1,471 research outputs found
Large magneto-optical Kerr effect in noncollinear antiferromagnets Mn ( = Rh, Ir, or Pt)
Magneto-optical Kerr effect, normally found in magnetic materials with
nonzero magnetization such as ferromagnets and ferrimagnets, has been known for
more than a century. Here, using first-principles density functional theory, we
demonstrate large magneto-optical Kerr effect in high temperature noncollinear
antiferromagnets Mn ( = Rh, Ir, or Pt), in contrast to usual wisdom.
The calculated Kerr rotation angles are large, being comparable to that of
transition metal magnets such as bcc Fe. The large Kerr rotation angles and
ellipticities are found to originate from the lifting of the band
double-degeneracy due to the absence of spatial symmetry in the Mn
noncollinear antiferromagnets which together with the time-reversal symmetry
would preserve the Kramers theorem. Our results indicate that Mn would
provide a rare material platform for exploration of subtle magneto-optical
phenomena in noncollinear magnetic materials without net magnetization
RNAi technology extends its reach: Engineering plant resistance against harmful eukaryotes
RNA interference (RNAi) is a homology-dependent gene silencing technology that is initiated by double stranded RNA (dsRNA). It has emerged as a genetic tool for engineering plants resistance against prokaryotic pathogens such as virus and bacteria. Recent studies broaden the role of RNAi, and many successful examples have described the application of RNAi for engineering plant resistance against a range of eukaryotic organisms. Expression of dsRNA directed against suitable eukaryotic pathogens target genes in transgenic plants has been shown to give protection against harmful eukaryotic species, including nematodes, herbivorous insects, parasitic weeds and fungi. This review addresses the progress of RNAi-based transgenic plant resistance against these four class eukaryotic pests, as well as future challenges and prospects.Key words: dsRNA, RNAi, crop resistance, biotechnology, nematode, insect, parasitic weed, fungus
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making
Market making (MM) has attracted significant attention in financial trading
owing to its essential function in ensuring market liquidity. With strong
capabilities in sequential decision-making, Reinforcement Learning (RL)
technology has achieved remarkable success in quantitative trading.
Nonetheless, most existing RL-based MM methods focus on optimizing single-price
level strategies which fail at frequent order cancellations and loss of queue
priority. Strategies involving multiple price levels align better with actual
trading scenarios. However, given the complexity that multi-price level
strategies involves a comprehensive trading action space, the challenge of
effectively training profitable RL agents for MM persists. Inspired by the
efficient workflow of professional human market makers, we propose Imitative
Market Maker (IMM), a novel RL framework leveraging both knowledge from
suboptimal signal-based experts and direct policy interactions to develop
multi-price level MM strategies efficiently. The framework start with
introducing effective state and action representations adept at encoding
information about multi-price level orders. Furthermore, IMM integrates a
representation learning unit capable of capturing both short- and long-term
market trends to mitigate adverse selection risk. Subsequently, IMM formulates
an expert strategy based on signals and trains the agent through the
integration of RL and imitation learning techniques, leading to efficient
learning. Extensive experimental results on four real-world market datasets
demonstrate that IMM outperforms current RL-based market making strategies in
terms of several financial criteria. The findings of the ablation study
substantiate the effectiveness of the model components
Radiative transitions in charmonium from twisted mass lattice QCD
We present a study for charmonium radiative transitions:
, and
using twisted mass lattice QCD gauge
configurations. The single-quark vector form factors for and
are also determined. The simulation is performed at a lattice
spacing of fm and the lattice size is . After
extrapolation of lattice data at nonzero to 0, we compare our results
with previous quenched lattice results and the available experimental values.Comment: typeset with revtex, 15 pages, 11 figures, 4 table
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