1,174 research outputs found
Competition between structural distortion and magnetic moment formation in fullerene C
We investigated the effect of on-site Coulomb interactions on the structural
and magnetic ground state of the fullerene C based on
density-functional-theory calculations within the local density approximation
plus on-site Coulomb corrections (LDA+). The total energies of the high
symmetry () and distorted () structures of C were
calculated for different spin configurations. The ground state configurations
were found to depend on the forms of exchange-correlation potentials and the
on-site Coulomb interaction parameter , reflecting the subtle nature of the
competition between Jahn-Teller distortion and magnetic instability in
fullerene C. While the non-magnetic state of the distorted
structure is robust for small , a magnetic ground state of the undistorted
structure emerges for larger than 4 eV when the LDA
exchange-correlation potential is employed.Comment: 4 figures, 1 tabl
Multiphoton tissue imaging by using moxifloxacin
Multiphoton microscopy has been widely used for in-vivo tissue imaging of various biological studies. However, its application to clinical studies has been limited due to either lack of clinically compatible exogenous contrast agents or weak autofluorescence of tissues. We investigated moxifloxacin as a contrast agent of cells for multiphoton tissue imaging. Moxifloxacin is an FDA approved antibiotic with relatively good pharmacokinetic properties for tissue penetration and intrinsic fluorescence. Two-photon microscopy (TPM) of moxifloxacin treated mouse corneas showed good tissue penetration and high concentration inside the corneal cells [1]. Cell labeling of moxifloxacin was tested in both cultured cells and isolated immune cells. Moxifloxacin tissue applications were tested in various mouse organs such as the skin, small intestine, and brain. Most of tissues were labeled well via topical administration, and only the skin required additional gentle removal of the outermost stratum corneum by tape stripping. TPM of these tissues showed non-specific cell labeling of moxifloxacin and fluorescence enhancement [2]. Although most of experimental results were from mouse tissues, its clinical application would be possible. Clinical application is promising since imaging based on moxifloxacin labeling could be 10 times faster than imaging based on endogenous fluorescence. Moxifloxacin labeling of cultured cells was demonstrated by comparing TPM images with and without moxifloxacin treatment. Bright fluorescence inside cells were observed only with moxifloxacin at the same imaging condition. TPM of the skin dermis visualized many dermal cells with increased fluorescence, and TPM of the villus in the small intestine showed the covering epithelial cells and cells inside the villus clearly.
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Epitaxially strained ultrathin LaNiO/LaAlO and LaNiO/SrTiO superlattices: a density functional theory + study
By employing first-principles electronic structure calculations we
investigate nickelate superlattices [LaNiO]/[LaAlO] and
[LaNiO]/[SrTiO] with (001) orientation under epitaxial tensile
strain. Within density functional theory augmented by mean-field treatement of
on-site electronic correlations, the ground states show remarkable dependence
on the correlation strength and the strain. In the weakly and intermediately
correlated regimes with small epitaxial strain, the charge-disproportionated
insulating states with antiferromagneitc order is favored over the other
orbital and spin ordered phases. On the other hand, in the strongly correlated
regime or under the large tensile strain, ferromagnetic spin states with
Jahn-Teller orbital order become most stable. The effect from polar interfaces
in LaNiO]/[SrTiO] is found to be noticeable in our
single-layered geometry. Detailed discussion is presented in comparison with
previous experimental and theoretical studies.Comment: 9 pages, 8 figure
Breaking Temporal Consistency: Generating Video Universal Adversarial Perturbations Using Image Models
As video analysis using deep learning models becomes more widespread, the
vulnerability of such models to adversarial attacks is becoming a pressing
concern. In particular, Universal Adversarial Perturbation (UAP) poses a
significant threat, as a single perturbation can mislead deep learning models
on entire datasets. We propose a novel video UAP using image data and image
model. This enables us to take advantage of the rich image data and image
model-based studies available for video applications. However, there is a
challenge that image models are limited in their ability to analyze the
temporal aspects of videos, which is crucial for a successful video attack. To
address this challenge, we introduce the Breaking Temporal Consistency (BTC)
method, which is the first attempt to incorporate temporal information into
video attacks using image models. We aim to generate adversarial videos that
have opposite patterns to the original. Specifically, BTC-UAP minimizes the
feature similarity between neighboring frames in videos. Our approach is simple
but effective at attacking unseen video models. Additionally, it is applicable
to videos of varying lengths and invariant to temporal shifts. Our approach
surpasses existing methods in terms of effectiveness on various datasets,
including ImageNet, UCF-101, and Kinetics-400.Comment: ICCV 202
Introducing Competition to Boost the Transferability of Targeted Adversarial Examples through Clean Feature Mixup
Deep neural networks are widely known to be susceptible to adversarial
examples, which can cause incorrect predictions through subtle input
modifications. These adversarial examples tend to be transferable between
models, but targeted attacks still have lower attack success rates due to
significant variations in decision boundaries. To enhance the transferability
of targeted adversarial examples, we propose introducing competition into the
optimization process. Our idea is to craft adversarial perturbations in the
presence of two new types of competitor noises: adversarial perturbations
towards different target classes and friendly perturbations towards the correct
class. With these competitors, even if an adversarial example deceives a
network to extract specific features leading to the target class, this
disturbance can be suppressed by other competitors. Therefore, within this
competition, adversarial examples should take different attack strategies by
leveraging more diverse features to overwhelm their interference, leading to
improving their transferability to different models. Considering the
computational complexity, we efficiently simulate various interference from
these two types of competitors in feature space by randomly mixing up stored
clean features in the model inference and named this method Clean Feature Mixup
(CFM). Our extensive experimental results on the ImageNet-Compatible and
CIFAR-10 datasets show that the proposed method outperforms the existing
baselines with a clear margin. Our code is available at
https://github.com/dreamflake/CFM.Comment: CVPR 2023 camera-read
Acute Interstitial Pneumonia in Siblings: A Case Report
Acute interstitial pneumonia (AIP) is a rapidly progressive condition of unknown cause that occurs in a previously healthy individual and produces the histologic findings of diffuse alveolar damage. Since the term AIP was first introduced in 1986, there have been very few case reports of AIP in children. Here we present a case of AIP in a 3-yr-old girl whose other two siblings showed similar radiologic findings. The patient was confirmed to have AIP from autopsy showing histological findings of diffuse alveolar damage and proliferation of fibroblasts. Her 3-yr-old brother was also clinically and radiologically highly suspected as having AIP, and the other asymptomatic 8-yr-old sister was radiologically suspected as having AIP
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