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Optical Imaging technology: A Useful Tool to Identify Remission in Cushing Disease After Surgery (vol 51, pg 120, 2019)

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HORMONE AND METABOLIC research 2019年第2期51卷 E1-E1页

作者： Afshari, Ali Keil, Margaret Lyssikatos, Charalampos Section on Analytical and Functional Biophotonics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH) Bethesda Maryland USA Section on Endocrinology and Genetics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH) Bethesda Maryland USA Section on Endocrinology and Genetics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH) Bethesda Maryland USA Section on Endocrinology and Genetics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH) Bethesda Maryland USA Service of Endocrinology and Nutrition Hospital Universitario Central de Asturias Instituto Universitario de Oncología del Principado de Asturias Universidad de Oviedo Oviedo Spain Section on Analytical and Functional Biophotonics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH) Bethesda Maryland USA Section on Analytical and Functional Biophotonics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH) Bethesda Maryland USA Section on Analytical and Functional Biophotonics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH) Bethesda Maryland USA Section on Signal Processing & Instrumentation Computational Biosciences and Engineering Laboratory Office of Intramural Research (OIR) Center for Information Technology (CIT) National Institutes of Health (NIH) Bethesda Maryland USA Section on Analytical and Functional Biophotonics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH) Bethesda Maryland USA Assistant Professor of Biomedical Engineering Colle

We recently reported the use of optical imaging technology to quantify facial plethora in endogenous Cushing syndrome (CS). In the present study, we studied a larger cohort of patients with Cushing disease (CD) and examined water content fraction as well as blood volume fraction as bio-optic markers for determining the efficacy of this methodology as a predictor of lasting remission after surgery for CS. We imaged 49 patients before and after transsphenoidal surgery (TSS) for Cushing disease (CD); 22 patients were also seen at 3-6 months, and 13 patients 12 months post-operatively. On all patients, we used multi-spectral imaging (MSI) to evaluate hemodynamic distributions as well as water content at a specific area of the face. We found a decrease in blood volume fraction after vs. before surgical treatment in the tested facial area in 37 of the 40 patients, as determined with biochemical markers (p<0.001). All patients that were followed up for up to 12 months showed the same decrease from preoperative values and they remained in remission from CD. We conclude that MSI can be used for the evaluation of remission from CD, at least in the immediate post-operative period and up to one year after surgery. The use of this technology can supplement biochemical and other testing for the evaluation of the various treatment modalities available for patients with CD.

关键词： cushing disease optical imaging technology bio-optic marker facial plethora serum cortisol water content volume

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Author Correction: Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

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Nature genetics 2023年第10期55卷 1778-1779页

作者： Nick Shrine Abril G Izquierdo Jing Chen Richard Packer Robert J Hall Anna L Guyatt Chiara Batini Rebecca J Thompson Chandan Pavuluri Vidhi Malik Brian D Hobbs Matthew Moll Wonji Kim Ruth Tal-Singer Per Bakke Katherine A Fawcett Catherine John Kayesha Coley Noemi Nicole Piga Alfred Pozarickij Kuang Lin Iona Y Millwood Zhengming Chen Liming Li Sara R A Wijnant Lies Lahousse Guy Brusselle Andre G Uitterlinden Ani Manichaikul Elizabeth C Oelsner Stephen S Rich R Graham Barr Shona M Kerr Veronique Vitart Michael R Brown Matthias Wielscher Medea Imboden Ayoung Jeong Traci M Bartz Sina A Gharib Claudia Flexeder Stefan Karrasch Christian Gieger Annette Peters Beate Stubbe Xiaowei Hu Victor E Ortega Deborah A Meyers Eugene R Bleecker Stacey B Gabriel Namrata Gupta Albert Vernon Smith Jian'an Luan Jing-Hua Zhao Ailin F Hansen Arnulf Langhammer Cristen Willer Laxmi Bhatta David Porteous Blair H Smith Archie Campbell Tamar Sofer Jiwon Lee Martha L Daviglus Bing Yu Elise Lim Hanfei Xu George T O'Connor Gaurav Thareja Omar M E Albagha Karsten Suhre Raquel Granell Tariq O Faquih Pieter S Hiemstra Annelies M Slats Benjamin H Mullin Jennie Hui Alan James John Beilby Karina Patasova Pirro Hysi Jukka T Koskela Annah B Wyss Jianping Jin Sinjini Sikdar Mikyeong Lee Sebastian May-Wilson Nicola Pirastu Katherine A Kentistou Peter K Joshi Paul R H J Timmers Alexander T Williams Robert C Free Xueyang Wang John L Morrison Frank D Gilliland Zhanghua Chen Carol A Wang Rachel E Foong Sarah E Harris Adele Taylor Paul Redmond James P Cook Anubha Mahajan Lars Lind Teemu Palviainen Terho Lehtimäki Olli T Raitakari Jaakko Kaprio Taina Rantanen Kirsi H Pietiläinen Simon R Cox Craig E Pennell Graham L Hall W James Gauderman Chris Brightling James F Wilson Tuula Vasankari Tarja Laitinen Veikko Salomaa Dennis O Mook-Kanamori Nicholas J Timpson Eleftheria Zeggini Josée Dupuis Caroline Hayward Ben Brumpton Claudia Langenberg Stefan Weiss Georg Homuth Carsten Oliver Schmidt Nicole Probst-Hensch Marjo-Riitta Jarvelin Alanna C Morrison Ozren Polasek Igor Department of Population Health Sciences University of Leicester Leicester UK. nick.shrine@leicester.ac.uk. Department of Population Health Sciences University of Leicester Leicester UK. Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre University of Nottingham Nottingham UK. Leicester National Institute for Health and Care Research Biomedical Research Centre Glenfield Hospital Leicester UK. Channing Division of Network Medicine Division of Pulmonary and Critical Care Medicine Department of Medicine Brigham and Women's Hospital Boston MA USA. Harvard Medical School Boston MA USA. COPD Foundation Washington DC USA. Department of Clinical Science Unversity of Bergen Bergen Norway. Nuffield Department of Population Health University of Oxford Oxford UK. MRC Population Health Research Unit University of Oxford Oxford UK. Department of Epidemiology and Biostatistics School of Public Health Peking University Health Science Center Beijing China. Department of Respiratory Diseases Ghent Universital Hospital Ghent Belgium. Department of Bioanalysis Faculty of Pharmaceutical Sciences Ghent University Ghent Belgium. Department of Epidemiology Eramus Medical Center Rotterdam The Netherlands. Department of Internal Medicine Eramus Medical Center Rotterdam The Netherlands. Center for Public Health Genomics University of Virginia Charlottesville VA USA. Department of Medicine Columbia University Medical Center New York NY USA. Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Human Genetics Center Department of Epidemiology Human Genetics and Environmental Sciences School of Public Health The University of Texas Health Science Center at Houston Houston TX USA. MRC Centre for Environment and Health Department of Epidemiology and Biostatistics School of Public Health Imperial College London London UK. Department of Epidemiology and Public Health Swiss Tropical

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Correction to: Double Vision Model Using Space-Time Function Control within Silicon Microring System

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Silicon 2020年第12期12卷 3057-3057页

作者： Bunruangses, M. Youplao, P. Amiri, I. S. Pornsuwancharoen, N. Yupapin, P. Department of Computer Engineering Faculty of Industrial Education Rajamangala University of Technology Phra Nakhon Bangkok Thailand Department of Electrical Engineering Faculty of Industry and Technology Rajamangala University of Technology Isan Sakon Nakhon Thailand Division of Materials Science and Engineering Boston University Boston USA Computational Optics Research Group Advanced Institute of Materials Science Ton Duc Thang University Ho Chi Minh City Vietnam Faculty of Applied Sciences Ton Duc Thang University Ho Chi Minh City Vietnam

The original version of this article unfortunately contained a mistake in the “Acknowledgments” section.

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Roadmap on Deep Learning for Microscopy

arXiv

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arXiv 2023年

作者： Volpe, Giovanni Wählby, Carolina Tian, Lei Hecht, Michael Yakimovich, Artur Monakhova, Kristina Waller, Laura Sbalzarini, Ivo F. Metzler, Christopher A. Xie, Mingyang Zhang, Kevin Lenton, Isaac C.D. Rubinsztein-Dunlop, Halina Brunner, Daniel Bai, Bijie Ozcan, Aydogan Midtvedt, Daniel Wang, Hao Sladoje, Nataša Lindblad, Joakim Smith, Jason T. Ochoa, Marien Barroso, Margarida Intes, Xavier Qiu, Tong Yu, Li-Yu You, Sixian Liu, Yongtao Ziatdinov, Maxim A. Kalinin, Sergei V. Sheridan, Arlo Manor, Uri Nehme, Elias Goldenberg, Ofri Shechtman, Yoav Moberg, Henrik K. Langhammer, Christoph Špačková, Barbora Helgadottir, Saga Midtvedt, Benjamin Argun, Aykut Thalheim, Tobias Cichos, Frank Bo, Stefano Hubatsch, Lars Pineda, Jesus Manzo, Carlo Bachimanchi, Harshith Selander, Erik Homs-Corbera, Antoni Fränzl, Martin de Haan, Kevin Rivenson, Yair Korczak, Zofia Adiels, Caroline Beck Mijalkov, Mite Veréb, Dániel Chang, Yu-Wei Pereira, Joana B. Matuszewski, Damian Kylberg, Gustaf Sintorn, Ida-Maria Caicedo, Juan C. Cimini, Beth A. Bell, Muyinatu Lediju A. Saraiva, Bruno M. Jacquemet, Guillaume Henriques, Ricardo Ouyang, Wei Le, Trang Gómez-De-Mariscal, Estibaliz Sage, Daniel Muñoz-Barrutia, Arrate Lindqvist, Ebba Josefson Bergman, Johanna Department of Physics University of Gothenburg Gothenburg41296 Sweden Dept. IT and SciLifeLab Uppsala University Sweden Department of Electrical and Computer Engineering Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Görlitz Germany Department of Renal Medicine Division of Medicine University College London Royal Free Hospital Campus London United Kingdom Artificial Intelligence for Life Sciences CIC Dorset United Kingdom Roche Pharma International Informatics Roche Diagnostics GmbH Mannheim Germany Department of Electrical Engineering and Computer Sciences UC Berkeley United States Technische Universität Dresden Faculty of Computer Science Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Center for Systems Biology Dresden Dresden Germany University of Maryland College Park United States Klosterneuburg3400 Austria School of Mathematics and Physics The University of Queensland Brisbane4072 Australia Australian Research Council Centre of Excellence for Engineered Quantum Systems The University of Queensland Brisbane4072 Australia Département d’Optique P. M. Duffieux Institut FEMTO-ST Université Franche-Comté CNRS UMR 6174 Besançon France Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA United States Department of Information Technology Uppsala University Sweden Department of Biomedical Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Elephas 1 Erdman Pl. Madison53705 United States University of Wisconsin–Madison Department of Medical Physics MadisonWI53705 United States Department of Molecular and Cellular Physiology Albany Medical College AlbanyNY12208 United States Research Laboratory of Electronics Electrical Engineering and Computer Science Massachusetts Institute of Technology BostonMA United States Center for Nanophase Materials Sciences Oak R

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

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Magneto-optical transport properties of monolayer transition metal dichalcogenides

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Physical Review B 2020年第4期101卷 045424-045424页

作者： Nguyen D. Hien Chuong V. Nguyen Nguyen N. Hieu S. S. Kubakaddi C. A. Duque M. E. Mora-Ramos Le Dinh Tran N. Bich Huynh V. Phuc Laboratory of Magnetism and Magnetic Materials Advanced Institute of Materials Science Ton Duc Thang University Ho Chi Minh City 758307 Vietnam Faculty of Applied Sciences Ton Duc Thang University Ho Chi Minh City 758307 Vietnam Department of Materials Science and Engineering Le Quy Don Technical University Hanoi 100000 Vietnam Institute of Research and Development Duy Tan University Da Nang 550000 Vietnam Department of Physics K. L. E. Technological University Hubballi-580 031 Karnataka India Grupo de Materia Condensada-UdeA Instituto de Física Facultad de Ciencias Exactas y Naturales Universidad de Antioquia UdeA Calle 70 No. 52-21 Medellín Colombia Centro de Investigación en Ciencias-IICBA. Universidad Autónoma del Estado de Morelos. Av. Universidad 1001 CP 62209 Cuernavaca Morelos Mexico Center for Theoretical and Computational Physics University of Education Hue University Hue 530000 Vietnam Physics Department University of Education Hue University Hue 530000 Vietnam Division of Theoretical Physics Dong Thap University Cao Lanh 870000 Vietnam

We study the optical transport properties of the monolayer transition metal dichalcogenides (TMDCs) such as MoS2, WS2, MoSe2, and WSe2 in the presence of a magnetic field. The TMDCs band structures are obtained and discussed by using the effective massive Dirac model, in which the spin and valley Zeeman effects as well as an external electric field are included. The magneto-optical absorption coefficient (MOAC) is derived as a function of absorbed photon energy when the carriers are scattered by random impurities combined with the intrinsic acoustic and optical phonons in TMDCs and the surface optical (SO) phonons of substrates. Our result shows that the spin-splitting feature appeared in all four TMDC materials. The combination of strong spin-orbit coupling (SOC) and Zeeman fields has doubled the Landau levels but has not changed the energy gap of the TMDCs monolayer, which can be controlled by the electric field. Because of their strong SOC effect, the absorption spectrum in monolayer TMDCs is separated into two separate peaks caused by spin up and down. At the low temperature, the MOAC intensity via impurity scattering is the biggest followed by that of the SO phonons while the intrinsic acoustic and optical phonon scatterings display the smallest. For the monolayer TMDCs on substrates, SiO2 always shows its superiority in comparison with the others. Among the four TMDC materials, MoSe2 shows the biggest MOAC intensity, while WS2 has the biggest value of the absorbed photon energy. The full-width at half-maximum (FWHM) via impurity scattering achieves its highest value in WS2, while this occurs in MoSe2 and MoS2 via intrinsic acoustic and optical phonon scatterings, respectively. Our estimation of mobility from FWHM gives good agreement with the experimental results in WS2.

关键词： Magneto-optical effect Magnetotransport Phonons Spin-orbit coupling Transport phenomena Transition metal dichalcogenides

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Two-dimensional ferromagnetic-ferroelectric multiferroics in violation of the d0 rule

arXiv

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arXiv 2019年

作者： Tan, Hengxin Li, Menglei Liu, Haitao Liu, Zhirong Li, Yuanchang Duan, Wenhui State Key Laboratory of Low-Dimensional Quantum Physics and Collaborative Innovation Center of Quantum Matter Department of Physics Tsinghua University Beijing100084 China Department of Physics Capital Normal University Beijing100084 China Institute of Applied Physics and Computational Mathematics PO Box 8009 Beijing100088 China Center for Nanochemistry College of Chemistry and Molecular Engineering Peking University Beijing100871 China Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing100081 China Institute for Advanced Study Tsinghua University Beijing100084 China

Contribution of d-electron to ferroelectricity of type-II multiferroics causes strong magneto-electric coupling and distinguishes them from the conventional type-I multiferroics. However, their therein polarization is too small because the ferroelectricity is merely a derivative from the magnetic order. Here we report a new class of multiferroic materials, monolayer VOX2 (X = Cl, Br, and I), which combine the advantages of type-I and type-II multiferroics. Both ferroelectricity and magnetism arise from the same V cation, where the filled d-orbital is perpendicular to an a priori ferroelectric polarization and thus poses no hindrance to ferroelectricity, indicating a violation of the usual d0 rule. This makes the combination of large polarizations and strong magneto-electric coupling possible. Our findings not only add new ferromagnetic-ferroelectric multiferroics, but also point to a unique mechanism to engineer multiferroics. Copyright © 2019, The Authors. All rights reserved.

关键词： Ferroelectricity

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Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction (vol 53, pg 65, 2021)

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NATURE GENETICS 2021年第3期53卷 413-413页

作者： Conti, David V. Darst, Burcu F. Moss, Lilit C. Saunders, Edward J. Sheng, Xin Chou, Alisha Schumacher, Fredrick R. Al Olama, Ali Amin Benlloch, Sara Dadaev, Tokhir Brook, Mark N. Sahimi, Ali Hoffmann, Thomas J. Takahashi, Atushi Matsuda, Koichi Momozawa, Yukihide Fujita, Masashi Muir, Kenneth Lophatananon, Artitaya Wan, Peggy Le Marchand, Loic Wilkens, Lynne R. Stevens, Victoria L. Gapstur, Susan M. Carter, Brian D. Schleutker, Johanna Tammela, Teuvo L. J. Sipeky, Csilla Auvinen, Anssi Giles, Graham G. Southey, Melissa C. MacInnis, Robert J. Cybulski, Cezary Wokolorczyk, Dominika Lubinski, Jan Neal, David E. Donovan, Jenny L. Hamdy, Freddie C. Martin, Richard M. Nordestgaard, Borge G. Nielsen, Sune F. Weischer, Maren Bojesen, Stig E. Roder, Martin Andreas Iversen, Peter Batra, Jyotsna Chambers, Suzanne Moya, Leire Horvath, Lisa Clements, Judith A. Tilley, Wayne Risbridger, Gail P. Gronberg, Henrik Aly, Markus Szulkin, Robert Eklund, Martin Nordstrom, Tobias Pashayan, Nora Dunning, Alison M. Ghoussaini, Maya Travis, Ruth C. Key, Tim J. Riboli, Elio Park, Jong Y. Sellers, Thomas A. Lin, Hui-Yi Albanes, Demetrius Weinstein, Stephanie J. Mucci, Lorelei A. Giovannucci, Edward Lindstrom, Sara Kraft, Peter Hunter, David J. Penney, Kathryn L. Turman, Constance Tangen, Catherine M. Goodman, Phyllis J. Thompson, Ian M., Jr. Hamilton, Robert J. Fleshner, Neil E. Finelli, Antonio Parent, Marie-Elise Stanford, Janet L. Ostrander, Elaine A. Geybels, Milan S. Koutros, Stella Freeman, Laura E. Beane Stampfer, Meir Wolk, Alicja Hakansson, Niclas Andriole, Gerald L. Hoover, Robert N. Machiela, Mitchell J. Sorensen, Karina Dalsgaard Borre, Michael Blot, William J. Zheng, Wei Yeboah, Edward D. Mensah, James E. Lu, Yong-Jie Zhang, Hong-Wei Feng, Ninghan Mao, Xueying Wu, Yudong Zhao, Shan-Chao Sun, Zan Thibodeau, Stephen N. McDonnell, Shannon K. Schaid, Daniel J. West, Catharine M. L. Burnet, Neil Barnett, Gill Maier, Christiane Schnoeller, Thomas Luedeke, Manuel Kibel, Adam S. Drake, Bettina F. Cussenot, Olivier Cancel-Tassin, Gerald Center for Genetic Epidemiology Department of Preventive Medicine Keck School of Medicine University of Southern California/Norris Comprehensive Cancer Center Los Angeles CA USA The Institute of Cancer Research London UK Department of Population and Quantitative Health Sciences Case Western Reserve University Cleveland OH USA Seidman Cancer Center University Hospitals Cleveland OH USA Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care University of Cambridge Strangeways Research Laboratory Cambridge UK Stroke Research Group Department of Clinical Neurosciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics University of California San Francisco CA USA Institute for Human Genetics University of California San Francisco CA USA Laboratory for Statistical Analysis RIKEN Center for Integrative Medical Sciences Yokohama Japan Department of Genomic Medicine National Cerebral and Cardiovascular Center Research Institute Suita Japan Laboratory of Clinical Genome Sequencing Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan Biobank Tokyo Japan Laboratory for Genotyping Development RIKEN Center of Integrative Medical Sciences Yokohama Japan Laboratory for Cancer Genomics RIKEN Center of Integrative Medical Sciences Yokohama Japan Division of Population Health Health Services Research and Primary Care School of Health Sciences Faculty of Biology Medicine and Health University of Manchester Manchester UK Warwick Medical School University of Warwick Coventry UK Epidemiology Program University of Hawaii Cancer Center Honolulu HI USA Behavioral and Epidemiology Research Group Research Program American Cancer Society Atlanta GA USA Institute of Biomedicine University of Turku Turku Finland Department of Medical Genetics Genomics Laboratory Division Turku University Hospital Turku Finland Department of Urolog

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

关键词： Epidemiology Genome-wide association studies Personalized medicine Prostate cancer

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First Measurement of A=4 Hypernuclei and Antihypernuclei at the LHC

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Physical Review Letters 2025年第16期134卷 162301-162301页

作者： S. Acharya A. Agarwal G. Aglieri Rinella L. Aglietta M. Agnello N. Agrawal Z. Ahammed S. Ahmad S. U. Ahn I. Ahuja A. Akindinov V. Akishina M. Al-Turany D. Aleksandrov B. Alessandro H. M. Alfanda R. Alfaro Molina B. Ali A. Alici N. Alizadehvandchali A. Alkin J. Alme G. Alocco T. Alt A. R. Altamura I. Altsybeev J. R. Alvarado C. O. R. Alvarez M. N. Anaam C. Andrei N. Andreou A. Andronic E. Andronov V. Anguelov F. Antinori P. Antonioli N. Apadula L. Aphecetche H. Appelshäuser C. Arata S. Arcelli R. Arnaldi J. G. M. C. A. Arneiro I. C. Arsene M. Arslandok A. Augustinus R. Averbeck D. Averyanov M. D. Azmi H. Baba A. Badalà J. Bae Y. W. Baek X. Bai R. Bailhache Y. Bailung R. Bala A. Balbino A. Baldisseri B. Balis Z. Banoo V. Barbasova F. Barile L. Barioglio M. Barlou B. Barman G. G. Barnaföldi L. S. Barnby E. Barreau V. Barret L. Barreto C. Bartels K. Barth E. Bartsch N. Bastid S. Basu G. Batigne D. Battistini B. Batyunya D. Bauri J. L. Bazo Alba I. G. Bearden C. Beattie P. Becht D. Behera I. Belikov A. D. C. Bell Hechavarria F. Bellini R. Bellwied S. Belokurova L. G. E. Beltran Y. A. V. Beltran G. Bencedi A. Bensaoula S. Beole Y. Berdnikov A. Berdnikova L. Bergmann M. G. Besoiu L. Betev P. P. Bhaduri A. Bhasin B. Bhattacharjee L. Bianchi J. Bielčík J. Bielčíková A. P. Bigot A. Bilandzic G. Biro S. Biswas N. Bize J. T. Blair D. Blau M. B. Blidaru N. Bluhme C. Blume G. Boca F. Bock T. Bodova J. Bok L. Boldizsár M. Bombara P. M. Bond G. Bonomi H. Borel A. Borissov A. G. Borquez Carcamo E. Botta Y. E. M. Bouziani L. Bratrud P. Braun-Munzinger M. Bregant M. Broz G. E. Bruno V. D. Buchakchiev M. D. Buckland D. Budnikov H. Buesching S. Bufalino P. Buhler N. Burmasov Z. Buthelezi A. Bylinkin S. A. Bysiak J. C. Cabanillas Noris M. F. T. Cabrera M. Cai H. Caines A. Caliva E. Calvo Villar J. M. M. Camacho P. Camerini F. D. M. Canedo S. L. Cantway M. Carabas A. A. Carballo F. Carnesecchi R. Caron L. A. D. Carvalho J. Castillo Castellanos M. Castoldi F. Catalano S. Cattaruzzi R. Cerri I. Chakaberia P. Chakraborty S. Chandra S. Cha Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France Variable Energy Cyclotron Centre Homi Bhabha National Institute Kolkata India European Organization for Nuclear Research (CERN) Geneva Switzerland Dipartimento di Fisica dell’Università and Sezione INFN Turin Italy Dipartimento DISAT del Politecnico and Sezione INFN Turin Italy Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN Bologna Italy Department of Physics Aligarh Muslim University Aligarh India Korea Institute of Science and Technology Information Daejeon Republic of Korea Faculty of Science P.J. Šafárik University Košice Slovak Republic Affiliated with an institute covered by a cooperation agreement with CERN Frankfurt Institute for Advanced Studies Johann Wolfgang Goethe-Universität Frankfurt Frankfurt Germany Research Division and ExtreMe Matter Institute EMMI GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt Germany INFN Sezione di Torino Turin Italy Central China Normal University Wuhan China Instituto de Física Universidad Nacional Autónoma de México Mexico City Mexico University of Houston Houston Texas USA Sungkyunkwan University Suwon City Republic of Korea Department of Physics and Technology University of Bergen Bergen Norway INFN Sezione di Cagliari Cagliari Italy Institut für Kernphysik Johann Wolfgang Goethe-Universität Frankfurt Frankfurt Germany INFN Sezione di Bari Bari Italy Physik Department Technische Universität München Munich Germany High Energy Physics Group Universidad Autónoma de Puebla Puebla Mexico Horia Hulubei National Institute of Physics and Nuclear Engineering Bucharest Romania University of Derby Derby United Kingdom Universität Münster Institut für Kernphysik Münster Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany INFN Sezione di Padova Padova Italy INFN Sezione di Bologna Bologna Italy Lawrence Berkeley National Laboratory Berkeley California USA SUBATECH I

In this Letter, the first evidence of the He¯Λ¯4 antihypernucleus is presented, along with the first measurement at the LHC of the production of (anti)hypernuclei with mass number A=4, specifically (anti)HΛ4 and (anti)HeΛ4. In addition, the antiparticle-to-particle ratios for both hypernuclei (H¯Λ¯4/HΛ4 and He¯Λ¯4/HeΛ4) are shown, which are sensitive to the baryochemical potential of the strongly interacting matter created in heavy-ion collisions. The results are obtained from a data sample of central Pb-Pb collisions, collected during the 2018 LHC data taking at a center-of-mass energy per nucleon pair of sNN=5.02 TeV. The yields measured for the average of the charge-conjugated states are found to be [0.78±0.19(stat)±0.17(syst)]×10−6 for the (anti)HΛ4 and [1.08±0.34(stat)±0.20(syst)]×10−6 for the (anti)HeΛ4, and the measured antiparticle-to-particle ratios are in agreement with unity. The presence of (anti)HΛ4 and (anti)HeΛ4 excited states is expected to strongly enhance the production yield of these hypernuclei. The yield values exhibit a combined deviation of 3.3σ from the theoretical ground-state-only expectation, while the inclusion of the excited states in the calculations leads to an agreement within 0.6σ with the present measurements. Additionally, the measured (anti)HΛ4 and (anti)HeΛ4 masses are compatible with the world-average values within the uncertainties.

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Teaching in the Age of Covid-19—The New Normal

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Postdigital science and Education 2022年第3期4卷 877-1015页

作者： Jandrić, Petar Martinez, Ana Fuentes Reitz, Charles Jackson, Liz Grauslund, Dennis Hayes, David Lukoko, Happiness Onesmo Hogan, Michael Mozelius, Peter Arantes, Janine Aldous Levinson, Paul Ozoliņš, Jānis John Kirylo, James D. Carr, Paul R. Hood, Nina Tesar, Marek Sturm, Sean Abegglen, Sandra Burns, Tom Sinfield, Sandra Stewart, Georgina Tuari Suoranta, Juha Jaldemark, Jimmy Gustafsson, Ulrika Monzó, Lilia D. Kokić, Ivana Batarelo Kihwele, Jimmy Ezekiel Wright, Jake Kishore, Pallavi Stewart, Paul Alexander Bridges, Susan M. Lodahl, Mikkel Bryant, Peter Kaur, Kulpreet Hollings, Stephanie Brown, James Benedict Steketee, Anne Prinsloo, Paul Hazzan, Moses Kayode Jopling, Michael Mañero, Julia Gibbons, Andrew Pfohl, Sarah Humble, Niklas Davidsen, Jacob Ford, Derek R. Sharma, Navreeti Stockbridge, Kevin Pyyhtinen, Olli Escaño, Carlos Achieng-Evensen, Charlotte Rose, Jennifer Irwin, Jones Shukla, Richa SooHoo, Suzanne Truelove, Ian Buchanan, Rachel Urvashi, Shreya White, E. Jayne Novak, Rene Ryberg, Thomas Arndt, Sonja Redder, Bridgette Mukherjee, Mousumi Komolafe, Blessing Funmi Mallya, Madhav Devine, Nesta Sattarzadeh, Sahar D. Hayes, Sarah Zagreb University of Applied Sciences Zagreb Croatia University of Wolverhampton Wolverhampton UK University West Trollhättan Sweden Kansas City Kansas Community College Kansas City USA Education University of Hong Kong Hong Kong China University College of Northern Denmark (UCN) Aalborg Denmark Further Education Worcester UK Institute of Development Studies University of Dar Es Salaam Dar es Salaam Tanzania School of Psychology National University of Ireland Galway Galway Ireland Mid Sweden University Östersund/Stockholm Sweden Victoria University Melbourne Australia Fordham University New York City USA College of Philosophy and Theology University of Notre Dame Australia Fremantle Australia Faculty of History and Philosophy University of Latvia Riga Latvia University of South Carolina Columbia USA Département des sciences de l’éducation Université du Québec en Outaouais Gatineau Canada Faculty of Education and Social Work University of Auckland Auckland New Zealand School of Architecture Planning and Landscape University of Calgary Calgary Canada Centre for Professional and Educational Development London Metropolitan University London UK Auckland University of Technology Auckland New Zealand Faculty of Social Sciences Tampere University Tampere Finland Department of Education Mid Sweden University Sundsvall Sweden Department of Applied Educational Science Umeå University Umeå Sweden Attallah College of Educational Studies Chapman University Orange USA Department of Pedagogy Faculty of Humanities and Social Sciences University of Split Split Croatia Department of Education Mzumbe University Morogoro Tanzania Center for Learning Innovation University of Minnesota Rochester Rochester USA Jindal Global Law School O.P. Jindal Global University Sonipat India MIMA School of Art and Design Teesside University Middlesbrough UK The University of Hong Kong Hong Kong China Dania Academy Randers Denmark University of Sydney Sydney Australia J

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Low-temperature electron-phonon interaction of quantum emitters in hexagonal boron nitride

arXiv

引用

arXiv 2019年

作者： Grosso, Gabriele Moon, Hyowon Ciccarino, Christopher J. Flick, Johannes Mendelson, Noah Toth, Milos Aharonovich, Igor Narang, Prineha Englund, Dirk R. Advanced Science Research Center City University of New York Photonics Initiative New YorkNY United States Physics Program Graduate Center City University of New York New YorkNY United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States School of Mathematical and Physical Sciences University of Technology Sydney UltimoNSW2007 Australia Center for Computational Quantum Physics Flatiron Institute New YorkNY United States

关键词： Electron-phonon interactions

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