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用卷积神经网络U-Net分割对比增强锥光束乳腺CT数据

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四川大学学报（自然科学版） 2024年第5期61卷 245-252页

作者：彭蹀苏桐郑伊能欧阳祖彬马强杨亮吕发金四川大学数学学院成都610064 重庆医科大学附属第一医院放射科重庆400042

乳腺肿瘤是一种常见的恶性肿瘤,其临床诊断不但费时费力,还容易出现误诊.本文旨在建立一个基于乳腺数据自动分割的乳腺肿瘤计算机辅助诊断模型,提高临床诊断的速度和准确率.为了用卷积神经网络U-Net模型分割对比增强锥光束乳腺计算机断... 详细信息

乳腺肿瘤是一种常见的恶性肿瘤,其临床诊断不但费时费力,还容易出现误诊.本文旨在建立一个基于乳腺数据自动分割的乳腺肿瘤计算机辅助诊断模型,提高临床诊断的速度和准确率.为了用卷积神经网络U-Net模型分割对比增强锥光束乳腺计算机断层扫描(Contrast-Enhanced Cone-Beam Breast CT,CE-CBBCT)数据,本文首先沿冠状面将3维数据转换成2维切片,通过数据默认的窗口对其进行归一化处理.实验结果显示,使用U-Net卷积神经网络对数据进行分割,Dice系数和IoU(Intersection over Union)分别为0.7920和0.6962.然后,本文用不同骨干网络(即各种深度学习分类网络)去替换U-Net的编码器,再次进行分割并对比不同特征提取对分割性能的影响,发现旋转增广方式可以提升各分割网络的性能.其中,基于ResNet152的U形分割网络的性能最好,Dice系数和IoU分别达到0.8410和0.7576.随后,本文又在所有模型中选取5个性能最好的模型组成一个集成模型,重复分割实验,发现此模型有最佳分割性能,平均Dice系数和IoU可达0.8463和0.7676,性能显著提升.值得指出的是,在处理数据时本文仅使用数据默认的窗口,降低了对人工的依赖.

关键词：乳腺肿瘤对比增强锥光束乳腺CT 分割 U-Net

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Quantifying the Temperature Effects on the Morbidity of Digestive Diseases In an Inland Plateau-Valley City

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Biomedical and Environmental Sciences 2024年第9期37卷 1101-1105页

作者： Pan ma Yang Yang Ning Zhou Xinzi Wang Yulu Wang Wenjuan Feng Zhaoqin Bai Shigong Wang Plateau Atmosphere and Environment Key Laboratory of Sichuan Province College of Atmospheric ScienceChengdu University of Information TechnologyChengdu 610225SichuanChina Chengdu Plain Urban Meteorology and Environment Observation and Research Station of Sichuan Province Chengdu 610225SichuanChina The Infectious Disease Department The First People’s Hospital of LanzhouLanzhou 730050GansuChina Meteorological Bureau of Jinnan District Tianjin 300350China Gansu University of Chinese Medicine Lanzhou 730000GansuChina

Extreme air temperature and increased weather oscillations caused by climate change have been threatening global *** conditions are external inducers that may trigger the onset of gastrointestinal diseases,in addition... 详细信息

关键词： Plateau weather consumption

Profound loss of microbial necromass carbon in permafrost thaw-subsidence in the central Tibetan Plateau

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Advances in Climate Change Research 2024年第4期15卷 647-657页

作者： Wen-Ting ZHOU Quan-Lian LI Shi-Chang KANG Xiao-Dong WU Tian ma Xiao-Bo WU Xin XIONG Tanuj SHUKLA maheswar RUPAKHETI Dipesh RUPAKHETI Da-He QIN Xiu-Feng YIN Cryosphere Research Station on the Qinghai-Tibet Plateau State Key Laboratory of Cryospheric ScienceNorthwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China Key Laboratory of Cryospheric Science and Frozen Soil Engineering Norhwest Instiute of Eco-Evironment and ResourcesChinese Academy of Scienes Lanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems and College of Pastoral Agriculture Science and TechnologyLanzhou UniversityLanzhou730020China Lushan Botanical Garden Chinese Academy of SciencesJiujiang 332900China Research Institute for Sustainability-Helmholtz Centre Potsdam Potsdam 14467Germany Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science and TechnologyNanjing 210044China

Climate warming is causing rapid permafrost degradation,including thaw-induced subsidence,potentially resulting in heightened carbon ***,our understanding of the levels and variations of carbon components in permafrost,particularly during the degradation process,remains *** uncertainties arising from this process lead to inaccurate assessments of the climate effects during permafrost *** vast expanses of permafrost in the Tibetan Plateau,there is limited research available on SOC components,particularly in the central Tibetan *** remarkable variations in hydrothermal conditions across different areas of the Tibetan Plateau,the existing limited studies make it challenging to assess the overall SOC components in the permafrost across the Tibetan Plateau and simulate their future *** this study,we examined the properties of soil organic carbon(SOC)and microbial necromass carbon(MicrobialNC)in a representative permafrost thaw-subsidence area at the southern edge of continuous permafrost in the central Tibetan *** results indicate that prior to the thaw-subsidence,the permafrost had a SOC content of 72.68±18.53 mg g^(-1),with MicrobialNC accounting for 49.6%.The thaw-subsidence of permafrost led to a 56.4%reduction in SOC,with MicrobialNC accounting for 70.0%of the lost *** constitutes the primary component of permafrost SOC,and it is the main component that is lost during thaw-subsidence *** in MicrobialNC are primarily correlated with factors pH,plant input,and microbial *** present study holds crucial implications for both the ecological and biogeochemical processes associated with carbon release from permafrost,and it furnishes essential data necessary for modeling the global response of permafrost to climate *** on this study and previous research,permafrost thawing in the Tibetan Plateau causes substantial loss of ***,there's remarkable heterogeneit

关键词： Tibetan Plateau Thaw-subsidence Soil organic carbon Microbial necromass carbon Amino sugars

甘肃省高等教育自学考试多元化评价实施调查研究——以护理本科专业为例

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河西学院学报 2024年第2期40卷 118-123页

作者：马竞竞杜发强何培宇甘肃省教育考试院甘肃兰州730000 甘肃医学院甘肃平凉744000

目的:构建甘肃省高等教育自学考试多元化评价体系,提高护理专业自学考试教育质量。方法:文献研究甘肃省自学考试发展历史;调研省内自学考试主管部门——甘肃省教育考试院及开展自学考试教育项目的兰州大学、甘肃医学院等高校,访谈相关... 详细信息

目的:构建甘肃省高等教育自学考试多元化评价体系,提高护理专业自学考试教育质量。方法:文献研究甘肃省自学考试发展历史;调研省内自学考试主管部门——甘肃省教育考试院及开展自学考试教育项目的兰州大学、甘肃医学院等高校,访谈相关工作人员;设计问卷调查10家医院494名医护人员、15名教师及251名自考生;构建以技能考核为主的多元化评价体系。结果:自学考试多元化评价可提高考生综合能力,67.73%的自考生和80%的教师支持增加实践技能考核,技能考核需占30%,采用专业核心课程闭卷考试+实践技能考核的评价模式。结论:多元化评价可提高自学考试教育质量,需要进一步推广完善。

关键词：自学考试多元化评价护理专业实践技能考核

A fluorescence-enhanced inverse opal sensing film for multi-sources detection of formaldehyde

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Food Science and Human Wellness 2024年

作者： Xiaokang Lu Bo Han Deyilei Wei Mingzhu Chu Haojie ma Ran Li Xueyan Hou Yuqi Zhang JiJiang Wang Key Laboratory of New Energy & New Functional materials， Shaanxi Key Laboratory of Chemical Reaction Engineering， College of Chemistry and Chemical Engineering， Yan’an University

The SiO2inverse opal photonic crystals (PC) with a three-dimensional macroporous structure were fabricated by the sacrificial template method， followed by infiltration of a pyrene derivative， 1-(pyren-8-yl)but-3-en-1-amine (PEA)， to achieve a formaldehyde-sensitive and fluorescence-enhanced sensing film. Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and formaldehyde (fa) to generate a strong fluorescent product emitted at ～480 nm， we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength. In virtue of the fluorescence enhancement property derived from slow photon effect of PC， fa was detected highly selectively and sensitively. The limit of detection (LoD) was calculated to be 1.38 nmol/L. Furthermore， the fast detection of fa (within 1 min) is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area. The prepared sensing film can be used for the detection of fa in air， aquatic products and living cells. The very close fa content in indoor air to the result from fa detector， the recovery rate of 101.5% for detecting fa in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.

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N,N-二乙基对苯二胺分光光度法检测生活饮用水中硫化物的注意事项探析

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实验室检测

实验室检测 2024年第6期2卷 153-156页

作者：刘驰青马加翠耿发梅昆明市五华区疾病预防控制中心

目的通过实验分析并总结影响使用N,N-二乙基对苯二胺分光光度法进行水中硫化物测定的因素和注意事项。方法采用N,N-二乙基对苯二胺分光光度法检测水中硫化物，用已知硫化物含量的标准样品验证方法准确性和精密度，对实验过程中的各个... 详细信息

目的通过实验分析并总结影响使用N,N-二乙基对苯二胺分光光度法进行水中硫化物测定的因素和注意事项。方法采用N,N-二乙基对苯二胺分光光度法检测水中硫化物，用已知硫化物含量的标准样品验证方法准确性和精密度，对实验过程中的各个环节进行分析。结果 N,N-二乙基对苯二胺分光光度法测定水中硫化物，其方法线性、精密度、准确性均满足分析要求，适合应用于清洁水中硫化物的检测。结论实验过程中需注意采样、标准溶液的配制和吸取、显色液的配制等环节，才能有满意的结果。

关键词：饮用水硫化物分光光度法检测注意事项

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防爆电器浇封复合物的介电强度试验工装研究

电气防爆 2024年第1期 30-31,35页

作者：杨法军张荣斌马国浩浙江方圆电气设备检测有限公司浙江嘉兴314001

针对GB/T 3836.9—2021的试验要求,设计了一种防爆电器浇封复合物介电强度试验工装。该工装利用导柱和导套,能够确保试验时电极在浇封复合物样块两侧对称放置,提高了试验结果的准确性。

关键词：防爆电器浇封复合物介电强度试验对称放置

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基于碳排放核算的CCUS源汇匹配和部署研究

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石油科技论坛 2024年第1期43卷 78-85页

作者：汪芳马建国李明卓高明张法提高油气采收率国家重点实验室中国石油勘探开发研究院中国石油油气和新能源分公司中国石油吉林油田公司二氧化碳开发公司

针对不同碳源捕集能耗、不同运输地貌和距离的压缩功耗,以及CO_(2)驱不同开发阶段能耗和泄漏的差异,以CCUS项目能耗和泄漏、散逸排放为约束条件,项目周期全流程净减排量最大为优化目标,建立碳减排量核算约束下符合油藏动态开发规律的CCU... 详细信息

针对不同碳源捕集能耗、不同运输地貌和距离的压缩功耗,以及CO_(2)驱不同开发阶段能耗和泄漏的差异,以CCUS项目能耗和泄漏、散逸排放为约束条件,项目周期全流程净减排量最大为优化目标,建立碳减排量核算约束下符合油藏动态开发规律的CCUS源汇匹配方法,可为“双碳”目标下CCUS技术产业布局和项目实施提供决策依据。以中国石油在鄂尔多斯盆地的CCUS产业规划为例,综合考虑现有煤电、煤化工碳源运行和装置服役时限、CO_(2)捕集能耗预测、CO_(2)驱注入倍数与循环气量,以及盆地内煤基工业产业布局规划等限制因素,按2025年、2030年、2040年、2050年和2060年5个阶段完成鄂尔多斯盆地CCUS项目源汇匹配优化和阶段部署,匹配的CCUS/CCS项目群在2025—2060期间累计注入CO_(2)约3.96×10^(8)t(含循环气0.48×10^(8)t),扣除各工艺能耗和泄漏排放后的CO_(2)净减排量可达2.54×10^(8)t,净减排效率约为72.9%。

关键词： CO_(2)捕集、利用与封存碳减排量核算源汇匹配优化管道部署规划

Adaptive Neighboring Selection Algorithm Based on Curvature Prediction in manifold Learning

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Journal of Harbin Institute of Technology(New Series) 2013年第3期20卷 119-123页

作者： Lin ma Cai-fa Zhou Xi Liu Yu-Bin Xu Communication Research Center Harbin Institute of Technology Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory

Recently manifold learning algorithm for dimensionality reduction attracts more and more interests, and various linear and nonlinear,global and local algorithms are proposed. The key step of manifold learning algorithm is the neighboring region selection. However,so far for the references we know,few of which propose a generally accepted algorithm to well select the neighboring region. So in this paper,we propose an adaptive neighboring selection algorithm,which successfully applies the LLE and ISOmaP algorithms in the test. It is an algorithm that can find the optimal K nearest neighbors of the data points on the manifold. And the theoretical basis of the algorithm is the approximated curvature of the data point on the manifold. Based on Riemann Geometry,Jacob matrix is a proper mathematical concept to predict the approximated curvature. By verifying the proposed algorithm on embedding Swiss roll from R3 to R2 based on LLE and ISOmaP algorithm,the simulation results show that the proposed adaptive neighboring selection algorithm is feasible and able to find the optimal value of K,making the residual variance relatively small and better visualization of the results. By quantitative analysis,the embedding quality measured by residual variance is increased 45. 45% after using the proposed algorithm in LLE.

关键词： manifold learning curvature prediction adaptive neighboring selection residual variance