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Key technology of mine underground mobile positioning based on {1.DAR and coded sequence pattern

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中国有色金属学会会刊：英文版 2011年第S3期21卷 570-576页

作者： wang zhi1, 2. WU {2.-xin1, 2. {2. hui-ying3 1. college of Resources and Civil Engineering, Northeastern university, Shenyang 110004, China 2. Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs and Ministry of Education, Beijing Normal university, Beijing 100875, China 3. college of computer {12. and technology, jilin university, changchun 130012. China [a] college of Resources and Civil Engineering Northeastern University Shenyang 110004 China [b] Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs and Ministry of Education Beijing Normal University Beijing 100875 China [c] college of {1. {2. and technology Jilin University Changchun 130012 China

Technologies of underground mobile positioning were proposed based on liDAR data and coded sequence pattern landmarks for mine shafts and tunnels environment to meet the needs of fast and accurate positioning and navigation of equipments in the mine underground without satellite navigation signals. A coded sequence pattern was employed for automatic matching of 3D scans. The methods of SIFT feature, Otsu segmentation and fast hough transformation were described for the identification, positioning and interpretation of the coded sequence patterns, respectively. The POSIT model was presented for speeding up computation of the translation and rotation parameters of liDAR point data, so as to achieve automatic 3D mapping of mine shafts and tunnels. The moving positioning experiment was applied to evaluating the accuracy of proposed pose estimation method from liDAR scans and coded sequence pattern landmarks acquired in an indoor environment. The performance was evaluated using ground truth data of the indoor setting so as to measure derivations with six degrees of freedom.

关键词： liDAR coded sequence pattern mobile positioning SLAM algorithm POSIT algorithm

Dose-dependent Cytotoxicity and Oxidative Stress Induced by "Naked" Fe_3O_4 Nanoparticles in Human Hepatocyte

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Chemical Research in Chinese Universities 2012年第1期28卷 114-118页

作者： liN Xin-li1, ZHAO Shu-hua1, ZHANG Long1, HU Gui-qin1, {2. zhi-wei1,3 and yaNG wen-sheng2.1. School of Public Health, jilin university, changchun 13002., P. R. China 2. college of Chemistry, jilin university, changchun {12. P. R. China 3. School of Public Health and Family Medicine, Capital Medical university, Beijing 100069, P. R. China jilin Univ Sch Publ Hlth Changchun 130021 Peoples R China jilin Univ Coll Chem Changchun 130012 Peoples R China Capital Med Univ Sch Publ Hlth & Family Med Beijing 100069 Peoples R China

The dose-dependent cytotoxicity effect on human hepatocyte（HL-7702.cells） induced by ＂naked＂ Fe3O4 nanoparticles was assessed through cell viabilities and lactate dehydrogenase（LDH） activities. Three important oxi dative indexes of the cells by glutathione peroxidase（GSH-Px）, superoxide dismutase（SOD） and malondialde hyde（MDA） were determined. The good correlation of the cell viabilities with their GSH-Px, SOD and MDA levels indicated that the cytotoxicity is related to activation of oxidative stress induced by Fe3O4 nanoparticles. The oxida tive stress also leads to corresponding DNA damage in a similar dose-dependent manner, followed by the changes of cell cycle and cell apoptosis. Such work provides important experimental data for the safety evaluation of superpa ramagnetic Fe3O4 nanoparticles.

关键词： Superparamagnetic Fe304 Cytotoxicity Oxidative stress DNA damage Cell cycle Cell apoptosis

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新一代高通量RNA测序数据的处理与分析

生物化学与生物物理进展 2010年第8期37卷 834-846页

作者：王曦汪小我王立坤冯智星张学工生物信息学教育部重点实验室清华信息科学与技术国家实验室(筹)生物信息学研究部清华大学自动化系北京100084 吉林大学计算机科学与技术学院长春130012

随着新一代高通量DNA测序技术的快速发展,RNA测序(RNA-seq)已成为基因表达和转录组分析新的重要手段.RNA-seq技术产生的海量数据为生物信息学带来了新的机遇和挑战.有效地对测序数据进行针对性的生物信息学处理和分析,成为RNA-seq技术... 详细信息

随着新一代高通量DNA测序技术的快速发展,RNA测序(RNA-seq)已成为基因表达和转录组分析新的重要手段.RNA-seq技术产生的海量数据为生物信息学带来了新的机遇和挑战.有效地对测序数据进行针对性的生物信息学处理和分析,成为RNA-seq技术能否在科学探索中发挥重大作用的关键.以新一代Illumina/Solexa测序平台所产生的数据为例,在扼要介绍高通量RNA-seq测序流程的基础上,对RNA-seq数据处理和分析的方法和现有软件做一个较为全面的综述,并对其中有待进一步研究的问题进行展望。

关键词：高通量RNA测序转录组基因表达数据处理与分析生物信息学

Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

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Advances in Atmospheric sciences 2024年第7期41卷 1326-1341页

作者： Lu li Yongjiu DAI Zhong{1. WEI Wei SHANGGUAN Nan WEI Yonggen ZHANG Qingliang li Xian-Xiang li School of Atmospheric sciences Sun Yat-sen UniversityGuangzhou 510275China Southern Marine science and Engineering Guangdong Laboratory(Zhuhai) Guangzhou 510275China Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Guangzhou 510275China Institute of Surface-Earth System science School of Earth System ScienceTianjin UniversityTianjin 300072China college of {1. {2. and technology Changchun Normal UniversityChangchun 130123China

Accurate soil moisture(SM)prediction is critical for understanding hydrological ***-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface *** addition to PB models,deep learning(DL)models have been widely used in SM predictions ***,few pure DL models have notably high success rates due to lacking physical ***,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM *** this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1.1. days of SM *** performances of the proposed hybrid models were investigated and compared with two existing hybrid *** results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid ***,the ensemble model performed best among all hybrid models at all forecast time scales and different soil *** is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 1.-day *** findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

关键词： soil moisture forecasting hybrid model deep learning ConvLSTM attention mechanism

sTREM-1.as promising prognostic biomarker for acute-on-chronic liver failure and mortality in patients with acute decompensation of cirrhosis

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World Journal of Gastroenterology 2024年第9期30卷 1177-1188页

作者： Song-Man Yu Hai li Guo-Hong Deng Xian-Bo {1. Xin Zheng Jin-Jun Chen Zhong-Ji Meng Yu-Bao Zheng {2.n-Hang Gao zhi-Ping Qian feng liu Xiao-Bo Lu Yu Shi Jia Shang Ruo-Chan Chen {2.n Huang Department of Infectious Diseases Xiangya HospitalCentral South UniversityChangsha 410000Hunan ProvinceChina Department of Gastroenterology Renji HospitalShanghai Jiao Tong University School of MedicineShanghai 200127China Department of Infectious Diseases Southwest HospitalThird Military Medical University(Army Medical University)Chongqing 400038China Center of Integrative Medicine Beijing Ditan HospitalCapital Medical UniversityBeijing 100020China Department of Infectious Diseases Institute of Infection and ImmunologyUnion HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430020Hubei ProvinceChina Department of Infectious Diseases Nanfang HospitalSouthern Medical UniversityGuangzhou 510515Guangdong ProvinceChina Department of Infectious Disease Taihe HospitalHubei University of MedicineShiyan 442009Hubei ProvinceChina Department of Infectious Diseases The Third Affiliated Hospital of Sun Yat-sen UniversityGuangzhou 510630Guangdong ProvinceChina Department of Hepatology The First Hospital of Jilin UniversityChangchun 130021Jilin ProvinceChina Department of liver Intensive Care Unit Shanghai Public Health Clinical CentreFudan UniversityShanghai 200093China Tianjin Institute of Hepatology Nankai University Second People's HospitalTianjin 300192China Infectious Disease Center The First Affiliated Hospital of Xinjiang Medical UniversityUrumqi 830054Xinjiang Uygur Autonomous RegionChina The State Key Laboratory for Diagnosis and Treatment of Infectious Diseases The First Affiliated Hospital of School of MedicineZhejiang UniversityHangzhou 310003Zhejiang ProvineChina Department of Infectious Diseases Henan Provincial People's HospitalZhengzhou 463599Henan ProvineChina Department of Infectious Diseases Hunan Key Laboratory of Viral HepatitisXiangya HospitalCentral South UniversityChangsha 110051Hunan ProvineChina

BACKGROUND Acute decompensation(AD)of cirrhosis is associated with high short-term mortality,mainly due to the development of acute-on-chronic liver failure(ACLF).Thus,there is a need for biomarkers for early and accurate identification of AD patients with high risk of development of ACLF and *** triggering receptor expressed on myeloid cells-{2.sTREM-{2.is released from activated innate immune cells and correlated with various inflammatory *** To explore the prognostic value of sTREM-{2.in patients with AD of *** A multicenter prospective cohort of 442.patients with cirrhosis hospitalized for AD was divided into a study cohort(n=309)and validation cohort(n={2.3).Demographic and clinical data were collected,and serum sTREM-{2.was measured at *** enrolled patients were followed-up for at least {2.*** In patients with AD and cirrhosis,serum sTREM-{2.was an independent prognosis predictor for {2.year survival and correlated with liver,coagulation,cerebral and kidney failure.A new prognostic model of AD(P-AD)incorporating sTREM-{2.blood urea nitrogen(BUN),total bilirubin(TBil),international normalized ratio(INR)and hepatic encephalopathy grades was established and performed better than the model for end-stage liver disease(MELD),MELD-sodium(MELD-Na),chronic liver failure-consortium(CliF-C)ACLF and CliF-C AD ***,sTREM-{2.was increased in ACLF and predicted the development of ACLF during first 2.-d *** ACLF risk score incorporating serum sTREM-{2.BUN,INR,TBil and aspartate aminotransferase levels was established and significantly superior to MELD,MELD-Na,CliF-C ACLF,CliF-C AD and P-AD in predicting risk of ACLF *** Serum sTREM-{2.is a promising prognostic biomarker for ACLF development and mortality in patients with AD of cirrhosis.

关键词： Soluble triggering receptor expressed on myeloid cell-1 Acute decompensation Cirrhosis Acute-on-chronic liver failure Prognostic biomarker

用距离传感器实时建立连续表面三维模型的方法

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吉林大学学报（工学版） 2003年第3期33卷 55-59页

作者：王德民李艾瑛刘子良吉林大学网络中心吉林长春130012 吉林大学计算机科学与技术学院吉林长春130025

提出了用距离传感器将不同方位上同一物体的实测数据(非连续、二维)实时地合成到同一个模型中,以便能快速得到一个具有连续表面的三维模型的方法。采用本算法规则,不到1.in即可在sun工作站用1.0×1.0的实测数据建立一个具有连续表面的... 详细信息

提出了用距离传感器将不同方位上同一物体的实测数据(非连续、二维)实时地合成到同一个模型中,以便能快速得到一个具有连续表面的三维模型的方法。采用本算法规则,不到1.in即可在sun工作站用1.0×1.0的实测数据建立一个具有连续表面的工作图像。

关键词：距离传感器实时处理三维模型表面连续算法

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天然气柴油双燃料准均质燃烧过程的研究

燃烧科学与技术 2004年第2期10卷 146-148页

作者：张纪鹏夏元东孙志军江华春李威李丽吉林大学汽车学院长春130025 河北农业大学水产学院秦皇岛066003 吉林建筑工程学院长春130021

通过发动机缸内分析法,对发动机的典型工况燃烧特性进行了试验研究,结果表明,天然气柴油双燃料在低速时具有比燃烧纯柴油高的指示压力,最高爆发压力大于纯柴油,最大压力升高率也具有相同的规律,且双燃料的循环变动量大于柴油;而在中、... 详细信息

通过发动机缸内分析法,对发动机的典型工况燃烧特性进行了试验研究,结果表明,天然气柴油双燃料在低速时具有比燃烧纯柴油高的指示压力,最高爆发压力大于纯柴油,最大压力升高率也具有相同的规律,且双燃料的循环变动量大于柴油;而在中、高转速下,其具有与低速情况相反的规律.

关键词：双燃料发动机均质压燃燃烧

Central nervous system efficacy of aumolertinib versus gefitinib in patients with untreated,EGFR-mutated,advanced non-small cell lung cancer:data froma randomized phase III trial(AENEAS)

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Cancer Communications 2024年第9期44卷 1005-1017页

作者： Shun Lu Xiaorong Dong Hong Jian Jianhua Chen Gongyan Chen Yuping sun yinghua Ji Zipingwang Jianhua Shi Junguo Lu Shaoshui Chen Dongqing Lv Guojun Zhang Chunling liu Juan li Xinmin Yu Zhong lin Zhuang Yu Zhehaiwang Jiuwei Cui Xingxiang Xu Jian Fang Jifeng feng zhi Xu RuiMa Jie Hu Nong yang Xiangdong Zhou XiaohongWu Chengping Hu zhihong Zhang You Lu yanping Hu liyan Jiang Qiming wang Renhua Guo Jianying Zhou Baolan li Chunhong Hu Wancheng Tong Helong Zhang linMa Yuan Chen zhijun Jie Yu yao Longzhen Zhang Jieweng Weidong li Jianping Xiong Xianwei Ye Jianchun Duan Haihua yang Meili sun HongyingWei JiaweiWei Zheyu Zhang QiongWu Department of Medical Oncology Shanghai Chest Hospital Shanghai JiaoTong UniversityShanghaiP.R.China Cancer Center Union Hospital Tongji Medical College Huazhong University of Science and TechnologyWuhanHubeiP.R.China Department of Medical Oncology-Chest Hunan Cancer Hospital&The Affiliated Cancer Hospital of Central South University Xiangya School of MedicineChangshaHunanP.R.China Thoracic OncologyMedicine HarbinMedical University Cancer HospitalHarbinHeilongjiangP.R.China Department of Oncology Jinan Central HospitalJinanShandongP.R.China Department of Oncology First Affiliated Hospital of Xinxiang Medical UniversityXinxiangHenanP.R.China Department of Chest Medicine Beijing Cancer HospitalBeijingP.R.China Department of Internal Medicine Linyi Cancer HospitalLinyiShandongP.R.China Department of Respiratory Medicine Nantong Tumor HospitalNantongJiangsuP.R.China Department of Oncology Binzhou Medical University HospitalBinzhouShandongP.R.China Breath Internal Medicine Taizhou Hospital of Zhejiang ProvinceLinhaiZhejiangP.R.China Department of Respiration The First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenanP.R.China Department of Lung Internal Medicine Affiliated Tumor Hospital of Xinjiang Medical UniversityUrumqiXinjiangP.R.China Department of Thoracic Oncology Sichuan Cancer HospitalChengduSichuanP.R.China Thoracic Medical Oncology Cancer Hospital of the University of Chinese Academy of Sciences(Zhejiang Cancer Hospital)HangzhouZhejiangP.R.China Department of Thoracic Oncology The Fifth Subsidiary Sun Yat-sen University HospitalZhuhaiGuangdongP.R.China Department of Oncology The Affiliated Hospital of QingdaoUniversityQingdaoShandongP.R.China Department of Oncology Shandong Cancer HospitalJinanShandongP.R.China Department of Oncology The First BethuneHospital of Jilin UniversityChangchunJilinP.R.China Department of Respiration Northern Jiangsu People’s Hospital Affiliated to Yangzhou UniversityYangzhouJiangsuP.R.China Department of Internal

Background:The initial randomized,double-blinded,actively controlled,phase III ANEAS study(NCT03849768)demonstrated that aumolertinib showed superior efficacy relative to gefitinib as first-line therapy in epidermal growth factor receptor(EGFR)-mutated advanced non-small cell lung cancer(NSCLC).Metastatic disease in the central nervous system(CNS)remains a challenge in the management of *** study aimed to compare the efficacy of aumolertinib versus gefitinib among patients with baseline CNS metastases in the ANEAS ***:Eligible patients were enrolled and randomly assigned in a 1.1.ratio to orally receive either aumolertinib or gefitinib in a double-blinded *** with asymptomatic,stable CNS metastases were ***-up imaging of the same modality as the initial CNS imaging was performed every 6 weeks for 1. months,then every *** responsewas assessed by a neuroradiological blinded,independent central review(neuroradiological-BICR).The primary endpoint for this subgroup analysis was CNS progression-free survival(PFS).Results:Of the 42. patients enrolled and randomized in the ANEAS study,1.6 patients were found to have CNS metastases(CNS Full Analysis Set,cFAS)at baseline by neuroradiological-BICR,and 60 of them had CNS target lesions(CNS Evaluable for Response,cEFR).Treatment with aumolertinib significantly prolonged median CNS PFS compared with gefitinib in both cFAS(2..0 vs.8.3 months;hazard ratio[HR]=0.31.95%confidence interval[CI],0.1.-0.56;P1.and cEFR(2..0 vs.8.3 months;HR=0.2.;95%CI,0.1.-0.57;P1..The confirmed CNS overall response rate in cEFRwas 85.7%and 75.0%in patients treated with aumolertinib and gefitinib,*** risk analysis showed that the estimated probability of CNS progression without prior non-CNS progression or death was consistently lower with aumolertinib than with gefitinib in patients with and without CNSmetastases at *** new safety findings were ***:The

关键词： aumolertinib brain metastasis non-small cell lung cancer third-generation EGFR-TKI

Characterization of acute-on-chronic liver diseases: A multicenter prospective cohort study

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World Journal of Hepatology 2024年第5期16卷 809-821页

作者： Yuan-yao Zhang Sen Luo Hai li Shu-Ning {2. Xian-Bo wang Xin Zheng yan Huang Bei-ling li yan-Hang Gao zhi-Ping Qian feng liu Xiao-Bo Lu Jun-Ping liu Hao-Tang Ren Yu-Bao Zheng Hua-Dong yan Guo-Hong Deng liang Qiao yan Zhang wen-Yi Gu Xiao-Mei Xiang Yi Zhou Yi-Xin Hou Qun Zhang yan Xiong Cong-Cong Zou Jun Chen Ze-Bing Huang Xiu-Hua Jiang Ting-Ting Qi Yuan-Yuan Chen Na Gao Chun-yan liu Wei Yuan Xue Mei Jing li Tao li Rong-Jiong Zheng Xin-Yi Zhou Jun Zhao Zhong-Ji Meng Department of Infectious Disease Institute of Biomedical ResearchRegulatory Mechanism and Targeted Therapy for Liver Cancer Shiyan Key LaboratoryHubei provincial Clinical Research Center for Precise Diagnosis and Treatment of Liver CancerTaihe HospitalHubei University of MedicineShiyan 442000Hubei ProvinceChina Department of Gastroenterology Renji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai 200120China Department of Infectious Diseases Southwest HospitalThe Third Military Medical University(Army Medical University)Chongqing 400000China Center of Integrative Medicine Beijing Ditan HospitalCapital Medical UniversityBeijing 100020China Department of Infectious Diseases Institute of Infection and ImmunologyUnion HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430020Hubei ProvinceChina Department of Infectious Diseases Hunan Key Laboratory of Viral HepatitisXiangya HospitalCentral South UniversityChangsha 110051Hunan ProvinceChina Hepatology Unit Department of Infectious DiseasesNanfang HospitalSouthern Medical UniversityGuangzhou 510515Guangdong ProvinceChina Department of Hepatology The First Hospital of Jilin UniversityChangchun 130021Jilin ProvinceChina Department of liver Intensive Care Unit Shanghai Public Health Clinical CentreFudan UniversityShanghai 200093China Tianjin Institute of Hepatology Nankai University Second People's HospitalTianjin 300192China Infectious Disease Center The First Affiliated Hospital of Xinjiang Medical UniversityUrumqi 830054Xinjiang Uygur Autonomous RegionChina Department of Infectious Diseases and Hepatology The Second Hospital of Shandong UniversityJinan 250000Shandong ProvinceChina State Key Laboratory for Diagnosis and Treatment of Infectious Diseases Collaborative Innovation Center for Diagnosis and Treatment of Infectious DiseaseThe First Affiliated HospitalZhejiang University School of MedicineHangzhou 310000Zhejiang ProvinceChina Department of Infectious Diseases The Thir

BACKGROUND Acute-on-chronic liver disease(AoCLD)accounts for the majority of patients hospitalized in the Department of Hepatology or Infectious *** To explore the characterization of AoCLD to provide theoretical guidance for the accurate diagnosis and prognosis of *** Patients with AoCLD from the Chinese Acute-on-Chronic liver Failure(ACLF)study cohort were included in this *** clinical characteristics and outcomes,and the 90-d survival rate associated with each clinical type of AoCLD were analyzed,using the Kaplan-Meier method and the log-rank *** A total of 3375 patients with AoCLD were enrolled,including 1.79(49.7%)patients with liver cirrhosis acute decompensation(LC-AD),850(2..2.)patients with ACLF,577(1..1.)patients with chronic hepatitis acute exacer-bation(CHAE),and 2.9(8.0%)patients with liver cirrhosis active phase(LC-A).The most common cause of chronic liver disease(CLD)was HBV infection(71.4%).The most common precipitants of AoCLD was bacterial infection(2..8%).The 90-d mortality rates of each clinical subtype of AoCLD were 43.4%(2.2.535)for type-C ACLF,36.0%(36/1.0)for type-B ACLF,2..0%(58/2.5})for type-A ACLF,9.0%(1.1.1.79)for LC-AD,3.0%(8/2.9)for LC-A,and 1.2.(7/577)for *** HBV infection is the main cause of CLD,and bacterial infection is the main precipitant of *** most common clinical type of AoCLD is *** diagnosis and timely intervention are needed to reduce the mortality of patients with LC-AD or ACLF.

关键词： Acute-on-chronic liver disease Acute-on-chronic liver failure liver cirrhosis Clinical features Prognosis