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A TPDP-MPM-based approach to understanding the evolution mechanism of landslide-induced disaster chain

Journal of Rock Mechanics and Geotechnical Engineering 2022年第4期14卷 1200-1209页

作者： wenjie du Qian Sheng Xiaodong Fu Jian Chen Yongqiang Zhou State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan430071China School of Engineering Science University of Chinese Academy of SciencesBeijing100049China China-Pakistan Joint Research Center on Earth Sciences CAS-HECIslamabadPakistan

With complex topographic and hydrological characteristics,the landslide-induced surge disaster chain readily develops in mountainous and gorge areas,posing a huge challenge for infrastructure *** landslide-induced surge disaster chain involves a complex fluid-solid coupling between the landslide mass and a water body and exhibits complex energy conversion and dissipation characteristics,which is challenging to deal with using traditional finite element *** this study,the energy evolution characteristics in the whole process of the disaster chain were first investigated,and the momentum-conservation equations for different stages were ***,the two-phase doublepoint material point method(TPDP-MPM)was used to model the landslide-induced surge disaster chain,and an experiment involving block-induced surge was modeled and simulated to validate this ***,three generalized models were established for the landslide-induced surge process in a U-shaped valley,including subaerial,partly submerged,and submarine *** interaction mechanism between the landslide mass and the water body in the disaster chain was revealed by defining the system energy conversion ratio and the mechanism of evolution of the disaster chain from the perspective of *** results help further evaluate the secondary disasters,given the submerged position of the landslide mass.

关键词： Disaster chain Landslide-induced surge Material point method(MPM) Energy evolution U-shaped valley

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Atomistic characterization of binding modes and affinity of peptide inhibitors to amyloid-β protein

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Frontiers of Chemical Science and Engineering 2014年第4期8卷 433-444页

作者： Fufeng LIU wenjie du Yan SUN Jie ZHENG Xiaoyan DONG Department of Biochemical Engineering and Key Laboratory of Systems Bioengineering (Ministry of Education) School of Chemical Engineering and Technology Tianjin University Tianjin 300072 China Department of Chemical and Biomolecular Engineering The University of Akron Akron OH 44325 USA Collaborative Innovation Center of Chemical Science and Engineering (Tianjin) Tianjin 300072 China

Abstract The aggregation of amyloid β-protein （Aβ） is tightly linked to the pathogenesis of Alzheimer＇s disease. Previous studies have found that three peptide inhibitors （i.e., KLVFF, VVIA, and LPFFD） can inhibit Aβ aggregation and alleviate Aβ-induced neurotoxicity. How- ever, atomic details of binding modes and binding affinities between these peptide inhibitors and Aβ have not been revealed. Here, using molecular dynamics simulations and molecular mechanics Poisson Boltzmann surface area （MM/PBSA） analysis, we examined the effect of three peptide inhibitors （KLVFF, VVIA, and LPFFD） on their sequence-specific interactions with Aβ and the molecular basis of their inhibition. All inhibitors exhibit varied binding affinity to Aβ, in which KLVFF has the highest binding affinity, whereas LPFFD has the least. MM/PBSA analysis further revealed that different peptide inhibitors have different modes of interaction with Aβ, consequently hotspot binding residues, and underlying driving forces. Specific residue-based interactions between inhibitors and Aβ were determined and compared for illustrating different binding and inhibition mechanisms. This work provides structure-based binding information for further modifica- tion and optimization of these three peptide inhibitors to enhance their binding and inhibitory abilities against Aβ aggregation.

关键词： Alzheimer's disease amyloid β-protein pep-tide inhibitors protein-protein interaction moleculardynamics simulation

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Source identification and prediction of nitrogen and phosphorus pollution of Lake Taihu by an ensemble machine learning technique

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Frontiers of Environmental Science & Engineering 2023年第5期17卷 27-40页

作者： Yirong Hu wenjie du Cheng Yang Yang Wang Tianyin Huang Xiaoyi Xu Wenwei Li CAS Key Laboratory of Urban Pollutant Conversion Department of Environmental Science and EngineeringUniversity of Science and Technology of ChinaHefei 230026China School of Software Engineering University of Science and Technology of ChinaHefei 230026China USTC-CityU Joint Advanced Research Center Suzhou Institute for Advanced Research of USTCSuzhou 215123China National and Local Joint Engineering Laboratory for Municipal Sewage Resource Utilization Technology Suzhou University of Science and TechnologySuzhou 215009China

Effective control of lake eutrophication necessitates a full understanding of the complicated nitrogen and phosphorus pollution sources,for which mathematical modeling is commonly *** contrast to the conventional knowledge-based models that usually perform poorly due to insufficient knowledge of pollutant geochemical cycling,we employed an ensemble machine learning(ML)model to identify the key nitrogen and phosphorus sources of *** ML models were developed based on 13 years of historical data of Lake Taihu’s water quality,environmental input,and meteorological conditions,among which the XGBoost model stood out as the best model for total nitrogen(TN)and total phosphorus(TP)*** results suggest that the lake TN is mainly affected by the endogenous load and inflow river water quality,while the lake TP is predominantly from endogenous *** prediction of the lake TN and TP concentration changes in response to these key feature variations suggests that endogenous source control is a highly desirable option for lake eutrophication ***,one-month-ahead prediction of lake TN and TP concentrations(R2 of 0.85 and 0.95,respectively)was achieved based on this model with sliding time window lengths of 9 and 6 months,*** work demonstrates the great potential of using ensemble ML models for lake pollution source tracking and prediction,which may provide valuable references for early warning and rational control of lake eutrophication.

关键词： Eutrophication Machine learning Water quality Nutrients Prediction

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Deciphering urban traffic impacts on air quality by deep learning and emission inventory

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Journal of Environmental Sciences 2023年第2期124卷 745-757页

作者： wenjie du Lianliang Chen Haoran Wang Ziyang Shan Zhengyang Zhou Wenwei Li Yang Wang School of Software Engineering University of Science and Technology of ChinaHefei 230026China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215123China Alibaba Inc. Hangzhou 310052China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China CAS Key Laboratory of Urban Pollutant Conversion Department of environmental science and EngineeringUniversity of Science and Technology of ChinaHefei 230026China USTC-CityU Joint Advanced Research Center Suzhou 215123China

Air pollution is a major obstacle to future sustainability,and traffic pollution has become a large drag on the sustainable developments of future ***,combined with the large volume of real-time monitoring data,we propose a deep learning model,iDeepAir,to predict surface-level PM2.5 concentration in Shanghai megacity and link with MEIC emission inventory creatively to decipher urban traffic impacts on air *** model exhibits high-fidelity in reproducing pollutant concentrations and reduces the MAE from 25.355μg/m^(3) to 12.283μg/m^(3) compared with other *** identifies the ranking of major factors,local meteorological conditions have become a nonnegligible ***-wise relevance propagation(LRP)is used here to enhance the interpretability of the model and we visualize and analyze the reasons for the different correlation between traffic density and PM_(2.5) concentration in various regions of ***,As the strict and effective industrial emission reduction measurements implementing in China,the contribution of urban traffic to PM_(2.5) formation calculated by combining MEIC emission inventory and LRP is gradually increasing from 18.03%in 2011 to 24.37% in 2017 in Shanghai,and the impact of traffic emissions would be ever-prominent in 2030 according to our *** also infer that the promotion of vehicular electrification would achieve further alleviation of PM_(2.5) about 8.45% by 2030 *** insights are of great significance to provide the decision-making basis for accurate and high-efficient traffic management and urban pollution control,and eventually benefit people’s lives and high-quality sustainable developments of cities.

关键词： PM_(2.5)concentration forecast Traffic emissions Deep learning Attention mechanism New energy vehicles

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A standardized dataset of built-up areas of China’s cities with populations over 300,000 for the period 1990-2015

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Big Earth Data 2022年第1期6卷 103-126页

作者： Huiping Jiang Zhongchang Sun Huadong Guo Qiang Xing wenjie du Guoyin Cai Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina Key Laboratory for Earth Observation of Hainan Province SanyaChina School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and ArchitectureBeijingChina

China’s urbanization has attracted a lot of attention due to its unprecedented pace and intensity in terms of land,population,and economic ***,due to the lack of consistent and harmonized data,little is known about the patterns and dynamics of the interaction between these different aspects over the past few *** with the implementation of the 2030 Agenda for Sustainable Development,a standardized dataset for assessing the sustainability of urbanization in China is *** this paper,we used remote sensing data from multiple sources(time-series of Landsat and Sentinel images)to map the impervious surface area(ISA)at five-year intervals from 1990 to 2015 and then converted the results into a standardized dataset of the built-up area for 433 Chinese cities with 300,000 inhabitants or *** dataset was produced following the well-established rules adopted by the United Nations(UN).Validation of the ISA maps in urban areas based on the visual interpretation of Google Earth images showed that the average overall accuracy(OA),producer’s accuracy(PA)and user’s accuracy(UA)were 91.24%,92.58%and 89.65%,*** with other existing urban built-up area datasets derived from the National Bureau of Statistics of China,the World Bank and UN-habitat indicated that our dataset,namely the stan-dardized urban built-up area dataset for China(SUBAD-China),provides an improved description of the spatiotemporal character-istics of the urbanization process and is especially applicable to a combined analysis of the spatial and socio-economic domains in urban *** applications of this dataset include combin-ing the spatial expansion and demographic information provided by UN to calculate sustainable development indicators such as SDG *** dataset could also be used in other multidimensional syntheses related to the study of urbanization in China.

关键词： Built-up area impervious surface area(ISA) remote sensing urbanization SDG 11.3.1

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Efficient replacement of long DNA fragments via non-homologous end joining at norrcoding regions

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Journal of Molecular Cell Biology 2021年第1期13卷 75-77页

作者： Shanye Gu Jia Li Siyuan Li Jianbin Cao Jiwen Bu Yonggang Ren wenjie du Zhecong Chen Chufan Xu Mingcang Wang Lai Jiang Cheng Huang Jiulin du Department of Anesthesiology and Surgical Intensive Care Unit Xinhua HospitalShanghai Jiao Tong University School of MedicineShanghai 200092China Drug Discovery Laboratory School of PharmacyShanghai University of Traditional Chinese MedicineShanghai 201203China Institute of Neuroscience State Key Laboratory of NeuroscienceCenter for Excellence in Brain Science and Intelligence TechnologyShanghai Research Center for Brain Science and Brain-Inspired IntelligenceChinese Academy of SciencesShanghai 200031China Department of Anesthesiology Affiliated Taizhou HospitalWenzhou Medical UniversityLinhai 317000China University of Chinese Academy of Sciences Beijing 100049China ShanghaiTech University Shanghai 200031China

Targeted double-strand breaks(DSBs)in genomes can be introduced efficiently by endonucleases(Umov et al.,2010;Jinek et al.,2012;Joung and Sander,2013),including zinc-finger nucleases,tran scription activator-like effector nu cleases,and clustered regularly in terspaced palindromic repeats(CRISPR)/*** DSBs,DNA repair is mainly via homology-directed repair(HDR)and/or non-homologous end joining(NHEJ)(Hustedt and durocher,2016).It was reported that genomic DNA replacement can be achieved via HDR at the site of DSBs in multiple organisms(Dickinson et al.,2013;Yang et al.,2013;Zu et al.,2013),but the efficiency is still not enough for general application,in particular for replacing long DNA fragment that is more than hundreds of base pairs(bps).As NHEJ is 10-fold more active than HDR at DSB sites(Mao et al.,2008),we speculated that NHEJ can be utilized to implement long genomic DNA replacement with high efficiency.

关键词： DNA joining homologous

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Application of Unmanned Aerial Vehicle Remote Sensing on Dangerous Rock Mass Identification and Deformation Analysis: Case Study of a High-Steep Slope in an Open Pit Mine

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Journal of Earth Science 2023年

作者： wenjie du Qian Sheng Xiaodong Fu Jian Chen Jingyu Kang Xin Pang Daochun Wan Wei Yuan State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of Sciences School of Engineering Science University of Chinese Academy of Sciences China-Pakistan Joint Research Center on Earth Sciences CAS-HEC Panzhihua Iron and Steel Group Mining Co. Ltd. Key Laboratory of Roads and Railway Engineering Safety Control of Ministry of Education Shijiazhuang Tiedao University

Source identification and deformation analysis of disaster bodies are the main contents of high-steep slope risk assessment, the establishment of high-precision model and the quantification of the fine geometric features of the slope are the prerequisites for the above work. In this study, based on the UAV remote sensing technology in acquiring refined model and quantitative parameters, a semi-automatic dangerous rock identification method based on multi-source data is proposed. In terms of the periodicity UAV-based deformation monitoring, the monitoring accuracy is defined according to the relative accuracy of multi-temporal point cloud. Taking a high-steep slope as research object, the UAV equipped with special sensors was used to obtain multi-source and multi-temporal data, including highprecision DOM and multi-temporal 3D point clouds. The geometric features of the outcrop were extracted and superimposed with DOM images to carry out semi-automatic identification of dangerous rock mass, realizes the closed-loop of identification and accuracy verification; changing detection of multi-temporal 3D point clouds was conducted to capture deformation of slope with centimeter accuracy. The results show that the multi-source data-based semi-automatic dangerous rock identification method can complement each other to improve the efficiency and accuracy of identification, and the UAV-based multi-temporal monitoring can reveal the near real-time deformation state of slopes.

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用于化学文摘生成的压缩算法

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计算机与应用化学 2010年第2期27卷 249-252页

作者：杜文洁沈阳师范大学职业技术学院辽宁沈阳110034

化学工作者经常要阅读大量的英文资料来获取本行业最新的研究成果和资源。但是,大量的阅读会占用很多宝贵的时间,从而增大查找工作的投入,降低工作效率。本论文研究一些文本压缩算法,利用当今文本处理领域现有的压缩算法,针对一些化学... 详细信息

化学工作者经常要阅读大量的英文资料来获取本行业最新的研究成果和资源。但是,大量的阅读会占用很多宝贵的时间,从而增大查找工作的投入,降低工作效率。本论文研究一些文本压缩算法,利用当今文本处理领域现有的压缩算法,针对一些化学文章进行人工信息抽取,生成相关的化学文摘。并聘请化学领域的专业人员对人工生成的文摘进行评估。结果表明人工生成的文摘比较理想,对化学工作者的资料查询和收集工作带来很大的帮助。压缩技术是文本处理的一个重要应用方向,句子的自动压缩是其基础部分。在这个领域的前沿技术中有很多种压缩算法,本论文采用了一种基于噪声信道模型(Noisy-Channel Model)的英文句子压缩方法,这种方法是利用概率句法分析来进行句子成分筛选和压缩。实验表明,这种压缩方法能够较好地应用于化学文摘的生成,保障化学文摘的概括性与准确性,保留了化学文章中的主要内容和核心思想。

关键词：压缩技术化学文摘

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脑卒中合并胃潴留患者经鼻空肠管肠内营养的疗效观察

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中国中西医结合急救杂志 2016年第5期23卷 536-538页

作者：杜文杰河北省定兴县医院河北保定072650

目的：观察脑卒中合并胃潴留患者经鼻空肠管肠内营养的临床疗效。方法选择2012年3月至2015年11月河北省定兴县医院收治的42例脑卒中合并胃潴留进行肠内营养支持的患者，按随机数字表法分为观察组和对照组，每组21例。两组均按指南给予... 详细信息

目的：观察脑卒中合并胃潴留患者经鼻空肠管肠内营养的临床疗效。方法选择2012年3月至2015年11月河北省定兴县医院收治的42例脑卒中合并胃潴留进行肠内营养支持的患者，按随机数字表法分为观察组和对照组，每组21例。两组均按指南给予常规治疗，床头抬高30°～45°，并进行胃肠减压；观察组患者置入鼻空肠管，给予肠内营养；对照组患者先给予肠外营养，待胃肠功能恢复后改经胃管给予肠内营养。于入院时和治疗2周后取血检测两组患者血糖、血浆总蛋白和白蛋白水平；比较两组三头肌皮褶厚度（TSF）、上臂围（MAC）、上臂肌围（AMC）等评价营养状况；观察两组腹泻、应激性溃疡、胃肠道感染、反流、高血糖、中心静脉感染等不良反应和并发症发生情况。结果两组治疗前血糖、白蛋白、总蛋白水平比较差异无统计学意义（均P＞0.05）。治疗后两组血糖水平均较入院时降低，且观察组的降低更为显著（mmol/L：6.45±2.15比7.68±2.68，P＜0.05）；对照组治疗后白蛋白、总蛋白均较入院时降低，而观察组无明显变化，对照组水平明显低于观察组〔白蛋白（g/L）：30.78±4.12比38.20±4.67，总蛋白（g/L）：63.91±4.32比67.11±3.12，均P＜0.05〕。治疗2周后两组营养状况指标TSF、MAC、AMC均较入院时降低，但观察组的降低程度不及对照组显著〔TSF（mm）：11.91±1.29比10.13±1.37，MAC（cm）：24.19±3.12比23.74±2.08，AMC（cm）：22.64±2.05比21.73±2.15，均P＜0.05〕。观察组患者不良反应发生率均较对照组明显降低（腹泻：9.5%比38.1%，应激性溃疡：4.8%比33.3%，反流：4.8%比28.6%，高血糖：9.5%比38.1%，均P＜0.05）；对照组患者中心静脉感染发生率为4.8%。结论对脑卒中合并胃潴留患者行空肠内营养支持可预防营养不良的发生，降低不良反应及并发症发率，促进患者康复。

关键词：脑卒中胃潴留肠内营养支持并发症

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绿色正义:概念演进、构成要素与运行系统

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社会科学战线 2023年第2期332卷 171-182页

作者：史云贵杜雯洁四川大学公共管理学院四川成都610064 四川大学国际关系学院四川成都610064

全球生态治理赤字折射出全球生态治理价值的缺位。人类对于全球生态治理价值的找寻,经历生态至上的生态正义、人类至上的环境正义,落脚于回归地球整体性的绿色正义。绿色正义是全球生态危机下生态治理的价值导向与评判标准。绿色正义由... 详细信息

全球生态治理赤字折射出全球生态治理价值的缺位。人类对于全球生态治理价值的找寻,经历生态至上的生态正义、人类至上的环境正义,落脚于回归地球整体性的绿色正义。绿色正义是全球生态危机下生态治理的价值导向与评判标准。绿色正义由绿色正义目标、绿色正义标准、绿色正义规范、绿色正义道德、绿色正义认知、绿色正义角色、绿色正义评价等要素构成。这些要素遵循“输入—转换—输出—反馈”机制耦合成绿色正义系统,于全球绿色空间中生产与传递绿色能量。绿色正义在追寻人类美好生活的正义目标下,分解为人类与自然协同演进的标准,通过赋值绿色规范与绿色道德,推动国家和个人绿色认知与绿色角色扮演,输出绿色行为结果。绿色正义是全球生态治理的价值重塑,有助于消除全球生态治理赤字,实现人与自然和谐共生的“善治”。

关键词：绿色正义全球生态治理环境正义绿色空间

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