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Early identification of stroke through deep learning with multi-modal human speech and movement data

Neural Regeneration Research 2025年第1期20卷 234-241页

作者： Zijun Ou Haitao wang Bin Zhang Haobang Liang Bei hu Longlong Ren Yanjuan Liu Yuhu Zhang Chengbo Dai Hejun Wu Weifeng Li Xin Li School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Department of Neurology Guangdong Neuroscience InstituteGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina Department of Emergency Medicine Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina

Early identification and treatment of stroke can greatly improve patient outcomes and quality of *** clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized *** this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute *** collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the *** compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and *** found that the findings of our deep learning model had a higher clinical value compared with the other ***,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech *** results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

关键词： artificial intelligence deep learning diagnosis early detection FAST screening stroke

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Origin软件在化工原理实验数据拟合中的应用

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实验技术与管理 2010年第1期27卷 86-88,93页

作者：王宇胡赟曹仲义杨祖荣北京化工大学化学工程学院

针对化工原理实验中图表、公式等计算较多的问题,目前普遍采用计算机软件辅助数据与图形处理,介绍了基于Origin软件对数据进行线性拟合与非线性曲线拟合的处理方法,将其应用于化工原理实验教学。该方法不仅有方便、快捷、准确性高的特点... 详细信息

针对化工原理实验中图表、公式等计算较多的问题,目前普遍采用计算机软件辅助数据与图形处理,介绍了基于Origin软件对数据进行线性拟合与非线性曲线拟合的处理方法,将其应用于化工原理实验教学。该方法不仅有方便、快捷、准确性高的特点,而且有良好的应用效果,有效地提高了学生的综合应用能力。

关键词： Origin软件化工原理实验线性拟合曲线拟合

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高职大学生就业能力研究

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杨凌职业技术学院学报 2018年第1期17卷 68-71页

作者：周广阔王云江王虎杨凌职业技术学院陕西杨凌712100

分析高职大学生就业能力及其现状,基于社会需求、企业需求及高职大学生自身认知的就业能力研究,提出了基于职业素质的高职大学生职业能力结构,为高职院校大学生人才培养提供借鉴。

关键词：高职大学生就业能力

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人血浆中胸腺肽α1的质谱定量方法初探

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分析测试学报 2004年第Z1期23卷 15-17页

作者：赵芊王洪允胡蓓江骥中国协和医科大学北京协和医院临床药理中心北京100730

　　胸腺肽α1(Thymosin α1)是一种由28个氨基酸组成的新型免疫调节因子,它可以启动T淋巴细胞的成熟、刺激分泌干扰素及各种淋巴介素,以及增强自然杀伤细胞介导的细胞毒性[1].临床应用范围较为广泛,主要用于治疗恶性肿瘤所致的免疫功... 详细信息

　　胸腺肽α1(Thymosin α1)是一种由28个氨基酸组成的新型免疫调节因子,它可以启动T淋巴细胞的成熟、刺激分泌干扰素及各种淋巴介素,以及增强自然杀伤细胞介导的细胞毒性[1].临床应用范围较为广泛,主要用于治疗恶性肿瘤所致的免疫功能低下,乙型、丙型肝炎及其并发症和严重感染或抗生素不能有效控制的感染等,具有广阔的应用前景[2].……

关键词： QSTAR API 3000 LC - MS - MS Thymosin a 1

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Deep learning-based software engineering: progress,challenges, and opportunities

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Science China(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing hu Yuan huANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo wang Chong wang Jiayi wang Tiantian wang Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

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GnIH在陆川仔公猪泌尿生殖系统及内分泌免疫系统中的分布

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西北农林科技大学学报（自然科学版） 2016年第12期44卷 16-20页

作者：霍孔林李昀王晓晔胡浩李建华李珣广西大学动物科学技术学院广西南宁530004 广西理工科学实验中心广西南宁530004

【目的】从形态学水平和分子水平探究促性腺激素抑制激素(GnIH)在陆川仔公猪泌尿生殖系统和内分泌免疫系统中的分布情况。【方法】采集30日龄健康陆川仔公猪的睾丸、附睾、附睾管、肾、肾上腺、甲状腺、腭扁桃体、脾、淋巴结、胸腺,采... 详细信息

【目的】从形态学水平和分子水平探究促性腺激素抑制激素(GnIH)在陆川仔公猪泌尿生殖系统和内分泌免疫系统中的分布情况。【方法】采集30日龄健康陆川仔公猪的睾丸、附睾、附睾管、肾、肾上腺、甲状腺、腭扁桃体、脾、淋巴结、胸腺,采用免疫组织化学和半定量RT-PCR的方法检测GnIH在其泌尿生殖系统和内分泌免疫系统的分布情况。【结果】免疫组织化学分析结果显示,在睾丸、附睾、附睾管、肾、肾上腺、甲状腺、腭扁桃体、脾、淋巴结、胸腺均有不同数量的GnIH免疫阳性细胞分布。半定量RT-PCR的检测显示,GnIH mRNA除了在甲状腺、脾和淋巴结无表达外,在其余组织均有不同程度的表达。【结论】GnIH在泌尿生殖系统和内分泌免疫系统分布广泛,提示GnIH在生殖、免疫和内分泌等生理过程中可能有重要作用。

关键词： GnIH 陆川仔公猪免疫组织化学半定量RT-PCR

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便携式近红外光谱仪在鉴定无花果品质中建模效果研究

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齐鲁工业大学学报 2019年第4期33卷 20-25页

作者：王允虎孙蕾王成忠孙锐齐鲁工业大学(山东省科学院)食品科学与工程学院济南250353 山东省林业科学研究院经济林所济南250014

为了分析便携式近红外光谱仪(MicroNIR)对无花果果实品质的建模效果,测试了成熟无花果的糖度、硬度等5项质构指标,建模方法采用偏最小二乘法回归。结果表明,MicroNIR结合遗传算法可以有效地预测无花果的糖度及质构特性。MicroNIR与遗传... 详细信息

为了分析便携式近红外光谱仪(MicroNIR)对无花果果实品质的建模效果,测试了成熟无花果的糖度、硬度等5项质构指标,建模方法采用偏最小二乘法回归。结果表明,MicroNIR结合遗传算法可以有效地预测无花果的糖度及质构特性。MicroNIR与遗传算法的结合在无花果品质鉴定方面有很大的应用潜力。

关键词： UVE算法遗传算法特征波长筛选近红外光谱分析

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Underground laboratories · Deep underground observation ·Scientific questions—Insights from observations of multi-physic fields in deep underground labs

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Science China Earth Sciences 2025年

作者： huiqi REN yun wang Chang CHEN Guangyu FU Longqing QIU Lianghui GUO Chengliang XIE Yongsheng HE Heping SUN Jiwen TENG Institute of Defense Engineering Academy of Military Sciences State Kay Laboratory of Geological Processes and Mineral Resources Key Laboratory of Intraplate Volcanoes and Earthquakes Ministry of Education China University of Geosciences (Beijing) Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences Institute of Geology and Geophysics Chinese Academy of Sciences

This paper presents a comprehensive review on recent development and research conducted in domestic and international underground laboratories. We first introduce the differences in three environments—surface, mountain tunnel cavities and underground coal mine tunnels—by examining cosmic ray background, ambient noises related to gravity and seismic measurement, and electromagnetic noises in magnetic and magnetotelluric measurements. We highlight potential misuse of the term Underground Lab or Deep Underground Lab when describing observations in different physical fields. We introduce unique features of underground coal mine tunnels in China, such as large spaces, ultra-quiet conditions, and ultra-clean environments. When comparing with mountain tunnel cavities and borehole observations, coal mine tunnel observations have superior long-term stability and high precision. Through observations and comparisons of multi-physic fields at surface and the deep underground, we find that the higher SNR seismic observations conducted in deep underground tunnels in coal mines are beneficial to improve velocity tomography of the solid earth. The gravity observation with a Superconducting Quantum Interference Device(SQUID) makes it possibly to capture slow earthquake, which has not been observed previously in the Chinese mainland. SQUID magnetic observations can detect fluctuations as weak as femto-Tesla(fT), enabling us to explore the attenuation of Schumann Resonance down to the solid Earth. This opens opportunities to investigate the connections between the Earth's magnetic field and the interactions within the human brain and heart. To improve the precision of quantum measurement,we should consider the possible effects of weak magnetic disturbances in deep underground environments. Finally, we discuss the importance of deep underground laboratories, observing facilities and techniques deployed in these laboratories, and their possible connection with respect to “deep space” an

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Ag/ZnO复合材料的制备及其光催化研究

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广州化工 2017年第15期45卷 70-72页

作者：王芸胡晓熙莫小荣钦州学院石油与化工学院广西高校北部湾石油天然气资源有效利用重点实验室广西钦州535011 钦州学院资源与环境学院广西钦州535011

通过光还原沉积改性法制备了含不同含量Ag的Ag/ZnO复合材料(0.5%,1%,2%,5%,10%),对其进行了X射线衍射,扫描电子显微镜表征,并利用光催化降解甲基橙溶液研究复合材料的光催化性能。结果表明:Ag仅负载在ZnO粒子表面上而未进入其晶格内。Ag... 详细信息

通过光还原沉积改性法制备了含不同含量Ag的Ag/ZnO复合材料(0.5%,1%,2%,5%,10%),对其进行了X射线衍射,扫描电子显微镜表征,并利用光催化降解甲基橙溶液研究复合材料的光催化性能。结果表明:Ag仅负载在ZnO粒子表面上而未进入其晶格内。Ag/ZnO复合材料可以有效地降解甲基橙;适量的Ag修饰ZnO可大大提高Ag/ZnO复合材料的光催化活性。过大的沉积量会导致Ag的浪费,且会使Ag/ZnO原子簇增大,不利于光催化反应的效率提高。

关键词： Ag/ZnO复合材料甲基橙光催化性能

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Growth behavior and electronic regulation of Pt on various Mo-based supports for hydrogen evolution electrocatalysis

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Science China Chemistry 2025年

作者： Lulu Chen Yichao huang Jiajun wang Meihong Liao Zhiyuan Liu Meiqi Liu Hanqing Cai Lin wang Lidong Gao Dawei hu Lianming Zhao Ning Pu Zhuangjun Fan State Key Laboratory of Chemical Safety School of Materials Science and Engineering China University of Petroleum (East China) School of Mechanical and Electronic Engineering Qingdao Binhai University Qingdao Chuangqi New Energy Catalysis Technology Co.Ltd. Sinopec Research Institute of Petroleum Processing Co.Ltd. Institute of Energy Hefei Comprehensive National Science Center

Insight into the growth behavior and electronic regulation of platinum （Pt） on various transition metal supports is paramount in developing high-performing electrocatalysts for hydrogen evolution reactions （HER）.Herein,we studied the influence of molybdenum-based supports （MoX,X=C,N,P,and S） on the growth behavior and electronic regulation of *** found that the formation energy variations between Pt single atom and clusters on MoX supports play a pivotal role in the growth behavior of ***,the electronic regulation of Pt induced by metal-support interaction may reflect the valence changes of Pt in Pt-MoX/*** Pt-MoC/C catalyst with a moderate valence state of Pt exhibits the best HER activity with an overpotential of 12.0 mV at 10 mA cm-2and a mass activity of 27.1 A mgPt-1,12.3 times as high as that of commercial 20 wt% Pt/*** work provides constructive guidance for the design of high-performance HER catalysts.

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