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Nature
Resumen/Descripción – provisto por la editorial en inglés
Nature is a weekly international journal publishing the finest peer-reviewed research in all fields of science and technology on the basis of its originality, importance, interdisciplinary interest, timeliness, accessibility, elegance and surprising conclusions. Nature also provides rapid, authoritative, insightful and arresting news and interpretation of topical and coming trends affecting science, scientists and the wider public.Palabras clave – provistas por la editorial
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Disponibilidad
| Institución detectada | Período | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | desde jul. 2012 / hasta dic. 2023 | Nature.com | ||
| No detectada | desde jul. 2006 / hasta ago. 2012 | Ovid |
Información
Tipo de recurso:
revistas
ISSN impreso
0028-0836
ISSN electrónico
1476-4687
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
1869-
Tabla de contenidos
AGN as potential factories for eccentric black hole mergers
J. Samsing
; I. Bartos; D. J. D’Orazio; Z. Haiman; B. Kocsis; N. W. C. Leigh; B. Liu; M. E. Pessah; H. Tagawa
Palabras clave: Multidisciplinary.
Pp. 237-240
Ultra-narrow optical linewidths in rare-earth molecular crystals
Diana Serrano; Senthil Kumar Kuppusamy; Benoît Heinrich; Olaf Fuhr; David Hunger; Mario Ruben; Philippe Goldner
Palabras clave: Multidisciplinary.
Pp. 241-246
Structure of the moiré exciton captured by imaging its electron and hole
Ouri Karni; Elyse Barré; Vivek Pareek; Johnathan D. Georgaras; Michael K. L. Man; Chakradhar Sahoo; David R. Bacon; Xing Zhu; Henrique B. Ribeiro; Aidan L. O’Beirne; Jenny Hu; Abdullah Al-Mahboob; Mohamed M. M. Abdelrasoul; Nicholas S. Chan; Arka Karmakar; Andrew J. Winchester; Bumho Kim; Kenji Watanabe; Takashi Taniguchi; Katayun Barmak; Julien Madéo; Felipe H. da Jornada; Tony F. Heinz; Keshav M. Dani
Palabras clave: Multidisciplinary.
Pp. 247-252
A large-scale microelectromechanical-systems-based silicon photonics LiDAR
Xiaosheng Zhang; Kyungmok Kwon; Johannes Henriksson; Jianheng Luo; Ming C. Wu
<jats:title>Abstract</jats:title><jats:p>Three-dimensional (3D) imaging sensors allow machines to perceive, map and interact with the surrounding world<jats:sup>1</jats:sup>. The size of light detection and ranging (LiDAR) devices is often limited by mechanical scanners. Focal plane array-based 3D sensors are promising candidates for solid-state LiDARs because they allow electronic scanning without mechanical moving parts. However, their resolutions have been limited to 512 pixels or smaller<jats:sup>2</jats:sup>. In this paper, we report on a 16,384-pixel LiDAR with a wide field of view (FoV, 70° × 70°), a fine addressing resolution (0.6° × 0.6°), a narrow beam divergence (0.050° × 0.049°) and a random-access beam addressing with sub-MHz operation speed. The 128 × 128-element focal plane switch array (FPSA) of grating antennas and microelectromechanical systems (MEMS)-actuated optical switches are monolithically integrated on a 10 × 11-mm<jats:sup>2</jats:sup> silicon photonic chip, where a 128 × 96 subarray is wire bonded and tested in experiments. 3D imaging with a distance resolution of 1.7 cm is achieved with frequency-modulated continuous-wave (FMCW) ranging in monostatic configuration. The FPSA can be mass-produced in complementary metal–oxide–semiconductor (CMOS) foundries, which will allow ubiquitous 3D sensors for use in autonomous cars, drones, robots and smartphones.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 253-258
Vertical MoS2 transistors with sub-1-nm gate lengths
Fan Wu; He Tian; Yang Shen; Zhan Hou; Jie Ren; Guangyang Gou; Yabin Sun; Yi Yang; Tian-Ling Ren
Palabras clave: Multidisciplinary.
Pp. 259-264
Electron-catalysed molecular recognition
Yang Jiao; Yunyan Qiu; Long Zhang; Wei-Guang Liu; Haochuan Mao; Hongliang Chen; Yuanning Feng; Kang Cai; Dengke Shen; Bo Song; Xiao-Yang Chen; Xuesong Li; Xingang Zhao; Ryan M. Young; Charlotte L. Stern; Michael R. Wasielewski; R. Dean Astumian; William A. Goddard; J. Fraser Stoddart
Palabras clave: Multidisciplinary.
Pp. 265-270
Au–Pd separation enhances bimetallic catalysis of alcohol oxidation
Xiaoyang Huang; Ouardia Akdim; Mark Douthwaite; Kai Wang; Liang Zhao; Richard J. Lewis; Samuel Pattisson; Isaac T. Daniel; Peter J. Miedziak; Greg Shaw; David J. Morgan; Sultan M. Althahban; Thomas E. Davies; Qian He; Fei Wang; Jile Fu; Donald Bethell; Steven McIntosh; Christopher J. Kiely; Graham J. Hutchings
Palabras clave: Multidisciplinary.
Pp. 271-275
Weak cubic CaSiO3 perovskite in the Earth’s mantle
J. Immoor; L. Miyagi; H.-P. Liermann; S. Speziale; K. Schulze; J. Buchen; A. Kurnosov; H. Marquardt
Palabras clave: Multidisciplinary.
Pp. 276-279
Restoring and attributing ancient texts using deep neural networks
Yannis Assael; Thea Sommerschield; Brendan Shillingford; Mahyar Bordbar; John Pavlopoulos; Marita Chatzipanagiotou; Ion Androutsopoulos; Jonathan Prag; Nando de Freitas
<jats:title>Abstract</jats:title><jats:p>Ancient history relies on disciplines such as epigraphy—the study of inscribed texts known as inscriptions—for evidence of the thought, language, society and history of past civilizations<jats:sup>1</jats:sup>. However, over the centuries, many inscriptions have been damaged to the point of illegibility, transported far from their original location and their date of writing is steeped in uncertainty. Here we present Ithaca, a deep neural network for the textual restoration, geographical attribution and chronological attribution of ancient Greek inscriptions. Ithaca is designed to assist and expand the historian’s workflow. The architecture of Ithaca focuses on collaboration, decision support and interpretability. While Ithaca alone achieves 62% accuracy when restoring damaged texts, the use of Ithaca by historians improved their accuracy from 25% to 72%, confirming the synergistic effect of this research tool. Ithaca can attribute inscriptions to their original location with an accuracy of 71% and can date them to less than 30 years of their ground-truth ranges, redating key texts of Classical Athens and contributing to topical debates in ancient history. This research shows how models such as Ithaca can unlock the cooperative potential between artificial intelligence and historians, transformationally impacting the way that we study and write about one of the most important periods in human history.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 280-283
Innovative ochre processing and tool use in China 40,000 years ago
Fa-Gang Wang; Shi-Xia Yang; Jun-Yi Ge; Andreu Ollé; Ke-Liang Zhao; Jian-Ping Yue; Daniela Eugenia Rosso; Katerina Douka; Ying Guan; Wen-Yan Li; Hai-Yong Yang; Lian-Qiang Liu; Fei Xie; Zheng-Tang Guo; Ri-Xiang Zhu; Cheng-Long Deng; Francesco d’Errico; Michael Petraglia
Palabras clave: Multidisciplinary.
Pp. 284-289