122 research outputs found
Direct observation of magnon-phonon coupling in yttrium iron garnet
The magnetic insulator yttrium iron garnet (YIG) with a ferrimagnetic
transition temperature of 560 K has been widely used in microwave and
spintronic devices. Anomalous features in the spin Seeback effect (SSE)
voltages have been observed in Pt/YIG and attributed to the magnon-phonon
coupling. Here we use inelastic neutron scattering to map out low-energy spin
waves and acoustic phonons of YIG at 100 K as a function of increasing magnetic
field. By comparing the zero and 9.1 T data, we find that instead of splitting
and opening up gaps at the spin wave and acoustic phonon dispersion
intersecting points, magnon-phonon coupling in YIG enhances the hybridized
scattering intensity. These results are different from expectations of
conventional spin-lattice coupling, calling for new paradigms to understand the
scattering process of magnon-phonon interactions and the resulting
magnon-polarons.Comment: 5 pages, 4 figures, PRB in pres
Easy and Efficient Transformer : Scalable Inference Solution For large NLP model
Recently, large-scale transformer-based models have been proven to be
effective over a variety of tasks across many domains. Nevertheless, putting
them into production is very expensive, requiring comprehensive optimization
techniques to reduce inference costs. This paper introduces a series of
transformer inference optimization techniques that are both in algorithm level
and hardware level. These techniques include a pre-padding decoding mechanism
that improves token parallelism for text generation, and highly optimized
kernels designed for very long input length and large hidden size. On this
basis, we propose a transformer inference acceleration library -- Easy and
Efficient Transformer (EET), which has a significant performance improvement
over existing libraries. Compared to Faster Transformer v4.0's implementation
for GPT-2 layer on A100, EET achieves a 1.5-4.5x state-of-art speedup varying
with different context lengths. EET is available at
https://github.com/NetEase-FuXi/EET. A demo video is available at
https://youtu.be/22UPcNGcErg
regSNPs-splicing: a tool for prioritizing synonymous single-nucleotide substitution
While synonymous single-nucleotide variants (sSNVs) have largely been unstudied, since they do not alter protein sequence, mounting evidence suggests that they may affect RNA conformation, splicing, and the stability of nascent-mRNAs to promote various diseases. Accurately prioritizing deleterious sSNVs from a pool of neutral ones can significantly improve our ability of selecting functional genetic variants identified from various genome-sequencing projects, and, therefore, advance our understanding of disease etiology. In this study, we develop a computational algorithm to prioritize sSNVs based on their impact on mRNA splicing and protein function. In addition to genomic features that potentially affect splicing regulation, our proposed algorithm also includes dozens structural features that characterize the functions of alternatively spliced exons on protein function. Our systematical evaluation on thousands of sSNVs suggests that several structural features, including intrinsic disorder protein scores, solvent accessible surface areas, protein secondary structures, and known and predicted protein family domains, show significant differences between disease-causing and neutral sSNVs. Our result suggests that the protein structure features offer an added dimension of information while distinguishing disease-causing and neutral synonymous variants. The inclusion of structural features increases the predictive accuracy for functional sSNV prioritization
Electric-field-driven Non-volatile Multi-state Switching of Individual Skyrmions in a Multiferroic Heterostructure
Electrical manipulation of skyrmions attracts considerable attention for its
rich physics and promising applications. To date, such a manipulation is
realized mainly via spin-polarized current based on spin-transfer torque or
spin-orbital torque effect. However, this scheme is energy-consuming and may
produce massive Joule heating. To reduce energy dissipation and risk of
heightened temperatures of skyrmion-based devices, an effective solution is to
use electric field instead of current as stimulus. Here, we realize an
electric-field manipulation of skyrmions in a nanostructured
ferromagnetic/ferroelectrical heterostructure at room temperature via an
inverse magneto-mechanical effect. Intriguingly, such a manipulation is
non-volatile and exhibits a multi-state feature. Numerical simulations indicate
that the electric-field manipulation of skyrmions originates from
strain-mediated modification of effective magnetic anisotropy and
Dzyaloshinskii-Moriya interaction. Our results open a direction for
constructing low-energy-dissipation, non-volatile, and multi-state
skyrmion-based spintronic devices.Comment: Accepted by Nature Communications 11, 3577 (2020
COVID-19 causes record decline in global CO2 emissions
The considerable cessation of human activities during the COVID-19 pandemic
has affected global energy use and CO2 emissions. Here we show the
unprecedented decrease in global fossil CO2 emissions from January to April
2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-{\sigma} uncertainty) when
compared with the period last year. In addition other emerging estimates of
COVID impacts based on monthly energy supply or estimated parameters, this
study contributes to another step that constructed the near-real-time daily CO2
emission inventories based on activity from power generation (for 29
countries), industry (for 73 countries), road transportation (for 406 cities),
aviation and maritime transportation and commercial and residential sectors
emissions (for 206 countries). The estimates distinguished the decline of CO2
due to COVID-19 from the daily, weekly and seasonal variations as well as the
holiday events. The COVID-related decreases in CO2 emissions in road
transportation (340.4 Mt CO2, -15.5%), power (292.5 Mt CO2, -6.4% compared to
2019), industry (136.2 Mt CO2, -4.4%), aviation (92.8 Mt CO2, -28.9%),
residential (43.4 Mt CO2, -2.7%), and international shipping (35.9Mt CO2,
-15%). Regionally, decreases in China were the largest and earliest (234.5 Mt
CO2,-6.9%), followed by Europe (EU-27 & UK) (138.3 Mt CO2, -12.0%) and the U.S.
(162.4 Mt CO2, -9.5%). The declines of CO2 are consistent with regional
nitrogen oxides concentrations observed by satellites and ground-based
networks, but the calculated signal of emissions decreases (about 1Gt CO2) will
have little impacts (less than 0.13ppm by April 30, 2020) on the overserved
global CO2 concertation. However, with observed fast CO2 recovery in China and
partial re-opening globally, our findings suggest the longer-term effects on
CO2 emissions are unknown and should be carefully monitored using multiple
measures
Near-real-time monitoring of global COâ‚‚ emissions reveals the effects of the COVID-19 pandemic
The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO₂) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO₂ emissions (−1551 Mt CO₂) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially
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