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Detection and Recognition of Spray Code Numbers on Can Surfaces Based on OCR

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Computers, Materials & Continua 2025年第1期82卷 1109-1128页

作者： Hailong wang Junchao Shi School of Computer Science Zhongyuan University of TechnologyZhengzhou450007China

A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number *** the coding number detection stage,Differentiable Binarization Network is used as the backbone network,combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection *** terms of text recognition,using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate the problem of coding recognition errors caused by image color distortion due to variations in lighting and background *** addition,model pruning and quantization are used to reduce the number ofmodel parameters to meet deployment requirements in resource-constrained environments.A comparative experiment was conducted using the dataset of tank bottom spray code numbers collected on-site,and a transfer experiment was conducted using the dataset of packaging box production *** experimental results show that the algorithm proposed in this study can effectively locate the coding of cans at different positions on the roller conveyor,and can accurately identify the coding numbers at high production line *** Hmean value of the coding number detection is 97.32%,and the accuracy of the coding number recognition is 98.21%.This verifies that the algorithm proposed in this paper has high accuracy in coding number detection and recognition.

关键词： Can coding recognition differentiable binarization network scene visual text recognition model pruning and quantification transport model

Small modifications of endo-functionalized cavities lead to large changes in molecular interaction in water

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Science China Chemistry 2025年第1期68卷 369-376页

作者： Song-Meng wang Hao Nian Yan-Fang wang Li-Shuo Zheng Yu-Tao Zheng Yi-Wei Dong Liping Huang Xiaoping wang Wei Jiang Liu-Pan Yang Department of Chemistry Southern University of Science and Technology School of Chemistry and Pharmaceutical Sciences State Key Laboratory for Chemistry and Molecular Engineering of Medicinal ResourcesGuangxi Normal University School of Pharmaceutical Science Hengyang Medical School University of South China

Studying molecular recognition in aqueous environments is crucial for understanding biological processes. Herein, we present a series of N-doped endo-functionalized anthracene-based cavities by introducing inward-directed pyridine units. The subtle modifications can significantly affect the binding properties of these receptors, which is similar to the mutations in biological systems. Combining theoretical calculations and molecular recognition experiments demonstrated that these “mutations” have an impact on the hydrophobicity and charge distribution of the hosts, consequently significantly influencing molecular *** is crucial for understanding the intricate mechanisms of molecular-level interactions in biological receptors.

关键词： host-guest interaction hydrophobic effect endo-functionalized cavity mutation pyridine

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泛系生克模式在经济系统评价中的应用

系统科学学报 1998年第2期12卷 83-87页

作者：柯洪路严薇王书田重庆建筑大学重庆400045 西南师范大学重庆400715

介绍泛系生克模式的理论基础、模式及其在经济系统评价中的应用.

关键词：泛系市场经济管理系统

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重症颅脑损伤不同阶段病情的观察与护理

中国医药科学 2013年第10期3卷 116-117,131页

作者：宋利梅杨冬颖张爱王建竹中国中医科学院望京医院神经外科北京100102

目的探讨重型颅脑损伤早、中、晚3个阶段病情的特点,针对性采取相应的护理措施,提高护理质量,降低死亡率。方法回顾63例重症颅脑损伤患者的临床资料,统计出现颅内迟发血肿、消化道应激性溃疡出血、肾功能衰竭、窒息、尿崩症等严重合并... 详细信息

目的探讨重型颅脑损伤早、中、晚3个阶段病情的特点,针对性采取相应的护理措施,提高护理质量,降低死亡率。方法回顾63例重症颅脑损伤患者的临床资料,统计出现颅内迟发血肿、消化道应激性溃疡出血、肾功能衰竭、窒息、尿崩症等严重合并症和并发症的时间。结果早期出现的并发症:颅内迟发血肿15例(15/15),尿崩症15例(15/15),窒息3例(3/3),死亡13例(13/16);中期肺部感染30例(30/38),消化道应激性溃疡,肾功能衰竭2例(2/3),死亡2例(2/16);晚期出现营养不良1例(1/1),死亡1例(1/16)。结论重型颅脑损伤病情重,变化快,死亡率高。但是每个阶段并发症和合并症的发生有一定的特点,根据这些特点采取针对性观察,及时发现病情的变化,及时有效的采取医疗和护理措施,有助于避免/减少并发症的发生,对降低死亡率提高生存质量有重要的意义。

关键词：重症颅脑损伤不同阶段病情变化护理措施

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高岚河大型底栖动物时空分布及影响因子研究

生物资源 2019年第5期41卷 426-433页

作者：许亚红郑子叶王建柱罗遵兰三峡大学生物与制药学院湖北宜昌443002 三峡库区生态环境教育部工程研究中心湖北宜昌443002 中国环境科学研究院北京100021

为了解大型底栖动物沿河流分布的物种丰富度变化及环境因子对其种群的影响,于2016年12月对高岚河的大型底栖动物进行了调查,并对理化指标进行了测定。研究结果发现,物种丰富度沿河流纵向梯度变化差异性不显著,生物多样性指数沿河流变化... 详细信息

为了解大型底栖动物沿河流分布的物种丰富度变化及环境因子对其种群的影响,于2016年12月对高岚河的大型底栖动物进行了调查,并对理化指标进行了测定。研究结果发现,物种丰富度沿河流纵向梯度变化差异性不显著,生物多样性指数沿河流变化差异不显著,说明高岚河大型底栖动物群落结构稳定。高岚河上游的生态指示种为高翔蜉和四节蜉,中游的生态指示种为四节蜉和萝卜螺,下游的指示种为萝卜螺。模糊聚类分析发现高岚河大型底栖动物类群可划分为3个生境类群,且在梯度分布下群落生境较相似,大型底栖动物群落间关系接近,分布均匀。典范对应分析发现影响大型底栖动物群落结构沿梯度分布的主要因子是海拔、pH、浊度和深度。

关键词：大型底栖动物高岚河物种丰富度生物多样性

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Near-perfect replication on amorphous alloys through active force modulation based on machine learning/neural network parameter prediction

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 181-191页

作者： Senkuan Meng Zheng wang Ruisong Zhu Ruijie Liu Jiang Ma Lina Hu Weihua wang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education) School of Materials Science and Engineering Shandong University College of Mechatronics and Control Engineering Shenzhen University Songshan Lake Materials Laboratory Institute of Physics Chinese Academy of Sciences

As a microforming technique, micro/nano-structural replication possesses advantages of high precision and efficiency. With the remarkable superplasticity in the supercooled liquid region, amorphous alloys or metallic glasses(MGs) are regarded as ideal materials for miniature fabrication. However, due to the intrinsic metastable nature of supercooled liquids, the design of imprinting processes for MGs poses a challenge. In the past, process parameters have largely relied on trial-and-error *** this work, a low-frequency active force modulation system is employed to apply a stable, precise, and real-time feedback stress field for imprinting of MG samples. Low-frequency vibrations can facilitate the filling of microstructures on the template surface by reducing the effective viscosity of the supercooled liquid. With the dataset composed of orthogonal experiments, a machine learning strategy based on back-propagation(BP) neural networks was utilized to construct a 3D parameter space for temperature, stress, and time, and to predict the corresponding filling ratio. Furthermore, the optimal combination of imprinting process parameters was identified, and its filling ratio was experimentally validated to reach as high as 0.94. The near-perfect replication of microstructures confirms the superiority of the active force modulation system and the data-driven strategy of machine learning-assisted parameter design. At the same time, this one-step microforming process provides a new approach to addressing the accuracy-cost trade-off dilemma in precision manufacturing.

关键词： metallic glass amorphous alloy microforming imprinting machine learning

Local-contrastive-learning machine with both generalization and adversarial robustness: A statistical physics analysis

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 109-123页

作者： Mingshan Xie Yuchen wang Haiping Huang PMI Lab School of Physics Sun Yat-sen University Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices Sun Yat-sen University

Distinct from human cognitive processing, deep neural networks trained by backpropagation can be easily fooled by adversarial examples. To design a semantically meaningful representation learning, we discard backpropagation, and instead, propose a local contrastive learning, where the representations for the inputs bearing the same label shrink(akin to boson) in hidden layers,while those of different labels repel(akin to fermion). This layer-wise learning is local in nature, being biologically plausible.A statistical mechanics analysis shows that the target fermion-pair-distance is a key parameter. Moreover, the application of this local contrastive learning to MNIST benchmark dataset demonstrates that the adversarial vulnerability of standard perceptron can be greatly mitigated by tuning the target distance, i.e., controlling the geometric separation of prototype manifolds.

关键词： machine learning statistical mechanics adversarial robustness neural networks

Dative B–N bonds weaven toward two-dimensional purely organic materials for single crystals

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Science China Chemistry 2025年第1期68卷 12-14页

作者： Wei-Lei Zhou Siwei wang Yong Chen College of Chemistry and Materials Science Inner Mongolia Key Laboratory of Chemistry for Nature Products and Synthesis for Functional Molecules Innovation Team of Optical Functional Molecular Devices Inner Mongolia Minzu University College of Chemistry Nankai University

Molecular topology is one of the important topics to study and understand the relationship between molecular structure and properties [1]. Particularly, two-dimensional (2D) materials with extremely high surface area and ultra-thin morphology have attracted considerable attention due to their unexpected properties in materials and chemistry [2,3].

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Cyano migration-mediated radical-polar crossover cyclopropanation

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Science China Chemistry 2025年第1期68卷 241-248页

作者： Ziqiang wang Yasu Chen Jie Li Chen Zhu Key Laboratory of Organic Synthesis of Jiangsu Province College of Chemistry Chemical Engineering and Materials ScienceSoochow University Frontiers Science Center for Transformative Molecules Zhangjiang Institute for Advanced Study and Shanghai Key Laboratory for Molecular Engineering of Chiral Drugs Shanghai Jiao Tong University

We report a novel cyano migration-mediated radical-polar crossover process, whereby both the sulfonylcyanation of aliphatic alkenes and the formation of cyclopropanes are concurrently achieved. This transformation yields a diverse array of multisubstituted cyclopropanes under mild photocatalytic conditions. Mechanistic studies elucidate that the reaction proceeds via intramolecular nucleophilic substitution, leading to the formation of the cyclopropane derivatives.

关键词： cyclopropanation cyano migration radical-polar crossover radical reactions