Results 161 to 170 of about 314 (211)

A Synergistic Strategy for Data‐Constrained Deep Learning in Materials Science

Materials Genome Engineering Advances, EarlyView.
This work develops a three‐stage machine learning framework for materials property prediction, integrating data preparation, graph‐based model training, and final property inference. By synergistically integrating attention pooling, multi‐task learning, auxiliary tasks, and classification‐corrected regression, this hybrid framework provide a ...
Chun Ting Shao, Yi Chen, Shan Man Song, Jian Xu, Peipei Yang, Qing Bo Yan, Gang Su   +6 more
wiley   +1 more source

Roadmap for Photonics with 2D Materials. [PDF]

ACS Photonics
de Abajo FJG, Basov DN, Koppens FHL, Orsini L, Ceccanti M, Castilla S, Cavicchi L, Polini M, Gonçalves PAD, Costa AT, Peres NMR, Mortensen NA, Bharadwaj S, Jacob Z, Schuck PJ, Pasupathy AN, Delor M, Liu MK, Mugarza A, Merino P, Cuxart MG, Chávez-Angel E, Švec M, Tizei LHG, Dirnberger F, Deng H, Schneider C, Menon V, Deilmann T, Chernikov A, Thygesen KS, Abate Y, Terrones M, Sangwan VK, Hersam MC, Yu L, Chen X, Heinz TF, Murthy P, Kroner M, Smolenski T, Thureja D, Chervy T, Genco A, Trovatello C, Cerullo G, Dal Conte S, Timmer D, De Sio A, Lienau C, Shang N, Hong H, Liu K, Sun Z, Rozema LA, Walther P, Alù A, Marini A, Cotrufo M, Queiroz R, Zhu XY, Cox JD, Dias EJC, Echarri ÁR, Iyikanat F, Herrmann P, Tornow N, Klimmer S, Wilhelm J, Soavi G, Sun Z, Wu S, Xiong Y, Matsyshyn O, Krishna Kumar R, Song JCW, Bucher T, Gorlach A, Tsesses S, Kaminer I, Schwab J, Mangold F, Giessen H, Sánchez MS, Efetov DK, Low T, Gómez-Santos G, Stauber T, Álvarez-Pérez G, Duan J, Martín-Moreno L, Paarmann A, Caldwell JD, Nikitin AY, Alonso-González P, Mueller NS, Volkov V, Jariwala D, Shegai T, van de Groep J, Boltasseva A, Bondarev IV, Shalaev VM, Simon J, Fruhling C, Shen G, Novko D, Tan S, Wang B, Petek H, Mkhitaryan V, Yu R, Manjavacas A, Ortega JE, Cheng X, Tian R, Mao D, Van Thourhout D, Gan X, Dai Q, Sternbach A, Zhou Y, Hafezi M, Litvinov D, Grzeszczyk M, Novoselov KS, Koperski M, Papadopoulos S, Novotny L, Viti L, Vitiello MS, Cottam ND, Dewes BT, Makarovsky O, Patanè A, Song Y, Cai M, Chen J, Naveh D, Jang H, Park S, Xia F, Jenke PK, Bajo J, Braun B, Burch KS, Zhao L, Xu X.   +147 more
europepmc   +1 more source

Inferring breeding phenology and reproductive success from the emergence of juveniles in population monitoring

Oikos, EarlyView.
Phenological shifts caused by climate change are increasingly documented in wild populations. These events may be inferred by examining changes in population abundance and age structure throughout the breeding season, often using citizen science. However, several gaps still limit optimal use of such data.
Paul Cuchot, Luis‐Miguel Chevin
wiley   +1 more source

Fuglede-Kadison determinant: theme and variations. [PDF]

Proc Natl Acad Sci U S A, 2013
de la Harpe P.
europepmc   +1 more source

The impact of COVID‐19 on public perceptions of wild meat in Central Africa

People and Nature, EarlyView.
Abstract Wild meat is a significant source of food and income generation in Central Africa. However, there is little knowledge of how the assumed link between COVID‐19 and wild meat consumption has been discussed by the media and received by the public. In this study, we conducted media content analysis of 264 articles published in 2019–2020 related to
Yuhan Li, Lude Kinzonzi, Paul Loundou, Divin Malekani, Krossy Mavakala, Christian Mikolo Yobo, Katharine Abernethy, Matilda Eve Dunn, Donald Midoko Iponga, Robert Mwinyihali, Joss Wright, Eleanor Jane Milner‐Gulland, Lauren Coad, Juliet H. Wright, Daniel W. S. Challender   +14 more
wiley   +1 more source

Perspective on computational simulations of glycosaminoglycans. [PDF]

Wiley Interdiscip Rev Comput Mol Sci, 2019
Nagarajan B, Sankaranarayanan NV, Desai UR.   +2 more
europepmc   +1 more source

Statistical post‐processing of operational dual‐resolution wind‐speed ensemble forecasts

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The performance of raw and post‐processed 50‐member medium‐ and 100‐member extended‐range 10‐m wind‐speed forecasts of the European Centre for Medium‐Range Weather Forecasts and their various dual‐resolution combinations is investigated. Results show that post‐processing improves skill and reduces the differences between the various configurations ...
Sándor Baran, Mária Lakatos
wiley   +1 more source

Accounting for animal movement during aerial imaging surveys

Remote Sensing in Ecology and Conservation, EarlyView.
Animals are not stationary during aerial surveys; if their movements are related to the movement of the aerial platform, then bias can be introduced into subsequent population count estimates. We sought to establish a framework for assessing the impacts of animal movement on count error and platform bias by comparing aggregated counts and relative ...
Rowan L. Converse, Christopher D. Lippitt, Steven E. Sesnie, David R. Stewart, Matthew J. Butler, Grant M. Harris   +5 more
wiley   +1 more source

Ground‐based robotic remote sensing for standardized biodiversity monitoring in coastal habitats

Remote Sensing in Ecology and Conservation, EarlyView.
Illustrated workflow of the proposed citizen‐to‐robot monitoring pipeline: (i) expert‐validated citizen observations are translated into AI models, (ii) deployed on a ground‐based robotic platform for proximal sensing of coastal dune habitats, (iii) enabling standardized detection of ecological targets (e.g., Pancratium maritimum & Brithys crini), and (
Giovanni Di Lorenzo, Simonetta Bagella, Micaela del Valle Rasino, Maria Laura Carranza, Manolo Garabini, Franco Angelini   +5 more
wiley   +1 more source

Partial Inductance Model of Induction Machines for Fault Diagnosis. [PDF]

Sensors (Basel), 2018
Pineda-Sanchez M, Puche-Panadero R, Martinez-Roman J, Sapena-Bano A, Riera-Guasp M, Perez-Cruz J.   +5 more
europepmc   +1 more source