511 research outputs found
Current-induced instability of domain walls in cylindrical nanowires
We study the current-driven domain wall (DW) motion in cylindrical nanowires
using micromagnetic simulations by implementing the Landau-Lifshitz-Gilbert
equation with nonlocal spin-transfer torque in a finite difference
micromagnetic package. We find that in the presence of DW Gaussian wave packets
(spin waves) will be generated when the charge current is applied to the system
suddenly. And this effect is excluded when using the local spin-transfer
torque. The existence of spin waves emission indicates that transverse domain
walls can not move arbitrarily fast in cylindrical nanowires although they are
free from the Walker limit. We establish an upper-velocity limit for the DW
motion by analyzing the stability of Gaussian wave packets using the local
spin-transfer torque. Micromagnetic simulations show that the stable region
obtained by using nonlocal spin-transfer torque is smaller than that by using
its local counterpart. This limitation is essential for multiple domain walls
since the instability of Gaussian wave packets will break the structure of
multiple domain walls.Comment: 5 pages, 6 figure
Reliability Analysis of Capacitors in Voltage Regulator Modules with Consecutive Load Transients
Joint-Modal Label Denoising for Weakly-Supervised Audio-Visual Video Parsing
This paper focuses on the weakly-supervised audio-visual video parsing task,
which aims to recognize all events belonging to each modality and localize
their temporal boundaries. This task is challenging because only overall labels
indicating the video events are provided for training. However, an event might
be labeled but not appear in one of the modalities, which results in a
modality-specific noisy label problem. In this work, we propose a training
strategy to identify and remove modality-specific noisy labels dynamically. It
is motivated by two key observations: 1) networks tend to learn clean samples
first; and 2) a labeled event would appear in at least one modality.
Specifically, we sort the losses of all instances within a mini-batch
individually in each modality, and then select noisy samples according to the
relationships between intra-modal and inter-modal losses. Besides, we also
propose a simple but valid noise ratio estimation method by calculating the
proportion of instances whose confidence is below a preset threshold. Our
method makes large improvements over the previous state of the arts (e.g. from
60.0\% to 63.8\% in segment-level visual metric), which demonstrates the
effectiveness of our approach. Code and trained models are publicly available
at \url{https://github.com/MCG-NJU/JoMoLD}.Comment: Accepted by ECCV 202
Linear Gaussian Bounding Box Representation and Ring-Shaped Rotated Convolution for Oriented Object Detection
In oriented object detection, current representations of oriented bounding
boxes (OBBs) often suffer from boundary discontinuity problem. Methods of
designing continuous regression losses do not essentially solve this problem.
Although Gaussian bounding box (GBB) representation avoids this problem,
directly regressing GBB is susceptible to numerical instability. We propose
linear GBB (LGBB), a novel OBB representation. By linearly transforming the
elements of GBB, LGBB avoids the boundary discontinuity problem and has high
numerical stability. In addition, existing convolution-based rotation-sensitive
feature extraction methods only have local receptive fields, resulting in slow
feature aggregation. We propose ring-shaped rotated convolution (RRC), which
adaptively rotates feature maps to arbitrary orientations to extract
rotation-sensitive features under a ring-shaped receptive field, rapidly
aggregating features and contextual information. Experimental results
demonstrate that LGBB and RRC achieve state-of-the-art performance.
Furthermore, integrating LGBB and RRC into various models effectively improves
detection accuracy
Large area growth and electrical properties of p-type WSe2 atomic layers.
Transition metal dichacogenides represent a unique class of two-dimensional layered materials that can be exfoliated into single or few atomic layers. Tungsten diselenide (WSe(2)) is one typical example with p-type semiconductor characteristics. Bulk WSe(2) has an indirect band gap (∼ 1.2 eV), which transits into a direct band gap (∼ 1.65 eV) in monolayers. Monolayer WSe(2), therefore, is of considerable interest as a new electronic material for functional electronics and optoelectronics. However, the controllable synthesis of large-area WSe(2) atomic layers remains a challenge. The studies on WSe(2) are largely limited by relatively small lateral size of exfoliated flakes and poor yield, which has significantly restricted the large-scale applications of the WSe(2) atomic layers. Here, we report a systematic study of chemical vapor deposition approach for large area growth of atomically thin WSe(2) film with the lateral dimensions up to ∼ 1 cm(2). Microphotoluminescence mapping indicates distinct layer dependent efficiency. The monolayer area exhibits much stronger light emission than bilayer or multilayers, consistent with the expected transition to direct band gap in the monolayer limit. The transmission electron microscopy studies demonstrate excellent crystalline quality of the atomically thin WSe(2). Electrical transport studies further show that the p-type WSe(2) field-effect transistors exhibit excellent electronic characteristics with effective hole carrier mobility up to 100 cm(2) V(-1) s(-1) for monolayer and up to 350 cm(2) V(-1) s(-1) for few-layer materials at room temperature, comparable or well above that of previously reported mobility values for the synthetic WSe(2) and comparable to the best exfoliated materials
Chemical constituents and hypoglycemic mechanisms of Dendrobium nobile in treatment of type 2 diabetic rats by UPLC-ESI-Q-Orbitrap, network pharmacology and in vivo experimental verification
Abstract: This study aimed to systematically explore the chemical constituents of D. nobile and its hypoglycemic effect by UPLC-ESI-Q-Orbitrap, network pharmacology and in vivo experiment. The chemical constituents of D. nobile were qualitatively analyzed, and the hypoglycemic compounds were quickly identified. Network pharmacological analysis and molecular docking technique were applied to assist in the elucidation of the hypoglycemic mechanisms of D. nobile. A type 2 diabetic mellitus (T2DM) rat model was established using the HFD and STZ method for in vivo experimental verification, and these T2DM rats were treated with D. nobile extract and D. nobile polysaccharide for two months by gavage. The results showed that a total of 39 chemical constituents of D. nobile, including
alkaloids, bibenzyls, phenanthrenes and other types of compounds, were identified. D. nobile extract and D. nobile polysaccharide could significantly ameliorate the body weight, hyperglycemia, insulin resistance, dyslipidemia and morphological impairment of the liver and pancreas in the T2DM rats. α-Linolenic acid, dihydroconiferyl dihydro-p-coumarate, naringenin, trans-N-feruloyltyramine, gigantol, moscatilin, 4-O-methylpinosylvic acid, venlafaxine, nordendrobin and tristin were regarded as the key hypoglycemic compounds of D. nobile, along with the hypoglycemic effect on the PI3K-AKT signaling pathway, the insulin signaling pathway, the FOXO signaling pathway, the improvement of
insulin resistance and the AGE-RAGE signaling pathway. The Western blotting experiment results confirmed that D. nobile activated the PI3K/AKT pathway and insulin signaling pathway, promoted glycogen synthesis via regulating the expression of glycogen synthase kinase 3 beta (GSK-3) and glucose transporter 4 (GLUT4), and inhibited liver gluconeogenesis by regulating the expression
of phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6 phosphatase (G6pase) in the liver. The results suggested that the hypoglycemic mechanism of D. nobile might be associated with liver glycogen synthesis and gluconeogenesis, contributing to improving insulin resistance and abnormal glucose metabolism in the T2DM rats
3D nongadolinium-enhanced mra using flow-sensitive dephasing (fsd) prepared balanced ssfp: identification of the optimal first-order gradient moment
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