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Prediction of sepsis within 24 hours at the triage stage in emergency departments using machine learning

World Journal of Emergency Medicine 2024年第5期15卷 379-385页

作者： Jingyuan Xie Jiandong Gao Mutian yang Ting zhang Yecheng liu Yutong Chen Zetong liu Qimin Mei Zhimao li Huadong Zhu Ji Wu Department of Electronic engineering Tsinghua UniversityBeijing 100084China Center for Big Data and Clinical Research Institute for Precision MedicineTsinghua UniversityBeijing 100084China Institute of Medical Technology Peking University Health Science CenterBeijing 100091China Emergency Department State Key Laboratory of Complex Severe and Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical Science and Peking Union Medical CollegeBeijing 100005China Department of Health Care Peking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100005China

BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing *** approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be *** methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to fi nd a light-weight,convenient prediction method through machine ***:We accessed the MIMIC-IV for sepsis patient data in the *** dataset comprised demographic information,vital signs,and synthetic *** Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED ***,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's *** percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold ***:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±*** model achieved similar performance on the testing set of 1,662 *** values showed that the fi ve most important features were acuity,arrival transportation,age,shock index,and respiratory ***:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage *** may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.

关键词： Sepsis Machine learning Emergency department Triage Informatics

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Large circuit models: opportunities and challenges

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Science china(information Sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min li Xingquan li Yu li Yun liANG Jinwei liU Yi liU Yibo liN guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI Zhiyao XIE Qiang XU Chenhao XUE Junchi YAN Jun yang Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi zhang Zuodong zhang Yuxiang ZHAO Hui-ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark Lab School of Integrated Circuits Peking University Faculty of Electrical engineering and Computer Science Ningbo University Department of Electronic and Computer engineering Hong Kong University of Science and Technology Department of Computer Science and engineering The Chinese University of Hong Kong School of Integrated Circuits Southeast University Huawei HiSilicon Peng Cheng laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

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基于MFDC-SSD网络的接触网定位线夹缺陷识别

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铁道学报 2024年第5期46卷 48-57页

作者：屈志坚张博语杨行李迪华东交通大学轨道交通基础设施性能监测与保障国家重点实验室江西南昌330013 华东交通大学电气与自动化工程学院江西南昌330013

针对接触网应用环境复杂,定位线夹体积小、安装方向特殊、不易识别,传统的目标检测算法效果较差等问题,基于多尺度特征融合密集连接网络模型,提出了一种接触网定位线夹缺陷检测新方法。首先结合DenseNet与Inception模块对SSD模型的特征... 详细信息

针对接触网应用环境复杂,定位线夹体积小、安装方向特殊、不易识别,传统的目标检测算法效果较差等问题,基于多尺度特征融合密集连接网络模型,提出了一种接触网定位线夹缺陷检测新方法。首先结合DenseNet与Inception模块对SSD模型的特征提取网络进行改进,在特定的特征层间共享上下文信息,提升特征提取能力。然后从网络深层到浅层,逐级采用FPN融合SSD检测的多尺度特征图,设计多特征融合的密集连接网络模型,最后将f GIoU作为边框损失函数,在训练中优化真实框和预测框的重合度。对采集的某段接触网定位线夹图像数据集进行检测识别。结果表明:该定位线夹缺陷检测方法可在复杂接触网背景下,对定位线夹脱落和松动进行检测,且在不同角度、亮度的图像中均具有较强的鲁棒性。

关键词：接触网缺陷识别定位线夹特征金字塔边界框损失函数

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基于属性约简与加权最优层次聚类的短期风速混合预测

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电网技术 2024年第5期48卷 2054-2063,I0067页

作者：秦本双杨子轶李琼林张朔严张文燕郭宇河南理工大学电气工程与自动化学院河南省焦作市454003 河南省煤矿装备智能检测与控制重点实验室河南省焦作市454003 国网河南省电力有限公司电力科学研究院河南省郑州市450052 湖南大学电气与信息工程学院湖南省长沙市410082

准确的风速预测是提高风功率预测精度的重要保障。为此,提出一种基于互信息(mutualinformation,MI)属性约简与加权最优层次聚类(weighting optimal hierarchy clustering,WOHC)的离群鲁棒极限学习机(outlier robust extreme learning machine,ORELM)风速混合预测方法。首先,计算32维风速属性特征与风速时间序列间的MI,分析不同特征与风速的相关性。在此基础上,分别采用最大相关最小冗余(maximum correlation minimum redundancy,MRMR)算法和WOHC算法实现风速属性特征的约简及风速样本数据的聚类划分,并通过最优化聚类预处理(clusters optimizationonpreprocessingstage,COPS)确定最优聚类数。然后,采用ORELM对不同样本集分别进行训练,构建ORELM风速混合预测模型。计算待预测点约简后的属性特征与每个聚类中心的欧式距离,选择匹配的ORELM模型进行风速预测。最后,结合东北某风电场实测数据对所提预测方法的有效性和准确性进行验证,结果表明所提方法具有较好的预测精度,能够满足实际风电场风速预测的需要。

关键词：风速混合预测属性约简 WOHC ORELM

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Organic-inorganic hybrid piezotronic bipolar junction transistor for pressure sensing

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Microsystems & Nanoengineering 2024年第3期10卷 229-244页

作者： Emad Iranmanesh Zihao liang Weiwei li Congwei liao Shunyu Jin Chuan liu Kai Wang Shengdong zhang Charalampos Doumanidis Gehan A.J.Amaratunga Hang Zhou Guangdong Provincial key laboratory of In-Memory Computing Chips School of Electronic and Computer EngineeringPeking University Shenzhen Graduate SchoolShenzhen 518055P.R.China School of Mechanical engineering Guangdong Technion-Israel Institute of TechnologyShantou 515063P.R.China state key laboratory of Microelectronics Device and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029P.R.China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 23000PR China School of Electronics and information Technology Sun Yat-sen UniversityNo.132 East Waihuan RoadGuangzhou 510006P.R.China Department of Mechanical Aerospaceand Biomedical EngineeringUniversity of South AlabamaShelby Hall3128MobileAL 36688USA Electrical engineering Division Department of EngineeringUniversity of Cambridge9 JJ Thomson AvenueCambridge CB30FAUnited Kingdom Zhejiang university International CampusHainingChina

With the rapid development of the Internet of Things(IoTs),wearable sensors are playing an increasingly important role in daily monitoring of personal health and *** signal-to-noise-ratio has become the most critical performance factor to *** enhance it,on the one hand,good sensing materials/devices have been employed;on the other hand,signal amplification and noise reduction circuits have been ***,most of these devices and circuits work in an active sampling mode,requiring frequent data acquisition and hence,entailing high-power *** this scenario,a flexible and wearable event-triggered sensor with embedded signal amplification without an external power supply is of great ***,we report a flexible two-terminal piezotronic n-p-n bipolar junction transistor(PBJT)that acts as an autonomous and highly sensitive,current-and/or voltage-mediated pressure *** PBJT is formed by two back-to-back piezotronic diodes which are defined as emitter-base and collectorbase *** force exertion on the emitter side,as a result of the piezoelectric effect,the emitter-base diode is forward biased while the collector-base diode is reverse *** to the inherent BJT amplification effect,the PBJT achieves record-high sensitivities of 139.7 kPa^(-1)(current-based)and 88.66 kPa^(-1)(voltage-based)in sensing *** PBJT also has a fast response time ofli ranging from a flying butterfly to a gentle finger ***,the PBJT advances the state of the art not only in terms of sensitivity but also in regard to being self-driven and autonomous,making it promising for pressure sensing and other IoT applications.

关键词： bipolar transistor IoT

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Improving Global VTEC inversion with Inequality Constraint Least Square

Improving Global VTEC inversion with Inequality Constraint L...

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第三届中国卫星导航学术年会

作者： Hongping zhang 1,2,Peiliang Xu 4,Maorong Ge 5,Wenhui Han 3 Changjiang Geng 2 1.state key laboratory of information engineering in surveying,mapping and remote sensing,wuhan university,wuhan 430070,china 2 GNSS Research Center,wuhan university,wuhan 43.079,china 3 School of Geodesy and Geomatics,wuhan university,wuhan 43.079,china 4.Disaster Prevention Research Institute,Kyoto university,Uji,Kyoto 611‐0011,Japan 5.Helmholtz Centre Potsdam,German Research Centre for Geosciences (GFZ),Telegrafenberg,14473 Potsdam,Germany

Currently,ground‐based GNSS stations of the International GNSS Service （IGS） are distributed unevenly around the *** of them locate on the mainland,while only a small part of them are scattered on some islands in the *** a consequence,grid vertical total electron content （VTEC） of ESA and CODE’s IONEX products appear many unreasonable zero values （in fact negative values）,especially for the years of 2008 and 2009 when the solar activity was rather *** improve this situation,this paper proposes an inequality‐constrained least squares method for the solution of Global Ionospheric mapping （GIM） with spherical harmonic functions by imposing non‐negative inequality constraints in the areas where negative VTEC values may *** then apply the new method to 2008 IGS *** results have shown that the new algorithm efficiently eliminates the unwanted behavior of negative VTEC values that can often be seen on both middle and high latitude area of south hemisphere （S90～S45） and north hemisphere （N5°～N9°） under current IGS *** repeatability of most GPS receivers’ DCBs have been improved ***,GIM products from this paper,CODE,JPL and ESA are compared with IGS final *** is found that inequality constraint improve the consistency of our GIM with them both at RMS and mean VTEC.

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基于双流并行全向扫描Mamba的遥感影像建筑物变化检测

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武汉大学学报（信息科学版） 2024年第9期49卷 1574-1585页

作者：厉芳婷张过周方栋王上梁思李志炜武汉大学测绘遥感信息工程国家重点实验室湖北武汉430079 湖北省航测遥感院湖北武汉430074 华中师范大学人工智能教育学部湖北武汉430079 91001部队北京100841

采用深度学习技术对海量遥感影像进行建筑物变化检测与解译分析,可以为自然资源要素管理和国土资源节约集约化提供关键科学依据和数据支持,对自然资源动态监测和空间治理现代化具有重要意义。状态空间模型Mamba结合了全局感受野与动态加... 详细信息

采用深度学习技术对海量遥感影像进行建筑物变化检测与解译分析,可以为自然资源要素管理和国土资源节约集约化提供关键科学依据和数据支持,对自然资源动态监测和空间治理现代化具有重要意义。状态空间模型Mamba结合了全局感受野与动态加权,在时间序列预测任务中能够更好地捕捉趋势和周期性信息,然而目前Mamba在遥感影像密集预测的研究尚不充分,对高分辨率遥感影像变化检测存在计算复杂度高、检测效率低等问题。对影响Mamba算法参数量的关键因素进行了深入分析,提出了双流并行全向扫描Mamba网络,构建通道内的数据并行化处理方法,在通道总数不变的情况下,有效减少单个Mamba块中数据的通道数,实现网络总体参数量的下降和高效的特征提取。在LEVIR-CD和WHU-CD两个数据集上进行了对比实验,结果表明,所提网络各项指标均优于非Mamba架构的网络,与基准网络对比训练效率分别提升了19.45%和8.26%,且在网络参数量与计算复杂度方面显著降低,分别降低了35.8%和22.4%。

关键词：高分辨率遥感影像变化检测深度学习状态空间模型双流并行

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Multi-omic Analyses Shed light on The Genetic Control of High-altitude Adaptation in Sheep

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Genomics, Proteomics & Bioinformatics 2024年第2期22卷 43-56页

作者： Chao li Bingchun Chen Suo Langda Peng Pu Xiaojia Zhu Shiwei Zhou Peter Kalds Ke zhang Meenu Bhati Alexander Leonard Shuhong Huang Ran li Awang Cuoji Xiran Wang Haolin Zhu Yujiang Wu Renqin Cuomu Ba Gui Ming li Yutao Wang Yan li Wenwen Fang Ting Jia Tianchun Pu Xiangyu Pan Yudong Cai Chong He liming Wang Yu Jiang Jian-lin Han Yulin Chen Ping Zhou Hubert Pausch Xiaolong Wang International Joint Agriculture Research Center for Animal Bio-Breeding Ministry of Agriculture and Rural Affairs/Key Laboratory of Animal GeneticsBreeding and Reproduction of Shaanxi ProvinceCollege of Animal Science and TechnologyNorthwest A&F UniversityYangling 712100China Animal Genomics ETH ZürichZürich 8092Switzerland Institute of Animal Science Tibet Academy of Agricultural and Animal Husbandry SciencesLhasa 850009China School of Biological and Pharmaceutical engineering Lanzhou Jiaotong UniversityLanzhou 730070China College of life Sciences Shaanxi Normal UniversityXi’an 710119China Zoology and Evolutionary Biology Department of BiologyUniversity of Konstanz78457 KonstanzGermany College of life and Geographic Sciences Kashi UniversityKashi 844000China Beijing key laboratory of Captive Wildlife Technologies Beijing ZooBeijing 100044China Department of Medical Research Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China key laboratory of Agricultural Internet of Things Ministry of Agriculture and Rural Affairs/Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent ServiceCollege of Information EngineeringNorthwest A&F UniversityYangling 712100China Institute of Animal Husbandry and Veterinary Medicine Xinjiang Academy of Agricultural and Reclamation SciencesShihezi 832000China state key laboratory of Sheep Genetic Improvement and Healthy Production Xinjiang Academy of Agricultural and Reclamation SciencesShihezi 832000China CAAS-ILRI Joint laboratory on livestock and Forage Genetic Resources Institute of Animal ScienceChinese Academy of Agricultural SciencesBeijing 100193China livestock Genetics Program International Livestock Research InstituteNairobi 00100Kenya

Sheep were domesticated in the Fertile Crescent and then spread globally,where they have been encountering various environmental *** Tibetan sheep has adapted to high altitudes on the Qinghai-Tibet Plateau over the past 3000 *** explore genomic variants associated with high-altitude adaptation in Tibetan sheep,we analyzed Illumina short-reads of 994 whole genomes representing∼60 sheep breeds/populations at varied altitudes,PacBio High fidelity(HiFi)reads of 13 breeds,and 96 transcriptomes from 12 sheep *** testing between the inhabited altitudes and 34,298,967 variants was conducted to investigate the genetic architecture of altitude *** accurate HiFi reads were used to complement the current ovine reference assembly at the most significantly associatedβ-globin locus and to validate the presence of two haplotypes A and B among 13 sheep *** haplotype A carried two homologous gene clusters:(1)HBE1,HBE2,HBB-like,and HBBC,and(2)HBE1-like,HBE2-like,HBB-like,and HBB;while the haplotype B lacked the first *** high-altitude sheep showed highly frequent or nearly fixed haplotype A,while the low-altitude sheep dominated by haplotype *** further demonstrated that sheep with haplotype A had an increased hemoglobin–O2 affinity compared with those carrying haplotype *** highly associated genomic region contained the EGLN1 gene which showed varied expression between high-altitude and low-altitude *** results provide evidence that the rapid adaptive evolution of advantageous alleles play an important role in facilitating the environmental adaptation of Tibetan sheep.

关键词： Environmental adaptation High altitude Hypoxia Selection signature Sheep

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Photonics-assisted THz wireless communication enabled by wide-bandwidth packaged backilluminated modified uni-traveling-carrier photodiode

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Opto-Electronic Science 2024年第7期3卷 20-29页

作者： Yuxin Tian Boyu Dong Yaxuan li Bing Xiong Junwen zhang Changzheng Sun Zhibiao Hao Jian Wang Lai Wang Yanjun Han Hongtao li lin Gan Nan Chi Yi Luo Beijing National Research Center for information Science and Technology(BNRist) Department of Electronic EngineeringTsinghua UniversityBeijing 100084China key laboratory of information Science of Electromagnetic Waves(MoE) Department of Communication Science and EngineeringFudan UniversityShanghai 200433China Flexible Intelligent Optoelectronic Device and Technology Center Institute of Flexible Electronics Technology of THUJiaxing 314000China

This paper presents a wide-bandwidth back-illuminated modified uni-traveling-carrier photodiode(MUTC-PD)packaged with standard WR-5 rectangular waveguide for high-speed wireless *** optimized epitaxy structure and coplanar waveguide electrodes,the fabricated 4-μm-diameter PD exhibits ultra-flat frequency response and high saturation *** passive circuits including low-loss bias-tee and E-plane probe are designed to package the PD into a compact module with waveguide *** packaged PD module has demonstrated a flat frequency response with fluctuations within±2.75 d B over a broadband of 140–220 GHz and a high saturated output power of-7.8 d Bm(166μW)at 140 *** wireless communication applications,the packaged PD is used to implement 1-m free space transmission at carrier frequencies of 150.5 and 210.5 GHz,with transmission rates of 75 and 90 Gbps,respectively.

关键词： modified uni-traveling-carrier photodiode integrated bias-tee E-plane probe flat frequency response high saturation power WR-5 output THz wireless communications

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自适应膨胀和结构嵌入的非对称哈希遥感图像检索算法

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地球信息科学学报 2024年第8期26卷 1926-1940页

作者：李强强李小军李轶鲲杨树文杨睿哲兰州交通大学测绘与地理信息学院兰州730070 地理国情监测技术应用国家地方联合工程研究中心兰州730070 甘肃省测绘科学与技术重点实验室兰州730070

随着遥感平台日新月异,遥感图像数量也呈指数级地增长,如何从遥感大数据中筛选出所需遥感图像,已成为遥感应用亟待解决核心问题之一。目前利用深度卷积神经网络获取图像深度特征被认为是图像检索中最为有效的方法。然而,由于其特征维度... 详细信息

随着遥感平台日新月异,遥感图像数量也呈指数级地增长,如何从遥感大数据中筛选出所需遥感图像,已成为遥感应用亟待解决核心问题之一。目前利用深度卷积神经网络获取图像深度特征被认为是图像检索中最为有效的方法。然而,由于其特征维度过高从而导致相似性度量困难,降低了检索的速度和精度。为此,本文提出了一种结合自适应膨胀卷积和结构嵌入网络的非对称哈希遥感图像检索方法。该方法首先设计了自适应膨胀卷积模块,该模块能够在不增加额外模型参数同时自适应地捕捉遥感图像的多尺度特征;其次,针对遥感图像中的结构信息提取不足问题,对已有的结构嵌入模块进行了优化改进,改进后模块能够有效提取遥感图像中的几何结构特征;最后针对类内差异性和类间相似性导致的检索效率低下问题,引入了成对相似性约束,使原始特征空间中遥感图像之间的相似性能在哈希空间中得到保留。通过在4个不同数据集上的对比实验,验证了本文方法优于现有的深度哈希图像检索方法。同时,通过消融实验验证了所提模型中各模块的有效性。

关键词：遥感图像检索残差网络深度哈希非对称哈希自适应膨胀结构编码多尺度特征

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