mixed norm and weighted nuclear norm as regularization terms is proposed. The proposed model simultaneously exploits the group sparsity of the high frequency and low-rankness of the low frequency in dictionary-domain. The mixed norm is used to constrain the high frequency part and the weighted nuclear norm is used to constrain the low frequency part. In order to make the proposed model easy to solve under the framework of alternative direction multiplier method (ADMM), iterative shrinkage threshold method and weighted nuclear norm minimization method are used to solve the two sub-problems. The validity of the model is verified experimentally through comparison with some state-of-the-art methods.
{"title":"An Image Denoising Model via the Reconciliation of the Sparsity and Low-Rankness of the Dictionary Domain Coefficients","authors":"Yifan Yang, Tao Zhang, Di Wu, Yu Zhao","doi":"10.1051/wujns/2023281061","DOIUrl":"https://doi.org/10.1051/wujns/2023281061","url":null,"abstract":"Sparse coding has achieved great success in various image restoration tasks. However, if the sparse representation coefficients of the structure (low-frequency information) and texture (high-frequency information) components of the image are under the same penalty constraint, the restoration effect may not be ideal. In this paper, an image denoising model combining mixed norm and weighted nuclear norm as regularization terms is proposed. The proposed model simultaneously exploits the group sparsity of the high frequency and low-rankness of the low frequency in dictionary-domain. The mixed norm is used to constrain the high frequency part and the weighted nuclear norm is used to constrain the low frequency part. In order to make the proposed model easy to solve under the framework of alternative direction multiplier method (ADMM), iterative shrinkage threshold method and weighted nuclear norm minimization method are used to solve the two sub-problems. The validity of the model is verified experimentally through comparison with some state-of-the-art methods.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41518734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1051/wujns/2023281053
Di Wu, Zhang Tao, Xutao Mo
Group sparse residual constraint with non-local priors (GSRC) has achieved great success in image restoration producing state-of-the-art performance. In the GSRC model, the [see formula in PDF] norm minimization is employed to reduce the group sparse residual. In recent years, non-convex regularization terms have been widely used in image denoising problems, which have achieved better results in denoising than convex regularization terms. In this paper, we use the ratio of the [see formula in PDF] and [see formula in PDF] norm instead of the [see formula in PDF] norm to propose a new image denoising model, i.e., a group sparse residual constraint model with [see formula in PDF] minimization (GSRC-[see formula in PDF]). Due to the computational difficulties arisen from the non-convexity and non-linearity, we focus on a constrained optimization problem that can be solved by alternative direction method of multipliers (ADMM). Experimental results of image denoising show that the pro-posed model outperforms several state-of-the-art image denoising methods both visually and quantitatively.
具有非局部先验的群稀疏残差约束（GSRC）在图像恢复中取得了巨大成功，产生了最先进的性能。在GSRC模型中，使用[参见PDF中的公式]范数最小化来减少组稀疏残差。近年来，非凸正则化项被广泛应用于图像去噪问题，在去噪方面取得了比凸正则化项更好的效果。在本文中，我们使用[Seee formula In PDF]和[Seee formula In PDV]范数的比率来代替[Seee公式In PDF]范数，提出了一种新的图像去噪模型，即具有[Seee ormula In PDP]最小化的组稀疏残差约束模型（GSRC-[Seee formula In PDFC]）。由于非凸性和非线性带来的计算困难，我们将重点研究一个可以通过乘法器的交替方向法（ADMM）求解的约束优化问题。图像去噪实验结果表明，该模型在视觉和定量上都优于几种最先进的图像去噪方法。
{"title":"Group Sparsity Residual Constraint Image Denoising Model with 𝒍1/𝒍2 Regularization","authors":"Di Wu, Zhang Tao, Xutao Mo","doi":"10.1051/wujns/2023281053","DOIUrl":"https://doi.org/10.1051/wujns/2023281053","url":null,"abstract":"Group sparse residual constraint with non-local priors (GSRC) has achieved great success in image restoration producing state-of-the-art performance. In the GSRC model, the [see formula in PDF] norm minimization is employed to reduce the group sparse residual. In recent years, non-convex regularization terms have been widely used in image denoising problems, which have achieved better results in denoising than convex regularization terms. In this paper, we use the ratio of the [see formula in PDF] and [see formula in PDF] norm instead of the [see formula in PDF] norm to propose a new image denoising model, i.e., a group sparse residual constraint model with [see formula in PDF] minimization (GSRC-[see formula in PDF]). Due to the computational difficulties arisen from the non-convexity and non-linearity, we focus on a constrained optimization problem that can be solved by alternative direction method of multipliers (ADMM). Experimental results of image denoising show that the pro-posed model outperforms several state-of-the-art image denoising methods both visually and quantitatively.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49548828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1051/wujns/2023281068
Yiwen Ren, Junhui Tao, Jie Li, Xinqi Chen, Lin Zhang, Chuanhui Wang, Haiqin Jin, Hongyan Qi, Zhu A. Wang, X. Xie, J. Pan
In this research project, copper and stainless steel were connected by two laser welding methods: straight seam welding and swing welding. Then, electronic tensile test machine, X-ray diffractometer, scanning electron microscope and metallographic microscope were used to analyze the tensile properties, macroscopic and microscopic structure morphology and phase of the welded joint. Based on the experimental results, we determined that the strength of the straight seam welded joint was higher. Because of the intermetallic compound near the weld in the swing welding process, it leads to stress concentration, crack cracking and strength reduction. In addition, the oscillating laser beam also leads to the disorderly direction of columnar crystal and coarse structure, which makes the joint strength decrease.
{"title":"Mechanical Properties of Laser Welded Joint of Copper and Steel Dissimilar Metals","authors":"Yiwen Ren, Junhui Tao, Jie Li, Xinqi Chen, Lin Zhang, Chuanhui Wang, Haiqin Jin, Hongyan Qi, Zhu A. Wang, X. Xie, J. Pan","doi":"10.1051/wujns/2023281068","DOIUrl":"https://doi.org/10.1051/wujns/2023281068","url":null,"abstract":"In this research project, copper and stainless steel were connected by two laser welding methods: straight seam welding and swing welding. Then, electronic tensile test machine, X-ray diffractometer, scanning electron microscope and metallographic microscope were used to analyze the tensile properties, macroscopic and microscopic structure morphology and phase of the welded joint. Based on the experimental results, we determined that the strength of the straight seam welded joint was higher. Because of the intermetallic compound near the weld in the swing welding process, it leads to stress concentration, crack cracking and strength reduction. In addition, the oscillating laser beam also leads to the disorderly direction of columnar crystal and coarse structure, which makes the joint strength decrease.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47500732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1051/wujns/2023281015
Xiaofang Xu
Projective Reed-Solomon code is an important class of maximal distance separable codes in reliable communication and deep holes play important roles in its decoding. In this paper, we obtain two classes of deep holes of projective Reed-Solomon codes over finite fields with even characteristic. That is, let [see formula in PDF] be finite field with even characteristic, [see formula in PDF], and let [see formula in PDF] be the Lagrange interpolation polynomial of the first [see formula in PDF] components of the received vector [see formula in PDF]. Suppose that the [see formula in PDF]-th component of [see formula in PDF] is 0, and [see formula in PDF],[see formula in PDF] where [see formula in PDF], and [see formula in PDF] is a polynomial over [see formula in PDF] with degree no more than [see formula in PDF]. Then the received vector [see formula in PDF] is a deep hole of projective Reed-Solomon codes [see formula in PDF]. In fact, our result partially solved an open problem on deep holes of projective Reed-Solomon codes proposed by Wan in 2020.
{"title":"On Deep Holes of Projective Reed-Solomon Codes over Finite Fields with Even Characteristic","authors":"Xiaofang Xu","doi":"10.1051/wujns/2023281015","DOIUrl":"https://doi.org/10.1051/wujns/2023281015","url":null,"abstract":"Projective Reed-Solomon code is an important class of maximal distance separable codes in reliable communication and deep holes play important roles in its decoding. In this paper, we obtain two classes of deep holes of projective Reed-Solomon codes over finite fields with even characteristic. That is, let [see formula in PDF] be finite field with even characteristic, [see formula in PDF], and let [see formula in PDF] be the Lagrange interpolation polynomial of the first [see formula in PDF] components of the received vector [see formula in PDF]. Suppose that the [see formula in PDF]-th component of [see formula in PDF] is 0, and [see formula in PDF],[see formula in PDF] where [see formula in PDF], and [see formula in PDF] is a polynomial over [see formula in PDF] with degree no more than [see formula in PDF]. Then the received vector [see formula in PDF] is a deep hole of projective Reed-Solomon codes [see formula in PDF]. In fact, our result partially solved an open problem on deep holes of projective Reed-Solomon codes proposed by Wan in 2020.","PeriodicalId":23976,"journal":{"name":"Wuhan University Journal of Natural Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46219050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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