检索结果-内蒙古大学图书馆

arXiv 2023年

作者： McClure, M.K. Rocha, W.R.M. Pontoppidan, K.M. Crouzet, N. Chu, L.E.U. Dartois, E. Lamberts, T. Noble, J.A. Pendleton, Y.J. Perotti, G. Qasim, D. Rachid, M.G. Smith, Z.L. Sun, F. Beck, Tracy L. Boogert, A.C.A. Brown, W.A. Caselli, P. Charnley, S.B. Cuppen, Herma M. Dickinson, H. Drozdovskaya, M.N. Egami, E. Erkal, J. Fraser, H. Garrod, R.T. Harsono, D. Ioppolo, S. Jiménez-Serra, I. Jin, M. Jørgensen, J.K. Kristensen, L.E. Lis, D.C. McCoustra, M.R.S. McGuire, Brett A. Melnick, G.J. Öberg, Karin I. Palumbo, M.E. Shimonishi, T. Sturm, J.A. van Dishoeck, E.F. Linnartz, H. Leiden Observatory Leiden University PO Box 9513 LeidenNL–2300 RA Netherlands Laboratory for Astrophysics Leiden Observatory Leiden University PO Box 9513 LeidenNL–2300 RA Netherlands Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States NASA Postdoctoral Program Fellow NASA Ames Research Center M/S 245-1 Moffett FieldCA94035 United States Institut des Sciences Moléculaires d’Orsay CNRS Univ. Paris-Saclay Orsay91405 France Leiden Institute of Chemistry Gorlaeus Laboratories Leiden University PO Box 9502 Leiden2300 RA Netherlands Physique des Interactions Ioniques et Moléculaires CNRS Aix Marseille Univ. Marseille13397 France Department of Physics University of Central Florida OrlandoFL32816 United States Max Planck Institute for Astronomy Königstuhl 17 HeidelbergD-69117 Germany Southwest Research Institute San AntonioTX78238 United States School of Physical Sciences The Open University Walton Hall Milton KeynesMK7 6AA United Kingdom Steward Observatory University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States Institute for Astronomy University of Hawai’i at Manoa 2680 Woodlawn Drive HonoluluHI96822 United States Department of Chemistry University of Sussex Falmer BrightonBN1 9QG United Kingdom Max-Planck-Institut für extraterrestrische Physik Gießenbachstrasse 1 Garching bei München85748 Germany Solar System Exploration Division NASA Goddard Space Flight Center GreenbeltMD20771 United States Radboud University Institute for Molecules and Materials Nijmegen6525 AJ Netherlands Center for Space and Habitability Universität Bern Gesellschaftsstrasse 6 Bern3012 Switzerland Departments of Astronomy & Chemistry University of Virginia CharlottesvilleVA22904 United States Institute of Astronomy Department of Physics National Tsing Hua University Hsinchu Taiwan Center for Interstellar Catalysis Department of Physics and Astronomy Aarhus University Ny Munkegade 120 Aarhus C80

Icy grain mantles are the main reservoir of the volatile elements that link chemical processes in dark, interstellar clouds with the formation of planets and composition of their atmospheres. The initial ice composition is set in the cold, dense parts of molecular clouds, prior to the onset of star formation. With the exquisite sensitivity of JWST, this critical stage of ice evolution is now accessible for detailed study. Here we show the first results of the Early Release science program "Ice Age" that reveal the rich composition of these dense cloud ices. Weak ices, including, 13CO2, OCN−13CO, OCS, and COMs functional groups are now detected along two pre-stellar lines of sight. The 12CO2 ice profile indicates modest growth of the icy grains. Column densities of the major and minor ice species indicate that ices contribute between 2 and 19% of the bulk budgets of the key C, O, N, and S elements. Our results suggest that the formation of simple and complex molecules could begin early in a water-ice rich environment. © 2023, CC BY.

关键词： Budget control

来源：评论

学校读者我要写书评

暂无评论

The Medium Energy (ME) X-ray telescope onboard the Insight-HXMT astronomy satellite

arXiv

引用

arXiv 2019年

作者： Xuelei, Cao Weichun, Jiang Bin, Meng Wanchang, Zhang Tao, Luo Sheng, Yang Chunlei, Zhang Yudong, Gu Liang, Sun Xiaojing, Liu Jiawei, Yang Xian, Li Ying, Tan Shaozhen, Liu Yuanyuan, Du Fangjun, Lu Yupeng, Xu Shuangnan, Zhang Huanyu, Wang Tipei, Li Chengmo, Zhang Xiangyang, Wen Mingyu, Ge Yupeng, Zhou Shaolin, Xiong Shu, Zhang Yongjie, Zhang Zehao, Cheng Fei, Zhang Maoshun, Li Xiaohua, Liang Min, Gao Enbo, Yang Xiaohang, Liu Hongwei, Liu Yirong, Yang Fan, Zhang Key Laboratory for Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Tsinghua University Beijing100084 China Beijing Key Laboratory of Space Thermal Control Technology Beijing Institute of Spacecraft System Engineering Beijing100094 China University of Science and Technology of China Hefei230022 China Guizhou University Guiyang550025 China Yantai University Yantai264005 China University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing100049 China

The Medium Energy X-ray telescope (ME) is one of the three main telescopes on board the Insight Hard X-ray Modulation Telescope (Insight-HXMT) astronomy satellite. ME contains 1728 pixels of Si-PIN detectors sensitive in 5-30 keV with a total geometrical area of 952 cm2. Application Specific Integrated Circuit (ASIC) chips, VA32TA6, is used to achieve low power consumption and low readout noise. The collimators define three kinds of field of views (FOVs) for the telescope, 1°×4°, 4°×4°, and blocked ones. Combination of such FOVs can be used to estimate the in-orbit X-ray and particle background components. The energy resolution of ME is ~3 keV at 17.8 keV (FWHM) and the time resolution is 255 μs. In this paper, we introduce the design and performance of ME. Copyright © 2019, The Authors. All rights reserved.

关键词： Application specific integrated circuits

来源：评论

学校读者我要写书评

暂无评论

Formation of a Magnetic Flux Rope in the Early Emergence Phase of NOAA Active Region 12673

arXiv

引用

arXiv 2019年

作者： Liu, Lijuan Cheng, Xin Wang, Yuming Zhou, Zhenjun School of Atmospheric Sciences Sun Yat-sen University Zhuhai Guangdong519082 China CAS center for Excellence in Comparative Planetology China School of Astronomy and Space Science Nanjing University Nanjing210023 China Max Planck Institute for Solar System Research Gottingen37077 Germany CAS Key Laboratory of Geospace Environment Department of Geophysics and Planetary Sciences University of Science and Technology of China Hefei Anhui230026 China

In this work, we investigate the formation of a magnetic flux rope (MFR) above the central polarity inversion line (PIL) of NOAA Active Region 12673 during its early emergence phase. Through analyzing the photospheric vector magnetic field, extreme ultraviolet (EUV) and ultraviolet (UV) images, extrapolated three-dimensional (3D) non-linear force-free fields (NLFFFs), as well as the photospheric motions, we find that with the successive emergence of different bipoles in the central region, the conjugate polarities separate, resulting in collision between the non-conjugated opposite polarities. Nearly-potential loops appear above the PIL at first, then get sheared and merge at the collision locations as evidenced by the appearance of a continuous EUV sigmoid on 2017 September 4, which also indicates the formation of an MFR. The 3D NLFFFs further reveal the gradual buildup of the MFR, accompanied by the appearance of two elongated bald patches (BPs) at the collision locations and a very low-lying hyperbolic flux tube configuration between the BPs. The final MFR has relatively steady axial flux and average twist number of around 2.1 × 1020 Mx and -1.5, respective. Shearing motions are found developing near the BPs when the collision occurs, with flux cancellation and UV brightenings being observed simultaneously, indicating the development of a process named as "collisional shearing" (firstly identified by Chintzoglou et al. 2019). The results clearly show that the MFR is formed by "collisional shearing", i.e., through shearing and flux cancellation driven by the collision between non-conjugated opposite polarities during their emergence. Copyright © 2019, The Authors. All rights reserved.

关键词： Shearing

来源：评论

学校读者我要写书评

暂无评论

The Effect of Relative Humidity on Eddy Covariance Latent Heat Flux Measurements and its Implication for Partitioning into Transpiration and Evaporation

SSRN

引用

SSRN 2022年

作者： Zhang, Weijie Jung, Martin Migliavacca, Mirco Poyatos, Rafael Miralles, Diego El-Madany, Tarek S. Galvagno, Marta Carrara, Arnaud Arriga, Nicola Ibrom, Andreas Mammarella, Ivan Papale, Dario Cleverly, Jamie Liddell, Michael J. Wohlfahrt, Georg Markwitz, Christian Mauder, Matthias Paul-Limoges, Eugenie Schmidt, Marius Wolf, Sebastian Brümmer, Christian Arain, M. Altaf Fares, Silvano Kato, Tomomichi Ardö, Jonas Oechel, Walter Hanson, Chad Korkiakoski, Mika Biraud, Sébastien Steinbrecher, Rainer Billesbach, Dave Montagnani, Leonardo Woodgate, William Shao, Changliang Carvalhais, Nuno Reichstein, Markus Nelson, Jacob A. Department of Biogeochemical Integration Max Planck Institute for Biogeochemistry Jena Germany Faculty of Bioscience Engineering Ghent University Ghent Belgium Italy CREAF Cerdanyola del Vallès Spain Universitat Autònoma de Barcelona Cerdanyola del Vallès Spain Climate Change Unit Environmental Protection Agency of Aosta Valley Aosta Italy Fundación Centro de Estudios Ambientales del Mediterráneo Valencia Paterna46980 Spain Technical University of Denmark Dept. of Environment and Resource Management Kgs. Lyngby Denmark Faculty of Science University of Helsinki P.O. Box 68 Helsinki00014 Finland University of Tuscia - DIBAF Viterbo01100 Italy IAFES Viterbo01100 Italy College of Science and Engineering James Cook University CairnsQLD4878 Australia Department of Ecology University of Innsbruck Innsbruck Austria Bioclimatology University of Göttingen Göttingen Germany Technische Universität Dresden Faculty of Environmental Sciences Dresden Germany Department of Geography University of Zurich Zurich8057 Switzerland Agrosphere Institute IBG-3 Forschungszentrum Jülich GmbH Jülich52425 Germany Department of Environmental Systems Science ETH Zurich Zurich8092 Switzerland Thünen Institute of Climate-Smart Agriculture Braunschweig Germany School of Earth Environment and Society McMaster University HamiltonON Canada National Research Council of Italy Institute of Bioeconomy Rome Italy Research Faculty of Agriculture Hokkaido University Sapporo Japan Department of Physical Geography and Ecosystem Science Lund University Sweden Global Change Research Group San Diego State University San DiegoCA United States Department of Geography University of Exeter Exeter United Kingdom Department of Forests Ecosystems and Society College of Forestry Oregon State University CorvallisOR United States Climate Sciences Department Lawrence Berkeley National Laboratory BerkeleyCA United States Garmisch-Partenkirchen Germany University of Nebraska

While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the method is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. The influence of these errors for different types of EC systems (e.g. open- or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of ET from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that high RH errors were most apparent during hours when RH was approximately 70% or higher. This underestimation was predominantly observed at sites using closed-path EC systems, with ET underestimations estimated at 58% when RH was higher than 90%. To assess the potential impact of high RH on ET and EC-based transpiration (T) estimates, ET was corrected using a machine learning based empirical approach and then partitioned into T and E using two different data-driven methods. Results showed opposite (increasing vs decreasing T-to-ET ratios, T/ET) responses owing to the contrasting ways the two methods model WUE. Analysis of T estimates based on three different ET correction approaches showed no clear improvement in correlation with independent sap flow based T. Overall, our results demonstrate the existence of high RH-related bias in water fluxes in the FLUXNET2015 dataset and suggest that the underestimation of ET is a significant source of uncertainty that must be reckoned with when estimating ecosystem T/ET and WUE. This work further demonstrates the need for high-quality, independent ecosystem water flux measurements to understand the uncertainties in EC-based ET and T estimates. © 2022, The Authors. All rights reserved.

关键词： Evapotranspiration

来源：评论

学校读者我要写书评

暂无评论

On the stability of nonlinear time-varying spacecraft control systems 68

On the stability of nonlinear time-varying spacecraft contro...

引用

68th International Astronautical Congress: Unlocking Imagination, Fostering Innovation and Strengthening Security, IAC 2017

作者： Xie, Yongchun Chen, Zhihua Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing100094 China Tianjin Key Laboratory of Microgravity and Hypogravity Environment Simulation Technology Tianjin330452 China

ISBN: (纸本)9781510855373

Stability is crucial for spacecraft control system. For rigid-body satellites or rigid-body satellites with flexible appendages, the closed-loop control systems are linear time-invariant (LTI) systems when linear controller, such as PID controllers are used. The stability of such kind of systems is usually analyzed by the Nyquist criterion. And the gain margin and phase margin of the control systems can be obtained. But for spacecraft with the consumption of liquid propellants, the Nyquist method is no longer suitable for stability analysis, especially when nonlinear controllers are used. Though Lyapunov stability analysis method can be used for time-varying linear or nonlinear systems, it cannot provide the stability margin that is widely used in engineering, thus limiting its practical applications. In order to solve this problem, a new framework for stability analysis of nonlinear time-varying systems based on computer simulation, which is suitable for engineering applications, is discussed in this paper. And some preliminary theoretical results are introduced. © 2017 International Astronautical Federation IAF. All rights reserved.

关键词： Closed loop control systems

来源：评论

学校读者我要写书评

暂无评论

URBAN FUNCTIONAL REGIONS DISCOVERING BASED ON DEEP LEARNING

URBAN FUNCTIONAL REGIONS DISCOVERING BASED ON DEEP LEARNING

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Fan Mou Rui Kong Kai Li Zezhong Zheng Jun Xia Yong He Mingcang Zhu Guoqing Zhou Hongsheng Zhang Zhigang Liu Ankai Hou Ling Jiang Shengli Wang Jiang Li School of Resources and Environment University of Electronic Science and Technology of China Chengdu PRC State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan University Wuhan PRC Sichuan Research Institute for Eco-system Restoration & Geo-disaster Prevention Chengdu PRC Department of Natural Resources of Sichuan Province Chengdu PRC Guangxi Key Laboratory for Spatial Information and Geomatics Guilin University of Technology Guilin PRC Institute of Space and Earth Information Science The Chinese University of Hong Kong Shatin Hong Kong State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences Beijing PRC Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

In recent years, the big data industry chain has become more mature. Analyzing and managing cities by utilizing various big data in cities has become a hot research topic. Urban functional regions discovering is one of the important applications. The mainstream in urban functional regions discovering are probabilistic topic models, such as latent Dirichlet allocation (LDA) based topic model, which seeing the regions as documents and their functions are their topics. These methods require feature engineering by hand, which will construct features of limited expressiveness. To overcome these methods' shortcomings, we introduced a deep learning topic model called document neural autoregressive distribution estimation (DocNADE) into urban functional regions mining. And we did an experiment to test its effect. The experimental result shows that this DocNADE framework has achieved a considerable result in urban function inference compared with Dirichlet Multinomial Regression (DMR) based topic model which is a state of the art of urban functional regions discovering.

关键词： Biological system modeling Deep learning Probabilistic logic Roads Urban areas Laboratories Data mining

来源：评论

学校读者我要写书评

暂无评论

Finite-Time Stability for Fractional-Order Bidirectional Associative Memory Neural Networks with Time Delays

引用

Communications in Theoretical Physics 2017年第2期67卷 137-142页

作者： Chang-Jin Xu Guizhou Key Laboratory of Economics System Simulation Guizhou University of Finance and Economics Guiyang 550004 China School of Mathematics and Statistics Henan University of Science and Technology Luoyang 471023 China School of Mathematics and Statistics Guizhou University of Finance and Economics Guiyang 550004 China

This paper is concerned with fractional-order bidirectional associative memory(BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag–Leffler functions, some sufficient conditions which ensure the finite-time stability of fractional-order bidirectional associative memory neural networks with time delays are obtained. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results.

关键词： BAM neural networks finite-time stability time delay Gronwall inequality

来源：评论

学校读者我要写书评

暂无评论

Global fire season severity analysis and forecasting

arXiv

引用

arXiv 2019年

作者： Ferreira, Leonardo N. Vega-Oliveros, Didier A. Zhao, Liang Cardoso, Manoel F. Macau, Elbert E.N. Associated Laboratory for Computing and Applied Mathematics National Institute for Space Research São José Dos Campos - SP Brazil School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Department of Computing and Mathematics University of São Paulo Ribeirão Preto - SP Brazil Center for Earth System Science National Institute for Space Research Cachoeira Paulista - SP Brazil Institute of Science and Technology Federal University of São Paulo São José Dos Campos - SP Brazil

Fire activity has a huge impact on human lives. Different models have been proposed to predict fire activity, which can be classified into global and regional ones. Global fire models focus on longer timescale simulations and can be very complex. Regional fire models concentrate on seasonal forecasting but usually require inputs that are not available in many places. Motivated by the possibility of having a simple, fast, and general model, we propose a seasonal fire prediction methodology based on time series forecasting methods. It consists of dividing the studied area into grid cells and extracting time series of fire counts to fit the forecasting models. We apply these models to estimate the fire season severity (FSS) from each cell, here defined as the sum of the fire counts detected in a season. Experimental results using a global fire detection data set show that the proposed approach can predict FSS with a relatively low error in many regions. The proposed approach is reasonably fast and can be applied on a global scale. Copyright © 2019, The Authors. All rights reserved.

关键词： Climate change

来源：评论

学校读者我要写书评

暂无评论

The Comparison of Different Visual Features for Visual Odometry

The Comparison of Different Visual Features for Visual Odome...

引用

IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)

作者： Yuehan Jiang Qing Wang Chaoyang Dong Min Zhou Kewei Zhong School of Automation Science and Electrical Engineering Beihang University Beijing People’s Republic of China School of Aeronautic Science and Engineering Beihang University Beijing People’s Republic of China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing People’s Republic of China Shanghai Aerospace Control Technology Institute Shanghai People’s Republic of China

ISBN: (数字)9781538611715

ISBN: (纸本)9781538611722

For robots to work effectively, the availability of a map with detailed information surrounding the workspace is an important requirement for indoor and outdoor tasks. This is usually achieved with using visual odometry techniques with feature-based methods. In this paper, we compare the performance of three different feature extraction methods: Scale Invariant Feature Transform (SIFT), Speed Up Robust Features (SURF) and Oriented FAST Rotated BRIEF (ORB). This paper presents experimental results on standard evaluation datasets and all experiments use measurement of the number of image correspondences as well as the ratio of good matched for the evaluation purpose. The results of experiments demonstrate that the performances of three methods in processing time, matching capability and accuracy. SIFT presents its stability in most scenarios although it is very slow. SURF is faster than SIFT and outperform SIFT on some scenarios. ORB is the most efficient feature and shows strong performance.

关键词： Feature extraction Detectors Robustness Visualization Transform coding Real-time systems Lighting

来源：评论

学校读者我要写书评

暂无评论

Association of PM2.5 Reduction with Improved Kidney Function:A Nationwide Quasiexperiment among Chinese Adults

健康数据科学（英文）

引用

健康数据科学（英文） 2022年第3期 25-33页

作者： Yiqun Han Tao Xue Frank J.Kelly Yixuan Zheng Yao Yao Jiajianghui Li Jiwei Li Chun Fan Pengfei Li Tong Zhu Environmental Research Group MRC Centre for Environment and HealthImperial College LondonLondonUK BIC-ESAT and SKL-ESPC College of Environmental Sciences and EngineeringCenter for Environment and HealthPeking UniversityBeijing 100871China Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijingChina Environmental Research Group MRC Centre for Environment and HealthImperial College LondonLondonUK Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental Planning100012 BeijingChina China Center for Health Development Studies Peking UniversityBeijingChina College of Computer Science and Technology Zhejiang UniversityHangzhouChina Computer Center Peking University and Peng Cheng LaboratoryChina Advanced Institute of Information Technology Peking UniversityChina BIC-ESAT and SKL-ESPC College of Environmental Sciences and EngineeringCenter for Environment and HealthPeking UniversityBeijing 100871China

*** evidence from human studies has revealed the adverse impact of ambient fine particles(PM2.5)on health outcomes related to metabolic disorders and distant *** exposure to ambient PM2.5 leads to kidney impairment remains *** rapid air quality improvement driven by the clean air actions in China since 2013 provides an opportunity for a quasiexperiment to investigate the beneficial effect of PM2.5 reduction on kidney *** on two repeated nationwide surveys of the same population of 5115 adults in 2011 and 2015,we conducted a difference-in-difference *** in long-term exposure to ambient PM2.5 were associated with changes in kidney function biomarkers,including estimated glomerular filtration rate by serum creatinine(GFRscr)or cystatin C(GFRcys),blood urea nitrogen(BUN),and uric acid(UA).*** a 10μg/m3 reduction in PM2.5,a significant improvement was observed for multiple kidney functional biomarkers,including GFRscr,BUN and UA,with a change of 0.42(95％confidence interval[CI]:0.06,0.78)mL/min/1.73m2,-0.38(-0.64,-0.12)mg/dL,and-0.06(-0.12,-0.00)mg/dL,respectively.A lower socioeconomic status,indicated by rural residence or low educational level,enhanced the adverse effect of PM2.5 on kidney *** results support a significant nephrotoxicity of PM2.5 based on multiple serum biomarkers and indicate a beneficial effect of improved air quality on kidney function.

关键词： association chinese improved function kidney with adults among nationwide quasiexperiment

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：