检索结果-内蒙古大学图书馆

Genome-wide association study of long COVID

Nature Genetics 2025年 1-16页

作者： Lammi, Vilma Nakanishi, Tomoko Jones, Samuel E. Andrews, Shea J. Karjalainen, Juha Cortés, Beatriz O’Brien, Heath E. Ochoa-Guzman, Ana Fulton-Howard, Brian E. Broberg, Martin Haapaniemi, Hele H. Kanai, Masahiro Pirinen, Matti Schmidt, Axel Mitchell, Ruth E. Mousas, Abdou Mangino, Massimo Huerta-Chagoya, Alicia Sinnott-Armstrong, Nasa Cirulli, Elizabeth T. Vaudel, Marc Kwong, Alex S. F. Maiti, Amit K. Marttila, Minttu M. Posner, Daniel C. Rodriguez, Alexis A. Batini, Chiara Minnai, Francesca Dearman, Anna R. Warmerdam, C. A. Robert Sequeros, Celia B. Winkler, Thomas W. Jordan, Daniel M. Rešcenko, Raimonds Miano, Lorenzo Lane, Jacqueline M. Chung, Ryan K. Guillen-Guio, Beatriz Leavy, Olivia C. Carvajal-Silva, Laura Aguilar-Valdés, Kevin Frangione, Erika Guare, Lindsay Vergasova, Ekaterina Marouli, Eirini Striano, Pasquale Zainulabid, Ummu Afeera Kumar, Ashutosh Ahmad, Hajar Fauzan Edahiro, Ryuya Azekawa, Shuhei Maj, Carlo Pensel, Max C. Miller, Abigail Nöthen, Markus M. Behzad, Pari Schultz, Sonja Heggemann, Julia Balla, Daniella Morrison, David R. Mooser, Vincent Perley, Danielle Ragoussis, Jiannis Rousseau, Simon Shi, Fangyi Lathrop, G. Mark Yanishevsky, Solomia Laurent, Laetitia Auld, Daniel Bertrand, Mylene Boisclair, Ariane Bourque, Guillaume Bujold, David Durand, Madeleine Adra, Darin St-Cyr, Janick Niemi, Mari E. K. Iyengar, Sudha K. Cai, Tianxi Cho, Kelly Sarvadhavabhatla, Sannidhi Donaire, Maria Sophia Valenzuela-Jorquera, Héctor Lamoza, Eduardo Arévalo, Tamara V. Retamales-Ortega, Rocío Sanhueza, Sergio Selman, Carolina S. Silva, Andrea X. Alarcon, Teresa A. Martínez, Matías F. Quiroga, Romina Zuñiga-Pacheco, Paula Zapata-Contreras, Daniela Yáñez, Cristian E. Quiñones, Luis A. Tobar-Calfucoy, Eduardo A. Monardes-Ramírez, Virginia A. Signore, Iskra A. Guajardo, Lissette G. Figueroa, Alvaro Oróstica, Karen Y. Muñoz, Christian A. Fuentes-Guajardo, Macarena Bocchieri, Pamela Cabrera, Camilo Echeverria, Cesar A. Cerpa, Leslie C. Donoso, Gerardo Gutiérrez-Richards, Scarlett Nova-Lamperti, Estefania Saez Hidalgo Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Department of Human Genetics McGill University Montreal QC Canada Centre for Clinical Epidemiology Department of Medicine Lady Davis Institute Jewish General Hospital McGill University Montreal QC Canada Kyoto-McGill International Collaborative Program in Genomic Medicine Graduate School of Medicine Kyoto University Kyoto Japan Department of Genome Informatics Graduate School of Medicine the University of Tokyo Tokyo Japan Research Fellow Japan Society for the Promotion of Science Tokyo Japan Department of Psychiatry and Behavioral Sciences University of California San Francisco San Francisco CA United States Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA United States Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA United States Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA United States Genomes for Life-GCAT Lab CORE Program Germans Trias i Pujol Research Institute (IGTP) Badalona Spain Grup de REcerca en Impacte de les Malalties Cròniques i les seves Trajectòries (GRIMTra) Barcelona Spain Sano Genetics Limited London United Kingdom Unidad de Biología Molecular y Medicina Genómica Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán Mexico City Mexico Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York City NY United States Broad Institute Cambridge MA United States Analytical and Translational Genetics Unit Massachusetts General Hospital Harvard Medical School Boston MA United States Department of Mathematics and Statistics University of Helsinki Helsinki Finland Department of Public Health University of Helsinki Helsinki Finland Institute of Human Genetics University of Bonn School of Medicine and University Hospital Bonn Bonn Germany MRC Integrat

Infections can lead to persistent symptoms and diseases such as shingles after varicella zoster or rheumatic fever after streptococcal infections. Similarly, severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection can result in long coronavirus disease (COVID), typically manifesting as fatigue, pulmonary symptoms and cognitive dysfunction. The biological mechanisms behind long COVID remain unclear. We performed a genome-wide association study for long COVID including up to 6,450 long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We discovered an association of FOXP4 with long COVID, independent of its previously identified association with severe COVID-19. The signal was replicated in 9,500 long COVID cases and 798,835 population controls. Given the transcription factor FOXP4’s role in lung physiology and pathology, our findings highlight the importance of lung function in the pathophysiology of long COVID. © The Author(s) 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analysis and computation of some tumor growth models with nutrient: From cell density models to free boundary dynamics

arXiv

引用

arXiv 2018年

作者： Liu, Jian-Guo Tang, Min Wang, Li Zhou, Zhennan Department of Mathematics Department of Physics Duke University School of Mathematics and Institute of Natural Sciences MOE-LSC Shanghai JiaoTong University Department of Mathematics Computational and Data-Enabled Science and Engineering Program State University of New York Buffalo United States Beijing International Center for Mathematical Research Peking University

In this paper, we study the tumor growth equation along with various models for the nutrient component, including the in vitro model and the in vivo model. At the cell density level, the spatial availability of the tumor density n is governed by the Darcy law via the pressure p\(n\) = nγ. For finite γ, we prove some a priori estimates of the tumor growth model, such as boundedness of the nutrient density, and non-negativity and growth estimate of the tumor density. As γ → ∞, the cell density models formally converge to Hele-Shaw flow models, which determine the free boundary dynamics of the tumor tissue in the incompressible limit. We derive several analytical solutions to the Hele-Shaw flow models, which serve as benchmark solutions to the geometric motion of tumor front propagation. Finally, we apply a conservative and positivity preserving numerical scheme to the cell density models, with numerical results verifying the link between cell density models and the free boundary dynamical *** Codes 35K55, 35B25, 76D27, 92C50 Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

来源：评论

学校读者我要写书评

暂无评论

Blood pressure trajectories from early life and their association with cognitive function changes in midlife

引用

Alzheimer's & Dementia 2021年第S10期17卷

作者： Ileana De Anda-Duran Camilo Fernandez-Alonso Owen T Carmichael Rhoda Au Lydia Bazzano Vijaya B Kolachalama Tulane School of Public Health and Tropical Medicine New Orleans LA USA Tulane University New Orleans LA USA Pennington Biomedical Research Center Baton Rouge LA USA Boston University Alzheimer’s Disease Center Boston University Boston MA USA The Framingham Heart Study Boston University School of Medicine Boston University School of Public Health Boston MA USA Boston University Schools of Medicine & Public Health Boston MA USA Hariri Institute for Computing and Computational Science & Engineering Boston University Boston MA USA College of Arts & Sciences Boston University Boston MA USA Boston University School of Medicine Boston MA USA Faculty of Computing & Data Sciences Boston University Boston MA USA Whitaker Cardiovascular Institute Boston University School of Medicine Boston MA USA

Background Hypertension (HTN) is a well-established risk factor for cognitive impairment and dementia. HTN-induced vascular endothelium and smooth muscle damage have been described as pivotal components of the pathophysiological cascade over the life-course. While the impact on cognitive function (CF) changes has been studied from midlife- to old age, the impact from childhood to middle age exposure remains poorly understood. We aimed to explore this relationship in a community-based cohort of middle-age adults. Methods The analysis included a total of 342 adult participants (67.3% Woman, 38.9% African American) from the Bogalusa Heart Study, with CF assessments at two time points, baseline (age 48.8 ± 4.9 years) and follow-up (age 51.7 ± 5.2 years), and at least 3 observations of BP since childhood. CF change was assessed by computing the difference of the two timepoints standardized global cognitive score (GCS) obtained from a battery of tests covering major neuropsychological domains. Systolic BP (SBP) trajectories were created using latent class trajectory modeling. Mixed linear models with unstructured covariance were used to determine the association between SBP trajectories and CF changes in midlife. Results Mean CF assessment follow-up was 2.9 ± 0.6 years, and mean follow-up for BP and other traditional cardiovascular (CV) risk factors was 41.8 ± 3.4 years. Three distinct trajectory classes of SBP were identified: increasing to plateau (n=226 [66.1%]), moderate- (n=54 [15.8%]) and high- (n=62 [18.1%]) increasing (see Figure 1). With the increasing to plateau SBP trajectory as reference, and after adjustment for modifiable dementia risk factors and traditional CV risk factors, the high-increasing SBP trajectory was associated with greater decrease in GCS (β= -1.22 [95%CI -2.39, -0.07]; p =0.038). The moderate-increasing SBP trajectory showed no statistically significant association with GCS change (β= -1.00 [95%CI -2.23, - 0.22]; p =0.109). (see Table 1) Conc

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients

arXiv

引用

arXiv 2021年

作者： Baheti, Bhakti Chakrabarty, Satrajit Akbari, Hamed Bilello, Michel Wiestler, Benedikt Schwarting, Julian Calabrese, Evan Rudie, Jeffrey Abidi, Syed Mousa, Mina Villanueva-Meyer, Javier Fields, Brandon K.K. Kofler, Florian Shinohara, Russell Takeshi Iglesias, Juan Eugenio Mok, Tony C.W. Chung, Albert C.S. Wodzinski, Marek Jurgas, Artur Marini, Niccolò Atzori, Manfredo Müller, Henning Grosbröhmer, Christoph Siebert, Hanna Hansen, Lasse Heinrich, Mattias P. Canalini, Luca Klein, Jan Gerken, Annika Heldmann, Stefan Hering, Alessa Hahn, Horst K. Meng, Mingyuan Bi, Lei Feng, Dagan Kim, Jinman Zeineldinal, Ramy A. Karar, Mohamed E. Mathis-Ullrich, Franziska Burgert, Oliver Abderezaei, Javid Pionteck, Aymeric Chopra, Agamdeep Kurt, Mehmet Yan, Kewei Yan, Yonghong Tang, Zhe Ma, Jianqiang Nasser, Sahar Almahfouz Kurian, Nikhil Cherian Meena, Mohit Shamsi, Saqib Sethi, Amit Tustison, Nicholas J. Avants, Brian B. Cook, Philip Gee, James C. Tian, Lin Greer, Hastings Niethammer, Marc Hoopesar, Andrew Hoffmannas, Malte Dalcaar, Adrian V. Christodoulidis, Stergios Estiene, Théo Vakalopoulou, Maria Paragios, Nikos Marcus, Daniel S. Davatzikos, Christos Sotiras, Aristeidis Menze, Bjoern Bakas, Spyridon Waldmannstetter, Diana Division of Computational Pathology Department of Pathology and Laboratory Medicine Indiana University School of Medicine IndianapolisIN United States Department of Electrical and Systems Engineering Washington University in St. Louis St. LouisMO United States GE HealthCare San RamonCA United States University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Mallinckrodt Institute of Radiology Washington University School of Medicine St. LouisMO United States Institute for Informatics Data Science & Biostatistics Washington University School of Medicine St. LouisMO United States Department of Bioengineering Santa Clara University Santa ClaraCA United States Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Computer Science TUM School of Computation Information and Technology Technical University of Munich Munich Germany Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Munich Germany Department of Nuclear Medicine University Hospital Regensburg Regensburg Germany University Hospital Regensburg Regensburg Germany Department of Radiology & Biomedical Imaging University of California San FranciscoCA United States Department of Radiology Duke University Medical Center DurhamNC United States Department of Radiology University of California San DiegoCA United States Helmholtz AI Helmholtz Munich Neuherberg Germany Penn Statistics in Imaging and Visualization Center Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Philadelphia United States Massachusetts General Hospital Harvard Medical School United States Centre for Medical Imaging Computing University College London United Kingdom The Hong Kong University of Science and Technology Hong Kong University of Applied Sciences West

Registration of longitudinal brain Magnetic Resonance Imaging (MRI) scans containing pathologies is challenging due to dramatic changes in tissue appearance. Although there has been considerable progress in developing general-purpose medical image registration techniques, they have not yet attained the requisite precision and reliability for this task, highlighting its inherent complexity. Here we describe the Brain Tumor Sequence Registration (BraTS-Reg) challenge, as the first public benchmark environment for deformable registration algorithms focusing on estimating correspondences between pre-operative and follow-up scans of the same patient diagnosed with a diffuse brain glioma. The challenge was conducted in conjunction with both the IEEE International Symposium on Biomedical Imaging (ISBI) 2022 and the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2022. The BraTS-Reg data comprise de-identified multi-institutional multi-parametric MRI (mpMRI) scans, curated for size and resolution according to a canonical anatomical template, and divided into training, validation, and testing sets. Clinical experts annotated ground truth (GT) landmark points of anatomical locations distinct across the temporal domain. The training data with their GT annotations, were publicly released to enable the development of registration algorithms. The validation data, without their GT annotations, were also released to allow for algorithmic evaluation prior to the testing phase, which only allowed submission of containerized algorithms for evaluation on hidden hold-out testing data. Quantitative evaluation and ranking was based on the Median Euclidean Error (MEE), Robustness, and the determinant of the Jacobian of the displacement field. The top-ranked methodologies yielded similar performance across all evaluation metrics and shared several methodological commonalities, including pre-alignment, deep neural networks, inverse consistency

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

SN 2022acko: the First Early Far-Ultraviolet Spectra of a Type IIP Supernova

arXiv

引用

arXiv 2023年

作者： Bostroem, K. Azalee Dessart, Luc Hillier, D. John Lundquist, Michael Andrews, Jennifer E. Sand, David J. Dong, Yize Valenti, Stefano Haislip, Joshua Hoang, Emily T. Hosseinzadeh, Griffin Janzen, Daryl Jencson, Jacob E. Jha, Saurabh W. Kouprianov, Vladimir Pearson, Jeniveve Meza Retamal, Nicolas E. Reichart, Daniel E. Shrestha, Manisha Ashall, Christopher Baron, E. Brown, Peter J. DerKacy, James M. Farah, Joseph Galbany, Lluís Hernández, J.I. González Green, Elizabeth Hoeflich, Peter Howell, D. Andrew Kwok, Lindsey A. McCully, Curtis Müller-Bravo, Tomás E. Newsome, Megan Gonzalez, Estefania Padilla Pellegrino, Craig Rho, Jeonghee Rowe, Micalyn Schwab, Michaela Shahbandeh, Melissa Smith, Nathan Strader, Jay Terreran, Giacomo Van Dyk, Schuyler D. Wyatt, Samuel Steward Observatory University of Arizona 933 North Cherry Avenue TucsonAZ85721-0065 United States Institut d’Astrophysique de Paris CNRS-Sorbonne Université 98 bis boulevard Arago Paris75014 France University of Pittsburgh 3941 O’Hara Street PittsburghPA15260 United States W. M. Keck Observatory 65-1120 Māmalahoa Highway KamuelaHI96743-8431 United States Gemini Observatory 670 North A‘ohoku Place HiloHI96720-2700 United States Department of Physics and Astronomy University of California Davis 1 Shields Avenue DavisCA95616-5270 United States Department of Physics and Astronomy University of North Carolina 120 East Cameron Avenue Chapel HillNC27599 United States Department of Physics and Engineering Physics University of Saskatchewan 116 Science Place SaskatoonSKS7N 5E2 Canada Department of Physics and Astronomy The Johns Hopkins University 3400 North Charles Street BaltimoreMD21218 United States Department of Physics and Astronomy Rutgers the State University of New Jersey 136 Frelinghuysen Road PiscatawayNJ08854-8019 United States Department of Physics Virginia Tech BlacksburgVA24061 United States Planetary Science Institute 1700 East Fort Lowell Suite 106 TucsonAZ85719-2395 United States Hamburger Sternwarte Gojenbergsweg 112 HamburgD-21029 Germany Homer L. Dodge Department of Physics and Astronomy University of Oklahoma 440 W. Brooks Rm 100 NormanOK73019-2061 United States Department of Physics and Astronomy Texas A&M University 4242 TAMU College StationTX77843 United States Las Cumbres Observatory 6740 Cortona Drive Suite 102 GoletaCA93117-5575 United States Department of Physics University of California Santa BarbaraCA93106-9530 United States Campus UAB Carrer de Can Magrans s/n BarcelonaE-08193 Spain Institut d’Estudis Espacials de Catalunya Gran Capità 2-4 Edifici Nexus Desp. 201 BarcelonaE-08034 Spain Instituto de Astrofísica de Canarias La Laguna TenerifeE-38205 Spain Universidad de La Lag

We present five far- and near-ultraviolet spectra of the Type II plateau supernova, SN 2022acko, obtained 5, 6, 7, 19, and 21 days after explosion, all observed with the Hubble Space Telescope/Space Telescope Imaging Spectrograph. The first three epochs are earlier than any Type II plateau supernova has been observed in the far-ultraviolet revealing unprecedented characteristics. These three spectra are dominated by strong lines, primarily from metals, which contrasts with the featureless early optical spectra. The flux decreases over the initial time series as the ejecta cool and line-blanketing takes effect. We model this unique dataset with the non-local thermodynamic equilibrium radiation transport code CMFGEN, finding a good match to the explosion of a low-mass red supergiant with energy Ekin = 6 × 1050 erg. With these models we identify, for the first time, the ions that dominate the early ultraviolet spectra. We present optical photometry and spectroscopy, showing that SN 2022acko has a peak absolute magnitude of V = −15.4 mag and plateau length of ∼ 115d. The spectra closely resemble those of SN 2005cs and SN 2012A. Using the combined optical and ultraviolet spectra, we report the fraction of flux as a function of bluest wavelength on days 5, 7, and 19. We create a spectral time-series of Type II supernovae in the ultraviolet, demonstrating the rapid decline of flux over the first few weeks of evolution. Future observations of Type II supernovae are required to map out the landscape of exploding red supergiants, with and without circumstellar material, which is best revealed in high-quality ultraviolet spectra. © 2023, CC BY.

关键词： Supernovae

来源：评论

学校读者我要写书评

暂无评论

The first nova eruption in a novalike variable: YZ Ret as seen in X-rays and γ-rays

arXiv

引用

arXiv 2021年

作者： Sokolovsky, Kirill V. Li, Kwan-Lok de Oliveira, Raimundo Lopes Ness, Jan-Uwe Mukai, Koji Chomiuk, Laura Aydi, Elias Steinberg, Elad Vurm, Indrek Metzger, Brian D. Babul, Aliya-Nur Kawash, Adam Linford, Justin D. Nelson, Thomas Page, Kim L. Rupen, Michael P. Sokoloski, Jennifer L. Strader, Jay Kilkenny, David Center for Data Intensive and Time Domain Astronomy Department of Physics and Astronomy Michigan State University 567 Wilson Rd East LansingMI48824 United States Sternberg Astronomical Institute Moscow State University Universitetskii pr. 13 Moscow119992 Russia Department of Physics National Cheng Kung University Tainan70101 Taiwan Departamento de Astronomia Instituto de Astronomia Geofísica e Ciências Atmosféricas Universidade de São Paulo Cidade Universitária R. do Matão 1226 SP São Paulo05508-090 Brazil Departamento de Física Universidade Federal de Sergipe Av. Marechal Rondon S/N SE São Cristóvão49100-000 Brazil Observatório Nacional Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil European Space Astronomy Centre Camino Bajo del Castillo s/n Urb. Villafranca del Castillo Villanueva de la Cañada MadridE-28692 Spain CRESST and X-ray Astrophysics Laboratory NASA/GSFC GreenbeltMD20771 United States Racah Institute of Physics The Hebrew University Jerusalem9190401 Israel Tartu Observatory University of Tartu Tõravere Tartumaa 61602 Estonia Department of Physics Columbia Astrophysics Laboratory Columbia University New YorkNY10027 United States National Radio Astronomy Observatory Domenici Science Operations Center 1003 Lopezville Road SocorroNM87801 United States Department of Physics and Astronomy University of Pittsburgh PittsburghPA15260 United States School of Physics and Astronomy University of Leicester University Road LeicesterLE1 7RH United Kingdom National Research Council Herzberg Astronomy and Astrophysics 717 White Lake Rd PO Box 248 PentictonBCV2A 6J9 Canada Department of Physics & Astronomy University of the Western Cape Private Bag X17 Bellville7535 South Africa Center for Computational Astrophysics Flatiron Institute 162 5th Ave New YorkNY10010 United States

Peaking at 3.7 mag on 2020 July 11, YZ Ret was the second-brightest nova of the decade. The nova’s moderate proximity (2.7 kpc, from Gaia) provided an opportunity to explore its multi-wavelength properties in great detail. Here we report on YZ Ret as part of a long-term project to identify the physical mechanisms responsible for high-energy emission in classical novae. We use simultaneous Fermi/LAT and NuSTAR observations complemented by XMM-Newton X-ray grating spectroscopy to probe the physical parameters of the shocked ejecta and the nova-hosting white dwarf. The XMM-Newton observations revealed a super-soft X-ray emission which is dominated by emission lines of C v, C vi, N vi, N vii, and O viii rather than a blackbody-like continuum, suggesting CO-composition of the white dwarf in a high-inclination binary system. Fermi/LAT detected YZ Ret for 15 days with the γ-ray spectrum best described by a power law with an exponential cut-off at 1.9 ± 0.6 GeV. In stark contrast with theoretical predictions and in keeping with previous NuSTAR observations of Fermi-detected classical novae (V5855 Sgr and V906 Car), the 3.5-78 keV X-ray emission is found to be two orders of magnitude fainter than the GeV emission. The X-ray emission observed by NuSTAR is consistent with a single-temperature thermal plasma model. We do not detect a non-thermal tail of the GeV emission expected to extend down to the NuSTAR band. NuSTAR observations continue to challenge theories of high-energy emission from shocks in novae. Copyright © 2021, The Authors. All rights reserved.

关键词： X ray scattering

来源：评论

学校读者我要写书评

暂无评论

Erratum for Wang et al., "Clinically Applicable System for Rapidly Predicting Enterococcus faecium Susceptibility to Vancomycin"

引用

Microbiology spectrum 2022年第1期10卷 e0261021页

作者： Hsin-Yao Wang Chia-Ru Chung Chao-Jung Chen Ko-Pei Lu Yi-Ju Tseng Tzu-Hao Chang Min-Hsien Wu Wan-Ting Huang Ting-Wei Lin Tsui-Ping Liu Tzong-Yi Lee Jorng-Tzong Horng Jang-Jih Lu Department of Laboratory Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Ph.D. Program in Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Computer Science and Information Engineering National Central Universitygrid.37589.30 Taoyuan City Taiwan. Graduate Institute of Integrated Medicine China Medical Universitygrid.254145.3 Taichung Taiwan. Proteomics Core Laboratory China Medical Universitygrid.254145.3 Hospital Taichung Taiwan. Graduate Program in Biomedical Information Yuan-Ze University Taoyuan City Taiwan. Department of Information Management Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City Taiwan. Clinical Big Data Research Center Taipei Medical University Hospital Taipei City Taiwan. Graduate Institute of Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Division of Haematology/Oncology Department of Internal Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Biosensor Group Biomedical Engineering Research Center Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Pathology Kaohsiung Chang Gung Memorial Hospitalgrid.413801.f and Chang Gung University College of Medicine Kaohsiung Taiwan. School of Life and Health Sciences The Chinese University of Hong Kong Shenzhen China. Warshel Institute for Computational Biology The Chinese University of Hong Kong Shenzhen China. Department of Bioinformatics and Medical Engineering Asia University Taichung City Taiwan. School of Medicine Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Medical Biotechnology and Laboratory Science Chang Gung Universitygrid.145695.a Taoyuan City Taiwan.

来源：评论

学校读者我要写书评

暂无评论

First-passage and first-hitting times of Lévy flights and Lévy walks

arXiv

引用

arXiv 2019年

作者： Palyulin, Vladimir V. Blackburn, George Lomholt, Michael A. Watkins, Nicholas W. Metzler, Ralf Klages, Rainer Chechkin, Aleksei V. Centre for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Nobelya Ulitsa 3 Moscow121205 Russia Max Planck Institute for the Physics of Complex Systems Nöthnitzer Straße 38 DresdenD-01187 Germany £ Centre for Fusion Space and Astrophysics University of Warwick Coventry United Kingdom MEMPHYS - Centre for Biomembrane Physics Department of Physics Chemistry and Pharmacy University of Southern Denmark Odense M5230 Denmark Institute for Physics & Astronomy University of Potsdam Potsdam-GolmD-14476 Germany Centre for the Analysis of Time Series London School of Economics and Political Sciences London United Kingdom Faculty of Science Technology Engineering and Mathematics Open University Milton Keynes United Kingdom Institut für Theoretische Physik Technische Universität Berlin Hardenbergstraße 36 Berlin10623 Germany Queen Mary University of London School of Mathematical Sciences Mile End Road LondonE1 4NS United Kingdom Akhiezer Institute for Theoretical Physics National Science Centre "Kharkov Institute of Physics and Technology" Kharkov61108 Ukraine

For both Lévy flight and Lévy walk search processes we analyse the full distribution of first-passage and first-hitting (or first-arrival) times. These are, respectively, the times when the particle moves across a point at some given distance from its initial position for the first time, or when it lands at a given point for the first time. For Lévy motions with their propensity for long relocation events and thus the possibility to jump across a given point in space without actually hitting it ("leapovers"), these two definitions lead to significantly different results. We study the first-passage and first-hitting time distributions as functions of the Lévy stable index, highlighting the different behaviour for the cases when the first absolute moment of the jump length distribution is finite or infinite. In particular we examine the limits of short and long times. Our results will find their application in the mathematical modelling of random search processes as well as computer algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Field heterogeneity detection based on the modified FastICA RGB-image processing

引用

Journal of Physics: Conference Series 2018年第1期1117卷

作者： L Mirvakhabova M Pukalchik S Matveev P Tregubova I Oseledets Skoltech Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology 1 Nobel Street Moscow 121205 Russia Marchuk Institute of Numerical Mathematics RAS 8 Gubkin Street 119333 Moscow Russia

In the light of the increasing demand for food production, climate change challenges, and economic pressure, precision farming is becoming an ever-growing market. Nowadays using satellite images for field zoning has become a widely spread technique employed in precision agriculture. Usually satellite images are used to evaluate Normalized Difference Vegetation Index (NDVI) as a common yield assessment. At the same time it is rather a challenging task to designing NDVI maps as compared to ordinary RGB images. We propose a new algorithm for site-specific zoning based on the performance of a well-known and widely used ICA algorithm (FastICA). We analyse high resolution RGB satellite images for 3 arable fields located in Kursk region, Russia, (2017) provided by the Planet Labs service. The main outcomes from this study are (i) the algorithm creates site-specific zoning maps with a relative accuracy of yield distribution maps between 0.78 and 0.89; (ii) the algorithm requires a relatively small dataset – from 8 to 10 RGB images. The obtained results indicate that the algorithm in question can be used not only to identify management zones but also to map the variations in yield within the fields.

关键词：

来源：评论

学校读者我要写书评

暂无评论

End-to-end symmetry preserving inter-atomic potential energy model for finite and extended systems

arXiv

引用

arXiv 2018年

作者： Zhang, Linfeng Han, Jiequn Wang, Han Saidi, Wissam A. Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University United States Institute of Applied Physics and Computational Mathematics China CAEP Software Center for High Performance Numerical Simulation China Department of Mechanical Engineering and Materials Science University of Pittsburgh United States Department of Chemistry and Department of Physics Princeton University United States Princeton Institute for the Science and Technology of Materials Princeton University United States Department of Mathematics Princeton University United States Beijing Institute of Big Data Research China

Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular interest is the inter-atomic potential energy surface (PES). Here we develop Deep Potential - Smooth Edition (DeepPot-SE), an end-to-end machine learning-based PES model, which is able to efficiently represent the PES of a wide variety of systems with the accuracy of ab initio quantum mechanics models. By construction, DeepPot-SE is extensive and continuously differentiable, scales linearly with system size, and preserves all the natural symmetries of the system. Further, we show that DeepPot-SE describes finite and extended systems including organic molecules, metals, semiconductors, and insulators with high fidelity. Copyright © 2018, The Authors. All rights reserved.

关键词： Potential energy

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：