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双色印刷设计在书籍设计中的应用探究

苏州工艺美术职业技术学院学报 2024年第2期 15-19页

作者：葛玉峰广陵书社

双色印刷设计指用两种油墨印制产品的设计。常规印刷定义为“青、品、黄、黑”四色印刷,而双色印刷设计是在“四色”中选择两种颜色来设计印刷。通过双色印刷设计能够轻松地突出书籍的色彩张力和视觉冲击力,从“四色”变成“两色”也被... 详细信息

双色印刷设计指用两种油墨印制产品的设计。常规印刷定义为“青、品、黄、黑”四色印刷,而双色印刷设计是在“四色”中选择两种颜色来设计印刷。通过双色印刷设计能够轻松地突出书籍的色彩张力和视觉冲击力,从“四色”变成“两色”也被设计师们称为“色简意深”理论。将“色简意深”的理念运用到书籍设计之中,让读者身临其境在书籍的内容氛围感之中,从而传达出设计者的情感。本研究通过案例分析从简练、质朴、复古的风格书籍视觉感观上探讨可以“叙述”的书籍设计之美、内容之美。

关键词：四色双色色简意深简练质朴

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骨盆与髋臼骨折治疗中需关注的几个问题

中华创伤骨科杂志 2024年第3期26卷 185-187页

作者：吴新宝杨明辉葛宇峰首都医科大学附属北京积水潭医院创伤骨科北京100035

骨盆与髋臼的解剖位置深在,毗邻结构复杂。因此,就创伤骨科医生而言,骨盆与髋臼骨折的处理具有极大的挑战性。急诊处理、骨折分型、手术时机、骨折复位质量、合并伤及医师的经验等因素都会影响骨折的预后。目前,由于人口老龄化问题的日... 详细信息

骨盆与髋臼的解剖位置深在,毗邻结构复杂。因此,就创伤骨科医生而言,骨盆与髋臼骨折的处理具有极大的挑战性。急诊处理、骨折分型、手术时机、骨折复位质量、合并伤及医师的经验等因素都会影响骨折的预后。目前,由于人口老龄化问题的日益严峻,骨盆与髋臼骨折的流行病学特征正在发生转变,同时计算机导航技术、3D打印技术及机器人辅助技术等新技术也在不断涌现,给骨盆与髋臼骨折的诊治带来了新的推动。本期共有6篇骨盆与髋臼骨折方面的文章,内容涉及到髋臼后壁骨折的治疗、髋臼骨折前方手术入路的改良、骨盆与髋臼骨折的通道螺钉技术及老龄化问题等,希望对读者的临床工作有一定借鉴意义。

关键词：急诊处理髋臼后壁骨折髋臼骨折手术入路骨折复位毗邻结构创伤骨科骨折分型

High-throughput phenotyping of plant leaf morphological, physiological,and biochemical traits on multiple scales using optical sensing

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作物学报:英文版 2023年第5期11卷 1303-1318页

作者： Huichun Zhang Lu Wang Xiuliang Jin Liming Bian yufeng ge College of Mechanical and Electronic Engineering Nanjing Forestry UniversityNanjing 210037JiangsuChina Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources Nanjing Forestry UniversityNanjing 210037JiangsuChina Institute of Crop Sciences Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and EcologyMinistry of AgricultureBeijing 100081China College of Forestry Nanjing Forestry UniversityNanjing 210037JiangsuChina Co-Innovation Center for Sustainable Forestry in Southern China and Key Laboratory of Forest genetics&Biotechnology of the Ministry of Education Nanjing Forestry UniversityNanjing 210037JiangsuChina Department of Biological Systems Engineering University of Nebraska-LincolnNE 68583USA

Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene action, and can be applied to optimize the quality of agricultural and forestry products. Because leaves often show the fastest responses to external environmental stimuli, leaf phenotypic traits are indicators of plant growth,health, and stress levels. Combination of new imaging sensors, image processing, and data analytics permits measurement over the full life span of plants at high temporal resolution and at several organizational levels from organs to individual plants to field populations of plants. We review the optical sensors and associated data analytics used for measuring morphological, physiological, and biochemical traits of plant leaves on multiple scales. We summarize the characteristics, advantages and limitations of optical sensing and data-processing methods applied in various plant phenotyping scenarios. Finally, we discuss the future prospects of plant leaf phenotyping research. This review aims to help researchers choose appropriate optical sensors and data processing methods to acquire plant leaf phenotypes rapidly,accurately, and cost-effectively.

关键词： Leaf traits Optical sensing Image processing Machine learning Artificial intelligence

Development of sensor systems for precision agriculture in cotton

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International Journal of Agricultural and Biological Engineering 2012年第4期5卷 1-14,F0003页

作者： Ruixiu Sui J.Alex Thomasson yufeng ge United States Department of Agriculture Agricultural Research ServiceCrop Production Systems Research UnitStonevilleMSUSA Biological&Agricultural Engineering Department Texas A&M UniversityCollege StationTXUSA

Precision agriculture(PA)is an information-based technology,using detailed information within an agricultural field to optimize production inputs on a spatially variable basis,maximize farm profit,and minimize environmental *** collection and processing plays a very important role in *** recent years PA technologies have been gradually adopted in cotton *** sensor systems for PA were developed and field-evaluated in cotton,including a plant height measurement system(PHMS),the Mississippi cotton yield monitor(MCYM),and cotton fiber quality *** PHMS used an ultrasonic sensor to scan the plant canopy and determine plant height in real time in situ.A plant height map was generated with the data collected with the *** plant height showed a close relationship with yield(R2=0.63)and leaf-nitrogen content(R2=0.48).The MCYM was developed for cotton yield mapping.A patented mass-flow sensor technology was employed in the *** sensor measured optical reflectance of cotton particles passing through the sensor and used the measured reflectance to determine cotton-mass flow *** tests indicated that the MCYM could measure cotton yield with an average error less than 5%,and it was easy to install and *** cotton fiber-quality mapping research involved a wireless cotton module-tracking system(WCMTS)and a cotton fiber quality mapping system(CFQMS).The WCMTS was based on the concept that a cotton fiber-quality map could be generated with spatial information collected by the system during harvesting coupled with fiber quality information available in cotton classing *** WCMTS was constructed and tested,and it operated according to design,with module-level fiber-quality maps easily made from the collected *** CFQMS was designed and fabricated to perform real-time measurement of cotton fiber quality as the cotton is harvested in the *** results indicated that the sensor was capable of accurately estim

关键词： sensor precision agriculture(PA) cotton yield monitor fiber quality plant height

基于CT影像的髋部肌肉因素与老年髋部骨折术后1年内独立行动能力恢复的相关性研究

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中华创伤杂志 2024年第6期40卷 531-538页

作者：葛宇峰高峰涂超王玲刘刚张雯双朱仕文杨明辉吴新宝首都医科大学附属北京积水潭医院创伤骨科北京100035 首都医科大学附属北京积水潭医院放射科北京100035

目的探讨基于CT影像测量的髋部肌肉因素与老年髋部骨折术后1年内独立行动能力恢复的相关性。方法采用前瞻性队列研究分析2018年11月至2019年12月首都医科大学附属北京积水潭医院收治的680例老年髋部骨折患者的临床资料。根据患者术后1... 详细信息

目的探讨基于CT影像测量的髋部肌肉因素与老年髋部骨折术后1年内独立行动能力恢复的相关性。方法采用前瞻性队列研究分析2018年11月至2019年12月首都医科大学附属北京积水潭医院收治的680例老年髋部骨折患者的临床资料。根据患者术后1年内是否恢复至伤前独立行动能力分为独立组和辅助组。记录两组性别、年龄、体重指数、个人史、居住习惯、既往疾病、Charlson合并症指数、实验室检验指标、骨折类型、麻醉类型、手术方式、参与康复训练、受伤至手术时间、髋部肌肉参数。髋部肌肉测量时,采用Osirix软件分别测量CT影像中臀大肌及臀中小肌的肌肉面积和密度,计算平均值并记作为髋部肌肉面积和肌肉密度;后将两类参数分别作性别校正后的Z-score标准化处理,以Z=0将髋部肌肉面积和密度分别分为高面积组(Z≥0)、低面积组(Z0.05)。在重复测量分析中,高面积组恢复独立行动能力的可行性是低面积组的1.84倍(OR=1.84,95%CI 1.33,2.53,P<0.01)。结论基于CT影像测量的髋部肌肉面积与老年髋部骨折患者术后1年内独立行动能力恢复密切相关,且髋部肌肉面积越大,独立行动能力恢复可能性也越大。

关键词：髋骨折体层摄影术螺旋计算机肌步行老年人

Evaluation of UAV-derived multimodal remote sensing data for biomass prediction and drought tolerance assessment in bioenergy sorghum

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The Crop Journal 2022年第5期10卷 1363-1375页

作者： Jiating Li Daniel P.Schachtman Cody F.Creech Lin Wang yufeng ge Yeyin Shi Department of Biological Systems Engineering University of Nebraska-LincolnLincolnNE 68583USA Department of Agronomy and Horticulture Center for Plant Science InnovationUniversity of Nebraska-LincolnLincolnNE 68588USA Center for Plant Science Innovation University of Nebraska-LincolnLincolnNE 68588USA Department of Agronomy and Horticulture Panhandle Research and Extension CenterUniversity of Nebraska-LincolnScottsbluffNE 69361USA

Screening for drought tolerance is critical to ensure high biomass production of bioenergy sorghum in arid or semi-arid environments. The bottleneck in drought tolerance selection is the challenge of accurately predicting biomass for a large number of genotypes. Although biomass prediction by lowaltitude remote sensing has been widely investigated on various crops, the performance of the predictions are not consistent, especially when applied in a breeding context with hundreds of genotypes. In some cases, biomass prediction of a large group of genotypes benefited from multimodal remote sensing data;while in other cases, the benefits were not obvious. In this study, we evaluated the performance of single and multimodal data(thermal, RGB, and multispectral) derived from an unmanned aerial vehicle(UAV) for biomass prediction for drought tolerance assessments within a context of bioenergy sorghum breeding. The biomass of 360 sorghum genotypes grown under well-watered and water-stressed regimes was predicted with a series of UAV-derived canopy features, including canopy structure, spectral reflectance, and thermal radiation features. Biomass predictions using canopy features derived from the multimodal data showed comparable performance with the best results obtained with the single modal data with coefficients of determination(R2) ranging from 0.40 to 0.53 under water-stressed environment and0.11 to 0.35 under well-watered environment. The significance in biomass prediction was highest with multispectral followed by RGB and lowest with the thermal sensor. Finally, two well-recognized yieldbased drought tolerance indices were calculated from ground truth biomass data and UAV predicted biomass, respectively. Results showed that the geometric mean productivity index outperformed the yield stability index in terms of the potential for reliable predictions by the remotely sensed ***, this study demonstrated a promising strategy for the use of different UAV-bas

关键词： Crop phenotyping Unmanned Aerial System(UAS) Thermal Machine learning Drought stress

骨科-老年科共管模式下手术治疗稳定型与不稳定型老年股骨转子间骨折的临床效果比较

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中华骨与关节外科杂志 2024年第7期17卷 622-627页

作者：刘刚陈依民葛宇峰谭哲伦高峰彭卫东杨明辉吴新宝首都医科大学附属北京积水潭医院创伤骨科北京100035

目的:比较骨科-老年科共管模式下手术治疗稳定型与不稳定型老年股骨转子间骨折的临床效果。方法:回顾性分析2015年5月至2017年4月首都医科大学附属北京积水潭医院收治的采用骨科-老年科共管模式下手术治疗的452例老年股骨转子间骨折患... 详细信息

目的:比较骨科-老年科共管模式下手术治疗稳定型与不稳定型老年股骨转子间骨折的临床效果。方法:回顾性分析2015年5月至2017年4月首都医科大学附属北京积水潭医院收治的采用骨科-老年科共管模式下手术治疗的452例老年股骨转子间骨折患者的临床资料,根据术前骨折分型将患者分为稳定型骨折组(180例)和不稳定型骨折组(272例)。记录并比较两组患者的死亡率及日常活动能力资料。结果:所有患者均获得36~71个月随访,平均(47.8±15.4)个月。术后3年及末次随访时,两组患者死亡率比较,差异均无统计学意义(P均>0.05)。末次随访时,两组患者日常活动能力比较,差异无统计学意义(P>0.05)。结论:骨科-老年科共管模式下手术治疗老年股骨转子间骨折,患者死亡率较高、活动能力明显下降,稳定型与不稳定型股骨转子间骨折患者死亡率和日常活动能力相似。

关键词：髋部骨折股骨转子间骨折老年中期随访

后壁压缩对切开复位内固定治疗髋臼后壁骨折疗效的影响研究

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中华创伤骨科杂志 2024年第3期26卷 188-193页

作者：葛宇峰高峰涂超刘刚杨明辉孙旭谭哲伦陈依民彭卫东吴新宝首都医科大学附属北京积水潭医院创伤骨科北京100035

目的探讨后壁压缩对切开复位内固定治疗髋臼后壁骨折疗效的影响。方法回顾性分析2017年1月至2020年12月期间首都医科大学附属北京积水潭医院创伤骨科采用切开复位内固定治疗的83例髋臼后壁骨折患者资料。根据后壁压缩与否分为两组:压缩... 详细信息

目的探讨后壁压缩对切开复位内固定治疗髋臼后壁骨折疗效的影响。方法回顾性分析2017年1月至2020年12月期间首都医科大学附属北京积水潭医院创伤骨科采用切开复位内固定治疗的83例髋臼后壁骨折患者资料。根据后壁压缩与否分为两组:压缩组33例,男26例,女7例;年龄(47.4±11.6)岁;后壁存在压缩。非压缩组50例,男43例,女7例;年龄(41.3±12.0)岁;后壁无压缩。比较两组患者的术后骨折复位质量、末次随访时患髋功能及随访期间并发症发生率等。采用多因素二元logistic回归和年龄亚组分析髋臼后壁压缩对功能结局的影响。结果压缩组患者的年龄、合并其他部位损伤比例及髋臼后壁粉碎比例显著大于非压缩组患者,差异均有统计学意义(P0.05)。所有患者术后获(44.5±13.3)个月随访。非压缩组患者术后骨折解剖复位率(96.0%,48/50)显著高于压缩组患者(57.6%,19/33),末次随访时改良Merle d’’Aubigné & Postel评分优良率(84.0%,42/50)也显著高于压缩组患者(51.5%,17/33),差异均有统计学意义(P0.05)。校正年龄、性别等一般资料后,两组患者髋关节功能比较差异仍有统计学意义(OR=0.23,95%CI:0.06~0.79,P=0.020)。后壁压缩对功能结局的影响在年龄≥50岁患者中差异有统计学意义(P=0.008),而在年龄<50岁患者中差异无统计学意义(P=0.194)。结论在髋臼后壁骨折中,相较于非压缩骨折,压缩骨折更容易导致较差的骨折复位质量,从而影响患者术后髋关节功能的恢复。后壁压缩对功能结局的影响在年龄≥50岁患者中更为显著。

关键词：髋臼骨折骨折固定术,内治疗结果后壁压缩切开复位

Self-Supervised Plant Phenotyping by Combining Domain Adaptation with 3D Plant Model Simulations: Application to Wheat Leaf Counting at Seedling Stage

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Plant Phenomics 2023年第2期5卷 226-238页

作者： Yinglun Li Xiaohai Zhan Shouyang Liu Hao Lu Ruibo Jiang Wei Guo Scott Chapman yufeng ge Benoit de Solan Yanfeng Ding Frédéric Baret Plant Phenomics Research Centre Academy for Advanced Interdisciplinary StudiesJiangsu Collaborative Innovation Center for Modern Crop ProductionNanjing Agricultural UniversityNanjingChina Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhanChina Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 Midori-choNishitokyo CityTokyoJapan School of Agriculture and Food Sciences The University of QueenslandSt.LuciaQueensland 4072Australia Department of Biological Systems Engineering University of Nebraska-LincolnLincolnNebraska 68583United States INRAE Avignon UniversitéUMR EMMAHUMT CAPTE228route de l’aérodrome-CS 4050984914 Avignon Cedex 9France ARVALIS Institut du Végétal 3 Rue Joseph et Marie Hackin75116 ParisFrance

The number of leaves at a given time is important to characterize plant growth and *** this work,we developed a high-throughput method to count the number of leaves by detecting leaf tips in RGB *** digital plant phenotyping platform was used to simulate a large and diverse dataset of RGB images and corresponding leaf tip labels of wheat plants at seedling stages(150,000 images with over 2 million labels).The realism of the images was then improved using domain adaptation methods before training deep learning *** results demonstrate the efficiency of the proposed method evaluated on a diverse test dataset,collecting measurements from 5 countries obtained under different environments,growth stages,and lighting conditions with different cameras(450 images with over 2,162 labels).Among the 6 combinations of deep learning models and domain adaptation techniques,the Faster-RCNN model with cycle-consistent generative adversarial network adaptation technique provided the best performance(R^(2)=0.94,root mean square error=8.7).Complementary studies show that it is essential to simulate images with sufficient realism(background,leaf texture,and lighting conditions)before applying domain adaptation ***,the spatial resolution should be better than 0.6 mm per pixel to identify leaf *** method is claimed to be self-supervised since no manual labeling is required for model *** self-supervised phenotyping approach developed here offers great potential for addressing a wide range of plant phenotyping *** trained networks are available at https://***/YinglunLi/Wheat-leaf-tip-detection.

关键词： Wheat seedling Plant